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Rebuilding Ukraine: The Gender Dimension of the Reconstruction Process

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The post-war reconstruction of Ukraine will have to comprehensively address a number of objectives to set the country on a path of stable, sustainable and inclusive growth. In this Policy Paper we argue that the principles of “building-back better” need to take the gender dimension under consideration. While the war has exposed women and men to different risks and challenges, various types of gender inequality were also pervading the Ukrainian society prior to it. Gender responsiveness in the preparation, design and execution of reconstruction programs is essential to ensure fair and effective allocation of the coming massive inflow of resources in the reconstruction effort. We argue that the principles and implementation mechanisms developed under the gender responsive budgeting (GRB) heading are suitable to apply in the process. We also document that the principles of GRB have in recent years become well established in Ukrainian public finance management and point out areas where the application of a GRB approach will be of particular importance.

Introduction

In August 2022, in the midst of the full-scale Russian invasion, the Ukrainian government adopted the State Strategy for ensuring equal rights and opportunities for women and men for the period until 2030 and approval of the operational plan for its implementation for 2022-2024 (Cabinet of Ministers of Ukraine, 2022), reaffirming its commitment to promote gender equality in Ukraine with a focus on empowering women and eliminating gender-based discrimination in all areas of life. The Strategy follows a number of earlier legislative initiatives that had placed gender equality at the center of Ukrainian public policy and included a comprehensive approach to the design of fiscal policy at the central and local government level, adopting the principles of gender responsive budgeting (GRB). Given substantial gender gaps in numerous areas of life in the Ukrainian society these principles will have to be considered in the future reconstruction process to address such disparities. Following the overall guidance presented by the authors of the CEPR Report published in late 2022, titled “Rebuilding Ukraine: Principles and policies” (Gorodnichenko et al., 2022), this Policy Paper examines some key dimensions of the future reconstruction of Ukraine from the perspective of gender equality with a focus on consistent and effective adoption of the principles of GRB.

Gorodnichenko et al. (2022) noted the critical importance of thinking already today about how Ukraine will rebuild after the war is over – “advanced planning and preparations now will save lives and increase chances of success (…) these steps will give hope to millions of Ukrainians that after the horrors of the war there is light at the end of the tunnel”. We argue, that if the reconstruction is to result in stable, sustainable development and bring tangible benefits to all Ukrainians, the principles of “building-back better” need to take the gender dimension under consideration. This is important for efficiency as well as equality reasons. Such an approach is fully consistent with the 2022 State Strategy which recognizes that gender equality is not only a human right but also a driver of economic growth and social development. The Strategy also provides a framework for mainstreaming gender into government policies and programs, including the budget, and recognizes the importance of gender budgeting as a tool for promoting gender equality and ensuring that public resources are allocated in a fair and equitable manner. Different forms of gender inequality permeated Ukrainian society before the war: while women were more educated than men, they were less likely to participate in the labor force, were severely under-represented in senior positions in business and politics as well as in fast-developing sectors such as information and communication technology, were earning lower wages, and were more likely to be victims of gender-based violence (see, e.g. World Economic Forum, 2021). The war has also exposed women and men to different risks and challenges (see, e.g., Berlin Perrotta and Campa, 2022). Gender responsiveness in the preparation, design and execution of the reconstruction programs is crucial to ensure fair and effective allocation of the vast amount of resources that will be mobilized through the reconstruction effort, providing a unique opportunity to address pre-war and war-related gender inequalities. We argue that the principles and implementation mechanisms developed under the heading of gender responsive budgeting are suitable tools to apply in the process. There are numerous examples from various post-disaster reconstruction experiences showing how sensitivity along the gender dimension can determine the success or failure of specific initiatives, and how thinking in advance along gender equality lines can help address the change from an ineffective and unfair status quo, to successfully “build-back better” (see Box 1).

The dimensions of post-war reconstruction of Ukraine covered in Gorodnichenko et al. (2022) range from necessary changes in governance, through reforms in the business and finance environment, energy and transportation infrastructure, as well as the labor market, the education and the healthcare system, to a discussion of the structure most efficient to deliver international aid. The Report offers an invaluable blueprint for peace-time reconstruction and development of Ukraine and constitutes a crucial reference point for the discussion about the efficient use of resources necessary to ensure rapid and sustainable development of the country. Below we build on its main principles, examine them through a gender lens and apply a gender responsive budgeting approach to highlight the areas where it can be used at different stages of the reconstruction process.

In what follows we draw on the growing literature in the fields, among others, of political economy, development, education and labor economics, that examines the importance of gender diversity and identifies implications of gender inequalities for socio-economic outcomes at the micro and the macro level. On the basis of this literature, we point out the dimensions of the reconstruction process where a gender responsive approach can be particularly beneficial, and specify the stages of the process where the principles of gender responsive budgeting can be effectively applied to ensure efficient and fair distribution of recovery resources. The paper begins with a brief introduction to gender budgeting (Section 2), followed by three sections focusing on key categories of the reconstruction. First, in Section 3, we discuss how a gender responsive approach can shape governance reforms in the post-war period. In Section 4 we examine how gender sensitivity combined with the principles of GRB can influence the allocation of recovery funds in the process of physical rebuilding after the war, as well as the design of the physical environment. Finally, Section 5 highlights the crucial role of human capital in post-war development and points out a number of areas where reconstruction policies might have to be carefully drafted, taking into consideration the specific needs and requirements of women and men. We stress throughout that the concept of gender budgeting and gender responsiveness has been exercised in Ukraine for some time and that it is well rooted in Ukrainian public policy making. These principles should thus come naturally to representatives of key institutions in the discussion of plans for the country’s reconstruction and their execution.

2. Applying Gender Responsive Budgeting Principles to the Process of Post-war Reconstruction

At the heart of gender responsive budgeting lies the recognition of the potential of financial and fiscal policies to influence gender disparities. Gender budgeting integrates “a clear gender perspective within the overall context of the budgetary process through special processes and analytical tools, with a view to promoting gender-responsive policies” (Downes et al. 2017). It is aimed at ensuring that fiscal policies and public financial management practices and tools are formulated and implemented with a view to promote and achieve gender equality objectives, and that adequate resources for achieving them are allocated (IMF, 2017). For GRB to be effective, gender considerations ought to be included in all the stages of the budget cycle, including:

  1. the setting of fiscal policy goals and targets
  2. the preparation of the annual budget and its approval by the legislature
  3. the control and execution of the approved budget
  4. the collection of revenues, the preparation of accounts, and financial reports
  5. the independent oversight and audit of the budget

At each stage of the process, different tools have been developed to ensure that discussion on the gender impact of a specific fiscal policy will constitute an integral part of budget decision-making, execution and reporting. These tools include documents ensuring that spending ministries and agencies are fully briefed on the legal and administrative procedures to be followed in implementing gender responsive budgeting as well as on the requirements to include gender-relevant indicators in budget requests, to provide data disaggregated by sex, or to request specific budgetary allocations for gender-related programs or projects (Budlender, 2015). Moreover, gender budget statements can be published with the budget document as strategic tools to implement gender-responsive policies by allocating adequate resources to reach strategic goals and measuring impact and results. Gender budgeting also includes requirements for gender-impact assessment of the potential direct and indirect effect of policy proposals on gender equality and more broadly on different groups in the society. The regulations may require such assessments to be made prior to implementation (ex-ante assessment) as well as after the roll out of the policies (ex-post evaluation).

The principles of GRB originated in the 1980s in the Australian government in the form of the so-called ‘Women’s Statement’. The principles were applied more broadly in transition and developing countries with support of UN Women and numerous NGOs and research institutions. In recent years, mainly as a result of recognition of the effectiveness of GRB from international financial institutions, such as the IMF, the World Bank and the OECD, the approach has been more firmly integrated with other existing budget tools. It has thus become much more common as a standard technical budget instrument in numerous developed and developing countries (For more details on the development of GRB theory and practice see for example: Budlender et al. 2002; O’Hagan and Klatzer 2018, and Kolovich 2018). Currently over ninety countries around the world apply some form of GRB. While in most of them its use has not been systematized and fully integrated in the overall budget process, countries such as Australia, Austria, Canada and the Spanish province of Andalusia apply GRB consistently across all levels of government and systematically monitor its execution. Ukraine is also among the countries that in recent years have made rapid progress towards comprehensive integration of GRB in its public policy (see Box 2).

The Ukrainian government firmly upheld the principles of GRB after the Russian invasion in February 2022, at a time when one might think that gender equality considerations would lose priority in the management of public finances. Throughout the war the Ministry of Finance has continued to ask line ministries to provide gender responsive budget requests, and fiscal policy has been monitored to ensure informed policies with regard to the distribution of the limited crisis-budget funds among different groups in society. These policies together with the State Strategy for ensuring equal rights and opportunities for women and men for the period until 2030 and approval of the operational plan for its implementation for 2022-2024 (Cabinet of Ministers of Ukraine, 2022), adopted in August 2022, reaffirm the Ukrainian government’s commitment to gender responsive policy making and lay the foundations for the application of such an approach during the post-war recovery process. Effective implementation of GRB principles requires specific knowledge and expertise, and the lack of which has often been a key challenge in meaningful integration of gender analysis in financial processes and documents. Competence in finance among civil servants in line ministries and the Ministry of Finance needs to be combined with gender expertise in sector budget analysis. Development of the combination of these competencies in Ukraine in recent years bodes well for integrating the GRB principles in the process of recovery and reconstruction.

At different stages of the reconstruction process the needs of various social groups along the gender dimension as well as others such as age, disability or religion, ought to be taken into account. To ensure fair and effective use of recovery funds the process should consider the following principles:

  • Participation: consultation with different population groups by gender, age, disability, profession, and other characteristics should enable assessment of the priority objectives for reconstruction in specific localities.
  • Equity: there is always a risk of neglecting the needs of different categories of people (e.g. people with disabilities) while focusing on the needs of the majority of the population.
  • Addressability: it is important to realize that a reconstruction program aimed at “everyone” risks significant misallocation of funds, reaching “no one”. A careful approach needs to consider different economic, cultural, recreational, educational and service needs of well-specified groups of individuals.

The planning and execution of the reconstruction process could follow the lines of intersectional gender budgeting analysis which focuses on the analysis of how different budget measures impact different groups of citizens – women and men – taking into account their disability status, age, place of residence and other variables. Taking as an example a foot bridge reconstruction, a gender responsive analysis would enable information on the citizens in the area, their needs, and their use of the infrastructure. The reconstructed bridge should benefit pedestrians, often women who might sell their products at the marketplace, or whose access to various services requires to cross the river. The analysis would also consider employment levels among women in the reconstruction of the bridge, etc. Considering the example of a school reconstruction, the process needs to consider if there are children in the area and/or whether they will return to that area with their families; whether there is/will be sufficient access to transportation and whether – in case the school is not reconstructed – the children can conduct their education in other schools in the area. Reconstructed educational institutions should consider gender-sensitive infrastructure and account for design of facilities, such as ramps, to address the needs of individuals with disabilities.

The Ukrainian government is strongly committed to supporting gender equality trough, among other means, gender mainstreaming processes with well-established legal frameworks for gender budgeting. Reconstruction efforts shall acknowledge and use the existing analytical tools in Ukraine to ensure that donor funds, projects and initiatives achieve their objective of sustainable and equitable development. Effective and fair distribution of the reconstruction funds will require that substantial care is paid to the analysis of the beneficiaries at the stages of planning and during reconstruction.

3. The Gender Perspective on Governance in Post-war Reconstruction

The institutional arrangements adopted both at the national level in Ukraine and at the international level for the administration and distribution of reconstruction funds will be of crucial importance to the success of recovery efforts and their translation into rapid and sustainable development of the country. In this Section we take the gender perspective on these two dimensions of governance. First, we argue that, at the national level, improvements could be made in the Ukrainian electoral system to extend women’s access to elected political positions in order to increase women’s influence in the overall process of policy-making. Drawing on international evidence we argue that this would not only further ensure support for the application of the gender budgeting approach, but it would also help selecting more competent and non-corruptible politicians. Second, we build on the proposal in Mylovanov and Roland (2022) to create an EU-affiliated agency that would manage the funds from multilateral donors (the “Ukraine Reconstruction and European Integration Agency” – UREIA) and examine how the GRB principles should be applied to efficiently integrate them with other dimensions of such an agency’s activities.

3.1 Increasing Women’s Representation in Ukrainian Political Institutions

In international comparisons, Ukraine lags behind in terms of women’s representation in politics, with gender gaps persisting in national as well as local institutions – in spite of some recent progress. It is likely that a large presence of women in political institutions would help addressing concerns regarding the effective implementation of the gender budgeting principles.  Local and central politicians could promote ex-post evaluations of local and national projects to verify that the intended gender-breakdown of beneficiaries were reached, and they could consider and implement corrective measures when unintended balances were found. In this respect we note, once again, that key decision-makers in Ukraine have shown strong commitment to the principles of gender-budgeting, by supporting and prioritizing its implementation – even during the dramatic circumstances of the Russian invasion (see Box 2). However, the commitment to gender-budgeting among policy-makers in Ukraine would likely become even stronger with a larger presence of women among them. The gender composition of political institutions has been shown to affect the allocation of public funds. For example, Chattopadhyay and Duflo (2004) find that female village chiefs in India tend to spend more money in budgetary areas that appear to be especially important for female villagers. Similarly, an analysis of the bills proposed by French legislators shows that women tend to work more on so called “women’s issues” (Lippmann, 2022). We would therefore expect female politicians to be more likely to support an effective implementation of gender-budgeting principles. Moreover, we expect project proposals crafted by more gender equal groups to be more representative of both women and men’s needs and priorities, which in turns should make the reconstruction process more balanced across different areas and allow it to address numerous inefficiencies of the pre-war status quo (see Box 1).

It is also worth noting that some literature in economics and political science documents that, as more women are elected to political institutions, the average “quality” of elected politicians tends to increase (Besley et al., 2020; Baltrunaite et al., 2018). Moreover, female policy-makers are less likely to engage in corruption and patronage (Brollo and Troiano, 2018; Dollar et al., 2001; Swamy et al., 2001), a dimension which will certainly be closely monitored at an international level, and one which is key in ensuring international public support for the reconstruction.  Policies that increase women’s representation in politics could thus also help improve the quality of democratic institutions, a development that is of utmost importance in the face of Ukraine’s ambition to join the EU. While the existing empirical evidence does not unanimously link women’s representation in politics to more women-friendly budgetary expenditures or better institutions, it is worth noting that there is also no evidence of any major drawback from policies that help women accessing political institutions. Increasing women’s representation in Ukrainian political institutions would also be in line with the argument that bringing a critical mass of new people in politics will help counteracting “oligarchizing” tendencies (Mylovanov and Roland, 2022) in the development of Ukrainian democracy. Numerous options are available in terms of changes in the political ‘rules of the game’ to help address the current underrepresentation of women in Ukrainian political institutions. In Box 3 we list a few of these options.

3.2 Gender Budgeting in the Work of UREIA

Gender-budgeting in the reconstruction process requires an ex-ante gender-analysis of the different projects being financed, which relies on the availability of sex-disaggregated data and specialized skills. Given that gender-budgeting has been part of Ukraine public finance system for a number of years, there is likely a good supply of trained personnel who can work together with international experts right from the beginning of the reconstruction.  Conducting the ex-ante work of gender assessment within the reconstruction agency should speed up the process that we envision, as the tasks involved will be routinely sourced to the same teams of skilled individuals who will analyze different projects through the gender-budgeting lens. The agency should then also be in charge of a centralized evaluation of the various gender-analysis results. This work of overview will provide a comprehensive picture of who is reached by the entire pool of available reconstruction funds, thus allowing to distinguish project-specific gender differences – which can be justified by specific needs being targeted at project-level – from a systematic bias toward one of the genders in the overall reconstruction process. A clear picture of who are the beneficiaries of specific reconstruction initiatives, including statistics disaggregated by gender and potentially by other characteristics, may play a key role in reassuring the Ukrainian society that the recovery funds are used to benefit a broad spectrum of the population, as well as in legitimizing the use of these funds in the eyes of the international donor community.

The conclusions of the international literature on the implications of women’s representation in political institutions for the scope of realized public initiatives mentioned in Section 3.1, pertain also to the functioning of the UREIA. The very design and composition of the agency’s staff ought to ensure gender diversity in its ranks at all levels of seniority to safeguard both the highest quality of the work being carried out by UREIA, as well as the appropriate scope of projects undertaken by the agency, most preferably supported by the principles of GRB. Recent empirical studies indicate that the personal traits of public procurement actors, such as their abilities or competencies, may play a key role in influencing procurement practices and outcomes (see, e.g., Best, Hjort and Szakonyi, 2022 or Decarolis et al., 2020), and gender-based variations in personal characteristics such as risk aversion, ethical values, and others have been demonstrated to be significant, including in the context of corruption (see a review in Chaudhuri, 2012).

4. Post-war Reconstruction: the Gender Perspective on Rebuilding the Physical Environment

The physical environment provides the background for the functioning of societies and at the same time, through its physical durability, imposes a long-lasting legacy that may determine the dynamics of social processes well beyond the time of construction. It shapes the organization of cities, the location and efficiency of public infrastructure, as well as the transport networks and it is also an influential precondition and determinant of behavior and outcomes. There is plenty of examples of how the physical environment affects economic outcomes, both at the individual and societal level. The presence of large infrastructures such as ports or highways determined the process of agglomeration (Ganapati, 2021; Faber, 2014), while paved roads and irrigation canals affect local development and structural transformation of rural areas (Aggarwal, 2018; Asher et al., 2022). Availability of urban green spaces has implications for health outcomes and violence (Kondo et al., 2018) and the safety of commuting routes affects girls’ college choices (Borker, 2021). Moreover, elements of the built environment may also affect social norms (Josa and Aguado, 2019; Baum and Benshaul-Tolonen, 2021).

The post-war reconstruction of the physical environment will shape the structure of Ukrainian cities and villages for decades to come, and hence the process ought to consider very broad aspects of influence of the built environment, with a clear focus on the identity of its users and beneficiaries. We firmly believe that the application of the principles of GRB will facilitate effective use of recovery resources and at the same time help address the inefficiencies of the pre-war status quo to create an environment which fairly takes into consideration the interests of both men and women. With respect to the physical environment in particular, obvious path dependencies limit swift changes to benefit women and other marginalized groups (Hensley, Mateo-Babiano, and Minnery 2014) and from this perspective the post-war recovery process can be thought of as a unique opportunity to address a number of imbalances.

4.1 Gender Mainstreaming in Urban Planning

It has been pointed out that gender mainstreaming in urban planning remains inadequate, which has been linked to the gender bias in the planning industry, both in terms of representation – who plans the cities affects how the cities are planned (Beall, 1996) – and the dominant culture (Sahama et al., 2012). It seems intuitive that a planning approach which takes into account how beneficiaries of the design are disaggregated by gender, and how the design affects the functioning of different groups, would result in an environment much more suited to the needs of these groups. The design should take into consideration different preferences with regard to employment, leisure, housing, open spaces, transportation, and the environment. Gender is relevant across all these issues in urban planning. Including more women in planning and decision-making might be the easiest way to ensure that such perspective is accounted for.

As we argue in Section 5, the effective use of Ukraine’s human capital will be essential for the success of its recovery process and further development. The built environment has important consequences in this realm and so, when rethinking cities, questions such as zoning, connectivity and mobility, as well as the quality of sidewalks and lighting need to be considered in relation to the necessity to juggle work, care for household members, and other daily duties (Grant-Smith, Osborne, and Johnson 2017). The rebuilt physical infrastructure will affect the lives of those who are particularly limited by safety concerns, and it will affect the quality of life of those who walk pushing a pram or supporting elderly relatives. These aspects have been shown to be particularly important for women, increasing their actual and perceived vulnerability when they travel around the city, cutting them off from after-dark activities (Ceccato et al., 2020), but also affecting life choices with a long-lasting impact (Borker, 2021). Utilizing Geographic Information Systems (GIS), satellite imagery and open data sources holds the promise of creating more effective methods for observing patterns of utilization of the city and incorporating a gender responsive approach along these lines in urban planning of reconstructed areas of Ukraine (Carpio-Pinedo et al., 2019).

4.2 Gender Sensitivity in the Design of Transport Infrastructure

Transport infrastructure is crucial to the development of society. When a large share of the infrastructure capital needs to be rebuilt or updated, as will be the case in Ukraine, this opportunity may be used to lay new foundations for both economic and social development. To make the most of such an opportunity, attention ought to be paid to a number of identified risks. Unequal resource distribution has been observed both in connection with new construction of infrastructure (MacDonald, 2005) and relocation of the same (Chandra, 2000; Unruh and Shalaby, 2012). The large stakes inherent in these projects can generate high incomes and rent-seeking leading to a deepening of inequalities and further marginalization of those already vulnerable from the conflict. As women have been particularly strongly affected by the war and the resulting internal displacement (Obrizan, 2022a), the reconstruction process ought to pay particular attention to the risks of exacerbating some unequal developments that emerged with the war. Women’s representation in budgeting, procurement, and decision-making might make these aspects more salient and facilitate their integration into the recovery process.

Mobility is connected with social inclusion, more general well-being and a higher quality of life (this literature is reviewed in Josa and Aguado, 2019). The transport infrastructure is particularly important from the point of view of gender equality as usage of transportation and transport mode preferences significantly vary across socio-economic groups, including by gender (Grieco and McQuaid, 2012; Ghani et al., 2016). In the reconstruction planning and rebuilding process the prioritization of public funding for roads, highways, and railways compared to slow modes, such as walking and cycling, should be put in relation to usage and preferences in different groups of the population. One way through which women are excluded, from mobility itself and from other economic outcomes that mobility would help to reach, such as education (Borker, 2021) and employment (Das and Kotikula, 2019), are safety concerns. In dozens of cities around the world, lack of safety and prevalence of sexual harassment in public transit has resulted in the creation of safe spaces to facilitate safer travel conditions for women (Kondylis et al., 2020). The reconstruction could put significant emphasis on the safety of public transportation which would benefit women in particular and facilitate their effective integration in the future aspects of socio-economic development.

4.3 The Gender Perspective in Increasing Energy Efficiency

One of the key focus points of post-war reconstruction will be rebuilding the energy infrastructure, which has, over the course of the war increasingly been a target of Russian bombing. This process will have to be accompanied by considerations of reorientation, in terms of the energy mix, with a focus on self-sufficiency and environmental sustainability, but also most likely of relocation. At the same time the country should pay significant attention to energy efficiency, which may significantly influence both the energy self-sufficiency of Ukraine and the environmental aspects of power and heating.

It is worth noting at this point that natural resources and their exploitation have significant implications for local communities with consequences from projects often spilling over to local attitudes, leading to gender inequalities through channels such as labor and marriage markets, environmental quality and health, fertility and violence (see a review in Baum and Benshaul-Tolonen, 2021). Both exploitation and new energy infrastructure projects – similar to other aspects of the build environment – will have to consider effective connection to the new urban and production mix, so that the energy infrastructure serves the new cities and the updated geographic distribution of various productive sectors, but also the impact that infrastructure positioning can have on surrounding communities. The presence of infrastructure may generate rents and inequality, and the same is true also for energy infrastructure.

The post-war reconstruction will also present a chance to substantially improve energy self-sufficiency through increased efficiency in energy consumption. Ukraine currently has an energy intensity in production that exceeds the EU average by a factor of 2.5. Although energy efficiency in industry and buildings represents the lion share of such gains, households’ consumption behavior has the potential to contribute substantially, both directly through the consumption of fuel and electricity, and indirectly through the consumption of goods and services (Bin and Dowlatabadi, 2005), as well as through the support for a green policy agenda (Douenne and Fabre, 2022). In this area women and gender-related attitudes might be particularly important. Recent literature claims that women tend to be more environmentally friendly than men, partly due to individual characteristics and attitudes considered more prevalent among women, such as risk aversion, altruism, and cooperativeness – important for environmental behaviors (Cárdenas et al., 2012 and 2014; Andreoni and Vesterlund, 2001). There is also empirical evidence that households where women have more decision power display higher energy-efficiency and energy savings (Li et al., 2019), while firms with more women in their board source significantly more energy from renewables (Atif et al., 2020). It might therefore prove instrumental that energy-efficiency policies directed to households (nudges, information/education, financial incentives) and firms respectively (including gender quotas in boards) take these aspects into account.

5. Post-war Reconstruction: the Gender Perspective on Rebuilding and Strengthening Ukraine’s Human Capital

The human cost of the Russian invasion of Ukraine, including the implications from the Russian occupation of Ukrainian territories since 2014, is immeasurable. The loss of lives, as well as the consequences of disabilities, physical injuries and mental trauma will scar the Ukrainian future for decades to come. The invasion has resulted also in massive displacement and emigration, as well as in the loss of numerous aspects of individual capacities. From the point of view of Ukraine’s reconstruction and future development, all these losses, apart from demonstrating dramatic individual human tragedies, need to be perceived as loss of an essential building block of socio-economic growth – human capital.

Successful post-war reconstruction of Ukraine and its long-term sustainable development can only be ensured if sufficient care is taken of areas which are key to the development and effective utilization of human capital. These cover, in particular but not exclusively, the areas of healthcare, education, research and the labor market and all of them have been extensively covered and discussed in Gorodnichenko et al. (2022, see chapters: 10, 11, 12, 13). Drawing on their general conclusions, we particularly focus on some of the gender aspects of human capital development in the context of planning Ukraine’s reconstruction. Highlighting gender aspects is sometimes misunderstood as being focused on achieving gender equality in numbers across domains. This is not our focus here. The starting point is to look at a number of empirical facts about actual conditions and, based on this, point to the importance of taking the gender dimension into account to achieve efficiency in the reconstruction process. Gender sensitivity seems particularly important in the area of human capital development, and given the fundamental role of human capital for growth (e.g., Barro, 2001; Squicciarini and Voigtländer, 2015; Goldin, 2016) it is essential for an effective use of reconstruction resources as well as for ensuring a cost-efficient, sustainable and fair process of redevelopment.

The reconstruction interventions we address in this Section are those in which the gender aspect is particularly salient. We categorize these under three broad overlapping headings: 5.1; supporting internally displaced individuals, returning international migrants, war veterans and other victims of conflict, 5.2; providing effective education and training to younger generations, and 5.2; reducing institutional constraints on labor market participation.

5.1 Supporting Internally Displaced, Returning International Migrants, War Veterans and Other Victims of Conflict

Forced internal displacement and international migration – apart from the resulting direct consequences for physical and mental health – comes with separation from family and local social networks, from jobs and schools as well as loss of physical and financial assets. According to UNWomen 7,9 million Ukrainians have been forced to leave the country and 90 percent of them are women with their children. Of the more than 5 million internally displaced 68 percent are women (as of Jan 2023; UNWomen, 2023). Many of those forced to move will either not be able to return home or will return to their localities devastated by the war along a number of dimensions.

Effective rebuilding and reconstruction will strongly rely on the input from these hundreds of thousands of individuals. We ought to bear in mind that a great majority of international war migrants are women, and supporting them in returning to Ukraine and in reintegration – often in places other than those they had left – will be of vital importance to the process of reconstruction. Significant care will also have to be taken of returning war veterans – most of whom are men, as well as victims of war related sexual violence – mostly women. Ukraine already counts more than 300,000 veterans from different armed conflicts on Ukrainian territory since 1992 – including 18,000 women or about 6 percent (Ministry of Veterans Affairs of Ukraine, 2022). According to the head of the Armed Forces of Ukraine, about 1 million are currently mobilized, with roughly 5 percent being women (Boyko, 2022). The Ministry of Social Policy of Ukraine (2022b) expects the number of veterans and their families to amount to 5 million. To support their involvement in the reconstruction process, short run interventions ought to address the following critical areas: housing and safety, physical and mental health, and active labor market policies. All these areas involve significant gender considerations.

a) Housing and safety

As many of the internally displaced and those returning to Ukraine from abroad will not be able to return to their homes, provision of safe and good quality housing will represent a major challenge in the reconstruction efforts. While ‘roof over your head’ is equally important for everyone, some aspects of the housing infrastructure, especially local safety and safe connectivity with other key locations, are of particular relevance to the wellbeing of women. Although already mentioned in in our discussion of reconstruction of the physical environment in Section 4, it is important to bear in mind that good quality housing and access to critical infrastructure and effective transportation networks have substantial implications for the effective ways of participation of different members of the society in its socio-economic activities. If the human capital of men and women is to be efficiently engaged in the reconstruction process and further developed, the physical context in which it will happen must be adjusted with the objectives of different groups in mind. Housing, neighborhood conditions, and safe transportation translate into access to jobs, training, education, and local services. The design of the physical reconstruction after the war ought to take these different perspectives into account along the lines of gender responsive budgeting to clearly delineate and correctly identify priorities for the allocation of recovery funds.

b) Physical and mental health support

It is clear that experiences from threat to one’s life and safety, the need to flee one’s home and search refuge, continued experience of insecurity, the direct exposure to terror and violence – including sexual violence – and war atrocities will leave a significant proportion of the Ukrainian population traumatized and in need of specialized mental health support. Additionally, numerous individuals will come out of the war with life-changing physical injuries, while to countless people the period of war will result in substantial neglect of common health problems which otherwise would have been taken care of. These dramatic consequences of war will have to be comprehensively addressed as part of the reconstruction effort to support the affected and vulnerable groups, with the aim to address both their physical and mental health deficiencies. The issues involved are too complex for a Policy Paper to deal with in detail – we can only highlight health as an area to be prioritized in the allocation of recovery funds. With that in mind it is important to stress that there are numerous examples in the public heath literature showing the significance of the gender perspective with regard to the efficient use of public resources and appropriate design of health interventions, taking into account the specific requirements of men and women both in physical and mental health (Abel & Newbigging, 2018; Chandra et al., 2019; Diaz-Granados et al., 2011; Judd et al., 2009; Oertelt-Prigione et al., 2017).

War veterans – primarily men – will be a group in need of particular concern and a comprehensive approach with regard to physical and mental health. Specific specialized support will have to be offered also to victims of conflict-related sexual violence – mostly women. The direct health support will often need to go along with education and training as well as assistance in such areas as housing and material conditions.

Already before the full-scale Russian invasion Ukraine had rolled out several programs in support of veterans from the ongoing 2014 conflict. These included establishing private or publicly co-funded therapy centers for treating posttraumatic stress disorder (Colborne, 2015) and creating organized groups of psychological and psychiatric specialists providing psychological assistance (Quirke et al., 2020). They also included conducting special trainings for general practitioners to provide mental health consultations to increase the overall capacity of Ukraine’s health care system to address mental health issues (Kuznetsova et al., 2019), and broadcasting national TV/social media awareness campaigns such as ‘Mental Health Awareness Week’ (Quirke et al., 2021). Since 2017, as part of the broader healthcare reform program, a thorough reform of the mental health services provision has been underway. The key identified challenges targeted with the reform were: securing human rights protection in mental health legislation, improving regulation of the mental healthcare sector and expanding delivery of mental health services outside of the institutionalized settings (The Ministry of Health of Ukraine, 2018; Weissbecker et al., 2017).

c) Active labor market policies (ALMP)

In precarious conditions in particular, women tend to be those responsible for care of elderly and children, which additionally contributes to disconnecting them from the labor market. It seems that large scale ALMP programs for displaced individuals and returning migrants will be essential to improve the match between skills and the local post-war labor market conditions.

With greater war time labor market disconnect among women, many of whom will have spent months without employment or in various forms of war-time subsistence work, ALMPs will be critical for many in the process of post-war reconstruction. Overview studies show that effectiveness of labor market interventions is generally positive for men and women (e.g. Card et al., 2010). These are often similar in size even though in settings with high employment gaps – such as in the case of Ukraine – the programs tend to be more effective for women (Bergman and van den Berg, 2008). Appropriate identification of skill shortages and provision of training can be an effective way of supporting the post-war Ukrainian labor market and the integration of women in particular. The design of these programs ought to pay special attention in order to avoid labor market stereotyping, to provide broad and integrated routeways to deliver the greatest pool of talent, and to ensure that men and women are appropriately matched to jobs suitable to their skills and abilities. Significant training programs should also be directed towards war veterans.

The skills training aspect of ALMPs has other important gender dimensions – women represent a large majority of Ukrainian teachers, and their skills can be utilized not only in schools but also in adult education and retraining, taking particular advantage of the extensive network of vocational education institutions. Similarly, around 83 percent of the country’s healthcare workers are women, and skills upgrading in the healthcare sector – especially focused on increasing the competence and skills of nurses to take over greater responsibilities for primary care – will constitute an important reform element in the Ukrainian healthcare sector (see Gorodnichenko et al., 2022, chapter 12).

5.2 Providing Effective Education and Training to Younger Generations

Ukrainian youth have in recent years faced a double blow to their educational development. The first one in the form of numerous Covid-19 pandemic related restrictions, followed by the disruption in their education process due to the Russian invasion. The latter especially affected those who had to flee their homes and leave their local schools, as well as those whose schools have been destroyed and rendered dysfunctional. However, many Ukrainian schools opted for or were forced to limit the extent of provided classes and/or provided some of the instruction online. According to UNICEF, the war in Ukraine has disrupted education for more than 5 million children (UNICEF, 2023). 60 percent of children have experienced different traumatic events such as separation from family and friends, moving to another region, shelling and bombing, having witnessed the death of relatives or loved ones, etc. In early 2023, 42 percent of children aged 3-17 studied online, 29 percent both online and in school/kindergarten, 26 percent attended educational institutions while 3 percent studied at home (Sociological Group Rating, 2023). As mounting evidence from the Covid-19 pandemic shows, such disruptions accumulate in the form of significant human capital losses (e.g., Gajderowicz et al., 2022, Contini et al., 2021) and post-war recovery will have to address these to minimize the losses to the pool of skills of the future Ukrainian work force.

Home schooling and school routines disrupted in various ways might, in particular in communities characterized by traditional gender norms, impose additional limitations on the education of girls who may be tasked with greater home and care responsibilities. Thus, while emphasis on catching up on effective learning will be of utmost importance for all students, from the point of view of gender equality, it will be particularly important to closely monitor the school coverage and return to standard school attendance among girls. As post-pandemic evidence from developing countries suggests this may be of particular relevance with regard to teenage students (Kwauk et al., 2021). Post-war recovery initiatives aimed at financial support for households ought to ensure that households with older children in particular do not need to trade off material conditions and schooling opportunities. This might call for programs designed to incentivize school attendance in particular among children in displaced families and for returning international migrants (Aygün et al., 2021).

The post-war reconstruction initiatives in education might also be a chance for the education system to be more forthcoming in promoting high skilled occupations among female students. The 2018 PISA study demonstrated that while Ukrainian 15-year-old girls and boys do equally well in mathematics and science, their objectives with regard to occupation – in particular in STEM areas – differ significantly (OECD, 2019).

5.3 Reducing Institutional Constraints on Labor Market Participation

In order to make most of the potential of the Ukrainian labor force in the process of post-war reconstruction, the plans ought to target various institutional constraints to labor market participation. In this respect the gender equality literature has stressed in particular the provision of early and pre-school childcare to facilitate employment of parents, and in particular of mothers (Addati et al., 2018; Attanasio et al., 2008; Azcona et al., 2020; Gammarano, 2020). Although much has been done during the past decades to improve women integration in the labor market, attitudes in the home and in the family care realm remain traditional and unbalanced (Babych et al., 2021; Obrizan, 2022b). This translates into an unequal division of care and work at home as well as participation in the labor market.

While childcare facilities have been shown to play a key role in supporting female participation in numerous contexts, they are going to be of particular importance to displaced families and returning international migrants, who may lack family support and social networks to organize informal care. Before the full-scale invasion, a relatively high proportion of children aged 3-5 and 5-6 (88 and 97 percent, respectively) were covered by institutional childcare (Ministry of Education and Science of Ukraine, 2021). Returning to such high levels of coverage will be an important element of the reconstruction process. Additionally, authorities should extend the coverage of childcare available to younger children, which in 2019 was much lower (18 percent).

Similarly, welfare arrangements in a broader sense are important to facilitate employment of all working age individuals, men as well as women. It is well established that in situations where government support is cut in various ways, it is typically the women who withdraw from the labor market to manage not just childcare but elderly care and other welfare functions (Mateo Díaz and Rodriguez-Chamussy, 2016). While a high proportion (54 percent) of people in Ukraine before the 2022 invasion declared that care duties should be equally divided between spouses, as many as 41 percent thought that it is the woman’s responsibility (Babych et al., 2021). This implies that it is still likely that, when faced with institutional and informal care constraints, it will be women who will be more likely to drop out of the labor market.

To facilitate effective reconstruction, high participation rates among both men and women will be of utmost importance. To achieve this, substantial reconstruction funding ought to be committed to ensure adequate care support directed both to parents of young children as well as to those with care responsibilities of older family members. Such support will be particularly important in localities with high numbers of internally displaced and returning international migrants. These needs should be correctly accounted for when planning the reconstruction process and allocation of funds, and the GRB approach is likely to be an essential instrument to ensure that objectives of different groups of the Ukrainian society are appropriately addressed.

Conclusions

Over the last few years, the Ukrainian government has introduced substantial reforms in the management of public finances with the aim of developing gender responsive procedures to ensure greater gender equality in the delivered outcomes. The government’s commitment was confirmed in August 2022 with the adoption of the State Strategy for ensuring equal rights and opportunities for women and men for the period until 2030 and approval of the operational plan for its implementation for 2022-2024 (Cabinet of Ministers of Ukraine, 2022). The implemented legislation and the experience from practicing gender responsive budgeting at different levels of government can prove to be an invaluable platform to be utilized in the post-war reconstruction process. Pre-war statistics from many areas of life in Ukraine demonstrated a high degree of inequality along the gender dimension. Gender gaps were high in employment, pay levels, the allocation of home and care responsibilities, and it could also be seen in senior positions in politics, company management, and academia. One of the many tragic consequences of the full-scale Russian invasion and the ongoing war is that these gaps are likely to grow.

If the post-war reconstruction process is to take the principles of “building-back-better” seriously, then, apart from many other dimensions which need to be considered (see Gorodnichenko et al., 2022), recovery planning and execution will also have to address various social inequalities, especially that along the gender dimension. As argued in this Policy Paper, to ensure fair and effective use of recovery funds, the reconstruction process should pay close attention to the identity of its beneficiaries, as well as the way decisions are being made. The authorities, including the central agency responsible for the reconstruction (e.g., UREIA, see Gorodnichenko et al., 2022), should take full advantage of existing tools and instruments of the gender responsive budgeting approach, as well as of an equitable representation within their ranks, and build on the basis of existing Ukrainian legislation and practice of gender budgeting (see Box 2). The reconstruction process will offer a unique chance to set Ukraine on the path of inclusive, stable and sustainable development. We have pointed out a number of areas in which the gender dimension will be particularly important – these include both the reconstruction and rebuilding of the physical environment as well as support and recovery of the full potential of Ukrainian citizens – old and young, men and women. The reconstruction of Ukraine will be a hugely challenging task, and it will have to involve massive resources. International support for channeling those funds to Ukraine and their effective use will depend on how effectively and how fairly they will be used. The application of gender responsive budgeting can help both in ensuring efficiency of allocation of the funds, and in strengthening the legitimacy for the provision of support by the international community.

References

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Gender Gap Widens During COVID-19: The Case of Georgia

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Gender inequality has been a persistent (albeit steadily improving) problem for years. The COVID-induced crisis put women in a disproportionately disadvantaged position, jeopardizing decades of progress achieved towards equality between men and women. However, these effects of the pandemic were not universal across countries. This policy brief aims to evaluate the gender-specific effects of the COVID-19 crisis in Georgia, looking at labor market outcomes and entrepreneurial activities. As expected, the impact of the pandemic was not gender-neutral in this regard, being especially harmful for women. As the Georgian economy rebounds after the crisis, we show that the widened gender gaps are partially offset only in certain aspects. In order to countervail the disproportionate effects of the pandemic, targeted policy measures are needed to stimulate women’s economic activity.

Introduction

Past economic recessions, including the COVID-induced crisis, have never been gender-neutral (e.g., Liu et al., 2021; Ahmed et al., 2020). While economic crises are usually associated with disproportionate negative impacts on labor market outcomes of men compared to women, the impact of the crisis is, debatably, more severe for women-led businesses as compared to their male-led counterparts (e.g., Torres, 2021; Nordman and Vaillant, 2014; Grimm et al.,2012).

The disproportionate labor market outcomes of economic crises are claimed to be due to the fact that men are predominantly employed in cyclical sectors such as construction or manufacturing; therefore, women have to increase their employment during economic downturns as a means of within-family insurance (Alon et al., 2021). The recent COVID-induced crisis, due to its unique nature, turns out to be an exception in this regard. The pandemic and the subsequently-adopted measures primarily adversely affected contact-intensive sectors (where the worker is required to perform tasks in close physical proximity to other people) that predominantly employ women (Mongey, Pilossoph, and Weinberg 2020; Albanesi and Kim 2021). Moreover, large-scale lockdowns increased the burden of unpaid care, which is generally shouldered by women disproportionately (Babych, 2021), leaving less available time for them to work. It should be noted that gender gaps in the labor market were a persistent (albeit steadily improving) problem even before the pandemic (Eurofound, 2016). Therefore, COVID-19 poses a threat jeopardizing the progress achieved in this direction and worsening gender inequality.

COVID-19 brought unprecedented adverse consequences for not only employed workers but entrepreneurs as well. Increased unpaid care and housework pose additional burdens on female top managers, making women-led businesses more vulnerable to the crisis.

The unequal gender implications of the COVID-19 crisis have been widely debated. Growing evidence (Albanesi and Kim 2021; Torres et al., 2021; Alon et al., 2020; Caselli et al., 2020, Fabrizio et al., 2021) attests that, on average, the effects of the pandemic put women in a disproportionately disadvantaged economic position. However, the extent of this effect varies across countries and is absent in some cases (Campa et al., 2021; Torres et al., 2021).

This policy brief aims to examine the gender-specific nature of the COVID-19 crisis in Georgia. With this aim, we study the differential effects of the pandemic on the economic activity of women in terms of labor market outcomes and entrepreneurship. First, we contrast labor market outcomes for Georgian men and women during the COVID-19 crisis. Secondly, we try to assess the magnitude of the disproportionate impact on women-led businesses compared to men-led ones. We calculate gender gaps across different measures of firm-level performance, such as sales revenue, liquidity and owners’ expectations of falling into arrears. Finally, we examine whether there are any signs of recovery yet in 2021 and draw policymakers’ attention to emerging issues.

Labor market highlights

The adverse effects of the pandemic on female employment were conditioned by both supply and demand-side factors. The latter include decreased economic activity, mainly in service-related sectors (hospitality, personal care, etc.) that are dominated by women (Eurofound, 2021). In Georgia, as of 2019, women constituted the majority of workers in sectors such as hospitality (56%), education (83%) and activities of households as employers of domestic personnel (99%) that experienced some of the sharpest declines in employment during 2020. Moreover, women are more likely to be employed in part-time and temporary jobs (14% of women, as opposed to 11% of men, were employed part-time as of 2019, Geostat Labor Force Survey 2019), leaving them more vulnerable during times of crisis.  Supply-side factors were triggered by the unequal burden of unpaid work generally undertaken by women in Georgia, mainly due to cultural reasons as well as the higher opportunity cost of time for men (women in Georgia on average earned 64% of men’s salaries in 2019, Geostat). School and daycare closures and decreased childcare involvement of grandparents increased household responsibilities for women. A UN Women survey-based study showed that in the midst of the pandemic in Georgia, around 42% of women reported spending more time on at least one extra domestic task as opposed to 35% of men (UN Women, 2020). This would naturally lead to more women than men leaving the labor force. Indeed, looking at the data, we see that in one year after the COVID-19 outbreak, women contributed to 98% (48,000 individuals) of the decrease in the Georgian labor force in 2020 (Geostat). Moreover, a close look at the percentage point difference between the labor force participation rates of Georgian men and women reveals a notable growth in the gender gap starting from 2020. The same can be said about employment rates (Figure 2).

Figure 1. Difference between male and female labor force participation and employment rates

Source: Geostat

To further elaborate on the tendencies in employment, Bluedorn et al. (2021) look at the differences between employment rate changes among male and female workers in 38 advanced and emerging economies. Replicating the exercise with the Georgian data, we can observe results similar to those obtained in Bluedorn et al. (2021). In Figure 2, we see differences between female and male employment rate changes. For each gender group, the latter is computed as an absolute difference between the quarterly employment rate and its annual average level from the previous year. Once the difference takes a negative value, implying that the drop in employment was sharper for women, one could say that we observe a “She-cession” phenomenon as termed by Bluedorn et al. (2021). As we can see, in 2020, the employment rate of women fell more than that of men. This widened gender gap was partially offset in 2021.

Figure 2. Employment rate changes by gender (deviation from the previous year average)

Source: Geostat

Remote work: a burden or a blessing for women?

One important aspect of the COVID-19 crisis was a wide-scale switch to remote work. This development had some gender-specific implications as well. The evidence shows that the prevalence of the switch to remote work was higher among women compared to men (41% vs. 37%) in the EU (Sostero et al., 2020). This tendency also holds in Georgia, where 11% of women as opposed to only 3% of men reported usually working from home in the last three quarters of 2020 (Julakidze and Kardava, 2021). It is not clear whether this tendency can be explained by gender-related occupational differences of male and female jobs (Dingel and Neiman, 2020; Boeri and Paccagnella, 2020; Sostero et al., 2020) or, rather, different personal choices of men and women working in the same occupations. Interestingly, across different countries, we observe a positive correlation between gender inequality (as measured by the Gender Inequality Index) and gender differences in the switch to remote work (measured by the ratio of the share of remote workers among female and male workers). To account for this observation, we can stipulate that gender differences in switching to remote work might be explained by differing gender roles in households, and in society at large, across countries (as proxied by the gender inequality index).

Figure 3. Relative prevalence of remote work among female and male workers

Source: Eurostat, Statistics Sweden, Statista, Geostat, UNDP Human Development Reports

Regardless of the reason, remote work is likely to have some important implications on gender roles. However, the directionality of these implications is not straightforward. On the one hand, remote work offers flexibility for women to juggle household and work responsibilities. On the other hand, since women compared to men have been shown to be more likely to use the time saved from commuting to engage in housework, the switch to remote work might increase their “total responsibility burden” (Ransome, 2007) and lead to time poverty (Peters et al., 2004; Hilbrecht, Shaw, Johnson and Andrey, 2008). Indeed, according to CARE International South Caucasus (2020), around 48% of female survey participants in Georgia placed additional effort into housework and childcare in the midst of the pandemic. Moreover, as women are more likely and expected to use remote working as a means of balancing work-life responsibilities (Moran and Koslowski, 2019) their bargaining power at work decreases relative to their male counterparts. This could have some adverse career implications for female workers. Recent enforced lockdowns might pose an opportunity in this regard, as once-remote work becomes something close to a “new normal” employers will likely decrease the penalty for remote workers.

Spotlight on women-led business performance during the COVID-19 crisis

Calamities brought by the pandemic worsened financial outcomes for enterprises, affecting their ability to operate and have stable financial income. Similar to other crises, the pandemic has not been gender-neutral (Liu et al., 2021; Ahmed et al., 2020) in terms of the effect on business performance.

Gaps in the performance of women- and men-led businesses have been prevalent beyond any economic crisis as well, and have been documented in a number of studies (e.g., Amin, 2011; Bardasi et al., 2011), registering gender differences in sales and productivity in favor of men-owned enterprises. As suggested by Campos et al. (2019), these performance gaps may be due to lower levels of capital owned by women as opposed to men, a smaller number of employees hired by women-owned firms, as well as different practices in using advanced business tools and innovation. In addition, the existence of these gender gaps has also been explained as stemming from the prevailing social norms that assign certain obligations to women. Nordman and Vaillant (2014) and Grimm et al. (2012) suggest that unpaid housework and family-care led to a constrained number of hours women could afford to spend on the work and management of firms, negatively affecting their productivity.

According to the Women Entrepreneurship Report (Global Entrepreneurship Monitor (GEM), 2021), the pandemic imposed an additional burden in terms of increasing family-care duties on women. The GEM survey (2021) conducted in 43 countries worldwide shows that the likelihood of enterprise closure is 20% higher for women-led compared to men-led businesses. The higher likelihood of closure reflects the adverse factors that may have hindered the operating capacity of firms. For example, a survey conducted by UNIDO (2020) suggests that, as a result of the Coronavirus crisis, African and Middle Eastern women-led firms experienced diminished revenues. In addition, 41% of women-led firms were short of cash flow and unable to fulfill financial obligations, while only 32% of male entrepreneurs were exposed to the same problem.

More rigorous analysis on this matter has been conducted by Torres et al. (2021) and Liu et al. (2021). They try to examine the asymmetric effects of the COVID-19 crisis on women-led firms in several dimensions utilizing new datasets from the World Bank: COVID-19 Follow-up Enterprise Survey and the World Bank Business Pulse Survey. The findings of Liu et al. (2021) for 24 countries from Central Europe & Central Asia and Sub-Saharan Africa confirm that during the pandemic women-led businesses are subject to a higher likelihood of closure than men-led businesses and that female top managers are more pessimistic about the future than their male counterparts. Finance and labor factors were mentioned to be the major contributors to these disadvantages; for example, women-led businesses were found to be less likely to receive bank loans compared to men-led businesses. Lastly, the disadvantages experienced by women-led firms were claimed to widen in highly gender-unequal economies and developing countries. Torres et al. (2021) study the impact of the early phase of the COVID-crisis on gender gaps in firm performance for 49 mostly low- and middle-income countries. The results demonstrate that women-led businesses experienced a greater reduction in sales and lower liquidity compared to their male counterparts, which has been reflected in a higher likelihood for women-led companies in several sectors to fall into arrears. On the other hand, as a response to changing circumstances, women-led firms were found to be more likely to increase the utilization of online platforms and make product innovations. Nevertheless, they struggled to obtain any form of public support.

The impact of the pandemic on firms was not gender-neutral in Georgia

The pandemic-induced fragile environment had an adverse impact on entrepreneurs in Georgia– the effects of the shock were significantly more severe for female entrepreneurs than for their male counterparts. In order to assess the gender differences in the impact of the pandemic on firms, we utilize firm-level data on Georgian enterprises from the second round of the World Bank COVID-19 Follow-up Enterprise Survey, conducted in October – November 2020.

Following the methodology as presented in Torres et al. (2021), we assess whether there are differences in the magnitude of reduction in sales revenue (self-reported percentage change in sales revenue one month before the interview as compared to the same period of 2019) and available liquidity for women- and men-led businesses, and whether falling into arrears in any outstanding liabilities is more expected by female top managers (in the next six months from the interview).

Depending on the type of dependent variable, continuous or binary, either Ordinary Least Squares (OLS) or Probit models are estimated, respectively. Along with the gender of the top manager of firms, we also control for sector and firm size. The Georgian database contains a total of 701 enterprises (581 SMEs and 120 micro-businesses).

Table 1. Magnitude of the disproportionate impact of COVID-19 on women-led businesses in Georgia, October-November 2020

Source: The World Bank COVID-19 Follow-up Enterprise Survey, Second Round. Author’s calculations. ***Significant at the 1% significance level; ** significant at the 5% significance level.

Table 1 presents the results of the regression analysis of gender differences among Georgian enterprises in terms of the impact of the pandemic. As observed, women-led businesses reported larger declines in sales, revenues, and liquidity. The predicted drop in sales was 18 percentage points (pp) higher for enterprises with a female top manager than for men-led firms. The larger drop in sales should have been reflected in the reduced cash flow availability and in hardship to cover operating costs. Indeed, as the results demonstrate, women-led enterprises are on average 12.9 pp more likely to have reduced availability of liquidity. This may explain women’s negative future expectations. Moreover, the average predicted probability of expecting to fall into arrears is 11.3 pp higher for women-led firms in Georgia as compared to men-led businesses.

The unequal effect of the COVID-19 crisis on women-led businesses might have been fueled by the disproportionate burden of unpaid care and housework shouldered by women in Georgia, leaving less time available for work and managing enterprises. On the other hand, as Torres et al. (2021) claim, female business owners tend to employ more female workers (the social group more exposed to the unequal burden of the pandemic) than male owners. This, in turn, could further hamper the productivity of women-led businesses and increase their vulnerability to economic shocks.

On the road to recovery

2021 has been characterized by a rather rapid recovery for the Georgian economy, as evidenced by the 10.6% (preliminary estimate) annual growth rate of real GDP. Signs of recovery can also be observed in the labor market – the labor force increased by 4% (YoY) in the 3rd quarter of 2021, while employment was also characterized by a growing trend (1%, YoY).

Along the lines of economic recovery, the gender gap in the labor market also seems to be narrowing. For instance, the steadily growing gap between male and female labor force participation rates seems to stagnate over 2021 (Figure 1). Moreover, as is illustrated in Figure 2 above, the difference between women’s and men’s employment rate changes is positive in 2021, meaning that the employment rate was increasing more (or decreasing less) for women. If this tendency persists, we might stipulate that the disproportionate effects of the COVID-19 crisis on female employment are on the way to recovery.

To examine whether Georgian firms have experienced concurrent movement in their performance along with the economic recovery, we utilize third-round data (from September 2021) of the World Bank COVID-19 Follow-up Enterprise Survey and scrutinize whether the gender differences have narrowed since the previous round of the survey (Table 2).

Table 2. Magnitude of the disproportionate impact of COVID-19 on women-led businesses in Georgia, September 2021.

Source: The World Bank COVID-19 Follow-up Enterprise Survey, Third Round. Author’s calculations. ***Significant at the 1% significance level.

Although the third-round survey data suggests that the predicted percentage drop in sales sharply declined for both men- and women-led businesses, the findings are not statistically significant and therefore cannot claim any signs of recovery in the gender gap in this respect. No signs of recovery are observed in terms of average predicted probability of reduced liquidity of firms and expectations of falling into arrears, either. Gender gaps in these two indicators still persist and are as strong in magnitude as in the second-round survey estimates (from October-November 2020). It seems that despite the economic rebound, not all traces of the pandemic crisis for firms have been eradicated from a gender perspective.

Conclusion

The pandemic came with high economic costs. It hit women disproportionately harder, adversely affecting their employment and entrepreneurial prospects. The unequal burden of the COVID-crisis shouldered by women in Georgia could be one of the reasons for the massive labor force dropouts among female workers and poor performance of women-led businesses. Georgian enterprises with female owners experienced a significantly larger decline in sales compared to their male-owned counterparts, consequently suffering from a shortage of cash flow and fears of falling into arrears.

Despite the great rebound in growth after the initial COVID-19 shock, the pandemic-associated increase in the gender gap seems to have been only partially offset in Georgia. In particular, there is a larger positive upsurge in women’s employment rate, as well as a diminishing difference between male and female labor force participation and employment rates. Following the ongoing recovery in sales revenue of Georgian enterprises (though the predicted gender difference was statistically insignificant), the gender gap in sales is shrinking too. But, in spite of the economic rebound, differences in available liquidity and expectations of falling into arrears have not yet been eradicated, indicating that the adverse influence of the pandemic on women still persists. It leaves female entrepreneurs a still more vulnerable group, which could be of special interest to policymakers to ease their liquidity problems.

Policies should also be directed towards encouraging women to become more economically active. In this regard, remote work seems to pose an opportunity if coupled with affordable childcare support policies.

References

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Female Representativeness and Covid-19 Policy Responses: Political Representation and Social Representativeness

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There is anecdotal evidence that countries with female leadership in policymaking are more efficient in combating the Covid-19 pandemic. This paper studies whether countries with high female representativeness in political and social layers respond differently to the Covid-19 outbreak. We explore patterns at a cross-country level, which enables us to consider the variation of gender implicated institutions. Our findings indicate that it is women’s social representation, rather than female political leadership, that has the potential to capture cross-country variation in Covid-19 policy responses. Our study confirms that well-functioning and effective institutions are not established from the top-down but rather from the bottom-up.

Introduction

In light of the Covid-19 outbreak and the resulting actions developed and implemented by countries worldwide, questions have been raised about government policy responses and what can trigger them. The pandemic brought forward the need for measures that help mitigate the spread of the virus such as hand washing, reduced face touching, face mask policies, and physical distancing. In many countries, the implementation of lockdowns and social distancing measures had a large impact on employment, including reductions in working hours, furloughs, and work from home arrangements (Brodeur et al., 2020; Coibion et al., 2020; Gupta et al., 2020). There are notable concerns about the potential damage non-pharmaceutical interventions can inflict on economies and labor markets (Andersen et al., 2020; Kong and Prinz, 2020). Further, the implementation of these measures requires certain institutional and individual behavioral changes. While some countries were successful in developing and implementing policy responses that addressed the challenges of the pandemic, others have experienced considerable difficulties.

There is anecdotal evidence suggesting that countries with female leadership in governmental policies are more efficient in combating the Covid-19 pandemic. Several articles from prominent media outlets, such as CNN, The Conversation and Forbes, hypothesize that female leaders are systematically better at managing the pandemic and that this divergence can be attributed to gender differences in management style and risk-taking behavior.

This policy paper explores whether countries distinguished by higher female representation in government policies, both in development and implementation, responded differently to the Covid-19 outbreak, and if so, how the response differed from other countries. For this purpose, we identify two layers of female representation: political representation and social representativeness. The layer of political representation considers the role of women’s representation in public policy design and implementation at the top level of executive and legislative institutions. Social representativeness captures women’s representativeness in different layers of society and spheres of life. It reflects social norms, legal inequality between men and women in different spheres of private, economic, and business life, as well as realized gender inequality, e.g., in labor market participation, education, or local leadership.

With respect to political representation, we address the question of whether countries distinguished by a higher female representation at top executive and legislative levels differ in terms of policy responses to Covid-19. With respect to social representativeness, we aim to capture the variation in these responses that may originate from differences in the expected reaction of the public, which in turn is driven by women’s representativeness in different layers of society. We derive evidence-based conclusions capturing the role of female leadership at the country’s executive and legislative level, as well as the role of gender representativeness in other layers and institutions of society.

The motivation for this research stems from the extensive literature on differences in values and social attitudes between men and women. For example, women have been shown to be more trustworthy, public-spirited, and likely to exhibit ‘helping’ behavior (Eagly and Crowley, 1986), vote based on social issues (Goertzel, 1983), score better on ‘integrity tests’ (Ones and Viswesvaran, 1998), take stronger stances on ethical behavior (Glover et al., 1997; Reiss and Mitra, 1998) and behave more generously when faced with economic decisions (Eckel and Grossman, 1998). Thereby, one may ask to which extent these differences transmit to public policies in societies where women are better represented, either politically or socially. While our study primarily concerns Covid-19 policy responses, we discuss other related literature on the relationship between women’s representativeness and public policy in the next section.

Our analysis shows that it is the women’s social representativeness layer, which can explain government reactions to the Covid-19 pandemic. This goes in line with the institutionalist literature, suggesting that more a gender-balanced character of institutions translates into policy measures and related outcomes. With this finding, our study suggests further evidence on the central role of institutions. Consistent with the existing evidence, we claim that well-functioning and effective institutions are not established from the top-down, but rather from the bottom-up (Easterly, 2008; Dixit, 2011; Greif, 2006). In such institutions, women’s participation in labor markets, businesses, and other spheres is essential as these are factors that distinguish countries in their response to the pandemic. While the evidence provided is suggestive, it opens further avenues for studies to assess causal relationships.

Covid-19 Policy Measurements

To conduct our analysis, we collect data from a number of different sources. For data on the Covid-19 situation and government policy responses, we use the Our World in Data portal. This online platform compiles a number of data sources, most of them updated on a daily basis. Statistics on female participation and leadership is retrieved from the World Bank and UNDP. Summary statistics of the variables are reported in Table A1 of the Appendix.

The policy response variables are based on a number of different measures implemented by national governments. These are aggregated into three composite indices: Stringency, Containment & health, and Economic support. (The index methodology can be found here.) We present the components of the three indices in Table 1 and a detailed description of the policy measures and their scoring in Appendix C.

As seen in Table 1, the Stringency and Containment & health indices have some common dimensions; containment & closure policies (C1 – C8) and public information campaign (H1). Both are rescaled to a value from 0 to 100 (100 = strictest). The Economic support index records measures such as income support and debt/contract relief and does not share any common dimensions with the other two policy response indices. The scale of the index also ranges from 0 to 100 (100 = full support). The extent of heterogeneity in government policy responses across countries is illustrated in Figures 1 – 3. While containment and closure policies are stricter in many Asian and Latin American countries, economic support is more extensive in many European countries, Canada, New Zeeland, and few other countries.

 Table 1. The structure of the Covid-19 policy measurements.

Note: Categories and assigned values of policy measurements are in Appendix C.

Figure 1. Stringency Index

Note: A choropleth map shows countries/territories by their Stringency index score, based on data collected from the portal of https://ourworldindata.org/policy-responses-covid. Countries are grouped into five groups (quantiles), from the lowest to the highest values of the index.

Figure 2. Economic support index.

Note: A choropleth map shows countries/territories by their economic support index score, based on data collected from the portal of https://ourworldindata.org/policy-responses-covid. Countries are grouped into five groups (quantiles), from the lowest to the highest values of the index.

Figure 3. Containment & health index.

Note: A choropleth map shows countries/territories by their Containment and health index scores, based on data collected from the portal of https://ourworldindata.org/policy-responses-covid. Countries are grouped into five groups (quantiles), from the lowest to the highest values of the index.

Female Representativeness: Layers and Indicators

Multiple studies in economics and political science suggest that the gender of public officials shapes policy outcomes (Chattopadhyay and Duflo, 2004; Iyer et al., 2012; Svaleryd, 2009). Evidence suggests that increasing the number of women in higher ranks of public administration (legislative bodies and ministries) has a substantial impact on the political office and policymaking (Borrelli, 2002; Davis, 1997; Reynolds, 1999). On the other hand, a number of studies demonstrate that gender has no association with policy outcomes (Besley et al., 2007; Besley and Case, 2003; Bagues and Campa, 2021). The role of the institutional setting and environment can, thus, be decisive in this regard. Women are also found to be more concerned about social policy issues and prefer higher social spending than men (Lott and Kenny, 1999; Abrams and Settle, 1999; Aidt and Dallal, 2008). Further, women are more likely to use a collective or consensual approach to problem and conflict resolution rather than an approach founded on unilateral imposition (Rosenthal, 2000; Gidengil, 1995).

In our study, the political representation layer is measured as female leadership at a country’s executive level (representation in government cabinets) and participation at the legislative institution (parliament) level. To assess this, we consider the following indicators: 1) the presence of a female president or prime minister and proportion of women in ministerial positions, and 2) women’s representativeness in legislative bodies measured as the proportion of seats held by women in national parliaments. The variation of these indicators across countries is illustrated in Figures B4 – B6 in the Appendix.

Our approach to social representativeness is in line with social role theory. This framework provides a theoretical explanation of a structural approach to gender differences (Eagly, 1987; Eagly and Karau, 2002; Wood and Eagly, 2009). It claims that men and women behave according to stereotypes associated with the social roles they occupy, and these differences can, in turn, influence the role of women in local governance and leadership. In line with other research on gender, the social role theory proposes a rigorous framework for analyzing the gendered aspect of government organizations. For instance, evidence shows that women tend to be more collaborative and democratic, hence demonstrating a more caring and community-oriented behavior (Eagly and Johannesen-Schmidt, 2001).

The gender aspect of local governance indicates that the personal preferences and opinions of leaders predominate and shape policymaking (Besley and Coate, 1997). Female leaders (including municipality heads) are more inclined to favor the inclusion of citizens in the decision-making process (Fox and Schuhmann, 1999; Rodriguez-Garcia, 2015), implying that the society is a more informed and engaged stakeholder in the public policymaking (Ball, 2009).  Given that municipalities are taking on a greater and more interactive role in citizens’ well-being, they become a key channel in reinforcing trust in government. Furthermore, the literature finds an interrelationship between female voters and government outcomes, whereby women’s enfranchisement affects government size and spending (Lott and Kenny, 1999; Miller, 2008, Aidt and Dallal, 2008). As such, this can lead to improvements in government outcomes and policy effectiveness. The evidence from Bloomberg’s Covid-19 Resilience Ranking suggests that success in containing Covid-19 while minimizing disruption appears to rely more on governments fostering a high degree of trust and societal compliance.

Furthermore, the patterns of gender relations in societies reflect formal and informal institutional rules and policies. Gender equality enhances good governance and helps to further improve relationships between government and citizens (OECD 2014). Similarly, Elson (1999) argues that labor markets are structured by practices, norms, and networks that are “bearers of gender”. Societies with better legal frameworks for women have more balanced gender participation in labor markets, governance, and leadership, along with more equal gender roles and less gender-biased stereotypes. We anticipate that better representation of women in policymaking in such societies is also reflected in the choice and effectiveness of Covid-19 policy measures.

Building on the above theories explaining the relevance of women’s representativeness in diverse societal layers for policy development and implementation, we identify three indices that have the potential to capture the effect of social representativeness – Women, Business and the Law index (WBLI), Gender Development Index (GDI) and Gender Inequality Index (GII). The WBLI is composed of eight indicators, covering different areas of the law related to the decisions women make at various stages of their career and life. These indicators include mobility, workplace, salary, marriage, parenthood, entrepreneurship, assets, and pension. Hyland et al. (2020) show that, globally, the largest gender inequalities are observed in the areas of pay and parenthood. That is, women are most disadvantaged by the legal system when it comes to compensation and how they are treated once they have children. The index scales from 0 to 100 (100 = equal opportunities). The diagram in Figure 4 illustrates how the components of the WBLI index measure key activities of economic agents throughout their life.

Figure 4. The linkages of 8 indicators in Women, Business and the Law index (WBLI)

Source. Women, Business and Law, 2020. World Bank Group.

The second index, the GDI, measures gender inequality in the achievements in three basic dimensions of human development: Health, measured by life expectancy at birth; Education, measured by expected years of schooling for children and mean years of schooling for adults aged above 25; and Command over economic resources, measured by estimated earned income.  The same dimensions are included in the Human Development Index (HDI), and the GDI is defined as the female-to-male HDI ratio (i.e. perfect gender equality corresponds to a GDI equal to one).

Turning to the third index measuring social representativeness, the GII reflects gender-based disadvantages in the following dimensions—reproductive health, empowerment, and the labor market. The index measures the loss in potential human development due to gender inequality in achievements across these dimensions. It ranges from zero, where women and men fare equally, to one, where one gender fares as poorly as possible in all measured dimensions. One of the dimensions of the GII, women’s empowerment, has a sub-dimension – “Female and male shares of parliamentary seats”, one of our indicators measuring political representation. Generally, we do not consider the two layers being as mutually exclusive, but intersections are expected to be minimal.

Central to our study, the three indices capturing social representativeness in a country encompass the institutional quality of its society from a gender development perspective. The distribution of each index across countries is shown in Figures B1 – B3 (See Appendix B).

Women’s Representativeness and Covid-19 Policy Responses: Partial Correlation Analysis

In this section, we explore the relationship between Covid-19 policy responses and the measures of political representation and social representativeness. For this purpose, we explore (i) correlations between the indicators and indices of the political and social representation layers and (ii) partial correlations between these measures and policy response indices.

We start with a correlation analysis of the different indicators in the layers. It shows that the WBLI is in high correlation with other representativeness variables. This index captures the legal equality between women and men which has been shown to be “associated with a range of better outcomes for women, such as more entrepreneurship, better access to finance, more abundant female labor supply, and reductions in the gender wage gap”. (WB, 2021). One can think of the GDI and GII indices, as well as the political representativeness indicators, as reflections of a broad policy framework in diverse areas of social, business, and legal activities. A legal environment that promotes gender equality, even if not sufficient by itself, is likely to lead to progress in these areas. Indeed, Hyland et al. (2020) show that greater legal equality between men and women is associated with a lower gender gap in opportunities and outcomes, fewer female workers in vulnerable positions, and greater political representation of women. This way, the WBLI may capture key predispositions for women’s representativeness in society. Further, Hyland et al. (2021) show that the WBLI index is in high (partial) correlation with country GDP per capita, polity score, legal origin, religion and geographic characteristics. This evidence suggests that the WBLI may have the capacity to reflect important country characteristics which ultimately shape cross-country institutional variation.

Table 2. Scatterplot table for GDI, GII and Women, Business and the Law Index, Proportion of seats in parliament held by women and Proportion of ministerial seats held by women.

Note: Scatterplots are constructed for 149 countries. Fitted lines are based on a quadratic function, shaded areas indicate 95 percent confidence intervals and country population is used for weights applied for fitted lines and bubbles. For each scatterplot, correlation coefficients and their significance are reported. *** p<0.01, ** p<0.05, * p<0.1.

Next, we explore partial correlations of these indicators with Covid-19 policy responses (Table 3). In this analysis, we control for a number of factors that potentially confound the relationship between a particular policy response and representation layer. Specifically, we control for (i) the number of infected cases per million inhabitants, (ii) the number of deaths per million, (iii) GDP per capita, and (iv) life expectancy. The number of infected cases and deaths enter the model in order to control for country differences in the spread and consequences of the virus. GDP per capita captures the stage of country development, accounting for cross-country differences in resource capacities and constraints. Both of these control variables are claimed to have an important role in Covid-19 related research (Coscieme et al., 2020; Aldrich and Lotito, 2020; Elgar, Stefaniak and Wohl, 2020; Gibson, 2020; Conyon and Thomsen, 2020). Life expectancy is an important proxy for country inhabitants’ resilience against the virus, conditioned by health and health infrastructures.

Significant correlations are observed between the WBLI and the three policy response indices. The correlation between the WBLI and Stringency (and Containment & health) index is negative, implying that lighter restrictions have been imposed in countries with better business and legal conditions for women. A positive correlation is observed between the WBLI and the economic support index, suggesting that countries with better conditions for women in diverse business and societal areas have provided more extensive economic support in the pandemic. This finding is in line with existing evidence showing that women are more concerned about social policy issues and prefer higher social spending than men (Lott and Kenny, 1999; Abrams and Settle, 1999; Aidt and Dallal, 2008). Also, lighter restrictions and more generous economic support do not presume any trade-off in terms of the allocation of financial resources constrained by a state budget.

Interestingly, we do not observe significant correlations between policy responses and other indicators of women’s representativeness. The only exception is a correlation between GDI and the Containment & health index, which is significant at the 10% level and hinges heavily on two outliers (if we drop the two outliers, the P-value of the correlation increases from 0.0931 to 0.2735).

Table 3. Scatterplots of policy responses and social representativeness and political representation variables.

Note: Scatterplots are constructed for 133 countries. Fitted lines are based on a quadratic function, shaded areas indicate 95 percent confidence intervals and country population is used for weights applied for fitted lines and bubbles. Correlation coefficients are reported with significance levels: *** p<0.01, ** p<0.05, * p<0.1.

In our partial correlation analysis, we do not control for the direct effects of the gender dimension of social norms and practices. Social norms, practices, as well as informal and formal rules can, however, explain a substantial part of the gender gap (Hawkesworth, 2003; Mackay, 2009; Franceschet, 2011; Elson, 1999; Froehlich et al., 2020) relevant for making decisions. Our measures of women’s political and social representativeness do not fully cover gender differences in norms and practices. As Hyland et al. (2020) point out, de-jure female empowerment does not necessarily translate into de-facto empowerment, especially in countries with social norms and informal rules that result in low representation of women in diverse societal spheres. The authors indicate that laws are actionable in a short period, while more time is needed to bring changes in social norms.  In our paper (Grigoryan and Khachatryan, 2021), we attempt to address this issue by incorporating the Social Institutions and Gender Index (SIGI) into the model and evaluating the confounding effect on the covariates of the model. We show that the WBLI captures the effect of the gender gap owing to social norms and practices on Covid-19 policy responses as measured by SIGI. This result suggests that the endogeneity arising from the omission of a measure of such a gender gap is likely to be minimal.

Discussion and Conclusions

Our correlation analysis suggests that it is the layer of women’s social representativeness that can explain the policy reactions of governments in times of the Covid-19 pandemic. This result is in line with the institutionalist literature on gender inequality and social role theory, which suggests that a more gender-balanced character of institutions translates into policy measures and related outcomes. Among the three indices constituting the social representativeness layer, the WBLI is, by construction, more inclusive in terms of capturing women’s role in diversified societal areas. From Table 2, we observe that the WBLI is the only index that is in strong correlation with all other indicators. We also identify strong dominance of the WBLI in correlations with policy responses: it is the only indicator that is significantly correlated with all three policy response measurements (Table 3).

To conclude, our results establish an association between female social representativeness, as measured by the (legal) equality of opportunities between men and women, and Covid-19 related policies. One potential interpretation of these findings concerns the central role of the gender balance in different institutions and layers of society in understanding policy responses to the Covid-19 pandemic. While it was parliaments and governments that implemented policies, we find that the measures undertaken correlate more strongly with factors related to the social representativeness of women rather than those related to their political representation. This suggests a dominant role of gender-balanced institutions at the ‘grass root’ level in terms of the scale and scope of the crisis response. Naturally, these institutions may result (or be correlated) with more gender-balanced political representation, but the latter alone is not helpful in explaining the variation in the reaction to the pandemic.  These results underline the importance of balanced gender representation in the labor market, business, and other spheres of social life.  Further investment and development of ‘grass root’ institutions that improve women’s socioeconomic opportunities, could provide a fundamental foundation for policy development in a crisis situation.

There could also be alternative interpretations of our findings. There is rich evidence that the gender dimension is deeply implicated in institutions (Acker, 1992; Chappell and Waylen, 2013; Lovenduski, 2005). Gender norms and gender practices have been shown to have an influence on the operation and interaction between formal and informal institutions (see, for instance, Chappell, 2010; Krook and Mackay, 2011; Chappell and Waylen, 2013) and the gender dimension of political institutions is reflected in their practices and values, hence affecting their outcomes (such as laws and policies), formation, and implementation (for instance, Acker, 1992). In turn, governmental policies and rules shape societal norms and expectations. These considerations imply that our results could be driven by the overall values, culture, and institutions of respective societies. These factors would both result in a more gender-neutral legal environment and ‘grass-root’ institutions, and ultimately, distinguish countries in their response to the Covid-19 pandemic. In this way, our results open an avenue for future studies in this important domain to better understand the causality of observed relationships.

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(The Appendix can be found in the PDF version of the brief)

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Public Healthcare Expenditures in Transition Countries: Does Government Spending Respond to Public Preferences?

An image of surgery room with two doctors in green protection gear representing public healthcare expenditures

The transition from centrally planned to free-market economies in 1989 initiated a period of social and economic upheaval in post-communist countries, which affected healthcare quality, expenditures, and outcomes. We use data from the Life in Transition Survey (LiTS) to demonstrate that in spite of improvements across various measures of these facets of the healthcare system, it remains the first choice for additional government spending among the public in all countries of the region included in this study. Preferences in priorities for extra budget spending were similar among men and women in respective countries, but the preference for additional healthcare spending was stronger among women than men. The transition countries are compared with Germany and Italy – two Western European LiTs survey participants, countries with higher spending, and better healthcare outcomes.

Introduction

Across the globe, the outbreak of the COVID-19 pandemic has brought a new spotlight to the preparedness of healthcare systems for profound shocks (Anser et al, 2020). Critical care is a particularly costly element of healthcare provision, and thus, under-resourced systems are uniquely susceptible to spikes in mortality resulting from an oversaturation of intensive care units during an epidemiological crisis of this sort. (Fowler et al, 2008; Mannucci et al, 2020) Considering the widespread discussion surrounding health system capacity and the necessity for implementing economically painful lockdowns when those limits are reached, pressure from society to increase public spending may grow even further. With these developments in mind, in this policy paper, we confront past expressions of preferences regarding public expenditures with changes in government spending on healthcare between 2006 and 2017. The analysis draws on the one hand on the data from the Life in Transition Survey (LiTS), and on the other on publicly available data on government expenditures and outcomes.

In the context of preferences for additional public spending, we present a descriptive summary of trends in government expenditures on healthcare in Armenia, Belarus, Estonia, Georgia, Latvia, Lithuania, Moldova, Poland, Russia, and Ukraine. We include Italy and Germany as wealthier Western benchmarks, for which the data became available in the second wave of the survey in 2010. Data on public healthcare spending shows that despite a clear and strong public preference for increased investment in healthcare provision, additional spending as a proportion of total government expenditures between 2006 and 2017 has been moderate in most countries, and even negative in some. It must be underlined that expenditures are not always reflected in healthcare outcomes, quality, and coverage. Issues of efficiency, system design, and underlying health conditions of the population play a significant role in the returns on investment. For instance, the United States has spent drastically more per capita on healthcare than any other country and yet ranked lowest in the Healthcare Access and Quality (HAQ) Index among comparable countries (Fullman et al, 2016). However, due to the focus of the survey on government spending, we emphasize government expenditures on healthcare as a pertinent measure, especially in relation to overall GDP, per capita spending, and the public budget as a whole.

There is mounting evidence that one of the most important elements in the mitigation of COVID-19 mortality is the ability to expand system capacity and acquire the necessary equipment (e.g. respirators, ventilators) while ensuring that there is equitable access to measures for spread prevention (e.g. testing) (Khan et al, 2020; Ranney et al, 2020; Wang and Tang, 2020). The increasing pressure on healthcare systems, coupled with the additional fiscal strain resulting from the economic fallout of the pandemic, could lead to further divergence between public preferences and government spending on healthcare.

Healthcare Systems During the Transition

The ability of transition countries to absorb the risks and short-term economic shocks associated with pivoting from a centrally planned to a free-market economy has had dramatic implications for healthcare systems. Although countries in this region were divergent in terms of underlying health conditions, levels of expenditures, and health outcomes, most of them fell victims to deficient funding and additional health risks associated with the initial increases in poverty that were commonplace (Adeyi et al, 1997)

Compared to other transition countries, Georgia and Armenia faced a sharper economic collapse as well as armed conflicts, which caused scarcity in the availability of public healthcare providers and spikes in out-of-pocket expenses. Belarus was slower in the implementation of economic reforms and faced issues of fiscal sustainability further down the line (Balabanova et al, 2012). However, following this short tumultuous period, countries transitioning away from centrally planned economies have generally invested heavily in healthcare since the early 1990s. In many cases, these investments were facilitated by rapid GDP growth and accompanied by significant improvements in life expectancy. For example, between 1989 and 2012, Latvia, Lithuania, and Poland increased their per capita healthcare expenditures by more than 1,000 PPP per year, with an increase in life expectancy ranging from 1.7 years in Lithuania to 5.8 years in Poland (Jakovljevic et al, 2015). Despite heterogeneous and extensive reforms in many of these countries, as well as mixed results in measurements of efficiency and outcomes, healthcare expenditures consistently rank as the top priority for further government spending among both men and women in each country. This consistency lends itself to further policy considerations.

Preferences for Government Spending in Transition Countries

As is demonstrated by Figure 1, in 2016, healthcare was the most common answer to the question – “Which field should be the first priority for extra government spending?”- for all ten post-transition countries included in our analysis (the other options were: education, housing, pensions, assisting the poor, public infrastructure, the environment, and other). The survey was carried out on a representative sample that covers approximately 1,000+ respondents from each of the 29 countries in wave I and up to 1,500+ respondents from each of the 34 countries in wave III (EBRD: LiTS, 2020). Despite intercountry differences, in 2016 healthcare persisted as the top priority for both men and women in every transition country we studied apart from Belarus. While healthcare remained the top priority on average, men expressed a higher preference for additional investment in education. In the countries where preferences for health were particularly strong, healthcare was the first priority for as many as 53.5% of Latvians, 47.7% of Poles, and 43.9% of Moldovans (Figure 1a). Notwithstanding some fluctuations in scale, these preferences were not only common across countries but also across time, with people expressing very similar preferences in the first two waves of the survey in 2006 and 2010. (See Annex Figure A1 and Figure A2). While healthcare remained a popular choice in Germany and Italy, spending on healthcare as a percentage of GDP was nearly twice that of any transition country in Germany. There, education outweighed healthcare among men and women in both available waves (II and III), while pensions surpassed healthcare among men in the latter wave. In Italy, despite a more comparable level of healthcare spending relative to the transition countries, a drastic shift took place as healthcare fell from being the first priority by a large margin of 24.9 percentage points (pp) in 2010 to becoming the second priority after pensions in 2016. This can likely be attributed to the prominence of pensions as a major political campaign issue following the austerity-driven reforms of 2011 (Alfonso and Bulfone, 2019).

 

Figure 1: 1a (left) : Preferences for additional government spending, 2016. / 1b (right): Preferences for additional healthcare spending by gender, 2016

Source: LiTS Wave III data (2016). Notes: Figures show proportions of declared preferences as replies to the question: “Which field should be the first priority for extra government spending?” For clarity of exposition the category ‘social assistance’ aggregates first priority choices of ‘assisting the poor’ and ‘housing’; the category ‘other’ also includes the least popular choices ‘public infrastructure’ and ‘environment’.

Moreover, it is evident that men and women within countries have rather similar preferences, as far as extra government spending is concerned. Not only is healthcare the first priority in all ten transition countries, but their second, third, and fourth choices are also very similar. When digging deeper into the differences that do exist, in every country except for Georgia women had a stronger preference for healthcare than men, and by as much as 8.8 pp, 8.4 pp, 7.8 pp, and 7.9 pp in Latvia, Germany, Belarus, and Russia respectively (Figure 1b). Conversely, in every case except for Georgia and Ukraine, men had a stronger preference for additional spending on education than women, most notably in Armenia – by 7.8 pp, Germany – by 5.7 pp, Lithuania – by 4.6 pp and Poland – by 3.9 pp. It is apparent that despite rapid investment in healthcare over the first two decades of the transition, there remains a widespread desire for further expansion of expenditures in this area.

Trends in Government Expenditures, 2006-2017

Considering the primacy of healthcare as the priority for additional government spending in all ten studied transition countries, we look at trends in aggregate statistics on government expenditures on healthcare over the surveyed period to explore the extent to which these preferences have been reflected in government spending. Taking the most basic measure into account in Figure 2a, i.e. public health expenditures as a percentage of GDP, among the transition countries only Georgia and Estonia have significantly increased their healthcare expenditures, by 1.6 pp and 1.2 pp, respectively. Lithuania, Poland, and Russia saw more moderate increases in the range of 0.6 pp and 0.2 pp. Other countries have remained essentially stagnant, apart from Moldova and Ukraine which saw a notable drop of 0.8 pp.  Considering that this measure is sensitive to fluctuations in GDP growth, we also consider public health spending as a proportion of all government expenditures (see figure A3 in the Annex), which is a better indicator of government priorities for additional spending from 2006 until 2017. Georgia was the only transition country with a significant increase in healthcare spending proportional to total government expenditures, nearly doubling it from 5.2% to 9.5%. Belarus, Estonia, Lithuania, Poland have implemented a more moderate redirection of the budget towards healthcare, increasing proportional expenditures by a factor of 1.26, 1.15, 1.21, and 1.21 respectively. In spite of public preferences, Armenia decreased the proportional share of the budget dedicated to healthcare by as much as 2.6 pp, Moldova, Russia, and Ukraine by 1.3 pp, and Latvia by 0.8 pp. Regardless of the direction of the trend, notwithstanding some slight convergence, no transition country spent as much of its budget on healthcare as Italy and Germany. The latter spent nearly two to four times as much on healthcare as a proportion of total expenditures compared to the studied transition countries, and this gap has been widening relative to all of those included in the analysis, apart from Georgia.

Figure 2: Public healthcare expenditures (% of GDP)

Source: WHO, 2020

While expenditures per capita are less indicative of government priorities in the budget, they are a better comparative measure for assessing the changes in healthcare provision, barring differences in efficiency. This comes with a huge caveat, namely that it is well established in the literature that additional healthcare expenditures often translate into “small to moderate” direct improvements in healthcare quality and outcomes due to inefficient spending or underlying factors (e.g. lifestyle choices, poverty) that are not addressed by investment in the healthcare system itself (Hussey et al, 2013; Self and Grabowski, 2003).  Nevertheless, this measure is more likely to translate to an improvement in the quality of care each person receives, and the data paints a more positive picture considering the clear preference of both men and women for higher spending. In Figure 3 we present healthcare expenditures per capita in USD, and apart from Italy and Ukraine, all of the countries have significantly increased spending between 2006 and 2017. While expenditures per capita in transition countries are dwarfed by Germany and Italy, Estonia, Georgia, and Lithuania have more than doubled their expenditures, and Armenia has more than tripled. Belarus, Latvia, Poland, Moldova, and Russia have also significantly increased their per capita spending on healthcare, by factors in the range of 1.54 and 1.91. However, while expenditures per capita is one indicator of improving healthcare quality, it does not identify government priorities and is largely dependent on overall economic growth (Fuchs, 2013; Bedir, 2016).

Figure 3: Health care expenditure per capita, USD

Source: WHO, 2020

In every country we include, increasing healthcare expenditure per capita is accompanied by advancements in many measures of healthcare outcomes for men and women. Between 2006-2017, life expectancy at birth increased across the board, with men in Russia experiencing the greatest improvement of 7.1 years (Figure 4a). These are promising trends – for women, life expectancy at birth improved by a larger margin in each transition country than in Germany or Italy, and the same can be said for men in every country apart from Armenia. Furthermore, the Healthcare Access and Quality (HAQ) index, which is composed of 32 indicators related to preventable causes of mortality, has improved across all 12 countries between 2005-2016. The change was most notable in Armenia, Belarus, Estonia, and Russia, constituting as much as 8.7, 10.2, 8.9, and 8.9 points out of a hundred, respectively (Figure 4b). These trends indicate convergence in the quality of healthcare as they significantly outpaced improvements in the HAQ index in Italy (3.1 points) and Germany (3.9 points). As of 2016, among the countries of interest, Georgia (67.1 points) and Moldova (67.4) had the lowest scores, while Germany (92.0) and Italy (94.9) scored highest, as could be expected based on healthcare spending measures presented in Figures 2 and 3.

Figure 4: 4a (left): Change in life expectancy, 2006-2017 / 4b (right): HAQ index

Source 4a: The World Bank (2020). Source 4b: Institute for Health Metrics and Evaluation (2018). Notes: The HAQ index is composed of 32 indicators, each related to a cause of death that is preventable with the proper healthcare. The scale ranges from 0 (worst) to 100 (best).

However, as presented in Figure 5, there is no clear relationship between the strength of the preference for additional healthcare spending and the scale of expansion in spending. Taking three of the four countries (Armenia, Belarus, and Russia) with the greatest improvement in the HAQ index as an example, there was virtually no change in healthcare spending as a percentage of GDP over the same period. These countries were also different in terms of how strong the preferences were for additional spending on healthcare as the first priority in 2006.

Figure 5: Public preferences and government healthcare spending (% of GDP)

Source: LiTS Wave I data (2006), The World Bank (2020). Notes: Germany and Italy were not included in the 2006 wave of the LiTS survey; thus, they are not shown here.

Conclusion

As we have demonstrated in this brief, in the ten post-communist countries for which we have analyzed LiTS data, there was a consistent and common preference for healthcare as the first priority for extra government spending between 2006 and 2016. We also find that in each country except Georgia, on average, women had a stronger preference for additional public healthcare spending, supporting a wealth of literature that suggests that women utilize healthcare services more frequently and spend more out of pocket on healthcare than men (Owens, 2008; Cylus et al, 2011; Williams et al, 2017). However, over the period we study, these preferences have not translated directly into a reallocation of budgetary resources. The countries with the strongest preferences for additional healthcare spending in 2006 did not experience the highest increases in any of the discussed measures of public healthcare expenditures since then.

People living in Italy and Germany chose an increase in public spending on healthcare as their first priority less frequently than residents of post-transition countries. Better understanding these differences requires further research, but there is likely a combination of factors that play into this effect. For one, wealthier Western countries performed better when looking at simple measures of healthcare outcomes such as life expectancy and deaths from non-communicable diseases (WHO, 2020), and hence other priorities may have gained in salience. Furthermore, they allocated a greater proportion of the public budget towards healthcare. This in part stems from the significant challenges associated with the transition following 1989. Healthcare systems in post-communist countries experienced a fiscal shock when joining the global economy, with the loss of centrally controlled price mechanisms causing an increase in the relative prices of healthcare inputs such as medicines and equipment (Obrizan, 2017). This was exacerbated by a shrinking capability of governments to spend more on healthcare related to the general economic shocks at that time and led to the passing over of costs to patients in the form of out-of-pocket expenses (Balabanova, et al. 2012).  Although access to healthcare and the quality of that care have improved after the transition (Romaniuk and Szromek, 2016), these have failed to converge towards Western European countries on a number of substantial measures up to this point. Before the commencement of the COVID-19 pandemic, government healthcare spending did not reflect the preferences of the public in any of the ten studied transition countries. The outbreak of the pandemic has not only intensified the pressure on the healthcare system but also brought about a number of negative economic consequences. This combination can be expected to simultaneously increase the strain on the public budget and necessitate difficult decisions of reallocation at a time when fiscal sustainability during a global recession is already being brought under question (Creel, 2020).

References

Note: Annex included in the attached PDF.

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

The Social Impacts of Covid-19 – Case for a Universal Support Scheme?

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Beyond its impact on the healthcare system, the Covid-19 pandemic has already reached labor markets throughout every economy via economic shocks. As of 1 April 2020, ILO estimates indicate a substantial rise in global unemployment, leading to a 6.7% decline in working hours in the second quarter of 2020, which is equivalent to 195 million full-time workers.[1] In this policy note we will draw the reader’s attention to the potential scale of the impact on the labor market and the respective social consequences in Georgia. We will identify a wide variety of groups affected by the Covid-19 crisis, with a special emphasis on the labor market, and provide our judgement on the possible extent of the repercussions. The current crisis affects almost every segment of the population, including members of the following large social groups:

  • Labor market participants face high risk of job loss. Fewer employment opportunities and broad scale layoffs force a large section of self-employed and salaried workers into challenging circumstances.
  • Recipients of Targeted Social Assistance (TSA) are at great risk of slipping deeper into poverty. While members of this group mostly rely on social assistance layouts, the supplementary income that they receive, often from informal sources, could be cut. In addition, the increased prices on food and other essential goods could be particularly detrimental to this group of people.
  • Senior citizens are extremely exposed to the danger of the virus and struggle with greater health risks.

Our analysis starts with an overview of the Georgian labor market and the short-term impacts of Covid-19 on workforce displacement throughout the various sectors. The impact is not gender neutral, as it affects men and women differently depending on the sector. Therefore, we will further provide the decomposition of the impacts on the labor market and propose gender-responsive solutions to the pandemic. To mitigate adverse effects across various vulnerable groups, we will review the existing theoretical and practical evidence on targeted and universal support schemes. An overview of international social support programs is moreover provided in this note. We will further analyze the relative merits and drawbacks of our pre-defined policy options based on a multi-criteria assessment in the context of the Covid-19 crisis and thereafter provide recommendations for policy implementation.

Covid-19 – Impact Across Sectors and an Overview of the Labor Market

Unemployment in Georgia is expected to experience a large-scale increase in the short-term, leading to massive social problems. Workers have been told to remain at home because of the broad virus containment measures taken during the outbreak. Those with the opportunity to work from home are relatively well-off, unlike the large variety of vulnerable groups affected by the lockdown. Low levels of economic activity impact almost all industries, and the most vulnerable sectors include accommodation and food services, most wholesale and retail trade and entertainment and recreation. These difficulties place hundreds of thousands at risk, either by downward adjustments to income or working hours, or by completely losing their jobs.

In order to evaluate Covid-19’s potential short-run effect on employment across various economic sectors, we have qualitatively assessed the strength of the impact at the sub-sectoral level,[2] taking into account the following: (1) list and scale of economic activities prohibited during the ‘lockdown’; (2) restrictions imposed on transportation; (3) drop in consumer demand; (4) fall in intermediate input use.

In Table 1 we present our assessment of the Covid-19 impact across sectors, coupled with the corresponding labor market statistics.[3]

Table 1: Covid-19 impact on possible workforce displacement across sectors.

Source: Authors’ sectoral assessments and calculations based on Geostat Labor Force Survey (LFS 2018).

The key findings from the labor market assessment include:

  • Close to 30 percent of hired workers face a high risk of job displacement, mostly driven by an expected fall in economic activity in the trade, construction, manufacturing, and accommodation and food services sectors;
  • The least impacted industries are projected to be education, public administration and defense, utilities, and health;
  • The majority of self-employed are active in the agricultural sector, which faces a moderate impact for several reasons: the closedown of open food markets, restrictions on transportation, and a partial decline in demand (mostly from the food service sector). Although agriculture is not projected to be severely affected, a substantial number of the self-employed (mostly subsistence farmers) in this sector, considering their significantly lower than average baseline earnings, may require special policy emphasis within this group.

Finally, it should be emphasized that the severity of impacts across sectors will further depend on the longevity of the lockdown measures and the sequence in which they may be lifted for different economic activities.

In addition to the assessments in Table 1, Annex 1 presents a correlation between our estimates weighted by sub-sectors and the ILO’s assessment of the current global impact of the crisis on economic output across the sectors. It should be further noted that, in most cases, the scale of impacts coincide, and the remaining differences are due to: (1) our approach being based on more detailed sub-sectoral data; (2) the ILO looks at the global impact, whereas we focus solely on Georgia.

Short-term Workforce Displacement Risks in Vulnerable Sectors

To alleviate social problems stemming from the labor market shock during the strict, short-term quarantine measures, the clear need for safety net programs has raised the important questions of how they should be designed and who the recipients of support should be.

The discussion of social program designs requires a thorough analysis of the potential target groups. As mentioned in the previous section, after drastic quarantine and lockdown measures, many people in Georgia are at risk of finding themselves without jobs or with decreased salaries and earnings, which, in turn, is a main cause of social problems, like the inability to provide food and other necessities. The highly affected groups, as outlined in Table 1, can be clustered across the following sectors of economy:

  • The accommodation and food service sector is currently the most directly and highly affected sector. Hotels and restaurants are completely closed for an uncertain period, except for the food delivery business. However, even this is constrained to certain periods of the day, since according to the state’s emergency rules after 21:00 all movement, including delivery, is forbidden.

Most people hired within accommodation businesses face temporary job loss. This group includes hotel administration staff, housekeeping staff, people working in hotel restaurants, etc. Similarly affected are employees in restaurants and cafés, faced with cutbacks in salaries, if not complete job loss.

Another significant group within this sector are the self-employed. Owners of small family hotels and restaurants, typically dependent on tourism expenditure, now find themselves without any cashflow.

  • A significant portion of the wholesale and retail trade sector also faces major shutdowns. To begin with, employees of trade centers and individual stores are now out of work for an indefinite period. These include consultants in clothing stores, hardware stores, household appliance stores, etc. A very limited number of shops that continue to work via online sales have retained several employees on decreased salaries.

The reality is also harsh for the self-employed in retail trade. Open marketplaces, including construction materials shops and farmers’ markets have been shut, and such people are left without a vital income source. It should also be noted that most of these workers are members of a lower social strata and are less likely to have enough, if any, savings for the quarantine period.

  • As for the relatively small, but equally affected, arts, entertainment and recreation sector, art galleries, museums, night clubs, theatres, movies, and sports and spa facilities, have all been closed down due to their ‘non-vital’ function. Salaried as well as self-employed workers in these sectors found themselves without employment soon after the state emergency was announced.
  • Additional highly affected groups are those hired and self-employed in the transportation sub-sectors. The closing of public transportation has left hired bus, metro, and minibus drivers entirely without work.

Other than hired employees, self-employed drivers for intercity transportation are now left without work since intercity commuting is now forbidden under the state of emergency. Comparatively less affected are self-employed taxi drivers, who are still allowed to work, however only between 06:00-21:00. The fact that many drivers previously worked night shifts, combined with declined daytime demand, results in significant cutbacks in daily earnings for taxi drivers.

  • Another significantly affected group are those workers employed in households. These include housemaids, nannies, private tutors, handymen, etc. Since everyone is being cautious and following social distancing instructions, many households have dismissed their hired help for an indeterminate period, and even those still employed have a hard time getting to work due to the suspension of public transport, and are therefore left without vital daily income.
  • The agriculture, forestry, and fishing sector, the largest in terms of employment, remains less affected relatively, though it is facing restrictions since restaurants and cafés require fewer agricultural products than before. Moreover, as farmers’ markets have closed, their access to marketplaces has become significantly constrained. Farmers are now supplying only supermarket chains and restaurants with delivery services, a significant economic decrease compared to the normal environment. It should also be noted that self-employed small farmers are in the majority in the sector. Such workers are likely without strong links to supermarket chains or restaurants, and therefore, they will be more noticeably affected by the economic impact.

An important specificity of self-employed and domestic workers is that many are also informally employed, thus their identification by official sources (i.e. in tax returns or small business registers) is extremely problematic. Thus, the existence of a large variety of potentially affected groups, as well the inability to correctly estimate the severity of impacts across groups, highlights the need for a temporary social protection mechanism that will cover all affected parties, particularly since the people included in the groups above are not typically the main recipients of social assistance programs.

Decomposition of Labor Market Impacts by Gender

In this section, we present the gender decomposition of labor market impacts, and conclude that unemployment-driven assistance may benefit men considerably more than women.

Chart 1 summarizes the distribution of self-employed and salaried men and women across low, medium, and highly affected industries, based on the sub-sectoral assessments previously described and using gender-disaggregated employment data.

Figure 1: COVID-19 impact on possible workforce displacement, by gender

Source: Authors’ sectoral assessments and calculations based on Geostat’s Labor Force Survey (LFS, 2018).

It is evident that the proportion of employed men is significantly higher in the most vulnerable sub-sectors. Such a picture is highlighted by the high male-employment ratios in construction, transportation, and parts of manufacturing, as well as the high female-employment in the minimally affected education and healthcare industries[4].

To summarize, during the current crisis men are more susceptible to job displacement, and if a social assistance policy is solely based on labor market outcomes, they will yield higher benefits. Such social support mechanisms will deepen existing gender inequalities[5] in the country as women face disproportionate and increasing burden of care work (in situation of lockdown).

Social Assistance Policy Objectives in a Crisis

Considering the diversity of groups influenced by the lockdown, any assistance program should have several main policy objectives:

  1. Maximizing the reach of a policy to those in need and minimizing their risk of impoverishment – a large part of the population is affected by the lockdown, thus there is a substantial risk of increasing poverty directly from job loss and indirectly via job losses within families. Social assistance should, in a best-case scenario, reach the maximum number of disadvantaged people, while avoiding providing assistance to the affluent.
  2. Minimizing fiscal pressure – social assistance can create substantial pressure on the budget, especially in the current situation as revenues have decreased due to the lockdown. Furthermore, people who do not require support should not receive assistance, thus, decreasing unjustified pressure on the budget.
  3. Progressivity and gender responsiveness – an assistance program should provide proportionally larger support to those in greater need and aim to balance support by gender.

To mitigate the negative social impact of the economic lockdown, the government will have to provide significant and effective social assistance. And this is where all governments face a key dilemma, as they decide between providing targeted versus universal assistance.

An Overview of Targeted vs. Unconditional Universal Assistance

Targeted assistance is based on the methodology to define target groups, this could be under a points-based system (similar to current targeted social assistance available in Georgia) or a certain criterion defining affected groups. Under any targeting approach, two major challenges exist: (i) missing certain affected people (exclusion error), where defining an ideal criterion is impossible; and (ii) supporting those who do not require any assistance (inclusion error). Hanna and Olken (2018)[6] show that targeted programs have the potential to maximize welfare, however, they require a substantial amount of data and effort to minimize errors in the inclusion and exclusion of recipients. They further illustrate that, under normal circumstances, to reach 80% of poor people, the inclusion error will be around 22-31%. Deciding on a targeting methodology can also be costly and time consuming. Klasen and Lange (2016)[7] highlight that there is little difference between simple targets, such as demography or geography, and more complex asset-based measures, and both make poor proxies as they do not capture poverty effects in great enough detail.

In contrast, a universal support scheme can also be considered; defined as an unconditional transfer to every member of society. From the administrative perspective it is substantially easier to organize and administer, as it will not require the formation of targeting methodology or identification of target groups. Compared to targeted assistance, universal support will simply not have exclusion errors. However, the universality of the scheme would be associated with large inclusion errors. Nevertheless, considering the current situation in Georgia, with a large variety of affected groups, the inclusion error need not be as high as in normal circumstances. As previously noted, due to the lockdown, the number of vulnerable groups will have increased substantially.

Unlike targeted support schemes, there is limited practical evidence behind the implementation of universal programs (Banerjee et al., 2019).[8] However, some of the impacts can be identified from existing pilot case studies, impact assessments of existing targeting schemes, and an analysis of theoretical knowledge. The key here is that the expected impacts depend substantially on the duration and type of the support scheme (i.e. direct cash transfers, provision of vouchers or coupons, tax credit).

For our purposes we assume that the duration of the support scheme will be relatively short-term (related to the length of the lockdown). Furthermore, there is nearly no practical evidence on the impact of the long-lasting universal support schemes (Banerjee et al. 2019). Theoretically, long-lasting universal support can have a negative impact on labor force participation. Moreover, Banerjee et al. (2017)[9] finds no evidence that unconditional transfers discourage work. Considering the characteristics of the crisis, labor market participation is already limited because of the lockdown.

In addition, direct unconditional cash transfers could serve the progressivity purpose well, as households in greater need will receive a larger portion of their income, compared to those who require less assistance. Progressivity will depend on whether the recipient of a cash transfer is a household or an individual. Providing a cash transfer to households might have a disproportionate impact on larger households, requiring them to sustain themselves with less money per capita. Another important point to consider is whether money should be provided to everyone or only to the working age population (those above 15 years of age).

Coupons and Vouchers vs. Direct Cash Transfer

The type of support scheme can have a substantial influence on its impacts from the welfare and macroeconomic perspectives. One form of support scheme is the provision of vouchers or coupons to help households with utility payments or to purchase essential goods. Utility vouchers will disproportionally support more well-off households that use more appliances. The universality of such vouchers is also questionable, as some households are not connected to the utility networks (for instance the natural gas network), and thus will not benefit at all from vouchers. Considering the situation, the positive impact of vouchers is that during such a lockdown utility companies will not face liquidity problems that may otherwise arise from increased delinquency rates.

On the other hand, cash transfers allow recipients to rationalize between the consumption of different types of goods. As opposed to the provision of coupons and vouchers, transfers could further increase welfare by allowing individuals to self-rationalize (Ghatak & Maniquet, 2019).[10]

A Review of Social Support Programs Internationally

In this section, we discuss various governments’ (Table 2) social protection measures during the Covid-19 crisis. The actions taken cover the different functions of social protection, such as unemployment benefits; special social assistance or direct cash transfers; wage subsidies; deferrals of tax payments; pensions and pension fund adjustments; sickness and childcare benefits; etc.

In order to promote income security and stimulate aggregate demand, several countries have introduced either universal or quasi-universal direct cash payments (e.g. Australia, Hong Kong, Singapore, Serbia, Greece, the US). In order to further ease liquidity constraints on individuals and enterprises, some countries have announced the deferral of certain tax payments, social security contributions, rent, and utility payments (e.g. Bulgaria, Estonia, Spain, Canada). In addition, several governments are providing grants and wage subsidies to SMEs, start-ups, and other hard-hit businesses to avoid the drop in revenues and safeguard employment. In most cases, these measures were supplemented by extended unemployment benefits.

Table 2: Covid-19 social protection measures, by country

Central, South, and Eastern European Countries Certain Social Protection Measures Taken

                                 

Estonia
  • Suspended payments to the Pillar II pension fund;
  • Support the Unemployment Insurance Fund to cover wage reductions.
Poland
  • Wage subsidies for employees of affected businesses and self-employed persons;
  • Self-employed and employees working on civil contracts will receive a one-time benefit.
Latvia
  • Covering 75% of employees’ wages (in sectors suffering losses as a result of the coronavirus crisis) from the state budget, with a maximum monthly payment per employee set at €700;
  • Exempting covered wages from personal income tax and social contributions.
Serbia
  • A universal cash transfer of 100 EUR to each citizen over 18 years old;
  • Wage subsidies, including a payment of minimum wages for all SME employees and entrepreneurs for three months;
  • Payment of 50% of the net minimum wage for three months for employees in large private sector companies and for employees who are currently not working.
Bulgaria
  • Government-backed payment of 60% of the salaries of employees working in affected sectors who might otherwise be laid off;
  • Deferral of various tax and utility payment deadlines;
  • Offering interest-free loans to workers put on leave;
  • The possibility for the registered unemployed to sign labor contracts with agriculture producers, without losing their unemployment benefits.
Albania
  • Government support of small businesses/self-employed that are forced to close activities due to the Covid-19 pandemic by paying their minimum salaries;
  • Doubling social assistance and unemployment payments;
  • Part of defense spending reallocated toward humanitarian relief for the most vulnerable.
Ukraine
  • Adopting legislation that allows households to deduct the expense of Covid-19 medicine from personal income tax;
  • Introducing a one-off pension increase to low-income pensioners of 1,000 UAH and a regular monthly 500 UAH pension top-up for retirees aged 80 years and over;
  • Canceling payment of the Single Social Contribution for several categories of payer between March-May 2020.
Asia-Pacific  
Hong Kong, China
  • A one-off universal cash transfer of 1,280 HKD (165 USD) for 7 million adult residents;
  • A one-off extra allowance for 1.33 million recipients of the standard Comprehensive Social Security Assistance Payment, Old Age Allowance, Old Age Living Allowance, or Disability Allowance.
Australia
  • A one-off payment of 750 AUD (431.9 USD) for social security, veterans and other income support recipients and eligible persons, assisting around 6.5 million lower income Australians.
New Zealand
  • A permanent increase in social spending to protect vulnerable people (over the next four years);
  • Wage subsidies for affected businesses in all sectors and regions;
  • An income support package for the most vulnerable, including a permanent 25 NZD per week benefit increase and a doubling of the Winter Energy Payment for 2020;
  • Covid-19 leave and self-isolation support.
Singapore
  • A one-off payment as quasi-Universal Basic Income. All Singaporeans aged 21 and above will receive a one-off cash transfer of 300 SGD (205.38 USD), 200 SGD (136.9 USD), or 100 SGD (61.5 USD), depending on their income. Cash-payouts will also be given to families with children and elderly parents;
  • Providing a 100 SGD (61.5 USD) supermarket voucher to lower-income households;
  • Taxi and private-hire car drivers affected by the Covid-19 outbreak (around 40,000 eligible drivers in Singapore) will receive up to 20 SGD (13.7 USD) per vehicle per day for three months;
  • Enhanced Wage Credit Schemes – (co-funding wage increases for Singaporean employees);
  • For low-wage workers, the government will provide a Workfare Special Payment. Singaporeans on Workfare will receive 20 per cent more for work completed in the past year, with a minimum cash pay-out of 100 SGD (61.5 USD).
Western Countries  
United States of America
  • Direct cash payments of $1,200 for those earning up to $75,000 and $500 per child;
  • One-time tax rebates for individuals;
  • Expanding unemployment benefits.
Canada
  • Temporary income support to workers staying at home without access to paid sick leave;
  • Support to individuals and families with low and modest incomes with a special top-up payment under the Goods and Services Tax (GST) credit;
  • An increase in childcare benefits;
  • Support to businesses through income and sales tax deferrals.
Germany
  • Providing $55 billion to help small businesses and the self-employed avoid bankruptcies, with cash payments of up to $16,225;
  • Offering $8.5 billion safety-net programs for the self-employed.
Greece
  • Transfers to vulnerable individuals, including cash stipends;
  • Full coverage of pension and health benefit payments for employees working in hard-hit firms and self-employed people;
  • Extension of unemployment benefits by two months, and paid leave for parents who have children not attending school;
  • Liquidity support for hard-hit businesses through subsidized loans, loan guarantees, interest payment subsidies, and deferred payments of taxes and social security contributions.
Spain
  • A temporary subsidy for household employees affected by Covid-19;
  • A temporary monthly allowance of around 430 EUR for temporary workers whose contract (of at least two months) expires during the state of emergency and who are not entitled to collect unemployment benefits;
  • Tax payment deferrals for small and medium enterprises and the self-employed for six months;
  • An allowance for self-employed workers affected by economic activity suspension.
Norway
  • Larger wage subsidies for temporary lay-offs and more generous unemployment benefits;
  • Expanded sickness, childcare, and unemployment benefits;
  • A compensation scheme for heavily affected but otherwise sustainable businesses;
  • Grants for start-ups.

Source: Policy Responses to Covid-19, IMF policy tracker, April 2020; Social protection responses to the Covid-19 crisis, ILO, March 2020; Countries’ public announcements of Covid-19 economic responses.

Alternative Policy Options

Considering the existing social challenges, policy objectives, and possible alternatives implemented around the world, we propose the following five policy options:

Option 1 – Targeted Assistance

Considering the current situation in Georgia, the state’s capacity to implement a targeted exercise is extremely limited. This is largely due to the lockdown and the complexity of matching the current economic challenges and general characteristics of target groups. One way for the government to target different groups would be to use its administrative resources and revenue service databases to identify affected unemployed people no longer receiving salaries. However, using these resources, it will be hard to identify the majority of self-employed and informal workers who have also lost their income (fully or partially) and are facing hardships; examples of these individuals may include a small business owner working at the Eliava construction materials market, a self-employed tourism sector worker, a domestic worker – a nanny or cleaning lady, etc. Under normal circumstances, such individuals do not require any social assistance, however due to the lockdown they may not have enough cash inflow to sustain their families.

Furthermore, targeted assistance can create perverse incentives for some employees. Depending on the amount of the assistance, employees (that are still allowed to work) whose net salaries are close to the assistance threshold, might be discouraged from work. For example, if targeted assistance is 200 GEL, a grocery store worker with a gross salary of 300 GEL might prefer to leave their job temporarily (as unpaid leave for example).

Furthermore, the government could target following socially vulnerable groups that are easier to identify, such as:

  • Receivers of targeted social assistance, adults – 297,094 individuals;
  • Receivers of targeted social assistance, under 18 – 161,374 individuals;
  • Pensioners – 765,911 individuals.

Providing additional support to these groups will mean indirectly covering some self-employed individuals and informal workers. Many of such socially vulnerable groups work informally or are self-employed. Furthermore, some individuals could potentially have family members that are either informally or self-employed.

To calculate the total number of people subject to the targeted scheme, we consider the above listed individuals and add the group of hired employees that may lose the job or may have to take unpaid leave. Based on our estimates, around 200,000 hired workers may lose their income. Adding this to the number of TSA recipients (458,468) and pensioners not receiving TSA payments (692,431) brings the total number of beneficiaries of a targeted assistance scheme to 1,350,899 individuals. Assuming, 150 GEL in assistance per adult, and 75 GEL for under 18s, this will bring the cost of targeted assistance to approximately 191 mln. GEL per month.

Option 2 – Income Tax Breaks

The second policy option to consider is a variation on a tax break (tax credit, lowering income, or other taxes)[11]. Such an assistance mechanism will not be universal and only benefit the taxpayers. Furthermore, it is not a fact that tax relief will be transferred from employers to employees. Thus, essential social assistance may not be provided to a large proportion of the population. In addition, due to the lockdown, opportunities for investments have shrunk and hence, most tax saving will not influence economic growth. Finally, a decrease in tax rates will create additional pressure on government revenues, already negatively influenced by the lockdown, which may potentially create fiscal problems.

Aside from the costs of tax breaks, one should also bear in mind that this policy option is only intended for income tax payers who managed to retain their jobs. In an optimistic scenario, about 200,000 of hired employees will be left jobless, thus, about 640 thousand people will be aided by tax breaks. If income tax for all these employees would be reimbursed, the cost of tax breaks would amount to approximately GEL 136 mln. (monthly). It should also be mentioned that if companies are not paying income tax to the government, they might fail to reimburse this money to their employees, leaving some people without any assistance.

Option 3 – Unconditional Universal Cash Transfers

The third policy option is unconditional universal cash transfers. In this case, the government would make an unconditional cash transfer to every member of society. From a practical perspective there are two important questions to be answered: (i) should cash transfers be provided to individuals or to households?; and, (ii) should cash transfers only be made to the working age population or to children as well?

To minimize the potential negative consequences stemming from the possible negative gender impacts, individual payments are the preferred system. This may be as men are more often than not considered to be heads of their households, and if assistance is household-based women may not be able to take full advantage of it.

Furthermore, to ensure the progressivity of a universal cash transfer, it should not be limited to the working age population. A common approach would be to give guardians of children a decreased amount of a standard Universal Basic Income (UBI) payment (Ghatak & Maniquet, 2019). The progressivity of such a scheme is an important advantage, as it ensures support to those people who are not participants of the labor market and dependents of employed family members. Thus, the universal system helps mitigate the substantial indirect impacts on poverty resulting from job losses.

A major drawback of the unconditional universal cash transfer is its expense. This is primarily due to the large inclusion error, which accompanies this system by its very definition. However, alternatively, in a targeted program the vast majority of the affected self-employed and domestic workers (in total, close to 50% of all employment) are nearly impossible to identify. Furthermore, due to the lockdown, the potential group under risk of impoverishment is greater than under normal conditions. Consequently, compared to a perfectly targeted system (without any inclusion or exclusion errors) an unconditional universal cash transfer would be only marginally costlier.

However, with imperfect targeting, an unconditional cash transfer would be substantially costlier compared to targeted assistance. Assuming 150 GEL assistance for all working age population (2,968,964 individuals) and 75 GEL for children (754,500 individuals), the total cost of unconditional universal cash transfers would be 502 mln. GEL per month.

Option 4 – An Opt-out/Opt-in Unconditional Universal Transfers

As previously mentioned, the significant cost of a universal support scheme is a notable challenge, particularly because budgetary fiscal pressure is already high due to decreased economic activity and tax revenues. Thus, implementing a potentially costly assistance program will be hard from a public finance perspective. To partially alleviate this problem and decrease the inclusion error of universal cash transfers, the government could implement it in the following ways:

  1. The government could offer unconditional transfers to all individuals whose income is impossible to identify, while providing an opt-out option in case they do not deem the assistance necessary (for example, individuals and their families with savings or those unaffected by non-labor income);
  2. The government may assist employed workers based on their income using the following two principles:
    1. Offer assistance using an opt-out option to everyone whose income is below a certain threshold (for example, 700 GEL gross salary for the month of March);
    2. Offer assistance using an opt-in option to everyone whose income is above the threshold.

Opt-out/opt-in universal cash transfers have the potential for governmental savings. To evaluate the expected cost of this option we assume that half of all employees (i.e. 430,000) with a salary of over 700 GEL gross would opt-in into the system. In this case, the total cost of opt-out/opt-in universal cash transfers would be up to GEL 470 mln. Furthermore, in the better-case scenario, where no employees with a gross salary over 700 GEL would opt-in into the system, the total cost of the cash transfer scheme would be up to GEL 437 mln. Thus, our expected cost of the opt-out/opt-in universal cash transfer will be an average of GEL 454 mln[12].

Option 5 – Conditional Cash Transfers

To decrease the fiscal pressure associated with unconditional universal cash transfers, the government could use relatively simpler methods to minimize inclusion errors in the system. In this case, the government could potentially exclude employees who may not face an urgent need for assistance. Firstly, the government could exclude individuals who received an income of over 40,000 GEL in 2019 from the program. Secondly, those workers with an average monthly income of 1,200 GEL in 2020 could also be left outside the assistance scheme. This will allow the government to limit the inclusion error of the cash transfer system, while keeping similar overall impacts.

We evaluate the expected cost of the conditional cash transfer assuming 30% of the hired workers (258,048) having monthly income above 1,200 GEL. Based on the same population data, as for calculation of the cost of the unconditional cash transfer, the expected cost for conditional cash transfer will be roughly GEL 463 mln.

Multi-Criteria Analysis of Policy Options

To summarize these options, we have created a multi-criteria assessment of the different possibilities for social assistance using our pre-defined policy objectives. We assess each policy option on a 5-point scale, with 1 representing the worst performance, while 5 showing perfect performance. The overall efficiency of the policy option is a simple average of points in each criterion.

Table 3: Multi-Criteria Assessment of different social assistance systems during Covid-19

Assessment Criteria Option 1 – Targeted Assistance Option 2 – Income Tax Break Option 3 – Unconditional Universal Cash Transfer Option 4 – Opt-out/opt-in Unconditional Universal Cash Transfer Option 5 – Conditional Cash Transfer

 

Monthly Cost of the assistance Scheme (mil. GEL) 191 136 502 454 463
1. Minimization of Exclusion Error (minimization of impoverishment risk) 3 1 5 5 4
2. Minimization of Inclusion Error (minimization of fiscal cost) 4 2 2 3 3
3. Ease of implementation 2 5 5 4 4
4. Progressivity 4 1 4 5 5
5. Gender responsiveness 3 2 5 5 5
 

Overall Efficiency

3.2 2.3 4.2 4.4 4.2

Summary and Recommendations

In this policy note, we have summarized the potential social impacts of Covid-19 and the subsequent lockdown caused by the pandemic. Our assessment of the sub-categories of employment show that there is a large group of mid to highly affected individuals among the employed populace. Around 30% of hired employees will be significantly influenced, while 22% will suffer a medium impact. The impact on the self-employed will also be substantial, roughly 15% of the group will be highly affected, where 84% of self-employed individuals will feel a medium impact from the lockdown. The impacts are also disproportionate from a gender perspective, posing a risk of unemployment-driven assistance benefitting men more so than women.

Having reviewed international responses to the Covid-19 crisis from 17 selected countries, the evidence compiled has helped to form possible designs for a social assistance program. We believe that direct cash transfers to individuals are preferable to providing assistance for the purchase of specific goods or services, as individuals can self-rationalize.

Our multi-criteria assessment shows that an opt-out/opt-in unconditional universal cash transfer is marginally better compared to other universal cash transfer schemes. It has the best performance in minimizing the risk of impoverishment. Furthermore, our analysis shows that under the current conditions, the government’s ability to correctly design a targeted program that is able to reach all affected individuals is limited. This is primarily due to the relatively high percentage of self-employed on the Georgian labor market. Consequently, a targeted program would have a limited impact on minimizing the risk of impoverishment. This is even more true for possible tax breaks. The greatest merit of a targeted program is that it imposes less fiscal pressure and is thus substantially less costly compared to a universal support scheme.

Annex 1 – Comparison of Sectoral Impact Assessments by ILO (globally) and ISET-PI (for Georgia)

Annex 2 – Summary of the assumptions used for calculating costs of different support schemes

  Indicator Amount
Population
A Working Age Population (>15)  2,968,964
B Population Below Working Age (<15)  754,500
C Total Population  3,723,464
Hired Workers  
D Total Hired Workers  860,161
E Hired Workers with salary above GEL 700  430,081
F Share of hired workers with salary above GEL 1,200 30%
G Total number of hired workers who lose labor income 200,000
H TSA Recipients (>18)  297,094
I Pension Recipients 692,431
J TSA Recipients (<18) 161,374
Cash Transfer
K Cash transfer per adult (GEL) 150
L Cash transfer per child (GEL) 75
  • [1] ILO Monitor 2nd edition: COVID-19 and the world of work, April 2020.
  • [2] NACE 2 classification system, 4-digit level
  • [3] Based on the Labor Force Survey, Geostat (2018)
  • [4] One has to note that the working environment for frontline health workers has changed and they are exposed to higher health risk and psychological stress, which regardless of relatively stable labor market positions makes them more vulnerable physically and psychologically.
  • [5] For example, more women live in poverty as demonstrated by the fact that 55% of social assistance recipients are women.
  • [6] Hanna, R. & Olken, B. (2018). Universal basic incomes vs. targeted transfers: anti-poverty programs in developing
  • countries. J. Econ. Perspect. 32(4):201–26.
  • [7] Klasen, S. & Lange, S. (2016). How narrowly should anti-poverty programs be targeted? Simulation evidence from Bolivia and Indonesia. Discuss. Pap. 213, Courant Res. Cent., Göttingen, Ger.
  • [8] Banerjee, AV., Niehaus, P. & Suri T. (2019). Universal basic income in the developing world. Annu. Rev. Econ. 11:961–85.
  • [9] Banerjee, AV., Hanna, R., Kreindler, G. & Olken B. (2017). Debunking the stereotype of the lazy welfare recipient: evidence from cash transfer programs. World Bank Res. Obs. 32:155–84
  • [10] Ghatak M. & Maniquet F. (2019). Some theoretical aspects of a universal basic income proposal. Annu. Rev. Econ.11.
  • [11] For the purposes of this policy option we will concentrate solely on income tax breaks.
  • [12] These scenarios do not consider additional potential saving from individuals with an opt-out option utilizing this opportunity.

Disclaimer

This policy brief was first published as an ISET policy note on April 17, 2020 under the title “The Social Impacts of COVID-19 – Case for a Universal Support Scheme?”.

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Safety of Older People During the Covid-19 Pandemic: Co-Residence of People Aged 65+ in Poland Compared to Other European Countries

Image of different age people holding hands representing older people in Poland and COVID19

Bearing in mind that the estimated fatality rates related to Covid-19 infections are substantially higher among older people, in this Policy Paper we focus on the demographic composition of households of people aged 65+ as one of the social risk factors that influence the consequences of the pandemic. In light of plans of easing isolation restrictions and a gradual return to higher economic activity, a key challenge for the coming weeks is to ensure the safety of those most at risk. Although lifting the lockdown mainly affects the lives of the working population and children, attention should be paid to the channels that could enhance transmission of the coronavirus among older people. This includes the prevalence of co-residence with those who will get back to their workplaces or schools once they are open again. Compared to other European countries, Poland has the highest rates of people aged 65+ sharing their households with younger adults and children with nearly 40% living together with people aged up to 50 years old (excluding partners). On the other hand, Nordic countries, the Netherlands, Belgium and Germany report far lower rates of co-residence among the older population. In these countries however, older people commonly reside in formal care facilities, which, in turn, have proved vulnerable to outbreaks of infections. This emphasizes that each country has to carefully determine its own strategy on the way to recovery. Among other factors, the pace at which restrictions on social distancing are lifted should take into account the prevalence of co-residence among the older population.

Introduction

According to the WHO, at the early stage of the Covid-19 epidemic, the fatality rate among coronavirus-infected people was estimated at about 3-4% (WHO 2020a), although estimates based on the data from European countries suggest that the rate is lower and is closer to 1.5% (ECDC 2020). The rate is quite varied from country to country; it also fluctuates over time. To a large extent, the figure depends on the number of tests conducted and, consequently, the reliability of information on the number of people infected (Roser et al. 2020). Nevertheless, both the risk of experiencing serious symptoms of the coronavirus infection and the risk of death from complications arising from the disease increase significantly with the age of the infected person. Furthermore, the risk is definitely higher for the patients with underlying conditions, in particular cardiovascular diseases, diabetes, or hypertension (Emami et al. 2020). The highest risk is observed among older persons, with the fatality rate of people infected fluctuating from 1.8%-3.5% in the 60-69 cohort, to 13.0%-20.2% in the 80+ cohort (Roser et al. 2020). Therefore, a major challenge in the area of health and socio-economic policy measures in the coming months is to keep the older population safe and contain the spread of coronavirus in that population.

This Policy Paper presents an analysis of the housing situation of people aged 65+ in Europe. Co-residence may be one of the relevant social risk factors that determine the probability of being infected with viruses which, like SARS-Cov-2, are spread through droplet transmission. As shown by research on intra-household transmission at the early stages of the epidemic in China, the majority (75%-85%) of clusters (group illnesses) were observed within households (WHO 2020b). Depending on the data, the coronavirus secondary attack rate within households is estimated at 7.6%-15.0% (Bi et al. 2020; KCDC 2020b), and from this perspective it is important to note that the incidence rate is the highest in the 20-29 age group, with most of them showing no symptoms of the disease while being able to infect others (KCDC 2020a).

Given the limited scope of labor market activity in the 65+ population, compliance with the self-isolation regime by this group will not interfere much with the gradual easing of socio-economic restrictions. Things look different among younger people due to their work or study, and among the youngest members of the population due to their school or pre-school attendance. In line with the regulations introducing the state of epidemic in Poland, since March 23rd, 2020, many workplaces have been operating on a remote basis, with their labor force doing work from home, and many companies and organizations having been closed. Similarly, the nurseries, kindergartens, schools and universities have been closed since the 16th of March this year. However, the government has already announced a plan to ease some of the restrictions to pave the way for a phased return to more intensive social contacts and economic activity (Council of Ministers 2020). Because of the shortcomings of distance learning and serious inequalities in access to education in this system (Myck et al. 2020), and considering the adverse impact of closed schools and kindergartens on the working parents, it seems imperative to resume the operation of these facilities as soon as possible.

A key challenge for the coming weeks will therefore be to reconcile the socio-economic benefits of lifting the lockdown with the risk of health implications arising from less stringent social distancing restrictions. Those implications may be particularly severe for older people. Thus, this Policy Paper discusses structural determinants of the well-being of older people, with a focus on the housing situation in European societies and the rate of co-residence with the younger population. The analyses outline the status in Poland in comparison to other European countries, pointing to a great diversity of health risks for older people. One factor is the difference in the prevalence of co-residence between the older and younger populace, and another is the prevalence of formalized care facilities. Next to disease statistics, these differences should be taken into account in any decisions on lockdown easing or a detailed design of policy measures.

In Poland, the percentage of people aged 65+ in co-residence with other members of the household aged 50 or below (excluding a spouse or partner) is 37.4% for the female population and 38.6% for the male population, i.e. the highest in Europe. In Poland, 12.0% of people aged 65+ share a household with school-age children (aged 7-18), and 7.7% live together with children aged 0-6. Co-residence with minors usually means, for obvious reasons, that the adult parents of the minors live under the same roof as well. However, Poland also reports one of the highest percentages of co-residence with other adults without minors. For example, 7.6% of people aged 65+ live in one household with people aged 19-30, and 17.3% share a household with adults aged 31-50 who are not their spouses or partners. It is worth noting, however, that in the European countries considered here a high percentage of co-residence is negatively correlated with the prevalence of collective dwelling facilities that deliver formalized care for older persons. In Poland, the supply of such institutions – whether public or private – has been very limited, with only 1.6% of people aged 80+ living in those facilities. In contrast, in Belgium, almost every fourth person of that age is a resident of such a facility. When it comes to the pandemic, it must be underscored that although in such institutions the interactions with younger people can be quite easily limited, the experience of many countries has shown that they have been quite vulnerable to coronavirus clusters and epidemic outbreaks.

Considering that Poland reports the highest percentage of co-residence among people aged 65+, particular attention should be paid to the challenges for health and socio-economic policy measures introduced in Poland to manage the intensity of social contacts during the pandemic. This, in particular, applies to the regulations on students returning to schools and the easing of social distancing rules for students and working adults. Therefore, in countries such as Poland, the restoration of frequent social contacts, which is necessary, inter alia, to put the economy back on track, will have to be accompanied with adequate safeguards for those who are most heavily exposed to negative health effects of Covid-19.

The first section of this Policy Paper reviews co-residence percentage data for the 65+ population, based on data for Europe (the European Union member states and Norway, Switzerland and the United Kingdom, for the remaining European countries the data is not available), from the 2017 European Union Statistics on Income and Living Conditions study (EU-SILC.) The second section presents data on older people living in long-term care facilities in a number of European countries, collected in recent years by the OECD.

1. Older People in Co-Residence With Other Members of the Household

In the analytical discussions below, the terms “co-residence” or “shared household” refer to a situation where persons aged 65+ live in one household with adults who are not their spouse or a partner, or with children under 19 years of age. In Poland, the percentage of households shared by people aged 65+ and children aged 18 or younger is one of the highest in Europe. Of all the older people in Poland that live in a household setting on a permanent basis (i.e. excluding those living in formalized care facilities), as many as 16.9% of women and 16.6% of men aged 65+ share a household with persons under 19 years of age (cf. Figure 1). With the exception of Slovakia and Romania, other countries report a much lower rate. In countries such as Norway, Sweden, Denmark, or the Netherlands, the rate is between 0.1% and 0.6% for women, and between 0.5% and 1.2% for men (65+ population).

Figure 1. Population aged 65+ in co-residence with persons other than their spouse/partner, by the age of the youngest member of the household

a) Male

b) Female

Source: Authors’ compilation based on the 2017 EU-SILC data.
Nota Bene: Share of 65+ population not living in formalized care facilities.

In Poland, approximately 12% of women and men aged 65+ share a household with students aged 7-18. In other words, more than 460k women and 280k men aged 65+ in Poland have direct, daily interactions with students attending schools (Table 1). In addition, 13.9% of women and 14.7% of men aged 65+ (530k and 360k, respectively) share a household with persons aged 19-30, who – according to research findings from other countries – demonstrate the highest incidence of coronavirus disease (KCDC 2020a). On top of that, these proportions are significantly higher in rural areas, and over 40% of the 65+ population in Poland live in rural areas. Compared to other countries in Europe, it is especially in the rural areas that Poland reports a significantly higher percentage of older people in co-residence with younger people (Figure 2). For example, while in Poland 19.0% share a household with children aged 7-18, and 21.1% with people aged 19-30, in Sweden in the 65+ population in rural areas those percentages are 0.4% and 1.0%, respectively, and in Belgium 1.9% and 1.5%. In urban areas the disparities in the demographic structure of households between Poland and other European countries are less pronounced, but still the share of the 65+ population in co-residence with younger people is among the highest in Europe; with 7.2% sharing a household with school children and 9.5% with adults aged 19-30. In Sweden these percentages are 0.7% and 1.7%, respectively, and in Belgium 1.2% and 3.8%.

Table 1: Population aged 65+ in Poland in co-residence with other members of the household (other than a partner/spouse).

  Urban Rural Total
  Male Female Male Female Male Female Total
Population aged 65+ (in thousands) 1 435 2 268 1 007 1 508 2 441 3 776 6 218
People in co-residence with a person aged (in thousands):
– 0-6 82 107 117 175 199 282 481
– 7-18 91 174 190 288 281 462 743
– 19-30 142 210 216 315 359 525 883
– 31-50 353 546 446 681 799 1227 2026
People in co-residence with a person aged (in %):
– 0-6 5.7% 4.7% 11.6% 11.6% 8.1% 7.5% 7.7%
– 7-18 6.4% 7.7% 18.9% 19.1% 11.5% 12.2% 12.0%
– 19-30 9.9% 9.2% 21.5% 20.9% 14.7% 13.9% 14.2%

Source: Authors’ compilation based on the 2017 EU-SILC data.

Nota Bene: Share of 65+ population not living in formalized care facilities.

Figure 2. Population aged 65+ in co-residence with other members of the household (other than a partner/spouse), by age of the other members of the household.

  1. Urban

Rural

Source: Authors’ compilation based on the 2017 EU-SILC data. Nota Bene: Countries: SE – Sweden, BE – Belgium, IT – Italy, HU – Hungary, ES – Spain, SK – Slovakia, PL – Poland. Share of 65+ population not living in formalized care facilities.

2. Residents of Formalized Care Facilities for Older Persons

Households where people aged 65+ live under one roof  with younger people (usually they are all family members) reflect the financial status of the family on the one hand, but on the other they offer care to those who might need it to due to their age or health status. In that respect, unlike many other countries in Europe, Poland has a very low share of older people who, due to barriers to independent living, decide to relocate to a formalized care facility or a similar setting. In 2017, less than 1% of the 65+ population in Poland lived in formalized care facilities; and for the 80+ population the share was only slightly higher and reached 1.6% (Figure 3). One reason is the low number of vacancies in such facilities: in 2017 in Poland there were, statistically, 12 beds per 1000 inhabitants aged 65+. For comparison, in Nordic countries (Denmark, Finland, Norway, Sweden) more than 12% of the 80+ population live in formalized care facilities for older people; in Luxemburg and Switzerland the rate is close to 16%, and in Belgium it is 24%. These countries also report a much higher availability: from 50 beds per 1000 people aged 65+ in Denmark to over 80 beds in Luxembourg. The share of older people living in formalized care facilities is also relatively high in countries such as Slovenia (12.6% for the 80+ population) or Estonia (9.9%).

Figure 3. Long-term care facilities – resources and utilization.

Source: Authors’ compilation based on the OECD data.
Nota Bene: According to the latest 2017 data available, with the exception of: Spain, Portugal – 2018 data; the Netherlands, Slovenia – 2016 data; Belgium, Denmark – 2014 data. The figure includes the European countries for which the data has been available. For Italy, only the data on the number of beds has been available, and for Portugal, only the data on the number of facility residents.

The isolation regime introduced to restrict the frequency of visits, side by side with a system of appropriate checks and controls for the staff, are relatively simple ways to reduce the risk of external coronavirus infection in formalized care facilities. Yet, as we have learnt from numerous examples in Poland and internationally, infection transmission between the residents or between the residents and the staff has been a frequent source of infection clusters and outbreaks. For example, in South Korea, even more than 30% of new coronavirus cases could be the result of transmission between hospital patients or nursing home residents (KCDC 2020a). In connection with a coronavirus outbreak in a formalized care facility in the USA, more than half of the residents had to be hospitalized and, eventually, 33.4% died (McMichael 2020). It seems that keeping the residents of formalized care facilities safe from the infection should be a priority in an epidemic control policy. However, the pace at which social distancing restrictions are lifted so that students can get back to schools and the lockdown in public spaces can be removed, should not have a vital impact on the safety of those living in the facilities, in contrast to the situation of older persons who share a household with younger persons.

Summary

The well-being of the groups with the biggest exposure to the grave outcomes of coronavirus infection deserves special attention when lifting the lockdown introduced in connection with COVID-19 pandemic. In this context, the housing situation of older people and the nature of the underlying social contacts are among important aspects to take into account in developing detailed regulations. As outlined in this Policy Paper, different countries in Europe report different status in that respect. Of all the countries in Europe, Poland has the highest share of the 65+ population co-residing with younger people. On the other hand, less than 1% of the 65+ population live in formalized care facilities. In Europe, the lowest share of co-residence is reported in the Nordic countries, the Netherlands, Germany and Belgium. At the same time, the share of the 65+ population residing in formalized care facilities in those countries fluctuates from 4% to 8%, reaching over 10% in the 80+ population.

In formalized care facilities, lockdown lifting will not have material impact on the safety of the residents or the risk of coronavirus transmission. In contrast, the households where older people live side by side with the younger populace may actually represent a significant risk factor in terms of the spread of the epidemic and infection transmission to those who are most heavily exposed to the grave complications of Covid-19.

In general in Poland, 37.4% of women and 38.6% of men aged 65+ share a household with people under 50 other than their spouse or partner. This is the highest rate of co-residence with younger people for this age cohort in Europe. In Denmark, this percentage is 1.3% for women and 3.3% for men. Even in Spain it is much less common for people aged 65+ to share a household with younger family members (the rates being 28.0% for women and 26.6% for men, respectively). Additionally, in Poland, especially in rural areas, many people aged 65+ live under one roof with school-age children (7-18 years of age: 19.1% of women and 18.9% of men in this age group, respectively); and even more (20.9% of women and 21.5% of men) share a household with adults aged 19-30, which is the age group where coronavirus infection is the most prevalent (KCDC 2020a).

In view of major discrepancies in the demographic structure of households between countries, it seems necessary to differentiate the social distancing rules and the pace with which these rules are to be eased, if one of the objectives is to protect the people exposed to the most serious consequences of coronavirus infection. Especially in such countries as Poland, the policy of gradual opening of schools and other institutions and phased recovery of economic activity should be accompanied by a broad-based communication campaign on how to protect the most vulnerable household members. It seems advisable that the campaign be conducted both in the mass media and in schools, workplaces, and public spaces.

References

Disclaimer

This Policy Paper was originally published as a CenEA Commentary Paper of 21st April 2020 on www.cenea.org.pl. The analyses outlined in this Policy Paper make part of the microsimulation research program pursued by CenEA. The analyses are based on EU-SILC 2017 data as part of microsimulation research using the EUROMOD model and have been provided by EUROSTAT, and on publicly available OECD data. EUROSTAT, the European Commission, the National Statistical Institutes in each country, or the OECD have no liability for the results presented in the Policy Paper or its conclusions.

This Policy Paper was prepared under the FROGEE project, with financial support from the Swedish International Development Cooperation Agency (Sida). FROGEE papers contribute to the discussion of inequalities in the Central and Eastern Europe.  For more information, please visit www.freepolicybriefs.com. The views presented in the Policy Paper reflect the opinions of the Authors and do not necessarily overlap with the position of the FREE Network or Sida.

Household Exposure to Financial Risks: The First Wave of Impact From COVID-19 on the Economy

An areal image of households in suburbs representing household financial risk exposure to covid19

Since March 12, 2020, Poland has been under an increasing degree of quarantine due to the COVID-19 pandemic. The strict isolation-driven lockdown measures have implied significant restrictions to social interactions and economic activity. While the duration of this lockdown and the resulting overall scope of economic implications are highly uncertain at this point, in this brief we take a closer look at the possible extent of the first wave of economic consequences of the pandemic faced by Polish households. This is done by identifying sectors of the economy whose operation has been severely limited due to the lockdown, such as those involving travel, close interpersonal contact and public gatherings or those related to the retail trade. We find that about 17.2% of Polish households include members active in these sectors, and for 5.2% of households, the risk can be described as high due to the nature of the employment relationship. According to our estimates, 780K people (57% of whom are women) face a high risk of negative economic consequences as a result of the first direct wave of implications of the pandemic.

Introduction

The full scale of the socio-economic impact of the COVID-19 outbreak is incalculable today, given the uncertainty of lockdown duration and the severity of the pandemic-driven slowdown in the international economy. Still, it is possible to analyze the direct implications of the lockdown, self-isolation and quarantine measures introduced over the last few weeks in an attempt to formulate a preliminary assessment of how the outbreak will affect households in economic terms. The priority challenge now is, of course, to contain the spread of the coronavirus, but as we identify the scale of potential economic consequences associated with the pandemic, we may help calibrate the safeguards that could protect households from the impact of the imminent economic slowdown.

In this commentary paper, based on the Household Budget Survey (HBS) data, the percentage of households (HHs) whose members are most at risk of losing their job or compromising their income due to the first wave of economic consequences of the pandemic is taken as a measure of the economic impact of the COVID-19 outbreak. The analysis looks into the population of people who are economically active (through employment or self-employment) in those sectors of the economy which are most exposed to the effects of the lockdown. We discuss the HHs with a particularly high risk of income deterioration in the breakdown according to the level of household income, the place of residence, and the family type. The first part of the paper presents a detailed description of the economic sectors which were considered to be particularly exposed to the risk associated with the first wave of economic consequences of the pandemic, together with risk level definitions. Analytical findings are presented in the second part of the paper.

Households at Risk of the Negative Impact of the First Wave of Economic Consequences of the COVID-19 Pandemic

The granularity of HBS data collected annually by Poland Statistics (GUS) is not sufficient for a very precise determination of the size of risk groups in terms of individual activity on the labor market, but the data can help identify the HHs whose members have been employed in the sectors of the national economy particularly affected by the pandemic, i.e. on the first line of exposure to its economic consequences. These are, in particular, economic sectors that involve frequent interpersonal contacts and large public gatherings: following the announcement of the state of epidemiological hazard in Poland on March 14th, 2020, serious restrictions have been imposed in those sectors in an effort to prevent the rapid spread of the coronavirus.

Pursuant to the Regulation of the Minister of Health of March 13th, 2020, on the announcement of the state of epidemiological hazard in the territory of the Republic of Poland, restrictions on doing business in the food industry, as well as in culture and entertainment, sport and recreation, hospitality and tourism have been imposed on a temporary basis (Ministry of Health 2020). The operation of large-size retail commerce facilities has also been restricted. In addition, self-isolation and social distancing result in significant decreases in the overall level of trade turnover. In view of the lockdown, we decided that the risk of economic slowdown also applies to the service sector and education (personal services included) for the purpose of this paper. The workforce from the above-mentioned sectors has been divided by type of employment contract, and those hired under a contract of employment (fixed-term or open-ended, regardless) have been ranked as less exposed to the risk of job loss or lower earnings, while all the others employed on civil law contracts (service contract, zero-hours contract, etc.) have been grouped under an elevated risk label. The elevated risk category includes all those who are self-employed in the above-mentioned sectors in Poland or abroad, regardless of whether they have employees onboard or not.

Exposure to Financial Risks in Families and Households

In accordance with the risk categories applicable to the economically active population, we can conclude that there are over 780 thousand members of the workforce (57 percent of them are women) who are particularly exposed to the negative economic consequences of the pandemic, as they work in the affected sectors of the economy on the basis of self-employment or contracts other than the contract of employment. In addition, 1.9 million people (70 percent of them are women) are employed in these sectors of the economy on contracts of employment. The status of the latter group is less precarious in the short term, but if the lockdown should continue in the long term, this population may also be affected.

The adverse impact of job loss or lower earnings will affect an entire household whose member works in a sector particularly affected by the crisis. Therefore, the risks below are presented in a breakdown by family type and by HH group aggregated according to the place of residence and income level. Moreover, the HHs were also grouped according to their members’ activity on the labor market, with analytical findings presented for all HHs and for the group of HHs with at least one economically active member in the HH.

The highest percentage of HHs whose members are particularly exposed to the negative consequences of the pandemic is reported in cities (Figure 1). For example, in cities with a population above 500,000, it is 6.6 percent of all HHs, and 9.1 percent of the HHs with at least one active member on the labor market. Additionally, in cities with a population count exceeding 500,000, 12.4 percent and 17.1 percent of the population, respectively, is employed in the affected sectors on the basis of an employment contract. In smaller cities/towns and in rural areas the percentage of HHs with the population most exposed to the crisis are slightly lower. In rural areas, it is 4.8 percent of all HHs and 6.4 percent of the HHs with at least one economically active member of the HH.

In terms of HH income levels, middle-income HHs demonstrate the highest percentage of those exposed to the negative consequences of the first wave of pandemic-driven impact on the economy (Figure 2). For example, in the 6th income decile group, in the population of HHs with at least one economically active member, 8.5 percent of HHs include a member who is economically active in an affected sector and working either on a self-employment basis or on a contract other than a contract of employment. Together with HH members who are economically active in those sectors on a contract of employment, the rate exceeds 30 percent.

Figure 1. Financial risk in the households in connection with the first wave of COVID-19 impact on the economy, by place of residence

Source: Authors’ compilation based on 2018 HBS data.
Nota Bene: Economically active HHs – households with at least one member of the household active on the labor market.

The percentage distribution of the HHs economically active in the affected sectors by family type is also uneven (Figure 3). In the group of families with at least one economically active member, the largest proportion of such HHs is reported in the group of single parents, with 31.5 percent working in the affected sectors and 6.6 percent in self-employment or on the basis of a contract other than the contract of employment. Similar percentages are reported for couples with children and at least one economically active HH member (24.2 percent and 7.8 percent, respectively.) Among working singles and couples with no dependent children, on average, one in five HHs has a HH member economically active in an affected sector. Of these HHs, 4.5 percent of the singles and 5.6 percent of the couples with no children are economically active in the affected sectors with contracts other than a contract of employment.

Figure 2. Financial risk in the households in connection with the first wave of COVID-19 impact on the economy, by income decile

Source: Authors’ compilation based on 2018 HBS data.
Nota Bene: Economically active HHs – households with at least one member of the household active on the labor market. Income decile groups are ten groups covering 10 percent of the population each, from households with the lowest disposable income to the most affluent households, on the basis of the so-called equivalent income, i.e. taking into account the differences in the size of the household using the modified OECD equivalence scale.

Figure 3. Financial risk in the households in connection with the first wave of COVID-19 impact on the economy, by family type

Source: Authors’ compilation based on 2018 HBS data. Nota Bene: Economically active HHs – households with at least one member of the household active on the labor market. The following family types are distinguished: Singles – working age singles without dependent children; Single parents – working age single parents with dependent children; Couples without children – working age married couples without dependent children; Couples with children – working age married couples with dependent children.

Summary

Although our estimates of the percentage of families and households potentially exposed to the negative effects of the first wave of economic consequences of the COVID-19 pandemic do not necessarily imply that such a high share will actually be affected, the mere fact that so many families face the prospect of a deteriorating financial condition should stimulate a wide array of public policy support mechanisms. The economic support package called the “anti-crisis shield”, announced by the Government of Poland on March 18th, is a reaction to this challenge, though specific details of the announced version of the program have not been disclosed to date (Government announcement 2020). Still, the main focus of the package is on support for enterprises and entrepreneurs to help them continue business operation by postponing the due dates of business taxes and levies, and partially subsidizing employment of the workforce already on board. There is no doubt, however, that if the general economic slowdown continues for more than a few months, enterprises will be forced to start the layoffs and the self-employed will have to deregister. Therefore, the public finance system must be prepared to provide direct financial support to the households and offer a comprehensive benefit package to those who are laid off and to their families.

It is to be hoped that the economic consequences of the pandemic will be short-lived, and business activity will recover quite quickly to the pre-existing levels. For this to happen, first of all, we must keep the enterprises afloat, especially the small and medium-sized enterprises. Secondly, a fast economic reboot will be easier if the existing employment relations are preserved, even if the workload or the wages are curtailed. To that end, one solution would be to provide periodic financial support to employees in the affected sectors, even without formal termination of the contract between the employee and the employer. If the lockdown continues for more than two or three months, the financial support provided for in the “anti-crisis shield” package, representing 40 percent of the wage, may turn out to be inadequate to keep current employment levels intact.

If the pandemic-driven economic slowdown is prolonged – and there is no way this option can be ruled out today – it should be remembered that, apart from the sectors included in the analysis, the remaining sectors of the Polish economy will also be affected by the negative consequences of the recession; and the prolonged slowdown will eventually lead to a significant increase in unemployment rates. If that happens, households will need support through social transfers, both in the form of the unemployment benefit and benefits not related to a beneficiary’s track record in social security contributions paid, i.e. the housing benefit and social welfare benefits. With the expected substantial increase in public spending, the current policy of the state, focused primarily on universal public benefits, would have to be refocused on the transfers targeted at the most vulnerable households.

References

Ministry of Health (2020). Regulation of the Minister of Health of the Republic of Poland of the 13th March 2020 on the announcement of the state of epidemiological hazard in the territory of the Republic of Poland.

Government announcement (2020). “Anti-crisis Shield” will protect companies and employees from the consequences of coronavirus epidemics.

Disclaimer

This brief was originally published as a CenEA Commentary Paper of 28th March 2020 on www.cenea.org.pl. The analyses outlined in this brief make part of the microsimulation research program pursued by CenEA Foundation. The data used in the analyses is based on the 2018 Household Budget Survey, as provided by Poland Statistics (GUS). Poland Statistics (GUS) has no liability for the results presented in the brief or its conclusions. Conclusions presented in the brief are based on Authors’ calculations based on the SIMPL model.

Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes. 

School Lockdown: Distance Learning Environment During the COVID-19 Outbreak

Image of an empty classroom representing distance learning environment during the COVID-19 outbreak

Students in Poland, as in many other countries, have been obliged to participate in distance learning as a result the COVID-19 pandemic and the lockdown of schools. Successful participation in this format of schooling requires some basic equipment (a computer with Internet connection) as well as adequate housing standards, in particular a separate room during online classes. Based on the data from the Household Budget Survey 2018, in this brief we take a closer look at the living conditions of schoolchildren in Polish households and their access to adequate infrastructure. Our findings indicate that in the case of 11.7 percent of households with schoolchildren aged 6-19 years housing conditions are insufficient for home schooling. Additionally, for about a quarter of households with schoolchildren distance learning can be a challenge due to inadequate technical equipment. These conditions vary significantly with household income and across urban and rural areas, which signals that prolonged distance learning in Poland is likely to exacerbate the influence of children’s socio-economic background on inequalities in education outcomes.

Introduction

In connection with the coronavirus COVID-19 outbreak, Poland’s Minister of Education, in a Regulation introduced on the 20th March 2020, postponed the end date of the lockdown of Polish schools until the 10th April 2020. Also, the regulation requires that education be organized for school-age students during this period by means of distance learning channels and methods (Ministry of Education 2020a). It is the responsibility of the principal of every educational facility to make sure that such education is provided. Furthermore, a “Guide to Education” was developed by the Ministry of Education with information and instructions on distance learning for all interested parties, such as school principals, teachers, parents and students (Ministry of Education 2020b). Due to the restrictions on the movement of people during the state of epidemic in Poland, effective as of the 20th March 2020, electronic media (the Internet and, potentially, the telephone) should serve as the main channel of communication between teachers and students/ parents.

Thus, since the 25th March 2020, 4.6M students in Poland have been studying remotely, and any decisions on reopening schools or extending the lockdown depend on the course of development of the pandemic. Even at the time of “regular” access to schooling, the discrepancies in living conditions between students, in particular in terms of their housing conditions and household infrastructure, have a substantial impact on the overall quality of learning and educational outcomes (e.g. Author et al. 2019; Guryan et al. 2008), all the more so when students have to switch to distance learning. In the current situation, substandard housing conditions and lack of access to a computer or the Internet can make it difficult or outright impossible for many students to access education in the coming weeks. Fair and equitable assessment of students’ skills and knowledge may also be affected, as well as their future academic achievements, especially for the cohorts who are about to complete their Grade 8 in the primary school and those who are preparing for their secondary school graduation examination (Polish: Matura). For a student to be able to participate in distance learning activities and benefit from online learning materials, s(he) must have access to a computer terminal with an Internet connection at home. In addition, it seems that effective distance learning requires adequate housing standards, such as a separate room for studying. The “Guide to Education” says little about the importance of these infrastructure- and housing-related factors, merely recommending that a problem, if any, should be reported to the school, and an adequate solution should be implemented in consultation with the form master.

As argued in this Policy Brief, the unexpected need for schools to switch to a distance learning environment will underscore the magnitude of inequalities among households (HHs) in terms of their access to the infrastructure required for the students to benefit from distance learning opportunities and the living conditions in which such distance learning is supposed to proceed. The findings in this Policy Brief are based on the latest data from the 2018 Household Budget Survey (HBS), as made available by Statistics Poland (GUS). Notably, while HH status regarding computer equipment and Internet access may have improved since the time the survey was conducted, it can be assumed that the living conditions reflected in survey data are an accurate representation of the present-day status.

The first part of the Policy Brief presents the living conditions of the HHs with students aged 6-19, attending schools of all levels, according to the number of rooms in a house or apartment. The analyses presented in the second part of the Policy Brief are focused on HH infrastructure required for distance learning. According to HBS data, in 11.7 percent of HHs with students the number of rooms is equal to or lower than the number of students. A total of 833K students live in those HHs. During the state of epidemic, when the adult population is also committed to the lockdown and self-isolation, the living conditions may not be optimum for home schooling. According to the 2018 HBS data, in 7.1 percent of HHs with students there is no computer or other similar device with Internet access, and in 17.3 percent of HHs the total number of such devices in the HH is lower than the number of students living in the HH. That means that for more than 1.6M students distance learning may be a serious challenge for technical reasons. In that context, it should be noted that the shortage of computer equipment in HHs varies significantly with HH financial conditions and place of residence. As discussed in the Policy Brief, the highest percentage of the HHs with inadequate supply of the equipment necessary for distance learning is reported in the bottom half of the income distribution, and in the HHs in rural areas.

1. Living Conditions of Students in Poland

The living conditions in which students are expected to continue their education over the next few weeks can affect the outcomes of distance learning and their academic achievements. Students who share a single-room dwelling unit with other members of the HH will experience particularly harsh conditions, especially in view of the lockdown also applying to adults. There are over 130K such students throughout Poland (Table 1), with top percentages reported in large cities (4 percent of HHs with students; Figure 1). Many HHs living in a two-room dwelling unit or house include only one student, but there are 490K students in two-room dwelling units or houses who share the two rooms with their school-age siblings.

In rural areas such HHs represent only 5.7 percent of the total (Figure 1), but in cities with populations exceeding 100K the figure is 7.6 percent, which means that the affected student population is 174K and 140K, respectively (Table 1). Another piece of pertinent statistics: in many of the HHs in multi-room dwelling units or houses (i.e. with three or more rooms), the number of students is equal to or greater than the number of rooms. In cities with populations exceeding 100K the figure is 1.2 percent of HHs with students, while in rural areas this ratio is 2.5 percent, with 116K students affected.

As illustrated in Figure 2, housing conditions that can be described as not conducive to distance learning vary significantly with HH income. At the bottom end of the income distribution scale, among HHs with students, there are significantly more HHs in which the number of rooms may be inadequate in relation to the number of students living there. In every fifth HH from the second and third income decile group, each of the students living there may not have a separate room at their disposal; whereas in the group of top income HHs (from the tenth decile group) with students, this ratio is only 3.7 percent.

Table 1 Student count in the breakdown according to their living conditions and place of residence

Source: Authors’ calculations based on 2018 HBS data (weighted based on Myck i Najsztub 2015.)

Figure 1 Count of rooms and students in households by place of residence

Source: Authors’ calculations based on 2018 HBS data (weighted based on Myck i Najsztub 2015.)

Figure 2 Count of rooms and students in households by income decile group

Source: Authors’ calculations based on 2018 HBS data (weighted based on Myck i Najsztub 2015).
Nota Bene: Income decile groups are ten groups covering 10 percent of the population each, from households with the lowest disposable income to the most affluent households, on the basis of the so-called equivalent income, i.e. taking into account the differences in the size of the household using the modified OECD equivalence scale.

2. Distance Learning Infrastructure in Households

To be able to use electronic educational materials available on the Internet; to participate in classes conducted by teachers on various online platforms; or even to send back homework assignments over the Internet; students need to have home access to a computer connected to the Internet (for simplicity, the term “computer” used in this Policy Brief means a computer or a similar device with Internet access).

According to 2018 HBS data, close to 330K students do not have home access to a computer connected to the Internet (Table 2). In the case of another 1.3M students, the number of such devices is lower than the number of students in the HH, so it may not be sufficient to satisfy the needs of all students undergoing parallel remote education in the HH. In other words, as many as 7.1 percent of HHs with students have no access to distance learning at all due to the lack of appropriate equipment, while for a further 17.3 percent of the HHs the shortage of relevant infrastructure may significantly impede distance learning efforts (Figure 3).

As shown in Figure 3, the challenge of inadequate infrastructure for distance learning is reported much more frequently in single parent HHs, as compared to couples with school-age children. Among students raised by a single parent, every tenth family does not have a computer with Internet access, and in every eighth family the number of such devices is insufficient for all the students living in the HH. Among married couples with children, 6.4 percent of families report no computer, and in 18.2 percent of families the number of computers is lower than the number of students in the HH.

Table 2 – Students with/without a computer with Internet access, by place of residence

Source: Authors’ calculations based on 2018 HBS data (weighted based on Myck i Najsztub 2015).
Nota Bene: The values shown in the Table refer to computers with an Internet connection. The total number of students is slightly different from the value shown in Table 1, because 2018 HBS survey sample for HH infrastructure has been reduced.

Figure 3 Computers with Internet access in households with students, by place of residence and family type

Source: Authors’ calculations based on 2018 HBS data (weighted based on Myck i Najsztub 2015). Nota Bene: Family types are listed within HH category.

Map 1 Computers with Internet access in student population, by region of the country

a) Student has no computer with Internet access at home

Source: Authors’ calculations based on 2018 HBS data (weighted based on Myck i Najsztub 2015).

b) Student must share the computer with school-age siblings

Source: Authors’ calculations based on 2018 HBS data (weighted based on Myck i Najsztub 2015).

According to HBS data, students living in rural areas may be particularly exposed to problems in using distance learning. Although the percentage of HHs with students that do not have a computer with Internet access in rural areas is similar to that reported for urban areas (regardless of the size of the city/town), there are visible discrepancies in the availability of a sufficient number of hardware items between different categories defined according to place of residence. In rural areas one in every five HHs reports that the number of computers in the HH is lower than the number of students, whereas in big cities (population above 100K) this issue is reported by 9.7 percent of the HH.

Inequalities in access to distance learning are also visible across Poland’s regions. As illustrated on Maps 1a and 1b, students from Lubuskie Voivodeship do not have access to a computer connected to the Internet (12.6 percent) or have to share a computer with school-age siblings (37.5 percent) much more often than students from other regions of the country. For comparison, 4.4 percent of the students from Zachodniopomorskie Voivodeship do not have a computer at home, and every fifth student does not have a computer for their personal use.

Significant differences in access to the infrastructure required for distance learning are also manifested in division by income deciles (Figure 4.) In the population of HHs with students, in the two bottom decile groups (i.e. among 20 percent of HHs with the lowest income), as many as one in ten HHs does not have a computer connected to the Internet, and another 20 percent plus cannot provide individual access to a computer for each of the school-age children. At the other end of income spectrum, only about 4.1 percent of HHs with students do not have a computer, and in the case of another 8.3 percent students do not have a computer for their personal use.

Figure 4 Computers with Internet access in households with students, by income decile group

Source: Authors’ calculations based on 2018 HBS data (weighted based on Myck i Najsztub 2015). Nota Bene: Income decile groups are ten groups covering 10 percent of the population each, from households with the lowest disposable income to the most affluent households, on the basis of the so-called equivalent income, i.e. taking into account the differences in the size of the household using the modified OECD equivalence scale.

Summary

According to 2018 Household Budget Survey data, close to 330K students do not have home access to a computer connected to the Internet; and in the case of another 1 320K students the number of computers in the HH is lower than the number of students living in the HH. Under such circumstances, distance learning on a regular basis during the COVID-19 outbreak is either outright impossible or very difficult. Due to infrastructure shortages, distance learning is particularly difficult for students living in the HHs in rural areas (30 percent of all HHs with students), but the difficulties of this nature are also reported by students living in big cities (17.1 percent of HHs). Single parent families are affected by a lack of computer equipment more frequently than married couple families (11.2 percent vs 6.4 percent); and the situation varies to a large degree depending on HH income levels. While in the HHs with students grouped in the bottom decile as much as 33.9 percent do not have access to a computer or have a computer to share with their school-age siblings, in the HHs from the top decile group the corresponding percentage is almost three times lower.

The housing conditions in which Polish students follow the curriculum are an additional impediment to distance learning. More than 130K students live in one-room dwelling units, and nearly 700K live in multi-room units where the number of rooms is the same or lower than the number of students in the HH. In terms of the housing stock, access to an adequate number of rooms for effective distance learning also varies with income level. While in the bottom two decile groups the number of rooms in relation to the number of students is insufficient for 16.6 percent and 20.7 percent of the HHs, in the top two income deciles the corresponding ratio is as low as 4.5 percent and 3.7 percent.

The longer the duration of the distance learning regime, the greater the impact of inequalities in access to distance learning for students. It may take a particular toll on the cohorts which complete their final year of each stage of education. The inequalities will be compounded by differences in support in distance learning the students can receive from their parents or guardians. A population of 720K students live in single-parent HHs, and 380K of those single parents are economically active; and speaking of the population of students living together with both parents, there are 2.6M students in whose case both parents were economically active at the point of the pandemic outbreak. Even if some parents have now been forced to cut down on their professional responsibilities, others continue working – either at the workplace or from home.

For many reasons, students as well as their parents, guardians and teachers are looking forward to students’ return to schools – it will be a long-awaited sign that the epidemic situation has stabilized. Yet, this moment will be especially important for those students for whom distance learning was a particular challenge due to their living or infrastructure-related conditions. In an effort to reduce inequalities in access to distance learning, educational facilities in cooperation with local authorities, should extend special support to the students for whom distance learning is difficult due to objective causes. It seems that the first step should be to collect specific information about the distance learning environment available to students and, if necessary, to fill in the gaps in computer equipment and Internet access. Furthermore, if the epidemic allows, it seems purposeful to introduce, to a limited extent and with appropriate security measures, direct contact between students and teachers, especially where effective distance learning turns out to be difficult or impossible to implement.

References

Disclaimer

This brief was originally published as a CenEA Commentary Paper of 28th March 2020 on www.cenea.org.pl. The analyses outlined in this brief make part of the microsimulation research program pursued by CenEA Foundation. The data used in the analysis is based on the 2018 Household Budget Survey, as provided by Poland Statistics (GUS). Poland Statistics (GUS) has no liability for the results presented in the brief or its conclusions. Conclusions presented in the brief are based on Authors’ calculations based on the SIMPL model.

CenEA is an independent research institute without any political affiliations, with main research focus on social and economic policy impact assessment, with a particular emphasis on Poland. CenEA was established by the Stockholm Institute of Transition Economics (SITE) and is a Polish partner of the FREE Network. CenEA’s research focuses on micro-level analyses, in particular in the field of labor market analysis, material conditions of households, and population ageing. CenEA is the Polish scientific partner of the EUROMOD international research project (European microsimulation model), and maintains its microsimulation model SIMPL. For more information, please visit www.cenea.org.pl.

This brief was prepared under the FROGEE project, with financial support from the Swedish International Development Cooperation Agency (Sida). Research in the FROGEE project contributes to the discussion of inequalities in the Central and Eastern Europe with a particular focus on the gender dimension. For more information, please visit www.freepolicybriefs.com. The views presented in the brief reflect the opinions of the Authors and do not necessarily represent the position of the FREE Network or Sida.

Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes. 

Foreign Investors on the Investment Climate in Latvia

Railway bridge across river Daugava representing Foreign Investors on the Investment Climate in Latvia FREE Network Image 01

This brief summarizes the results of an annual study on the development of the investment climate in Latvia from the viewpoint of key foreign investors – companies that have made the decision to invest in the country and have been operating here for a considerable time period. The study was initiated in 2015 and aims to assess investors’ evaluation of the government policy initiatives to improve the investment climate in Latvia. It also aims to provide an in-depth exploration of the main challenges for and concerns of the foreign investors, both by identifying problems and offering solutions. The study draws on a survey/ mini case studies of the key foreign investors in Latvia. Our findings suggest that in recent years, some progress has been achieved on a number of dimensions that are crucial for the competitiveness of the investment climate in Latvia, such as the political efforts by the government of Latvia to improve the investment climate, the overall attitude to foreign investors, and labour efficiency. At the same time, foreign investors see little, if any, improvement with regards to other key areas, such as the availability of labour, the quality of education, the court system, corruption and the shadow economy.

Introduction

The study on the development of the investment climate in Latvia from the viewpoint of key foreign investors in Latvia was first launched in 2015 by the Foreign Investors’ Council in Latvia (FICIL) in cooperation with the Stockholm School of Economics in Riga (SSE Riga). This study aims to foster evidence-based policy decisions and promote a favourable investment climate in Latvia by:

  • (i) Assessing how foreign investors evaluate the government’s efforts and current policy initiatives aimed towards improving the investment climate in Latvia, and
  • (ii) Providing an in-depth exploration of the main challenges and concerns for the foreign investors, both by identifying problems and offering solutions.

The study draws on a survey/mini case studies of the key foreign investors in Latvia. The first 2015 wave of the survey covered 28 key foreign investors in Latvia. Our panel has gradually expanded over time, reaching 47 participating companies in 2019. From September to early November 2019, we interviewed 47 senior executives representing companies that are key investors in Latvia. Altogether, these companies (including their subsidiaries) contribute to 23% of Latvia’s total tax revenue from foreign investors, 9% of the total profit and employ 11% of the total workforce employed by foreign investors in Latvia, where by foreign investors we mean companies with above a 145 000 EUR turnover and 50% foreign capital (data form Lursoft, 2018).

All interviews were conducted by FICIL board members. The guidelines for the interviews consist of the following key parts:

  • (i) Assessment of whether, according to foreign investors, the investment attractiveness of Latvia has improved during the past 12 months;
  • (ii) Assessment of the work of Latvian policy-makers in improving the investment climate during 2019;
  • (iii) Evaluation of progress in the major areas of concern identified by foreign investors in Latvia in 2015, including demography, access to labour, level of education and science, quality of business legislation, quality of the tax system, support from the government and communication with policy-makers, unethical or illegal behaviour on the part of entrepreneurs, unfair competition, uncertainty, the court system and the healthcare system in Latvia.

Furthermore, in the 2019 study we included questions related to some of the key issues discussed between foreign investors and policymakers during 2019, including the tax system, the stability of the financial sector and the quality of higher education and science in Latvia.

Investment Attractiveness of Latvia: Key Concerns of Foreign Investors in Latvia

The results of the 2019 study suggest that, even though the assessment of foreign investors with regards to the investment attractiveness of Latvia and the work of policy-makers to improve the investment climate in Latvia is still at the average level, it shows some positive tendencies. Namely, on a scale from 1 to 5, where ‘1’ means that there are no improvements at all, ‘3’ some positive improvements and ‘5’ significant improvements, the development of the investment climate in 2019 was evaluated as ‘2.6’ (‘2.5’ in 2018 and 2017). Furthermore, when asked to score the policy-makers’ efforts to improve the investment climate in Latvia, using a scale of 1-5, where ‘1’ and ‘2’ were fail and ‘5’ was excellent, investors responded with an average of ‘2.9’ in both the 2017 and 2018 studies, whereas in 2019, the score improved to ‘3.1’.

Foreign investors were also asked to evaluate whether there has been any progress within the key areas of concern as identified in 2015. The results of the most recent study suggest that the demographic situation, which in the long term reflects both the availability of labour and market size, is still among the key challenges for the foreign investors. Namely, on the scale from 1-5 (where an indicator value of 1 means that Latvia is not competitive and 5 means that Latvia is very competitive in this dimension), investors assessed the demographic situation of Latvia with only ‘1.5’ in 2019. Furthermore, as many as 35 (out of 47) foreign investors stated that they had not seen any progress in this area over the past 12 months. This lack of progress is, perhaps, not very surprising as demographic changes may take substantial time.

Another two key areas where investors would like to see more progress are the quality of education and science and the availability of labour. On a 5-point scale, the quality of education and science was evaluated with ‘2.7’ in 2019 (‘3.0’ in 2018, ‘3.1’ in 2017) and 30 out of the 47 investors interviewed have seen no progress in the development of education and science in Latvia over the past 12 months. The availability of labour was evaluated with ‘2.8’ in 2019 (‘2.7’ in 2018 and 2017); investors scored the availability of blue-collar labour with ‘2.4’ in 2019 (‘2.3’ in 2018, ‘2.5’ in 2017) and the availability of labour at management level with ‘3.1’ (‘3.0’ in 2018, ‘2.9’ in 2017). The majority, i.e. 39 of 47 investors have also seen no progress with regards to the access to labour during the past 12 months. In this context, however, it should be emphasised that the efficiency of labour is increasing in Latvia, according to foreign investors: in 2018, it was assessed with ‘2.9’, yet, in 2019, investors evaluated the efficiency of labour in Latvia with ‘3.4’ out of ‘5’.

The quality of health and social security as well as the quality of business legislation are yet another two indicators of the competitiveness of the investment climate in Latvia that have been evaluated around the average level of ‘3’. Further, 33 of 47 investors have seen no progress with regards to improvement of the healthcare system in Latvia over the past 12 months.

While the overall standard of living is evaluated rather positively at ‘3.8’ in 2019, there is still not much improvement in this indicator as compared to the previous three years. One encouraging result of the 2019 study is that according to foreign investors, the attitude towards foreign investors is gradually improving in Latvia: from ‘3.2’ and ‘3.1’ in 2016 and 2017 to ‘3.6’ in 2018 and reaching ‘3.7’ in 2019.

The foreign investors in Latvia who took part in the 2019 study also expressed an expert opinion with regards to whether there has been any progress during the previous 12 months in the other areas of concern. In this light, the perception of uncertainty should be highlighted. As many as 25 (out of 47 investors) have seen no progress in this area, 16 have seen partial progress and 6 stated that there has been progress in reducing uncertainty. The court system of Latvia is another area where many foreign investors have seen no progress, i.e. 22 said ‘no progress’, 23: ‘partial progress’ and only 1 that there has been progress in the development of the court system in Latvia.

Specific Issues: Tax System, Stability of the Financial System and Quality of Higher Education and Science

In the 2019 study, we also initiated an in-depth exploration related to three key issues of concern extensively discussed between foreign investors and Latvia’s government during the FICIL High Council 2019 spring meeting, and throughout the year 2019 in general. These are: (i) the tax system, (ii) the stability of the financial system, and (iii) the quality of higher education and science. Foreign investors were asked to comment on the current situation and progress over the past years, as well as to provide suggestions to the policymakers in order to improve the situation in the particular area.

(i) Tax system:

The most recent tax reform was implemented in 2018, and the newly elected government has announced that the next reform will take place in 2021. Therefore, this year we asked investors to evaluate the results of the previous tax reform in Latvia. We also asked investors to comment on whether the recent tax reform has brought any benefits to their company and the overall economy of Latvia. On average, foreign investors scored the results of the previous tax reform in Latvia with ‘3.1’, i.e. slightly above the average.

Overall, at least one part of the foreign investors who took part in the 2019 studies highlighted that the previous tax reform was a step ‘in the right direction’. In particular, the zero-rate on reinvested profit was highlighted by a large number of investors as a very positive improvement. In some cases, investors also praised the progressivity of labour tax rates. However, a number of foreign investors highlighted that the tax system has actually become more complex after the reform. Investors also expressed suggestions for further steps to improve the tax system in Latvia, and these are as follows:

Avoid uncertainty. Stability and predictability of the tax system is what the majority of the foreign investors wish to see. In essence, this means fewer changes to the tax system.

Simplify and explain. Investors highlight that paying taxes should be a “simple task” and easy to understand. According to the viewpoints of foreign investors, there is also the potential for improvement with regards to how the responsible organisations, such as the State Revenue Service, communicate changes in the tax system to the private sector.

(Continue) the shift from taxing labour to consumption. Some of the investors that took part in the 2019 studies see that the process has been initiated by the previous tax reform and recommend continuing in this direction.

(ii) Stability of the financial sector in Latvia.

On average, foreign investors evaluated the progress with regards to the effectiveness of combating economic and financial crime with 3.2, i.e. above average. We then asked foreign investors whether they have felt any negative effects on their companies with regards to the situations in the financial sector over the past 2 years. We received some positive opinions, yet the negative ones prevailed. Namely, foreign investors highlighted the reputation risks of Latvia that often impact upon the operation of their companies and create challenges when working with foreign banks.

(iii) Quality of university education and science in Latvia.

Here, foreign investors were asked to reflect upon whether they were aware of any activities that policymakers carried out during the past year to improve the situation. On a positive note, a number of investors mentioned the recent development of the University of Latvia and Riga Technical University’s campuses. Some investors also highlighted that the reform to change the governance model of higher education institutions, initiated by the Ministry of Education and Science, was a good step towards improving the quality of higher education and science in Latvia. However, we also received a number of negative opinions, such as “Nothing has been accomplished, just talking”.

When asked “What changes would you suggest to improve the quality of education and science in Latvia and why? How would this help the business environment, e.g. companies such as yours?”, foreign investors emphasised the following:

Higher education (and science) is too local, fragmented and outdated. In essence, investors pointed out that there are simply too many higher education institutions in Latvia, that they work with outdated methods and are afraid (with no good reason) to open up internationally – also by attracting top quality foreign staff.

Change the governance of higher education institutions in Latvia is another strong request from foreign investors in Latvia. Many investors believe that changes in the financing model should also follow.

Improved connection between education and science and the world of business was yet another important aspect which was highlighted during the 2019 interviews, and also strongly emphasised in the previous studies.

Further Investment Plans and Message to the Prime Minister

When asked whether they plan to increase their investments in Latvia, as many as 64% of the investors interviewed answered with ‘yes’ (in the 2018 study, 55% interviewed answered with ‘yes’), 25% said ‘no’ (35% in the 2018 study) and 11% answered that ‘it depends on the circumstances’ (10% in the 2018 study) or that they have not yet decided.

Finally, we invited foreign investors to send a message to the Prime Minister of Latvia: one paragraph on what should be done to improve the business climate in Latvia, from the viewpoint of a foreign investor. These messages closely parallel the other findings of the 2019 study, stressing a number of key concerns that foreign investors are still facing in Latvia: the situation with regards to demography, quality of education and science, availability of labour, challenges with corruption and the shadow economy as well as needs for improvements in the health care sector amongst others.

Conclusions

The findings of the 2019 study on the view of the key foreign investors of the investment climate in Latvia suggest that in recent years, some progress has been achieved on a number of dimensions, such as political effort to improve the investment climate, attitude towards foreign investors, and labour efficiency. At the same time, foreign investors see little, if any, improvement with regards to other key areas, such as the availability of labour, the quality of education, the court system, corruption and the shadow economy.

Our findings highlight the need to continue policy-makers’ efforts to improve the investment climate in Latvia and provide policymakers with better grounds for making informed policy decisions with respect to the entrepreneurship climate in Latvia. We also hope that our study will further facilitate constructive communication between foreign investors and the government of Latvia.

References

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Human Trafficking, Prostitution Legislation, and Data

An image of red light street with signs of striptease club representing human trafficking and prostitution legislation

This report is the compilation of exploratory research work conducted within a project led by Giancarlo Spagnolo (SITE and EIEF), together with Maria Perrotta Berlin (SITESSE) and Ina Ganguli (UMass Amherst). Whilst investigating the effects of asymmetric punishment in the regulation of prostitution, the interaction of markedly different legislations for this along the Franco-German border was of interest. In this report, we present gathered information and data regarding human trafficking and sex work in Germany. We begin by broadly outlining both topics and continue with presenting points that should be considered in future research. The results from a limited survey, where sex workers and counsellors were interviewed, are also presented.

Exploring the Interaction Between Sex Work Regulation and Human Trafficking along the Franco-German Border

In this report, we present data regarding human tracking and the forced prostitution with which it is often connected, as well as data regarding voluntary and consensual sex work. Though we present these topics alongside one another because of the many possible ways in which they may be connected, we do not make any correlating assumptions.

There are different claims regarding the existence of a correlation between sexual exploitation and prostitution policies. Working under the assumption that a correlation does exist, it is still unclear what it would look like (Sonnabend and Stadtmann, 2018). While some argue that legalising sex work leads to an increased social acceptance of the phenomenon and thereby also increased demand for voluntary sex work. It also makes it easier and cheaper for criminals to track people and find customers that, unwittingly or not, pay for sex from victims of human tracking for sexual exploitation (Sonnabend and Stadtmann, 2018; Cho et al., 2013; Jakobsson and Kotsadam, 2013).

On the other hand, restricting or criminalising sex work may make it less likely for such victims, as well as buyers of sexual services of any kind, to collaborate with police forces to report illicit activities related to human tracking (Bisschop et al., 2017; Cunningham and Shah, 2014). Thus, when sex work is criminalised, any that remains will move into the dark, and hence become much more difficult to control (Scoular, 2010).

Sonnabend and Stadtmann (2018) found that different empirical studies have given rather contradictory results. For instance, whilst Cho et al. (2013) found a positive correlation between legal prostitution and tracking flows comparing existing data from over 150 countries, they also acknowledged that this needed to be considered with caution due to the lack of consistent data on human tracking across countries.

On the other side of the spectrum, a report by the New Zealand Government (2008) and a study on human tracking in Europe (Hernandez and Rudolph, 2015) suggest that no links between the sex industry and human tracking can be made. Instead, Hernandez and Rudolph would argue that human tracking in Europe stems mostly within already existing migratory and refugee corridors and is more likely to happen where host countries have weaker institutions, higher general crime rates and more liberal border controls. Host countries’ rates of asylum seekers, however, do not seem to play a role in the extent of human tracking.

Sonnabend and Stadtmann (2018) also endeavoured to calculate the effects of the Nordic model on sex work. They found that the prohibition of sex work is likely to create more loopholes and worse conditions for voluntary prostitution, and thus conditions that facilitate sexual exploitation and human tracking. As can be deduced from this brief introduction, any pre-existing view on the interplay between sex work and human tracking can be easily reinforced as virtually every standpoint can find some support in research. Throughout this report, we attempt to present the information we have gathered bearing these disparate previous findings in mind.

This report consists of six sections. This brief introduction is followed by a section that elaborates on the connections that can be made between human tracking and prostitution legislation. Section 3 presents current issues regarding human tracking internationally, as well as a compilation of the available data for Germany. Section 4 focuses on Germany and the legislative and regulatory environment under which lawful sex work is carried out there. Thereafter, we present some findings from a limited field survey of actors within the prostitution scene along the Franco-German border. We round this report off with a conclusion, briefly summarising and discussing our findings.

Regulatory Efforts

Regardless of how sex work and human tracking may be related, the likelihood of discovering tracking victims can be affected by the policies in place surrounding prostitution. Opponents of laws restricting prostitution often argue that when sex trade is outlawed, even if only for one party (as in the case of the Nordic model) the activity does not cease to exist, but is simply moved into the black market. Getting a full grasp of the extent of human tracking within the already restricted environment of prostitution will be considerably more difficult than if it had been within a legalised setting that allowed for regulatory oversight. However, as will discussed in this report, getting the regulatory oversight right is a challenge and there are considerable legitimate criticisms of this liberal stance too.

Table 1 Varieties of Legislation

Table 1 Varieties of Legislation

Varieties of Legislation

Across Europe, we find different kinds of prostitution legislation. Countries have chosen to combat the negative elements often associated with sex trade in ways that differ greatly in mechanisms and outcomes. These can be grouped into four overarching groups, all working in somewhat different ways, presented in Table 1 above.

Historically, prostitution has been a highly sensitive issue. Traditional moral and religious values all over Europe have condemned extramarital sex of any kind. Laws have ranged from outlawing prostitution to barely touching the topic. This becomes apparent when looking at the four overarching types of legislation that we will cover in this section. Abolitionist and prohibitionist policies present the two dominant legal traditions.

The four groups do not only differ from one another, but there is great variation between countries of each respective group, perhaps with the exception of countries that have neo-abolitionist policies. For instance, while brothels are legal in Germany and the Netherlands, Latvia has chosen to regulate prostitution from an abolitionist standpoint by making sex work a licensed profession but largely does nothing more (Cabinet of Ministers (Latvia), 2008). In Turkey, prostitution was legalised already in 1923. In recent years, however, Turkey has been a lot more restrictive in issuing new licenses (Sussman, 2012).

Figure 1 Typical Historical Development of Legislation

Figure 1 Typical Historical Development of Legislation

The prohibitionist group differs less in terms of legislation and more when it comes to enforcement. The enforcement of these policies tends to be weak, with measures needed to ensure that no prostitution is carried out behind closed doors largely lacking. We find the greatest in-group variation amongst the abolitionist countries. This approach is also the one that is least easily defined. In a sense, it, therefore, becomes a catch-all term for countries that fall outside of the scope of the other three groups.

The reasons for the differences in legislation on this matter is that countries, for varying reasons, have chosen to prioritise different goals. This is obvious when looking at the mechanisms of each type in Table 1. What they all have in common, however, is that without diligent enforcement of the laws, illegal prostitution is likely to persist.

Project and Intentions

As part of a research project at the Stockholm Institute of Transition Economics (SITE) in which researchers Giancarlo Spagnolo (SITE), Maria Perrotta Berlin (SITE) and Ina Ganguli (UMass Amherst) are looking into the effects of asymmetric punishment in legislation, the neo-abolitionist ‘Nordic model’ for prostitution is of interest.

Though the focus is placed on Scandinavia, France came into the picture as similar legislation was adopted there in April 2016. As a result of the change in France, which presumably made it harder for people to purchase sexual services, it became interesting to see how potential consumers may take advantage of the open border to Germany, where prostitution is legal. Before the law changed, the exchange of sex for money had been legal, with some restrictions on solicitation. Running a brothel, pimping or paying for sex with a minor had, however, never been allowed. With the change towards asymmetric punishment, selling sex for money remained legal whereas purchasing it was now considered a crime.

This put the two most recently developed types of prostitution legislation, regulationst in Germany and neo-abolitionist in France, next to one another along the Franco-German border. The effects of the cross-border dynamics are what we, as research assistants to the team at SITE, tried to map. We assumed that the regulationist approach of Germany would enable us to more easily investigate the effects of the change in legislation in France across the border.

For this reason, we investigated how customers and working conditions, among other things, changed in areas of Germany neighbouring France. As our research progressed, this underlying assumption would prove to be less straightforward than we had thought originally. Though we cannot give a conclusive answer to how the change in regulation came to affect the market for sex in Germany, we gained insights and gathered information that we have compiled in this report.

The State of Human Tracking

. . . the recruitment, transportation, transfer, harbouring or receipt of persons, by means of the threat or use of force or other forms of coercion, of abduction, of fraud, of deception, of the abuse of power or of a position of vulnerability or of the giving or receiving of payments or benefits to achieve the consent of a person having control over another person, for the purpose of exploitation. Exploitation shall include, at a minimum, the exploitation of the prostitution of others or other forms of sexual exploitation, forced labour or services, slavery or practices similar to slavery, servitude or the removal of organs.

— DEFINITION OF ‘TRAFFICKING IN PERSONS’, ARTICLE 3, PARAGRAPH (A) OF THE UN PROTOCOL TO PREVENT, SUPPRESS AND PUNISH TRAFFICKING IN PERSONS, ESPECIALLY WOMEN AND CHILDREN, SUPPLEMENTING THE UNITED NATIONS CONVENTION AGAINST TRANSNATIONAL ORGANIZED CRIME

The international community has long been struggling with the prevalence of human tracking. Initially, under the heading of slavery, human tracking has, through multiple conventions over the past 150 years, been explicitly restricted and outlawed by most countries. Though what we regard today as human tracking and modern slavery might not resemble stereotypical ideas from the past, at its core, it is still very much the same. We consider a situation as human tracking when a person is involuntarily under the control of another and forced to commit acts against his or her own will.

As the definition above is read, we see that human tracking can encompass many different criminal acts. However, there are three basic elements that are needed to legally define a situation as an instance of human tracking: an act, a means, and a purpose of exploitation. Because of its often hidden nature, the full extent of human tracking is difficult to map. Nonetheless, many countries across the world acknowledge the seriousness of the issue and are making efforts to combat it. Policymakers are further aware that the fight against human tracking is wholly dependent on international cooperation given that perpetrators often exploit vulnerable people by removing them from their countries of origin.

Once again, when discussing sexual exploitation in tracking, it is inevitable that regulations regarding prostitution will have to be discussed. Though sexual exploitation in trafficking does not necessarily entail prostitution, it is a straightforward way for trackers to monetise an already illicit activity. However, this does not mean that tracking for sexual purposes will be the underlying cause for all sex work, or even related to it in general, especially in jurisdictions where it is permitted. The relationship between prostitution and human tracking is complex and multifaceted and is deserving of thoughtful analysis.

A Lack of Reliable Information

There is uncertainty surrounding the prevalence of human tracking. Due to its illicit nature, it is hard to grasp really how widespread it is. It is only possible, as with any other black market good or criminal activity, to observe the number of detected instances of tracking. Currently, 173 of 193 UN member states have ratified the Palermo protocol on tracking in persons (UN Treaties Collection, 2019). In 160 of those, human tracking has been explicitly criminalised, and the numbers we have to rely on come from those countries (Chatzis, 2018). In the period 2012-2014, the United Nations Oce on Drugs and Crime (2016), UNODC, reported a total of 63,251 victims worldwide. Compared to estimates ranging in the tens of millions from the ILO (2012) among others, the number of detected victims is minuscule (US State Department, 2017).

There is also an under-reporting of different kinds of tracking. Especially organ removal is yet to be sufficiently mapped (Chatzis, 2018). Using any currently existing data involves an inherent bias stemming from this under-reporting that should be kept in mind. There are, however, some obvious tendencies shown in the data available to us, that help us in understanding human tracking at large.

A clear majority of reported victims are women, though the share of men has increased over time and is substantial. Data from 2014 published by the UNODC (2016) puts men at 21 per cent of victims. Men are particularly under-represented among victims of sexual exploitation; women make up 97 per cent of those exploited for sexual purposes (Chatzis, 2018). Men are considerably more likely to be exploited as forced labour. Namely, 85 per cent of detected male victims were exploited for labour. Overall, the victims of forced labour are in 63 per cent of all cases male (Chatzis, 2018).

Reasons for Persistence

Regardless of many efforts to combat this problem, human tracking persists. According to Chatzis (2018), the reasons for this lie not only in the complex nature of the crime, but also (i) in the widespread use of the internet in facilitating it, (ii) in an international trend to deregulate labour markets, and (iii) in increased flows of migration. Especially in Europe, labour markets have seen a push from politicians asking for more flexibility after the most recent recession. Conflicts around the world, particularly in the Middle East, saw the nationalities of tracking victims mirror those of increased outward migration (Chatzis, 2018).

The sheer number of refugees over the most recent years, and the strain this has put on countries, agencies and organisations, has also added to a likely increase in the undetected cases of tracking. European countries have not been capable of effectively screening for likely victims of tracking (Chatzis, 2018). One could even claim that the incapability in understanding the mechanisms of tracking has caused some European countries to induce it, albeit inadvertently. For instance, the Italian government’s agreement with Libyan authorities to stem the flow of migrants across the Mediterranean has been reported to create slave-like conditions for predominantly African migrants in Libya (Kirchgaessner and Tondo, 2018). This was also reflected in our study, which will be further discussed below, counsellors working in Germany that we interviewed had personally met Nigerian women, whose experience as victims of sex tracking began in Libya.

Public Official Figures

Available data allow us to make some general statements concerning the types of tracking around the world. A majority of detected tracking victims globally have been victims of sexual exploitation. However, the most prevalent kind of tracking changes with geography. In Africa, victims are more commonly detected in circumstances defined as forced labour, rather than as sexual exploitation. However, this information comes with the caveat that it could instead be a reflection of what kind of tracking rapporteurs in different parts of the world are able to detect.

When looking at Europe, the most recent figures from 2016 reported by the UNODC show that the share of detected tracking victims that had suffered sexual exploitation is substantial, reportedly more than two-thirds of victims were tracked for sex (UNODC, 2018b). Similar numbers were reported for Western and Southern Europe, a region largely made up of the countries that were part of the Western Bloc, in the preceding report from the UNODC (2016). Throughout Western and Southern Europe, twelve (thirteen) countries reported the 12,226 (12,775) victims detected there come from all over the world in 2016 (2014), with citizenships in 124 (137) different countries.

There are, however, some clear trends that can be gleaned from the numbers. For Western and Southern Europe, victims more frequently come from outside the country they are detected in or nearby countries. A third of victims had their origin in Central and South-Eastern Europe, an area largely corresponding to countries of the former Eastern Bloc that have now become part of the European Union (UNODC, 2018b). This share was the same in 2014 (UNODC, 2016). The remainder is largely made up of victims from Africa and East Asia.

German Data

The Federal Criminal Police Oce (Bundeskriminalamt), BKA, is the government agency that compiles data for all sorts of criminal activities across the country. The BKA annually publishes a report on the state of human tracking in Germany, currently under the name of ‘Bundeslagebild Menschenhandel’. Again, when viewing these figures, we need to keep in mind that the numbers presented here only concern the detected instances of human tracking.

These reports, from 1999 until now, are available online at the BKA’s website. The most recent report for 2018 was made public in September 2019. Though the structure of the report differs slightly from year to year, there are some tables that are available throughout the period. For this report, we have primarily used the disclosure of nationalities of victims of human tracking for sexual exploitation. As could perhaps be expected, the vast majority of reported victims over the past 20 years come from Europe. Over time, we see a decreasing trend in the number of victims of human tracking. However, due to the relatively low levels of human tracking from non-European countries, this trend is really only noticeable for victims of European origin.

Figure 2 Non-European Victims by Continent (1999-2018)

Figure 2 Non-European Victims by Continent (1999-2018)

Figure 3 Victims of European and Unknown Backgrounds (1999-2018), incl. Germans from 2003

Figure 3 Victims of European and Unknown Backgrounds (1999-2018), incl. Germans from 2003

Ideally, we would want to disaggregate the data and look at individual countries instead of continents. However, the BKA does not publicly disclose the figures for all countries. What it does, though, is feature numbers for a selection of countries of origin each year. Though not explicitly stated, it is likely to be the most frequent origin countries for each year. In Table 2 below, we show which countries appear and when. An important change in the report is the inclusion of German victims from 2003 (BKA, 2003).

Table 2: Specified Origin Countries of Victims of Tra�cking 11 for Sexual Exploitation

Table 2: Specified Origin Countries of
Victims of Tracking 11
for Sexual Exploitation

Figure 4 Victims from Specified FSU Countries (1999-2005)

Figure 4 Victims from Specified FSU Countries (1999-2005)

Throughout the period and not subject to any major change, is that most victims of human tracking are citizens of Central and Eastern European countries. However, over the course of 18 years, there are some changes regarding which countries are more and less prominent.

At the turn of the millennium, countries of the former Soviet Union (FSU) constituted a majority of all non-German human tracking victims. This can be said despite having explicit data for only five of those countries, Russia, Ukraine, Belarus, Lithuania and Latvia, in the period 1999-2002. For 2003-2007, it is possible to observe a shift where the share and number of these countries decrease in conjunction with them being less and less mentioned in BKA’s reporting.

Bulgaria and Romania first appear in the 2001 report and the number of victims rises sharply until 2003. Since then, there have been fluctuations in the number of reported victims from these two countries, but they have overall been somewhat stable at a considerably higher level than before. Since 2008, they have made up more than 55 per cent of the European non-German victims, and the majority of all non-German nationalities for all but three years.

Figure 5 The Most Frequent Origin Countries 2018 (2001-2018)

Figure 5 The Most Frequent Origin Countries 2018 (2001-2018)

Figure 6 Total Number of Victims 1999-2018

Figure 6 Total Number of Victims 1999-2018

Prostitution in Germany

In the past 30 years, prostitution laws in Germany have undergone numerous changes. Not only German law is likely to have affected the prevalence of prostitution within the country, though. The expansion of the EU and domestic as well as EU-wide policies in relation to it, policies in neighbouring countries, and major geopolitical events might have all contributed to the current state of prostitution and human tracking in Germany.

However, the greatest change is arguably the 2001 law, the Prostitutionsgesetz (ProstG), which institutionalised prostitution in Germany, taking the exchange of sex for money from a legal grey area into a legally recognised occupation. In principle, this regulationist approach could bring illegal and criminal acts often related to the sex trade, such as human tracking, to the surface, thereby creating a safer prostitution market for both sex workers and consumers through the possibility of regulatory oversight. However, with time, polarised opinions have been raised about this policy. Some have praised the ProstG as a milestone for sex workers’ rights. Others have proclaimed that Germany has become an exploitative ‘battery cage’ (Conrad and Felden, 2018). There have been several previous investigations into the ways in which the ProstG has impacted the state of prostitution, as well as reports on human tracking in Germany reaching different conclusions (e.g. Tavella, 2008; Czarnecki et al., 2014; Gunderson, 2012; Kavemann and Steffan, 2013).

With time, it became clear that legalisation without regulation may be fertile soil for the uncontrolled growth of prostitution activities. For this reason, the German government enacted the Prostituiertenschutzgesetz (ProstSchG), or the ‘Prostitute Protection Act’, in July 2017. The act added a number of statutory requirements on sex workers, which we will cover shortly. Germany’s approach to prostitution represents an interesting case in the European context, where prostitution has typically been very differently conceptualised and thus, legally dealt with.

The Evolution of German Law

The most significant shift for Germany is arguably the recently mentioned ProstG, which created the occupational status for sex work in Germany. It was enacted after extensive debate. Sex workers had voiced their misgivings with the then-current legislation, where prostitution was not illegal but without a legitimate position in society. Brothels and sex workers were perceived to be prevented from achieving acceptable standards in their working conditions because of the regulations in place. From the early 1980s to the mid-90s, several debates on the topic were held in the Bundestag. Draft legislation was rejected in June 1998 by the governing centre-right CDU/FDP coalition. The following centre-left SPD/Greens government brought the proposals back to parliament, which then later passed them with support from all parties bar the CDU/CSU group on 20 December 2001. The law came into force on January 1, 2002 (Kavemann and Steffan, 2013).

With ProstG, sex work was set on an equal legal footing to any other kind of profession. Those practising it were now entitled to social insurance and were given the legal means to demand payment from customers (Kavemann and Steffan, 2013). However, there are geographical restrictions on prostitution, which vary between states. The 1974 Einfu ̈hrungsgesetz zum Strafgesetzbuch, EGStGB, contains one article (number 297), which is of particular relevance.

The EGStGB article gives states the right to restrict the areas and times in which prostitution is allowed through decrees. For municipalities (Gemeinde) with a population above 20,000 inhabitants, a part of the municipality can be set off-limits for prostitution, with the option to forbid it completely in municipalities with up to 50,000 inhabitants. This law has been used as a justification for instance in Baden-Wu ̈rttemberg and Saarland, where prostitution has been forbidden in municipalities with less than 35,000 inhabitants since 1979 and 1982 respectively. The law also allows for restrictions regarding which times of the day prostitution is permitted.

In October 2016, the Bundestag passed the ProstSchG, effective as of 1st July 2017. introducing new regulations on the trade of sex. To lawfully work as a prostitute, one would now have to register as such and thereafter carry a work ID. Registration requires valid ID documents, a health check-up and a yearly health examination to maintain the status. Furthermore, the registration needs to be renewed every two years. In order to protect sex workers’ right to anonymity, one may be registered under a pseudonym if requested.

Additional provisions in ProstSchG include barring registrations if there is evidence of the registration being induced by third parties, or when in the last six weeks of pregnancy. When registering, the responsible agency is required to inform sex workers of their rights and responsibilities, including what the ProstSchG entails, such as consultation opportunities in relation to health and pregnancy, and how to get help in emergencies. Additionally, all prostitution-related businesses, such as brothels and Laufhauser (establishments where sex workers rent rooms), need to register and get permits as well.

Lastly, the ProstSchG also introduced a statutory condom requirement during intercourse. Not following this requirement could result in a fine of up to 50,000 Euros. Though the law as a whole was welcomed by most states, especially because of the statutory permission requirement (Erlaubnispflicht), many of the other requirements are related to significant implementation costs.

In connection to the introduction of ProstSchG, the German Federal Statistical Oce, Destatis, was tasked with gathering statistics on several of the registration requirements now statutorily demanded (law ProstStatV, 2017) from state and local authorities. As of yet, there have been significant difficulties in gathering this data. At the time of writing this report, only ten of Germany’s sixteen states have provided any data. The data provided is also incomplete, with several Landkreise and even some major cities unable to successfully roll out the new legislation (Destatis, 2019). Hopefully, many of the current data issues will be mitigated in the future.

The Extent of Prostitution in Germany

Though a country with regulationist policies, Germany has little publicly available statistics concerning the state of prostitution in Germany. A central issue is and has long been the actual size of the sex trade market. One figure that is often referred to in many newspaper articles is that of 400,000 prostitutes. It has been circling around in the media for at least the past 15 years and we have not been able to identify the original source.

However, the estimates vary widely depending on the paper reporting the number, and there is generally no reference to how estimates were created or by whom. One extensive, though not exhaustive search by us found the total number of prostitutes in Germany over the past 20 years to reportedly range from a lower bound of 60,000 (Stephani, 2017) to an upper bound of 700,000 (Junge, 2001). The most recent official number of issued licenses (from 31st December 2017), however, are 1,350 across Germany (See Table 3 below)4 and a total of 7,000 having reported to relevant authorities (Destatis, 2019).

Today, prostitution is commonplace across Germany. In German and international media, the country is often referred to as one of the prostitution hubs of Europe. One figure that is commonly referred to in the media is that of 1.2 million transactions a day (Junge, 2001). Though again, this is only an estimate with unclear foundations. Three surveys conducted between 2012 and 2015, one by bi-weekly women’s magazine Brigitte and two by the German edition of Playboy, had German men responding to if and how often they buy sex. There were considerable differences in their results, indicating that between 10 and 88 per cent of German men had bought sex at some point (Crocoll, 2013; FOCUS Online, 2012; 2015).

Table 3 Number of Issued Licences by State

Table 3 Number of Issued Licences by State

By moving away from sex workers having the option to register as such on their social insurance and instead of making it mandatory to register to get a permit, the German government hopes to tackle the difficulties it has had in understanding the full extent of the prostitution market. In 2013, the Federal Employment Agency reported that the number of women registered as sex workers on their social insurance was 44 (Meyer and Nagel, 2013). Beyond doubt, this figure did not correspond to reality.

In a study included in the 2007 governmental evaluation of ProstG, 305 sex workers completed written interviews to explore some of the reasons why the number of registered sex workers was so low. Only 1 per cent of respondents had a formal employment contract as sex workers, while some had other professions outside of prostitution. A clear majority (roughly 70 per cent) said they were freelancing. Responses from brothel operators also indicated that sex workers were given the option to be registered as “employees of an artists’ agency or as a prostitute” (BMFSFJ, 2007). This demonstrates the failure to turn sex work into a profession like any other, which might be related to the common stigma associated with this profession, and likely spurred on the introduction of the ProstSchG measures.

Changes Outside of Germany

Table 4 Changes abroad likely to have impacted the German market for sex

Table 4 Changes abroad likely to have impacted the German market for sex

Apart from domestic reforms in regulation, the German market for sex is likely to have been affected by multiple outside factors since the enactment of the 2001 ProstG. Together with our initial point of interest, the French reform in 2016, we have listed some of the most prominent events in Table 4 above.

EU Enlargement

On 1 May 2004, the European Union gained ten new member states: Cyprus, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Slovakia, and Slovenia. Roughly two and a half years later, in 2007, Bulgaria and Romania also joined. In this period, the European Union saw the number of member states rise from 15 to 27 and its total population increased by roughly a quarter (Eurostat, 2018). All these countries were and still are, below the EU-28 GDP per capita average, together with only four ‘old’ members (Eurostat, 2017).

Since their accession, there has been a considerable movement of labour across Europe from these countries (European Commission, 2011). However, there were certain provisions in place for both accession groups, restricting the free movement of labour from those countries to Germany at first. Full freedom was not granted until seven years after joining (Andor, 2014; European Commission, 2018).

Ukraine

Following the annexation of Crimea by the Russian Federation and the subsequent war in Donbas, around 1.6 million people have been displaced according to the UN (2018). The majority of those are registered as internally displaced within Ukraine, but around 1 million people have sought asylum in neighbouring countries. In the period from 2011 to 2015, a report commissioned by the International Organisation for Migration (IOM) and written by the market research institute GfK estimated that the share of the population vulnerable to human tracking rose from 14 to 21 per cent, a 50 per cent increase (GfK, 2015). In 2017, that share had not changed (GfK, 2017).

At the same time, the number of registered tracked persons has followed a bit of a U-curve. The OSCE (2016) reported that the number was 380 in 2006, and in 2015 it was 111 and during the first ten months of 2016 only 96. The UNODC (2018a), however, presents slightly different numbers from the Ukrainian Ministry of Social Policy, totalling 83 in 2015. From 2014 to 2017 they report the number of victims rising from only 27 to 198. According to the UNODC, a majority of victims were tracked for labour exploitation, but the share of those exploited for sexual purposes increased from a few percents initially to around a quarter in 2017. The discrepancy in the numbers reported by the UNODC and the OSCE is an issue, though.

Additionally, the change in visa rules for Ukrainian (and Georgian) citizens in 2017 eased access to the Schengen area. If in possession of a biometric passport, Ukrainian citizens could now go to Schengen countries without a visa (European Commission, 2019). In a small survey, conducted in December 20175, we found through interviews with sex workers and counsellors in Germany that there has been a perceived increase in sex workers from Ukraine recently. Again, we need to acknowledge that the origin countries of sex workers do not necessarily indicate activities surrounding human tracking. There are, however, reasons to assume that with an increased migratory flow from Ukraine, human tracking activities may possibly take advantage of the same corridor.

Migration Crisis

As mentioned in the case of the war in eastern Ukraine, displaced people and refugees are exposed to an increased risk of being tracked (IOM, 2015). In armed conflict, fighting groups not uncommonly abduct and recruit men, women and children to be forcibly used as combatants, sexual and domestic slaves, forced labour or coerced into marriages (UNODC, 2016). Chatzis (2018) also stressed conflict as one of the main reasons for the persistence of tracking.

Though the number of reported cases of tracking from especially Syria initially went up following the outbreak of the Syrian Civil War, absolute levels remained relatively low (UNODC, 2016). As noted by Chatzis (2018) though, it is not safe to say that this is an accurate reflection of reality as the crisis created circumstances where screening for tracking was, and in part still remains, neglected.

France

On the 6th of April 2016, France implemented the ‘Nordic model’, designed to discourage buyers of prostitution and ease pressures on prostitutes. Those caught buying sex could face up to 3500 Euros in fines for repeat offences and fines of up to 1500 Euros for first-time offences (McPartland, 2016). Before the law changed, France would have been categorised as a country with abolitionist legislation. It had in place restrictions on pimping, brothels, and solicitation, while the passive solicitation of customers had been banned in 2003 (Chrisafis, 2012). However, with regard to the fundamental act of paying and being paid for sex, there was no statutory ban (RFI, 2015).

EU Directive

The 2011 EU Directive ‘on preventing and combating tracking in human beings and protecting its victims’ (Directive 2011/36/EU) was agreed by the Council to homogenise the varying national regulations of this cross-country problem. It replaced a 2002 Council Framework Decision. For Germany, it included new penal provisions, which would ease the implementation against trackers and tracking (CBSS, 2016).

In the directive, member states were requested to transpose it by April 6th, 2013. By that date, Germany was the sole member state not to have transposed the directive into law (European Parliament, 2016). Not until roughly three years later in July 2016 did the Bundestag pass a bill proposed by the federal government to turn it into law. Even after the decision, implementation would wait until 1st July 2017.

Though Germany today has the legislative tools to combat tracking, critics lament the lenient application of laws. Only 26 per cent of the trackers convicted receive prison sentences, leaving potential trackers less than deterred (US State Department, 2017).

Data Gathering Mission

As any publicly available data on prostitution in Germany has been fraught with issues, the research team at SITE decided to get in touch with those most familiar with the subject: sex workers, brothel owners, as well as people working closely with sex workers and potential victims of human tracking, this last group henceforth referred to as counsellors. These counsellors worked in the public sector and for non-profit organisations as either health care professionals or social workers. By reaching out to all three groups, we intended to get closer to finding out the answers to the questions at the core of this effort: What were the effects on sex work and human tracking in the German regulationist environment caused by a change from abolitionist to neo-abolitionist legislation in France? More specifically, would sex buyers become more likely to go from France to Germany than they had been before to circumvent the risk of sanctions?

Method

To uncover the dynamics of the prostitution market in Germany, we deployed a mixed-method approach to create a holistic picture of the sex work market at the German border (Plowright, 2011), combining quantitative and qualitative methods. Specifically, we held semi-structured interviews with counsellors working with sex workers and victims of human tracking for the purpose of sexual exploitation active in the region along the border. This allowed the interviewees to share relevant information. Through our interactions, we could also gain vital knowledge of how to improve our plan for approaching and surveying sex workers.

One crucial constraint when interacting with sex workers in the field was time. As we could not offer any financial incentives, we developed a questionnaire (see Appendix) that would be able to capture the information we were searching for, without taking up too much of their time. Questions ranged from asking the sex workers about the extent to which they felt safe, liked or disliked their working conditions, to what the perceived national backgrounds of their clients were. The questionnaire aimed particularly at asking about possible changes in the nationalities they served, their profits, and prices they could charge over the preceding two years.

Most questions did not mention the law change in France or the possible difference in the number of French customers, although it was asked at the end of the survey in case this had not been mentioned by the interviewees. With the help of our counsellor contacts, we created a questionnaire that could be answered quickly, within 5-10 minutes from when we first approached them. It enabled us to gather mostly quantitative data with some minor scope for open answers, allowing some data of a qualitative nature as well.

When working with a sensitive subject such as sex work, it is crucial to respect the personal integrity of everyone involved. This meant that we had to ensure the sex workers’ anonymity, not record the conversations and even limit the sharing of raw data between researchers. One counsellor emphasised that many sex workers typically hide their occupation from their wider social circle, often even close family, due to the stigma and fear of social exclusion.

There is also a tendency for many sex workers to be reluctant about reporting the sometimes precarious conditions they live or work under, due to the stigma they face. Our efforts tried to mitigate this issue, committing ourselves to not share information that could identify them afterwards even within the research team. Of course, this did not apply to the experts we interviewed. These latter interviews were recorded and transcribed to ensure the completeness of the information provided.

Data

Geographically, we endeavoured to interview sex workers and brothel owners as close to the French border as possible. Specifically, this meant that the interviews we carried with these actors were in the cities of Saarbrucken, Saarlouis, Offenburg, Trier, and Freiburg and the village Rilchingen- Hanweiler outside of Saarbrucken. In order to get a more general understanding of sex work and human tracking across Germany, as well as more border-specific insights, we primarily interviewed counsellors exposed to the German-French border dynamics, based in Kehl, Strassbourg, Heilbronn, Freiburg, and Trier, but also some farther away in Berlin and Dortmund.

When approaching sex workers in the field, we learned quickly the truth of what counsellors had already warned us of. Out of 44 sex workers, only 17 accepted to be interviewed when approached. The survey was conducted in October and November 2017, generally late at night and either in a street setting or in a brothel. More than half of the sex workers (around 60%) had at that point been working in the sector for more than 1.5 years and almost a quarter for more than 8 years. Three-quarters of the sample was judged to have a good of comprehension of the questions, whereas language proved to be a considerable problem with the remainder of our interviewees.

Table 5 Nationalities of surveyed sex workers

Table 5 Nationalities of surveyed sex workers

Nine semi-structured interviews with counsellors working directly with either sex workers and/or victims of human tracking working along the Franco-German border were conducted. These interviews took place in person or over the phone. In both cases, they were recorded and later transcribed. These experts were working, as previously mentioned, either in publicly run health institutions that directed their services specifically towards the needs of sex workers or at NGOs aiming to support sex workers or victims of human tracking in various concerns.

In contrast to the mostly quantitative data obtained from the interviews with sex workers, the interviews with counsellors were of a qualitative nature and allowed a more nuanced understanding of the complexities surrounding sex work and sexual exploitation across the German-French border.

Limitations and Difficulties

Initially, our plan had been to reach out to sex workers through health organisations that counsel them on a regular basis. However, we faced major obstacles to that. These organisations work for a long time to establish trust between them and this vulnerable and often stigmatised part of society. For this reason, they were very hesitant to arrange any contact between us and the sex workers they counsel. Research and health experts have repeatedly shown how hard it is to detect whether or not a sex worker is the victim of human tracking. It often takes social workers a long time of counselling until a sex worker decides to open up about the reasons that led them to pursue sex work.

For this reason, the options of gathering data were few, and sex workers had to be approached during their working time in brothels or street prostitution areas. This, in turn, caused several difficulties.

First, it highlighted the lack of resources at our disposal. Approaching subjects in the field is one of the most costly methods, particularly when dealing with a hidden population such as this. Whatever information we would be able to gather would not necessarily provide a representative sample of answers.

Second, whether in the context of a brothel or on the street, sex workers usually have a limited time in which they actually earn money. In most cases, street prostitution is not only limited to certain streets, but also to certain times of the day. For instance, in Saarbrucken, it is only allowed between 10 pm and 6 am. As for brothels, sex workers generally have to pay high rents for a limited number of hours there. Considering that we could not offer financial compensation for the interviews, many women felt disturbed by the request, even if it took only 10 minutes, as it could mean the loss of a potential client.

Third, most women working as sex workers often hide their occupation from friends and family members. When working, they generally use other names, thereby enacting the role of their sex worker persona. This makes it harder from a research perspective to ask questions that might touch upon their more private experiences outside their role as a sex worker. For instance, the probability of finding a robust indicator of their real-life satisfaction or health may be rather low.

Fourth, when visiting brothels, there was another complication that emerged for the researcher- in-field. Most people who go to brothels want to be guaranteed privacy. This, however, can be disturbed if it becomes clear that an observer who is not part of the milieu is in the brothel. For this reason, most attempts to talk to prostitutes within brothels failed.

Lastly, a major limitation in the data gathering process was the language barrier between us and many sex workers. The lacking language skills were an important indicator to understand that these women were less likely to have spent a long time in Germany. However, it also made it difficult to ensure that they understood the questions posed in the survey. In some cases, sex workers with better German skills translated on behalf of their colleagues, which in turn may have caused some inaccuracies.

Findings

On sex work conditions and the impact of changes in prostitution law in France
By surveying sex workers, we could not find any evidence for our working hypothesis. The change of the French prostitution law did not seem to increase the number of French people coming to Germany to buy sex. From the interviews with sex workers that we carried out, all but one assessed the number to be the same, while the last one, based in Offenburg, stated that there had been an increase in tourism from France. Neither had there been any noticeable difference in the number of customers from any of the countries listed in our questionnaire: the US, the UK, France, Italy, Spain, and Russia.

A possible reason for this seemingly minimal change in the influx of French customers was suggested by a health expert working both in France and in Germany with sex workers. According to her, there had been very few cases of prosecution of prostitution customers despite in France the law (Kehl/Straßburg BE0009). This can be disputed though, as the Coalition Against Prostitution (2017) reported that 937 sex buyers were arrested in the first year following the implementation of the law, rising to 4000 by early 2019 according to the Fondation Scelles (2019). Where most of these arrests have happened is not disclosed though. If there are geographical differences across France, it could mean that there are regions in France, possibly bordering Germany, where it may still be safe enough for sex buyers not feeling the need to go elsewhere. Should that be the case, then it could be a reason why no increase in the German sex work market can be detected.

Asked about more general changes taking place since 2016, sex workers and health experts reported that the economic conditions for prostitutes had worsened considerably. Five out of the 17 sex workers, based in different cities, reported that prices for their services had dropped. According to them, this was related to two recent developments within the market. Firstly, more and more women from Eastern European countries such as Bulgaria and Romania were working as sex workers. Considering the comparatively low salaries in these countries, these sex workers tend to be more willing to compete by lowering their prices. Secondly, according to sex workers, customers claim to have less money and thus bargain more.

From the questions posed on our questionnaire, we are unable to clearly identify whether the prices had been falling since 2016 or if it is a continuation of a more long-term trend. Although several women indicated that the decline in prices was recent, those who did had only worked for less than five years.

When responding to questions regarding health and overall life satisfaction, half of the interviewed sex workers claimed that they felt completely safe while working, against almost a quarter that did not. Looking more closely at the ten sex workers that said they had been working in milieu for at least five years, just three of them claimed to feel safe. Therefore, it seems that sex workers who have worked longer in the milieu feel less confident about their safety.

Overall, the sex workers who worked predominantly in the context of street prostitution reported feeling less safe, and also a lower overall life satisfaction, than those in brothels. When asked about their personal health, no sex worker reported to be unwell, but six of them refused to answer this question.

Counsellor Inputs

Migratory flows from Eastern Europe
Many of the counsellors we interviewed seemed to agree that the total number of active sex workers did not necessarily differ since the implementation of the ProstG in 2002. However, those who had been working in the field for many years said they had noticed the proportion of foreign-born prostitutes rising significantly with the implementation of the 2001 law. All but two of the seven counsellors we interviewed estimated that the share of non-German sex workers was above 50 per cent. Those of the other view still believed it to be above a quarter. An earlier policy report by the Institute for East and Southeast European Studies from August 2015 confirmed this belief (Petrungaro and Selezneva, 2015). The fact that most of our counsellors found prostitutes to be majority non-German corresponds with earlier findings that showed this share for female sex workers rising from 52% in 1999 to 63% in 2008 (TAMPEP, 2008).

What they did all agree on, however, was that Eastern Europe was the most common background of foreign sex workers, which is also the case in the data we gathered. More specifically, women from Bulgaria and Romania form a majority within the group of sex workers in Germany who recently took up this profession. Women from Asian countries, such as Thailand, as well as from Latin America were observed to be the second-largest group of people working as sex workers by counsellors. Though, they were far fewer than their Eastern European colleagues. For example, in Strasbourg the most frequent nationality among sex workers was Bulgarian (Straßburg/Kehl, BE0004). Around Saarbrucken, we got to talk predominantly to Romanian and Bulgarian sex workers.

Our survey of sex workers indicated that the high share of Bulgarian and Romanian sex workers was to be found especially in street prostitution contexts. In brothels, we found a more diverse ethnic composition (Saarbrucken, BE0003). Some counsellors, for instance, one in Kehl, claimed that this shift towards more and more women from Bulgaria and Romania is strongly correlated with the incorporation of Eastern European countries in the EU. For sex workers, this meant that they were particularly vulnerable in the transition phase that new member states had to go through after becoming an EU member but before being allowed unrestricted freedom of movement, as they were not eligible for the protections in the 2002 German law (Kehl/Straßburg, BE0009).

According to a counsellor working with sex workers in Trier, the socio-economic background of sex workers from Romania and Bulgaria varies. Some of the women are students in their home countries and thus highly qualified in the labour market. They often work in rather high-priced brothels. At the same time, there are also women who are living under very poor conditions (Trier, BE0008).

A further finding from our interviews was in contrast to a common belief that sex workers migrate to Germany. Counsellors reported that it is very common for sex workers to have a permanent base in their origin country and only travel to Germany, as well as Austria and Switzerland, in order to earn a living and support their families for shorter periods (Trier, BE0008). There are some women, however, who do not have the know-how to organise their own trips, and thus, stay at one place for longer and end up settling down in Germany (Trier, BE0008). Often, the families and close acquaintances back home know little about the occupation of the women.

From the interviews, we got to understand more about the mobility of sex workers. Sex workers that come to Germany commonly also travel throughout the country to pursue work. This makes them different from domestic sex workers, who are usually based in one place and do not travel around far away to pursue work. According to a social worker in Dortmund (BE0006), the police refers to the high mobility of foreign prostitutes within German borders as ‘prostitution tourism.’

Our survey showed a certain (albeit weak) relationship between sex workers’ country of origin and the number of years they had been working in Germany. Of the 17 respondents, those who stated to have worked in Germany for less than 3 years were exclusively Romanian and Bulgarian nationals. The over-representation of Romanian nationals also strengthens the view that it is among the most dominant origin countries in the current German prostitution market. For Bulgaria, our survey did not have a similar over-representation.

In Saarbrucken, counsellors reported that with the change of the visa-rules for Ukraine, more and more Ukranian women started working as sex workers in and surrounding Saarbrucken. However, according to one counsellor, none of them showed indications of being victims of human tracking (BE0003). In the tracking data from the BKA, there was an uptick in the number of Ukrainian victims in 2016, 22 compared to 2 for 2015. However, for the most recent report, Ukraine did not feature and we are therefore unable to say what the situation is like now.

Origin Countries of Victims
Of the information that we could gather from our interviews, there were some things that stood out to us. Repeatedly, Eastern Europe and West Africa were mentioned as the primary origins of tracking victims. Particularly one country was mentioned repeatedly: Nigeria.

One of our counsellors in Saarbrucken noted that women from Nigeria were more likely to be victims of human tracking. To get from Nigeria to Germany is generally rather difficult and they are therefore more exposed to be exploited by trackers (Saarbrucken, BE0003). In Freiburg we met with another counsellor who also emphasised the plight of Nigerian women, going so far as to say that since the refugee crisis, human tracking patterns have changed and Nigerian sex workers in Germany are mostly always victims of human tracking (Freiburg, BE0007). A counsellor working in Kehl and Strassbourg also noted how the refugee crisis has been used to bring vulnerable women from Nigeria to Germany. Summarising, it seems to be the case that the poorer the country, the more likely it is that the woman you encounter in this milieu is a victim of human tracking (Kehl/Straßburg BE0009).

In Dortmund, one counsellor noted that West African (and Nigerian) women have often been tracked elsewhere too (Dortmund, BE0006). A fellow counsellor working in Kehl and Strassbourg gave a similar account. Probably throughout the refugee crisis, women from non-EU states have been particularly over-represented. This does not mean that there are not any EU-citizens who are victims of human tracking, but right now, the biggest stream of human tracking victims are Nigerian women, who usually apply for asylum in Germany. They have come from Nigeria, often through Libya, then to Italy, and further on to other EU states. Once they reach Germany, some seem to attempt to save themselves from further exploitation, but sometimes they remain under the control of their trackers (Kehl/Straßburg BE0009).

In Heilbronn, one expert was keen to also discuss the German victims of tracking, who according to BKA statistics made up around a quarter of all victims. These usually fall prey to a partner who uses the ‘lover boy method’ making a woman, or usually young girl, fall in love with him and later forcing her into prostitution (Heilbronn, BE0002).

Changing characteristics of human tracking in Germany over time
In Saarbrucken, one counsellor also noted how the nature of human tracking has changed over the past 10–15 years, with trackers becoming more and more subtle. Where they before were much more violent towards their victims, they seem to have adopted strategies in order to hide the signs of violence and tracking better and instead apply more psychological violence. According to this person, it is also increasingly common for a family member or partner to be involved in the tracking. Overall, the lines drawn between prostitution and human tracking appear to become increasingly blurry and hard to detect. It makes it more difficult for victims to identify themselves as such, and in turn complicates legal processes as it is sometimes hard to prove whether a person working as a prostitute did it voluntarily or under coercion (Saarbrucken, BE0003).

As for the trend in human tracking, there appear to be differing opinions. In Heilbronn, one counsellor reported the number of cases rising. However, it is difficult to say if this is a reflection of an actual increase or of heightened awareness among the general public with the influx of West Africans (Heilbronn, BE0002). In Trier, however, the situation was perceived to have improved slightly, with one counsellor (BE0008) noting that stricter laws seem to lower the number of cases of human tracking.

Conclusion

Though interlinked, it is important that prostitution and human tracking for sexual exploitation are not associated by default. There are many sex workers that have practised their profession free from any undue influence by a third party. However, there is undoubtedly an abundance of evidence showing that this is not always the case. For the past few decades, however, policymakers have been attempting novel legislative approaches to create a clear delineation between these two phenomena.

The initiative behind this report was the interest in legislation introducing asymmetric punishment. As has been described above, the Nordic model’s approach in which only the party purchasing sex is committing an offence applies a similar sort of mechanism to the market for prostitution. Though this topic has been covered before, it still represents an area of rather novel research. Generating broad-brush findings applicable to all settings is unlikely, but findings that are relevant and robust for a specific time and place might be obtainable with the right methodology.

The introduction of new regulations regarding prostitution in France was therefore of great interest, as the proximity to other countries, especially Germany, where sex work has been a legal profession since 2002, could mitigate the issues on finding good data. The outset of our research efforts was a belief, now in hindsight perhaps rather naive, that data would be more readily available in the German regulationist institutional setting.

As was later discovered, data availability was an issue there too. Recent legislative efforts, namely the 2017 ProstSchG, might amend the most pressing concerns. However, it is more than likely that outright criminal activities are being perpetuated within the scope of a regulated market for sex. Finding methods that accurately track the effects of this law is an area of crucial research. In futures studies on this topic, remaining aware of unrelated events and changes that might possibly affect this policy is important. For larger countries, differences within a country also need to be considered. In the case of Germany, the federal structure allows Bundeslander to adopt slightly different policies.

We were not able to identify robust indicators that suggest a changing inflow of customers from France to Germany after the 2016 neo-abolitionist law in France. Assuming that the law has not been implemented and enforced sufficiently, this may also raise a question that affects the scope of this report. For instance, one may ask whether the ‘Nordic model’ of prostitution policy is easily implemented in different countries disregarding the cultural, institutional and social characteristics that originally brought it about and if it is reasonable to expect similar outcomes in each setting. Investigating which characteristics are important would improve any future changes of this kind elsewhere.

We can, however, confidently argue for additional research on cross-country sex work, as well as on the working conditions and financial situations those operating within the milieu face. Though we were unable to establish robust evidence on the interplay between sex work and human tracking, we were repeatedly told that general flows of migrant workers temporary working in Germany, mostly from Eastern Europe, affect conditions within the milieu. In this regard, sex work differs little from other business sectors that report similar concerns. This issue was particularly significant for street workers, especially since they already (and possibly because of this) reported to feel much less safe than those working in brothels.

On a practical level, our attempt to survey sex workers taught us just how difficult it is to gain the trust needed to obtain information from sex workers. Since prostitutes are only identifiable while they are working, remaining cautious of not being perceived as contributing to the experienced stigma sex workers face is imperative. For those not working in brothels and Laufhauser, there are generally also rather strict restrictions in place for when and where they may operate. Regardless of setting though, there tend to be time pressures whilst at work, meaning many approached to answer questions will decline that request. Building a dataset of any significant size will, therefore, require significant time and resources.

Having spent significant time working on this project, we have few clear-cut answers to give. Prostitution and human tracking may be intertwined. However, how they correlate and the causal relations between them remains a perplexing matter. By talking to people working in and around the milieu and improving the availability of data, the general understanding can be greatly improved. For instance, through the interviews we conducted in late 2017 with counsellors providing support to sex workers in Germany, the uptick in 2018 of detected Nigerian victims of human tracking for sexual exploitation was in part foreseen. This highlights the need for better and more data, as well as research covering sex work and human tracking so that both topics can be addressed appropriately and more effectively in the future.

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