Tag: Georgia
Risks of Russian Business Ownership in Georgia
This policy brief addresses risks tied to Russian business ownership in Georgia. The concentration of this ownership in critical sectors such as electricity and communications makes Georgia vulnerable to risks of political influence, corruption, economic manipulation, espionage, sabotage, and sanctions evasion. To minimize these risks, it is recommended to establish a Foreign Direct Investment (FDI) screening mechanism for Russia-originating investments, acknowledge the risks in national security documents, and implement a critical infrastructure reform.
Russia exerts substantial influence over Georgia. First and foremost, Russia has annexed 20 percent of Georgia’s internationally recognized territories of Abkhazia and South Ossetia. Further, it employs a variety of hybrid methods to disrupt the Georgian society including disinformation, support for pro-Russian parties and media, trade restrictions, transportation blockades, sabotage incidents, and countless more. These tactics aim to hinder Georgia’s development, weaken the country’s statehood, and negatively affect pro-Western public sentiments (Seskuria, 2021 and Kavtaradze, 2023).
Factors that may also increase Georgia’s economic dependency on Russia concern trade relationships, remittances, increased economic activity driven by the most recent influx of Russian migrants, and private business ownership by Russian entities or citizens (Babych, 2023 and Transparency International Georgia, 2023). This policy brief assesses and systematizes the risks associated with Russian private business ownership in Georgia.
Sectoral Overview of Russian Business Ovnership
Russian business ownership is significant in Georgia. Recent research from the Institute for Development of Freedom of Information (IDFI) has addressed Russian capital accumulation across eight sectors of the Georgian economy: electricity, oil and gas, communications, banking, mining and mineral waters, construction, tourism, and transportation. Of the eight sectors considered by IDFI, Russian business ownership is most visible in Georgia’s electricity sector, followed by oil and natural gas, communications, and mining and mineral waters industries. In the remaining four sectors considered by IDFI, a low to non-existent level of influence was observed (IDFI, 2023).
Figure 1. Overview of Russian Ownership in the Georgian Economy as of June 2023.

Source: IDFI, 2023.
There are several reasons for concern regarding the concentration and distribution of Russian business ownership in the Georgian economy.
First, it is crucial to keep Russia’s history as a hostile state actor in mind. Foreign business ownership is not a threat in itself; However, it may pose a threat if businesses are under control or influence of a state that is hostile to the country in question (see Larson and Marchik, 2006). Business ownership has been a powerful tool for the Kremlin, allowing Russia to influence various countries and raising concerns that such type of foreign ownership might negatively affect national security of the host country (Conley et al., 2016). Similar concerns have become imperative amidst Russia’s full-scale war in Ukraine (as, for instance, reflected in Guidance of the European Commission to member states concerning Russian foreign acquisitions).
Further, Russian business ownership in Georgia is particularly threatening due to the ownership concentration within sectors of critical significance for the overall security and economic resilience of the country. While there is no definition of critical infrastructure or related sectors in Georgia, at least two sectors (energy and communications) correspond to critical sectors, according to international standards (see for instance the list of critical infrastructure sectors for the European Union, Germany, Canada and Australia). Such sectors are inherently susceptible to a range of internal and external threats (a description of threats related to critical infrastructure can be found here). Intentional disruptions to critical infrastructure operations might initiate a chain reaction and paralyze the supply of essential services. This can, in turn, trigger major threats to the social, economic, and ecological security and the defense capacity of a state.
Georgia’s Exposure to Risks
Identifying and assessing the specific dimensions of Georgia’s exposure to risks related to Russian business ownership provides a useful foundation for designing policy responses. This brief identifies six distinct threats in this regard.
Political Influence
Russia’s business and political interests are closely intertwined, making it challenging to differentiate their respective motives. This interconnectedness can act as a channel for exerting political influence in Georgia. Russians that have ownership stakes in Georgian industries (e.g. within electricity, communications, oil and gas, mining and mineral waters) have political ties with the Russian ruling elite facing Western sanctions, or are facing sanctions themselves. For instance, Mikhail Fridman, who owns up to 50 percent of the mineral water company IDS Borjomi, is sanctioned for supporting Russia’s war in Ukraine. Such interlacing raises concerns about indirect Russian influence in Georgia, potentially undermining Georgia’s Western aspirations.
Export of Corrupt Practices
The presence of notable Russian businesses in Georgia poses a significant threat in terms of it nurturing corrupt practices. Concerns include “revolving door” incidents (movement of upper-level public officials into high-level private-sector jobs, or vice versa), tax evasion, and exploitation of the public procurement system. For instance, Transparency International Georgia (2023) identified a “revolving door” incident concerning the Russian company Inter RAO Georgia LLC, involved in electricity trading, and its regulator, the Georgian state-owned Electricity Market Operator JSC (ESCO). One day after Inter RAO Georgia LLC was registered, the director of ESCO took a managerial position within Inter RAO Georgia LLC. Furthermore, tax evasion inquiries involving Russian-owned companies have been documented in the region, particularly in Armenia, further highlighting corruption risks. We argue that such corrupt practices might harm the business environment and deter future international investments.
Economic Manipulation
A heavy concentration of foreign ownership in critical sectors like energy and telecommunications, also poses a risk of manipulation of economic instruments such as prices. The significant Russian ownership in Armenia’s gas distribution network exemplifies this threat. In fact, Russia utilized a price manipulation strategy for gas prices when Armenia declared its EU aspirations. Prices were then reduced after Armenia joined the Eurasian Economic Union (Terzyan, 2018).
Espionage
Russian-owned businesses within Georgia’s critical sectors also pose espionage risks, including economic and cyber espionage. Owners of such businesses may transfer sensitive information to Russian intelligence agencies, potentially undermining critical infrastructure operations. As an example, in 2022, a Swedish business owner in electronic trading and former Russian resident, was indicted with transferring secret economic information to Russia. Russian cyber-espionage is also known to be used for worldwide disinformation campaigns impacting public opinion and election results, compromising democratic processes.
Sabotage
The presence of Russian-owned businesses in Georgia raises the risk of sabotage and incapacitation of critical assets. Russia has a history of using sabotage to harm other countries, such as when they disrupted Georgia’s energy supply in 2006 and the recent Kakhovka Dam destruction in Ukraine (which had far-reaching consequences, incurring environmental damages, and posing a threat to nuclear plants). These incidents demonstrate the risk of cascading effects, potentially affecting power supply, businesses, and locations strategically important to Georgia’s security.
Sanctions and Sanction Evasion
Russian-owned businesses in Georgia face risks due to Western sanctions as they could be targeted by sanctions or used to evade them. Recent cases, like with IDS Borjomi (as previously outlined) and VTB Bank Georgia – companies affected by Western sanctions given their Russian connections – highlight Georgia’s economic vulnerability in this regard. Industries where these businesses operate play a significant role in Georgia’s economy and job market, and instabilities within such sectors could entail social and political concerns. There’s also a risk that these businesses could help Russia bypass sanctions and gain access to sensitive goods and technologies, going against Georgia’s support for international sanctions against Russia. It is crucial to prevent such sanctions-associated risks for the Georgian economy.
Assessing the Risks
To operationalize the above detailed risks, we conducted interviews with Georgian field experts within security, economics, and energy. The risk assessment highlights political influence through Russian ownership in Georgian businesses as the foremost concern, followed by risks of corruption, risks related to sanctions, espionage, economic manipulation, and sabotage. We asked the experts to assess the severity level for each identified risk and notably, all identified risks carry a high severity level.
Recommendations
Considering the concerns detailed in the previous sections, we argue that Russia poses a threat in the Georgian context. Given the scale and concentration of Russian ownership within critical sectors and infrastructure, a dedicated policy regime might be required to improve regulation and minimize the associated risks. Three recommendations could be efficient in this regard, as outlined below.
Study the Impact of Adopting a Foreign Direct Investment Screening Mechanism
To effectively address ownership-related threats, it’s essential to modify existing investment policies. One approach is to introduce a FDI screening mechanism with specific functionalities. Several jurisdictions implement mechanisms with similar features (see a recent report by UNCTAD for further details). Usually, such mechanisms target FDI’s that have security implications. A dedicated screening authority overviews investment that might be of concern for national security and after assessment, an investment might be approved or suspended. In Georgia, a key consideration for designing such tool includes whether it should selectively target investments from countries like Russia or apply to all incoming FDI. Additionally, there’s a choice between screening all investments or focusing on those concerning critical sectors and infrastructure. Evaluating the investment volume, possibly screening only FDI’s exceeding a predefined monetary value, is also a vital aspect to consider. However, it’s important to acknowledge that FDI screening mechanisms are costly. Therefore, this brief suggests a thorough cost and benefit analysis prior to implementing a FDI screening regime in Georgia.
Consider Russian Ownership-related Threats in the National Security Documents
Several national-level documents address security policy in Georgia, with the National Security Concept – outlining security directions – being a foundational one. Currently, these concepts do not specifically address Russian business ownership-related threats. When designing an FDI screening mechanism, however, acknowledging various risks related to Russian business ownership must be aligned with fundamental national security documents.
Foster the Adoption of a Critical Infrastructural Reform
To successfully implement a FDI screening mechanism unified, nationwide agreement on the legal foundations for identifying and safeguarding critical infrastructure is needed. The current concept for critical infrastructure reform in Georgia envisages a definition of critical infrastructure and an implementation of an FDI screening mechanism. We therefore recommend implementing this reform in the country.
Conclusion
This policy brief has identified six distinct risks related to Russian business ownership in several sectors of the Georgian economy, such as energy, communications, oil and natural gas, and mining and mineral waters. Even though Georgia does not have a unified definition of critical infrastructure, assets concentrated in these sectors are regarded as critical according to international standards. Considering Russia’s track record of hostility and bearing in mind threats related to foreign business ownership by malign states, this brief suggests regulating Russian business ownership in Georgia by introducing a FDI screening instrument. To operationalize this recommendation, it is further recommended to consider Russian business ownership-related threats in Georgia’s fundamental security documents and to foster critical infrastructural reform in the country.
References
- Babych, Y. (2023). The Georgian Economy after One Year of Russia’s War in Ukraine: Trends and Risks. ISET Policy Institute. https://iset-pi.ge/storage/media/other/2023-03-13/6982ed30-c1ad-11ed-896a-efa0ef78cee7.pdff
- Conley, H. A., Mina, J., Stefanov, R., & Vladimirov, M. (2016). The Kremlin Playbook: Understanding Russian Influence in Central and Eastern Europe. Center for Strategic and International Studies. https://csis-website-prod.s3.amazonaws.com/s3fs-public/publication/1601017_Conley_KremlinPlaybook_Web.pdf
- Institute for Development of Freedom of Information (IDFI). (2023, June). Russian Capital and Russian Connections in Georgian Business. https://idfi.ge/public/upload/Analysis/Russian%20capital%20and%20Russian%
20connections%20in%20Georgian%20business.pdf - Kavtaradze, N. (2023). Hybrid Warfare and Russia’s Modern Warfare. Georgian Foundation for Strategic and International Studies (GFSIS). https://gfsis.org.ge/files/library/opinion-papers/201-expert-opinion-eng.pdf
- Larson, A. P., & Marchik, D. M. (2006). Foreign Investment and National Security. ETH Zurich. https://www.files.ethz.ch/isn/20513/2006-07_ForeignInvestmentCSR.pdf
- Seskuria, N. (2021). Russia’s “Hybrid Agression” against Georgia: The Use of Local and External Tools. Center for Strategic and International Studies. https://csis-website-prod.s3.amazonaws.com/s3fs-public/publication/210921_Seskuria_Russia_Georgia.pdf?VersionId=__d9rw2TtaDba9xaHASf6lCEmJ.oqhA7
- Terzyan, A. (2018). The anatomy of Russia’s grip on Armenia: Bound to Persist? https://www.econstor.eu/bitstream/10419/198543/1/ceswp-v10-i2-p234-250.pdf
- Transparency International Georgia. (2023). Georgia’s Economic Dependence on Russia: Impact of the Russia-Ukraine War. Transparency International Georgia. https://transparency.ge/en/post/georgias-economic-dependence-russia-impact-russia-ukraine-war-1
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.
Potential Climate Change Impacts on Women’s Vulnerability in Georgia
Climate change can increase the vulnerability of women to various risks, including natural disasters, food insecurity, water scarcity, and health problems. Women may also face unique challenges in accessing resources and services, which can limit their ability to adapt to a changing climate. Developing countries, with their more traditional gender roles, are even more likely to experience disproportionate impacts of climate change on women, and Georgia is no exception. Thus, the country needs to address this problem through a comprehensive approach which accounts for the social, economic, and environmental factors that contribute to gender inequality.
Introduction
According to Georgia’s fourth national communication report to the United Nation’s Framework Convention on Climate Change, the negative impacts of climate change on ecosystems and the economy can hinder Georgia’s path toward sustainable development. Therefore, a key focus for the country should be to develop climate-resilient practices and reduce the vulnerability of communities exposed to these impacts.
The climate scenarios in the communication report present a worrying picture of warming trends in the country, mainly due to increased temperatures in the last summer and autumn seasons, as depicted in Figure 1 (MEPA, 2021). Such alterations in weather patterns often lead to glacier retreat, water scarcity, coastal erosion, and biodiversity loss in different regions of Georgia (ibid).
Figure 1. Average summer and winter temperatures in Georgia, 1900-2021.

Source: Climate Change Knowledge Portal (World Bank, 2021).
An increasing body of international research has demonstrated that climate change can have adverse effects on agricultural production, food security, water management, and public health. Furthermore, research has revealed that these effects are not gender-neutral, with women and children being among the most affected groups (World Bank Group, 2021).
Climate Change Impacts on Women – A Georgian Perspective
Women in developing countries like Georgia experience various impacts of climate change, which affect them differently than men. The effects might vary according to region or community, but some common signs can be identified. The main channels through which women are disproportionally affected by climate change are discussed in the following sub-sections.
Health Impacts
Climate change has a significant effect on human health, with women being more vulnerable due to various cultural, social, and economic factors (Sbiroli et al., 2022). In particular, women appear to be more susceptible to infectious diseases and undernutrition, especially in middle and low-income countries (ibid).
Springmann et al. (2016) found that, by 2050, Georgia could experience about 32.36 climate-related deaths per million due to malnutrition caused by a lack of fruits and vegetables in people’s diets and due to increased health complications associated with undernutrition. In Georgia, malnutrition is a significant gender equality concern. According to the Global Nutrition Report, women in Georgia disproportionally experience exposure to undernutrition translated into underweight. Similarly, women represent the majority of Georgians with obesity (26.8 percent, compared to 22.2 percent among men). Both these issues may be further exacerbated by climate change in the future.
Furthermore, in Georgia, women are more likely to care for sick family members. According to Geostat, 31 percent of women who have sick or dependent family members are involved in providing them care, compared to only 15 percent of the men. This puts women at greater risk of exposure to climate change-induced infectious diseases, given that research has demonstrated an increased risk of such diseases worldwide, including in areas in Europe that have climate profiles similar to Georgia (Mora et al., 2022; Gray et al., 2009).
Figure 2. Prevalence of underweight among adults (>18) in Georgia, 2000-2016.

Source: Global Nutrition Report (2023).
Water and Food Scarcity
Climate change is also known to affect food and water supply through changes in agricultural conditions, droughts, and floods. In developing countries as women are often responsible for food and water supply, they are disproportionally affected by water shortages resulting from climate change (Figueiredo & Perkins, 2013). Women in poor rural households in Georgia are likely to face similar challenges.
Women in Georgia also play a crucial role in agriculture (according to Geostat, 47 percent of workers in agricultural holdings were women in 2021). Fluctuations in temperature and precipitation patterns can reduce crop yields, leading to lower income and food insecurity. This may disproportionately affect female farmers, as access to agricultural technologies, land ownership and lack of necessary knowledge and skills are some of the significant barriers for women involved in agriculture in Georgia (Gamisonia, 2015).
Economic Impacts and Access to Resources
One of the main reasons to why women are disproportionally affected by climate change is that their underlying economic conditions are less favourable than men’s (Yadav & Lal, 2018). In 2021, the majority of people outside the labor force were women (65 percent), while men constituted 35 percent (Geostat). It is important to mention that in the same year, only 33 percent of women were employed in Georgia, compared to 49 percent of men. Additionally, the average salary for women was 1056 GEL (813 GEL in the agricultural sector), while men earned an average of 1538 GEL (1006 GEL in the agricultural sector). Finally, although poverty rates among women in Georgia are slightly lower than among men, 17.1 vs. 17.9 percent respectively (absolute poverty rates in 2021), the poverty data does not account for the gender-biased distribution of household resources. Women face larger barriers in obtaining financial resources (collaterals, loans, etc.) than men because they own less property. For different types of property, only 44 percent are owned by at least one woman, according to the National Agency of Public Registry of Georgia. The corresponding number for men is 56 percent. Geostat data further indicates that households headed by men make up 63 percent of the total number of households, whereas households headed by women account for only 37 percent. These unfavorable conditions hinder women’s access to vital information and resources required for climate change adaptation and mitigation.
The discussed impacts may be especially prominent for women in poor rural households. Climate change-induced natural disasters are typically more detrimental for households dependent on agriculture (Dagdeviren et al., 2021), especially subsistence farmers and poor agricultural workers (in particular those without access to technology or resources). In Georgia, women are in majority in both these categories.
Natural Disasters and Displacement
Climate-driven disasters are over 14 times more likely to cause fatalities among women and children than men, according to UNHCR (2022). Additionally, women in agrarian societies impacted by climate change are less likely to use adaptive measures, putting them at higher risk of displacement (Palacios, Sexsmith, Matheu & Gonzalez, 2023). Such risks are also likely to pertain to the rural areas of Georgia.
Georgia’s International Obligations and Policies
In previous decades Georgia has made significant progress when it comes to incorporating gender equality and climate change into the policy agenda. In particular, Georgia follows numerous international legislative initiatives regarding sustainable development, gender equality, and climate change.
Georgia is a party to the Paris Agreement and the Beijing platform (a comprehensive roadmap for women’s rights and empowerment, which lists the problems associated with gender inequality and different strategies to overcome them, signed by Georgia in 1995). It is also a signatory of the Gender Action Plan (GAP), adopted a year after the Paris Agreement to integrate gender into targets and increase effectiveness, fairness, and sustainability.
The updated Nationally Determined Contribution (NDC) of Georgia includes a dedicated section on gender and climate change. This section aims to promote gender mainstreaming, encourage equal participation, empower women, build capacity, and develop climate policies that are responsive to gender considerations. Furthermore, the Long-term Low-emission Development Strategies for Paris Agreement parties (including Georgia) has a communication and awareness-raising strategy that seeks to address gender, youth, and people with disabilities in its outreach efforts (United Nations, 2022).
Despite these commitments, Georgia is lagging when it comes to tackling the issues of climate change and gender in coordination. For example, even though Georgia has adopted a Gender Equality Law and Action Plan, it does not address climate change issues. Therefore, municipalities are not required to consider gender aspects of climate change impacts.
Identified Gaps and Policy Recommendations
Despite the number of policies and measures undertaken, unsolved problems hinder the country’s ambition to adhere to gender-mainstreamed climate change-addressed policymaking.
For example, there is a lack of gender-disaggregated data on the impacts of climate change in Georgia, which prevents policymakers from developing targeted strategies to address women’s needs. Therefore, collecting and analyzing disaggregated data with gender-specific impacts in mind is recommended. Additionally, involving women in decision-making and ensuring their participation in climate change efforts is crucial as their unique experiences and perspectives can inform more effective and equitable responses to climate change impacts.
As previously mentioned, climate change in Georgia is expected to exacerbate water and food scarcity, which can disproportionately affect women. Therefore, implementing climate-resilient water management strategies and increasing access to climate-resilient agricultural practices, such as crop diversification and improved irrigation systems, can help increase farm productivity and reduce the adverse impacts of climate change on women.
Furthermore, there is a need to provide women with access to financial resources and services and to address gender-based inequalities that may limit women’s ability to access information and resources necessary for climate change adaptation and mitigation.
Finally, addressing the impacts of climate change on women in Georgia will require a coordinated and sustained effort from a range of stakeholders, including governments, civil society organizations, and local communities, so that women are not left behind in the global effort to address the impacts of climate change.
Conclusion
To effectively address the impacts of climate change on women in Georgia, it is essential to recognize that various social, economic, and cultural factors shape women’s experiences. For example, women in rural areas may face different challenges than women in urban areas; women with few economic means may be disproportionately affected by climate change. Therefore, policies should not only integrate gender-mainstreaming, but also account for these heterogeneities, to ensure that different parties of the society are adequately addressed within the climate change policy agenda.
References
- Dagdeviren, H., Elangovan, A., & Parimalavalli, R. (2021). Climate change, monsoon failures and inequality of impacts in South India. Journal of Environmental Management.
- Figueiredo, P., & Perkins, P. E. (2013). Women and water management in times of climate change: participatory and inclusive processes. Journal of Cleaner Production, 188-194.
- Gamisonia, N. (2015). Climate Change and Women. Heinrich Böll Stiftung.
- Global Nutrition Report. (2023). Global Nutrition Report. https://globalnutritionreport.org/resources/nutrition-profiles/asia/western-asia/georgia/
- Geostat. https://www.geostat.ge/en
- Gray, J. S., Dautel, H., Estrada-Peña, A., Kahl, O., & Lindgren, E. (2009). Effects of Climate Change on Ticks and Tick-Borne Diseases in Europe. National Library of Medicine.
- MEPA. (2021). Fourth National Communication of Georgia to the UNFCCC. Tbilisi: UNDP.
- Mora, C., McKenzie, T., Gaw, I. M., Dean, J. M., Hammerstein, H. v., Knudson, T. A., Franklin, E. C. (2022). Over half of known human pathogenic diseases can be aggravated by climate change. Nature Climate Change.
- National Agency of Public Registry of Georgia. https://www.napr.gov.ge/
- Palacios, H. V., Sexsmith, K., Matheu, M., & Gonzalez, A. R. (2023). Gendered adaptations to climate change in the Honduran coffee sector. Women’s Studies International Forum.
- Sbiroli, E., Geynisman-Tan, J., Sood, N., Maines, B. A., Junn, J. H.-J., & Sorensen, C. (2022). Climate change and women’s health in the United States: Impacts and opportunities. The Journal of Climate Change and Health.
- Springmann, M., Mason-D’Croz, D., Robinson, S., Garnett, T., Godfray, H. C., Gollin, D., Scarborough, P. (2016). Global and regional health effects of future food production under climate change: a modelling study. National Library of Medicine.
- UNHCR. (2022). Gender, Displacement and Climate Change. Potsdam Institute for Climate Impact Research.
- United Nations. (2022). Long-term Low-emission Development Strategies. United Nations.
- World Bank Group. (2021). Climate Risk Country Profile: Georgia. World Bank Group.
- World Bank. (2021). Climate Change Knowledge Portal. https://climateknowledgeportal.worldbank.org/country/georgia
- Yadav, S. S., & Lal, R. (2018). Vulnerability of women to climate change in arid and semi-arid regions: The case of India and South Asia. Journal of Arid Environments, 4-17.
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.
Would a Higher Minimum Wage Meaningfully Affect Poverty Levels Among Women? – A Simulation Case from Georgia
In economic literature the effect of minimum wage on the labour market and its relevance as an anti-poverty, equality-enhancing policy tool, is a matter of vigorous debate. The focus of this policy brief is a hypothetical effect on poverty rates, particularly among women, following an increase in the minimum wage in Georgia. A simulation exercise (Babych et al., 2022) by the ISET-PI research team shows that, in Georgia, a potential increase in the minimum wage is likely to result in an overall positive albeit small reduction in poverty rates in general. At the same time, women are likely to gain more from such minimum wage policy than men. The findings are consistent with the literature claiming that a minimum wage increase alone may not result in meaningful poverty reduction. Any minimum wage increase should thus be enhanced by other policies such as training programs increasing labor force participation among women.
Many countries around the world have enacted minimum wage laws. According to the International Labour Organization (ILO) “Minimum wages can be one element of a policy to overcome poverty and reduce inequality, including those between men and women” (ILO, 2023). In economic literature, the minimum wage debate has been particularly acute, with pros and cons of the minimum wage increases, their effect on the labor market, and their relevance as an anti-poverty and equality-enhancing policy tool fiercely contested in empirical studies and simulation studies. In this policy brief, we focus on the effect of a minimum wage increase in Georgia on poverty rates, and in particular poverty rates among women.
Minimum Wage Effects
According to the European Commission (2020) a number of benefits is associated with the introduction of minimum wage. These benefits include a reduction in in-work poverty, wage inequality and the gender pay gap, among others.
International evidence, however, cautions against considering an increase in minimum wage as the silver bullet to end poverty. A 2019 report by the International Labour Organization (ILO, 2019) shows that the incidence of poverty among the working poor is comparable to the incidence of poverty among individuals outside of the labor market. Therefore, even if an increase in minimum wages would lift all working poor out of poverty, a substantial number of poor would remain.
Moreover, minimum wage can have a potential adverse effect on employment of the most vulnerable by deterring firms from hiring low-wage, low-skilled labor (Neumark, 2018). The adverse employment effect will be stronger if current wages correspond more closely to the real productivity of labor. In such scenario companies would lose by retaining low-productivity workers and, likely respond to the increase in minimum wage by laying off workers, resulting in the loss of wages, rather than in their increase. On the other hand, if salaries are lower than the real productivity of the less productive workers, companies might still be able to profit from employing them and will not be forced to lay them off, resulting in a wage increase for low-wage workers.
Whether – and to what extent – the introduction of a minimum wage reduces poverty and/or assists low-income households then depends on how many individuals are going to lose their jobs, how many workers will maintain their jobs and receive a higher wage, and where these winners and losers are positioned along the distribution of family incomes.
With regard to employment effects, the results are not perfectly homogeneous. On the one hand, a large body of evidence suggests that minimum wages do lower the number of jobs accessible to low-skill employees (Sabia, Burkhauser and Hansen, 2012; Sotomayor, 2021; Neumark, 2018) On the other hand, some scholars argue that once the study design is changed to take into account the non-random distribution of minimum wage policies in different parts of the country in question, the “disemployment effect” of minimum wage policies (considering the example of United States) largely disappear (Allegretto et al., 2013; Dube et al., 2010).
With regards to poverty, a number of studies look at minimum wage as an anti-poverty policy tool for developing countries and consider its effectiveness in reducing poverty and/or inequality. For example, a study by Sotomayor (2021) suggests that poverty and income inequality in Brazil decreased by 2.8 and 2.4 percent respectively within three months of a minimum wage increase. Effects diminished with time, particularly for bottom-sensitive distribution measures, a process that is consistent with resulting job losses being more frequent among poorer households. The fact that the subsequent yearly increase in the minimum wage in Brazil resulted in a renewed drop in poverty and inequality shows that possible unemployment costs might be outweighed by benefits in the form of higher pay among working persons and – potentially – by positive spillover effects such as increased overall consumption.
Minimum Wage and Female Poverty
As in the case of poverty in general, there is some discrepancy in the literature on whether a minimum wage increase would help reduce poverty among women. Single mothers have been the focus of research in this regard since they are typically the most vulnerable low-wage workers, likely to be hurt by the loss of employment following an increase/ introduction of a minimum wage. Burkhauser and Sabia (2007) argue that the minimum wage increases in the U.S. (1988-2003) did not have any effect on the overall poverty rates, on the poverty rates among the working poor, or on poverty among single mothers. They argue that an increase in Earned Income Tax Credit (EITC), which provides a wage subsidy to workers depending on income level, tax filing status, and the number of children, would have a higher impact on poverty, in particular among single mothers.
In the meantime, Neumark and Wascher (2011) find that EITC and minimum wage reinforce each other’s positive effect for single women with children (boosting both employment and earnings), but negatively affects childless single women and minority men. Another study on the U.S. (Sabia, 2008) looked at the effect of minimum wage increases on the welfare of single mothers, finding that most of them were unaffected as they earned above-minimum wage. Single mothers with low-education levels did not see an increase in net incomes due to the negative effect on employment and hours worked: for low-skilled individuals, a 10 percent increase in minimum wage resulted in an 8.8 percent decline in employment and an 11.8 percent reduction in hours worked.
Yet another study (DeFina, 2008) focus on child poverty rates and show that minimum wage increases have a positive (reducing) impact on child poverty in female-headed families. The effect is small but significant (a 10 percent increase in the minimum wage decreases child poverty rates by 1.8 percentage points), controlling for other factors.
Ultimately, the effect of minimum wage on poverty among women or female-headed households is somewhat ambiguous. It depends on the poverty threshold used, other policy instruments (such as the EITC), existing incentives to enter employment and how, in the specific country of interest, labor laws may affect the employer’s cost of hiring (e.g. for France, see Laroque and Salanie, 2002).
The discussion is however relevant for countries like Georgia, where the wage gap between men and women is quite large, and where more women than men tend to work in low-wage and vulnerable jobs. While the overall poverty gap between men and women in Georgia is insignificant (mainly because poverty is measured at the household level), the gap becomes apparent when comparing female-headed households to male-headed ones. The poverty rates in the former case are nearly 2 percentage points higher in Georgia (20 percent vs. 18.3 percent in 2021). The poverty rates are the highest among households with only adult women (39.3 percent for all-female households vs. 20.1 percent overall in 2018).
A Simulation of a Minimum Wage Raise in Georgia
The Georgian minimum wage legislation dates back to 1999. The presidential decree N 351 from June 4, 1999 states that the minimum (monthly) wage that is to be set in Georgia is equal to 20 GEL (with some specific exceptions in the public sector). This is a non-binding threshold. Therefore, one has to think carefully what consequences might arise from raising the minimum wage to a much higher level. In addition to previously discussed aspects, one issue to keep in mind is the different average wages across different regions in Georgia. For example, a national minimum wage increase might have more of an impact in poorer regions, where both wages and incomes are lower, while it may still be non-binding in Tbilisi.
The ISET-PI research team (Babych et al., 2022) use Georgian micro data from the Labor Force Survey (LFS) and the Household Integrated Expenditure Survey (HIES), to simulate the effect of instituting a nation-wide minimum wage on both employment and poverty rates in different regions of Georgia. One focus area of the study was to analyze the effects of a minimum wage increase on female poverty. As with any exercise using a simulation approach, this study is subject to limitations imposed by the assumptions used, e.g. how much labor demand would respond to changes in the minimum wage, etc. The study considered two hypothetical thresholds of the minimum wage; 250 and 350 GEL respectively.
Figure 1. Share of private sector employees earning below certain thresholds, by gender, 2021.

Source: Authors’ calculations based on the Labor Force Survey (Geostat, 2021).
The expected household income after the minimum wage increase was calculated and then compared to the poverty threshold (for each household in a standard way, using the “adult equivalence” scale). According to this methodology, any person who lives in a household which falls below the poverty threshold is considered to be poor. A “working poor” household is defined as a household below the poverty threshold where at least one adult is working.
Figure 1 shows that there is a substantial share of both men and women whose monthly wage income falls below the hypothetical minimum wage thresholds. In addition, women are more than two times as likely to be earning below these thresholds. However, the possible impact from an increased minimum wage on female vs. male poverty is not clear-cut. Since many women are part of larger households which include adult males, their possible income losses/gains may be counterbalanced by income gains/losses of male family members, leaving the overall effect on household income ambiguous.
In addition, poverty rates are not likely to be much affected by a minimum wage increase if most poor households are “non-working poor” (where adult family members are either unemployed or outside of the labor force), a consideration particularly relevant for Georgia. The share of poor individuals who live in “working poor” households (with at least one household member employed) is just 41 percent nationally (and 35 percent in rural areas), meaning that close to 60 percent of poor individuals nationwide (and 65 percent in rural areas) are not likely to be directly affected by minimum wage increases.
Female vs. Male Poverty: Scenarios Following a Minimum Wage Increase
As one can see in Figure 2, increased minimum wages tend to reduce poverty, but the impact is not larger than one percentage point. Not surprisingly, females benefit more than males (0.3 and 0.8 percentage points vs. 0.2 and 0.9 percentage points poverty reduction for men and women respectively, under different threshold scenarios). The maximum positive impact on poverty reduction is observed under a higher minimum wage threshold.
Figure 2. Estimated impact on poverty rates, based on the national subsistence minimum.

Source: Authors’ calculations based on the Household Integrated Expenditure Survey (Geostat, 2021).
The impact of an increased minimum wage on the expected median consumption of households doesn’t exceed a few percentage points either, as illustrated in Figure 3.
Figure 3. Median monthly consumption per “equivalent adult” in the household under the status quo and minimum wage scenarios, 2021.

Source: Authors’ calculations based on the Household Integrated Expenditure Survey (Geostat, 2021).
The impact is greatest in urban areas other than Tbilisi (between a 2.5 percent and a 4.2 percent increase in median consumption relative to the status quo). The lower impact in Tbilisi is most likely driven by relatively higher wages, while the low impact in rural areas is likely driven by lower participation in wage employment.
Conclusions
In the hypothetical case of Georgia, an impact of a minimum wage increase on poverty rates is expected to be limited, in line with the literature. In our study this finding is mostly driven by the fact that only a relatively small share of poor individuals live in “working poor” households (about 40 percent, nationally). The remaining 60 percent of poor individuals will be unaffected by the reform.
The quantitative impact on female and male poverty is estimated to be low, although the female poverty rate reduction is somewhat larger than among males.
It is important to note that the analysis doesn’t consider possible differential impacts on different groups of vulnerable families, such as families with small children and single mothers with small children. Some reasons to why groups of households may or may not be affected by the hypothetical minimum wage increase, based on their employment status and other factors, have been discussed above.
Another important point is that our exercise should not be seen as an argument against an increase of the minimum wage in Georgia. Instead, it suggests that such a reform would not have much of an impact if done in isolation. Indeed, the existing literature on minimum wage seems to be in consensus on the fact that minimum wage policies would be more impactful if supplemented by the following measures:
- Maintain and expand targeted social assistance to groups that do not benefit or that are losing jobs/incomes as a result of the minimum wage changes
- Have job re-training programs in place to help laid-off workers
- Have human capital investment programs in place to increase workers’ productivity, in particular for low-productivity sectors
- Consider other support instruments targeted toward the most affected groups of the population such as single working mothers etc.
These recommendations should be incorporated in the policy making regarding minimum wages in Georgia.
Acknowledgement
We are grateful to Expertise France for financially supporting the original report (Babych et al., 2022), which features some of the results and points raised in this policy brief.
References
- Allegretto, S., Dube, A., Reich, M., & Zipperer, B. (2017). Credible Research Designs for Minimum Wage Studies: A Response to Neumark, Salas, and Wascher. ILR Review, 70(3), 559–592. https://doi.org/10.1177/0019793917692788
- Babych, Y., Pignatti, N., Chapichadze, A., Lobzhanidze, G. and Shubitidze, E. (2022). Report on Minimum Wage in Georgia. ISET Policy Institute. Unpublished manuscript.
- Belman, D. and Wolfson, Paul J. (2014). What Does the Minimum Wage Do? Kalamazoo, MI: W.E. Upjohn Institute for Employment Research. https://doi.org/10.17848/9780880994583
- Burkhauser, R. V. and Sabia, J. J. (2007). The effectiveness of minimum‐wage increases in reducing poverty: Past, present, and future. Contemporary Economic Policy, 25(2), 262-281. https://doi.org/10.1111/j.1465-7287.2006.00045.x
- DeFina, R. H. (2008). The impact of state minimum wages on child poverty in female-headed families. Journal of Poverty, 12(2), 155-174. https://doi.org/10.1080/10875540801973542
- Dube, A., T.W. Lester, and M. Reich. 2010. Minimum Wage Effects Across State Borders: Estimates Using Contiguous Counties. The Review of Economics and Statistics, 92(4), 945–964. https://doi.org/10.1162/REST_a_00039
- European Commission. (2020). Proposal for a directive of the European parliament and of the council on adequate minimum wages in the European Union. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52020PC0682GEOSTAT
- International Labour Organization (ILO). (2023). https://www.ilo.org/global/topics/wages/minimum-wages/definition/lang–en/index.htm
- International Labour Organization (ILO). (2019). The working poor or how a job is no guarantee of decent living conditions chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.ilo.org/wcmsp5/groups/public/—dgreports/—stat/documents/publication/wcms_696387.pdf
- Geostat. (2021). https://www.geostat.ge/en
- Laroque, G. & Salanié, B. (2002). Labour market institutions and employment in France. Journal of Applied Econometrics, 17(1), 25-48. https://doi.org/10.1002/jae.656
- Neumark, D. & Wascher, W. (2011). Does a higher minimum wage enhance the effectiveness of the Earned Income Tax Credit? ILR Review, 64(4), 712-746. https://doi.org/10.1177/001979391106400405
- Neumark, D. (2018). Employment effects of minimum wages. IZA World of Labor 2018: 6. https://wol.iza.org/articles/employment-effects-of-minimum-wages/long
- Sabia, J. J., Burkhauser, R. V. & Hansen, B. (2012). Are The Effects Of Minimum Wage Increases Always Small? New Evidence From A Case Study Of New York State. Sage Publications, 350-376. https://doi.org/10.1177/001979391206500207
- Sabia, J. J. (2008). Minimum wages and the economic wellbeing of single mothers. Journal of Policy Analysis and Management, 27(4), 848-866. https://doi.org/10.1002/pam.20379
- Sotomayor, O. J. (2021). Can the minimum wage reduce poverty and inequality in the developing world? Evidence from Brazil. World Development 138. https://doi.org/10.1016/j.worlddev.2020.105182.
Disclaimer: Opinions expressed during events and conferences are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
An Overview of the Georgian Wine Sector
Georgia has an 8000-year-old winemaking tradition, making the country the first known location of grape winemaking in the world. In this policy brief we analyze and discuss major characteristics of the wine sector in Georgia, government policies regarding the sector and major outcomes of such policies. The brief provides recommendations on how to ensure sustainable development of the sector in a competitive, dynamic environment.
Introduction
The Georgian winemaking tradition is 8000 years old, making Georgia the world’s first known location of grape winemaking. There are many traditions associated with Georgian winemaking. One of them is ‘Rtveli’ – the grape harvest that usually starts in September and continues throughout the autumn season, accompanied with feasts and celebrations. According to data from the National Wine Agency, the annual production of grapes in Georgia is on average 223.6 thousand tones (for the last ten-years), with most grapes being processed into wine (see Figure 1).
Figure 1. Grape Processing (2013-2021)

Source: National Wine Agency, 2022. Note: Some producers do not participate In Rtveli and the total annual quantity of processed grape in the country might therefore be higher than the numbers presented in the figure.
Wine is one of the top export commodities for Georgia. It constituted 21 percent of the total Georgian agricultural export value in 2021 (Geostat, 2022). Since 2012 wine exports have, on average, grown 21 percent in quantitative terms, and by 22 percent in value (Figure 2). The average price per ton varies from 3 thousand USD to 3.9 thousand USD (Figure 2). Exports of still wine in containers holding 2 liters or less constitute, on average, 96 percent of the total export value.
Figure 2. Georgian Wine Exports (2012-2021)

Source: Geostat, 2022.
The main destination market for exporting Georgian wine is the Commonwealth of Independent States (CIS) countries which account for, on average, 78 percent of the export value (2012-2021). The corresponding share for EU countries is 10 percent. As of 2021, the top export destinations are Russia (55 percent), Ukraine (11 percent), China (7 percent), Belarus (5 percent), Poland (6 percent), and Kazakhstan (4 percent). While Russia is still a top market for Georgian wine, Russia’s share of Georgian wine exports declined after Russia imposed an embargo on Georgian wines in 2006. The embargo forced market diversification and even after the reopening of the Russian market and Georgian wine exports shifting back towards Russia, its share declined from 87 percent in 2005 to 55 percent in 2021.
While there are more than 400 indigenous grape varieties in Georgia, only a few grape varieties are well commercialized as most of the exported wines are made of Rkatsiteli, Mtsvane, Kisi, and Saperavi grape varieties (Granik, 2019).
Government Policy in the Wine Sector
The Government of Georgia (GoG) actively supports the wine sector through the National Wine Agency, established in 2012 under the Ministry of Environmental Protection and Agriculture (MEPA). The National Wine Agency implements Georgia’s viticulture support programs through: i) control of wine production quality and certification procedures; ii) promotion and spread of knowledge of Georgian wine; iii) promotion of export potential growth; iv) research and development of Georgian wine and wine culture; v) creation of a national registry of vineyards; and vi) promotion of organized vintage (Rtveli) conduction (National Wine Agency, 2022).
During 2014-2016, the GoG’s spending on the wine sector (including grape subsidies, promotion of Georgian wine, and awareness increasing campaigns) amounted to 63 million GEL, or 22.8 million USD (As of November 1, 2022, 1 USD = 2.76 GEL according to the National Bank of Georgia). Out of the spending, illustrated in Figure 3, around 40-50 percent was allocated to grape subsidies implemented under the activities of iv) (as mentioned above).
There are two types of subsidies used by the GoG– direct and indirect. Direct subsidies imply cash payments to producers per kilogram of grapes. As for indirect subsidies, they entail state owned companies purchase grapes from farmers.
Starting from 2017, the GoG decided to abandon the subsidiary scheme and decrease its spending on of the wine sector. The corresponding figure reached a minimum of 9.2 million GEL (3.3 million USD) in 2018. Meanwhile, the grape production has been increasing, reaching its highest level in 2020 (317 thousand tons). In 2020, the GoG resumed subsidizing grape harvests to support the wine sector as part of the crisis plan aimed at tackling economic challenges following the Covid-19 pandemic. The corresponding spending in the wine sector increased from 16.7 million GEL (around 6 million USD) in 2019 to 113.4 million GEL (41 million USD) in 2020, out of which the largest share (91 percent) went to grape subsidies. In 2021, the GoG continued its extensive support to the wine sector and the corresponding spending increased by 44 percent, compared to 2020. The largest share again went to grape subsidies (90 percent).
Figure 3. Grape Production and Government Spending on the Wine Sector (2014-2021)

Source: Ministry of Finance of Georgia, National Statistics Office of Georgia, Author’s Calculations, 2022.
In 2022, the GoG have continued subsidizing the grape harvest to help farmers and wine producers sell their products. During Rtveli 2022, wine companies are receiving a subsidy if they purchase and process at least 100 tons of green Rkatsiteli or Kakhuri grape varieties grown in the Kakheti region, and if the company pays at least 0.90 GEL per kilogram for the fruit. If these two conditions are satisfied, 0.35 GEL is subsidized from a total of 0.9 GEL per kilogram of grapes purchased (ISET Policy Institute, 2022). Moreover, the GoG provides a subsidy of 4 GEL per kilogram for Alksandrouli and Mujuretuli grapes (unique grape varieties from the Khvanchkara “micro-zone” of the north-western Racha-Lechkhumi and Kvemo Svaneti regions), if the buying company pays at least 7 GEL per kilogram for those varieties (Administration of the Government of Georgia, 2022). Overall, about 150 million GEL (54.2 million USD), has been allocated to grape subsidies in 2022.
Policy Recommendations
Although the National Wine Agency is supposed to implement support programs in various areas like quality control, market diversification, promotion and R&D, these areas lack funding, as most of the Agency’s funds are spent on subsidies. Given that the production and processing of grapes have increased over the years, subsidies have been playing a significant role in reviving the wine sector after the collapse of the Soviet Union (Mamardashvili et al., 2020). However, since the sector is subsidized as of 2008, the grape market in Georgia is heavily distorted. Prices are formed, not on the bases of supply and demand but on subsidies, which help industries survive in critical moments, but overall prevent increases in quality and fair competition. They further lead to overproduction, inefficient distribution of state support and preferential treatment of industries (Desadze, Gelashvili, and Katsia, 2020). After years of subsidizing the sector, it is hard to remove the subsidy and face the social and political consequences of such action.
Nonetheless, in order to support the sustainable development of the sector, it is recommended to:
- Replace the direct state subsidy with a different type of support (if any), directed towards overcoming systemic challenges in the sector related to the research and development of indigenous grape varieties and their commercialization level.
- Further promote Georgian wine on international markets to diversify export destination markets and ensure low dependence on unstable markets like the Russian market. Although wine exporters have in recent years entered new markets, to further strengthen their positions at those markets, it is vital to:
- ensure high quality production through producers’ adherence to food safety standards.
- promote digitalization – e-certification for trade and distribution, block chain technology for easier traceability and contracting, e-labels providing extensive information about wine etc. – enabling producers to competitively operate in the dynamic environment (Tach, 2021)
- identify niche markets (e.g. biodynamic wine) and support innovation within these sectors to ensure competitiveness of the wine sector in the long-term (Deisadze and Livny, 2016).
References
- Administration of the Government of Georgia. (2022). “Gov’t releases updated conditions for vineries in grape harvest subsidies”
- Deisadze, S., Gelashvili, S. and Katsia, I. (2020). ”To Subsidize or Not to Subsidize Georgia’s Wine Sector?”, ISET Economist Blog.
- Deisadze, S. and Livny, E.(2016). “Back to the Future: Will an Old Farming Practice Provide a Market Niche for Georgian Farmers?”, ISET Economist Blog.
- GeoStat. (2020). Statistics of food balance sheets, retrieved from: https://www.geostat.ge/en/modules/categories/297/food-security
- Mamardashvili, P., Gelashvili, S., Katsia, I., Deisadze, S., Ghvanidze, S., Bitsch, L., Hanf, J. H., Svanidze, M. and Götz, L. (2020). “The Cradle of Wine Civilization”—Current Developments in the Wine Industry of the Caucasus”. Caucasus Analytical Digest (CAD), Vol 117.
- Granik, L. (2019). “Understanding the Georgian Wine Boom”. SevenFiftyDaily.
- ISET Policy Institute, 2022. “Agri Review October 2022“
- Ministry of Finance of Georgia. (2022). Statistics of State Budget, retrieved from: https://www.mof.ge/en/4537
- National Wine Agency (NWA). (2022). Main activities the agency, retrieved from: https://wine.gov.ge/En/Page/mainactivities
- Tach, L. (2021). “What Are The Future Digital Technology Trends In Wine? New OIV Study Reveals Answers”. Forbes.
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
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
- Ahmed, Tanima; Muzi, Silvia; Ueda Kohei. 2020. “Do Crises Hit Female-Managed and Male-Managed Firms Differently?” Evidence from the 2008 Financial Crisis, Enterprise Note Series, 39.
- Albanesi, Stefania; and Jiyeon Kim, 2021. “The Gendered Impact of the COVID-19 Recession on the US Labor Market”, NBER Working Paper Series, 28505.
- Alon, Titan; Coskun, Sena; Doepke, Matthias; Koll, David; and Michèle Tertilt, 2021. “From Mancession to Shecession: Women’s Employment in Regular and Pandemic Recessions”, NBER Working Paper Series, 28632.
- Alon, Titan; Doepke, Matthias; Olmstead-Rumsey, Jane; and Michèle Tertilt, 2020. “This Time It’s Different: The Role of Women’s Employment in a Pandemic Recession”, NBER Working Paper Series, 27660.
- Amin, Mohammad, 2011. ” Labor Productivity, Firm-size and Gender: The Case of Informal Firms in Argentina and Peru”, World Bank Group Enterprise Note, 22.
- Babych, Yaroslava, 2021. “Global Gender Gap in Unpaid Care: Why Domestic Work Still Remains a Woman’s Burden”, FROGEE Policy Brief Series, 4.
- Bardasi, Elena; and Shwetlena Sabarwai, 2011. ” How do female entrepreneurs perform? evidence from three developing regions”, Small Business Economics, 37, 417–441.
- Bluedorn, John C.; Caselli, Francesca G.; Hansen, Niels-Jakob H.; Shibata, Ippei; and Marina Mendes Tavares, 2021. “Gender and Employment in the COVID-19 Recession: Evidence on “She-cessions””, IMF Working Papers, 21/095.
- Boeri, Tito; Caiumi, Alessandro; and Marco Paccagnella, 2020. “Mitigating the work-safety trade-off”, COVID Economics, 2, 60-66.
- Campa, Pamela; Roine, Jesper; and Svante Strömberg, 2021. “Unequal Labour Market Impacts of COVID-19 in Sweden – But Not Between Women and Men”, Intereconomics, 56.
- CARE, 2020. “Rapid Gender Assessment”.
- Caselli, Francesca G.; Grigoli, Francesco; Sandri, Damiano; and Antonio Spilimbergo, 2020. “Mobility under the COVID-19 Pandemic: Asymmetric Effects across Gender and Age”, IMF Working Papers, 20/282.
- Dingel, Jonathan I.; and Brent Neiman, 2020. “How Many Jobs Can be Done at Home?”, NBER Working Paper Series, 26948.
- Eurofound, 2016. “The gender employment gap: Challenges and solutions”, Publications Office of the European Union, Luxembourg.
- Eurofound, 2021. “COVID-19: Implications for employment and working life”, Publications Office of the European Union, Luxembourg.
- Fabrizio, Stefania; Gomes, Diego B. P.; and Marina Mendes Tavares, 2021. “COVID-19 She-Cession: The Employment Penalty of Taking Care of Young Children”, IMF Working Papers, 21/058.
- Global Entrepreneurship Monitor, 2021, “Women’s Entrepreneurship 2020/21 – Thriving Through Crisis.”
- Grimm, Michael; Knorringa, Peter; and Jann Lay, 2012. “Constrained Gazelles: High Potentials in West Africa’s Informal Economy”, World Development, 40(7), 1352–1368.
- Hilbrecht, Margo; Shaw, Susan M.; Johnson, Laura C.; and Jean Andrey, 2008. “‘I’m Home for the Kids’: Contradictory Implications for Work–Life Balance of Teleworking Mothers”, Gender, Work and Organization, 15, 454-476.
- ILO, 2020. “Survey of Women Leading Micro, Small and Medium Businesses About the Main Challenges They Face as a Result of the Coronavirus Crisis.”
- Julakidze, Mery; and Gocha Kardava, 2021. “Five Ways Covid-19 Affected the Georgian Labor Market in 2020”, ISET Economist Blog.
- Liu, Yu; Wei, Siqi; and Jian Xu, 2021. “COVID-19 and Women-Led Businesses around the World”, Finance Research letters, 43.
- Mongey, Simon; Pilossoph, Laura; and Alex Weinberg, 2020. “Which Workers Bear the Burden of Social Distancing?”, NBER Working Paper Series, 27085.
- Moran, Jessica; and Alison Koslowski, 2019.“Making use of work–family balance entitlements: how to support fathers with combining employment and caregiving”, Community, Work and Family, 22, 111-128.
- Nordman, Christophe, Jalil; and Julia Vaillant, 2014.“ Inputs, Gender Roles or Sharing Norms? Assessing the Gender Performance Gap Among Informal Entrepreneurs in Madagascar”, IZA Discussion Paper.
- Peters, Pascale; Tijdens, Kea G.; and Cécile Wetzels, 2004. “Employees’ opportunities, preferences, and practices in telecommuting adoption”, Information and Management, 41,469-482.
- Ransome, Paul, 2007. “Conceptualizing boundaries between ‘life’ and ‘work’”, The International Journal of Human Resource Management, 18, 374-386.
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- Torres, Jesica; Maduko, Franklin; Gaddis, Isis; Iacovone, Leonardo; and Kathleen Beegle, 2021. “The impact of the Covid-19 pandemic on Women-Led Businesses”, The World Bank Policy Research Working Paper, 9817.
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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.
Assessing a Model for the Implementation of an Equal Pay Review and Reporting (EPRR) Methodology in Georgia
Georgia’s gender pay gap has started to attract the attention of the population and policymakers alike. The gap persists despite working women generally reporting better labor-market skills and personal characteristics. It has been argued that this could be the result of systematic gender-based workplace wage discrimination, resulting in unequal pay for equal work. The discussion that ensued highlights how the fight to guarantee equal pay for equal work could benefit from establishing an Equal Pay Review and Reporting Mechanism. In response, the ISET-PI team – after reviewing the best international practices – devised and tested an excel based tool that could help companies and governmental agencies identify, monitor, and fight gender discrimination in Georgia. The main quantitative result of the exercise identified that, should reporting be made mandatory, extending the obligation to companies that employ up to 50 people would make the administrative costs for companies and public administration up to twenty times higher; thus, the usefulness of the tool was found to be substantially limited when applied to smaller companies. Finally, the exercise emphasized the reluctance of companies to provide the data required, leading to the conclusion that the successful implementation of such an initiative would require the enforcing agency to have the legal authority to sanction failures to provide the necessary data.
Introduction
One of the key gender inequality indicators is the gender pay gap – or gender wage gap – calculated as the average difference between the remuneration for men and women in the labor market. Its evolution is monitored worldwide, and closing this gap is considered a key step towards more inclusive and prosperous economies and societies. According to the World Economic Forum, as of 2020, no country (including the top-ranked ones) had yet achieved gender parity in wages.
In Georgia, the unadjusted hourly gender pay gap amounts to 17.7 percent of the average male hourly wage (UN Women, 2020). Moreover, when controlling for personal characteristics of men and women, the adjusted hourly gender pay gap in Georgia is estimated to be 24.8 percent (UN Women, 2020). This implies that women, on average, have better observable labor-market characteristics but are still paid less than men.
These findings prompted a core discussion within the Georgian society on the presence of unequal pay for equal work in Georgia as one of the possible reasons for the gap and how to tackle the problem. The idea of equal pay for equal work entails that individuals in the same workplace are given equal pay if they perform the same type of work. Consequently, this potential source of the pay gap can only be verified at the individual employer level. This is accomplished by calculating the unexplained gender pay gap at the organizational/employer level and validating whether, and why, these differences exist.
Given the attention the topic holds in the national discourse, ISET Policy Institute created and tested an excel tool, built in line with the international best practices and adapted to the Georgian context, to help employers and government offices identify and measure the differences in wages between men and women performing equal work. During this process, the team learned several noteworthy lessons, as summarized in this policy brief.
International Experience
There is growing consensus that transparency is critical when dealing with pay inequality and, therefore, gender pay reporting should become the norm. Since 2010, several (mostly developed) countries have introduced reporting schemes to monitor gender pay gaps, promote awareness about gender equality issues throughout society (particularly among employees), and increase organizations’ accountability to address gender inequalities (Equileap, 2021).
However, the gender pay gap is a key issue for which the disclosure of information remains particularly low. Equileap’s 2021 report revealed that 85 percent of organizations worldwide did not publish information on remuneration differences between female and male workers in 2020.
Three countries, according to Equileap, lead the way in gender pay gap reporting: Spain, the UK, and Italy (Figure 1). In each of these top three countries, reporting is mandatory.
Figure 1. Percentage of organizations publishing gender pay information, per country

Source: Equileap, 2021. The figure only includes countries for which more than 49 surveyed organizations were included in the Equileap dataset.
However, even in these countries, and, more generally, in all countries scrutinized by Equileap but Iceland, firms with 50 or fewer employees are not required to report on gender pay gaps.
The Case of Georgia
Georgian legislation clearly establishes the principle of equal pay for equal work for all employees. The requirement applies to both public and private organizations. Nevertheless, enforcement of the law remains a significant challenge.
At present, Georgia has no reporting requirements regarding employee salaries for private organizations. It has not yet designed a reporting scheme for equal pay for equal work, nor has it assigned the task of collecting this information to any governmental body.
Moreover, Labour Inspectorate representatives state that few wage discrimination cases are currently being filed in the country. The main reason behind this is that norms regarding equal pay for equal work have never been properly specified. In addition, there are no explicit criteria defining the concept of ‘equal work’. Thus, employers and employees alike do not seem to fully understand the phrase – equal pay for equal work.
The Excel Tool
After a careful review of the three tools presently utilized to calculate gender pay inequality (the Swiss Logib, the German Logib-D, and the Diagnosis of Equal Remuneration (DER) tool developed by UN Women), ISET-PI built a Georgian model as a modified version of the DER tool that is adapted to the Georgian context and includes some variables from the Swiss tool.
The tool itself is an excel file with several worksheets. The two main facets are the inputted data sheet and the results sheet. Companies may input information on their employees in the data sheet, and the findings will then be demonstrated in the results sheet. The tool first identifies people performing the same work, and classifies jobs based on their official titles, alongside managerial responsibilities and skill requirements. After individuals are grouped by job, the tool calculates the average salary within each group separately for men and women. Thereafter, the pay gap is calculated based on the average salary for the two gender groups.
With the support of the Employers’ Association, several companies of all sizes were approached to test the tool. Unfortunately, only a few agreed to participate, and just two completed the trial: one small-sized enterprise (with 50 or fewer employees) and a large-sized enterprise (with 250 or more employees).
While low participation rates have significantly limited our analysis, we still obtained several important insights which are discussed in the next subsection.
Findings
Firstly, it is important to note that companies’ willingness to share anonymized salary data was very low, even among the companies that completed the test.
Secondly, the usefulness of the tool for obtaining a comprehensive view of equal pay for equal work in small companies (with 50 or fewer employees) appeared fairly limited as few people within the same firm perform the same job.
Thirdly, we performed a simple cost assessment exercise to evaluate the compliance costs – to both companies and the government – of collecting and reporting the gender pay gap. We found that extending the data collection requirement to small companies would increase the compliance costs by up to 20 times (high-cost scenario) compared to an example where small companies are exempt. This is because there are many more small companies in Georgia (146,802), than those classified as medium or large ones (2,752 and 609, respectively).
In addition, during the implementation of the exercise, we became aware of the following:
- Under the existing legal provisions, it would be extremely difficult to introduce the EPRR in a mandatory format – no governmental agency could sanction companies for failing to comply.
- Opting for the mandatory option and sanctioning the emergence of unequal pay in certain job categories could incentivize companies to manipulate the data input. In this case, therefore, it would be ill-advised to provide the full tool to companies, as they could more easily adjust data inputting to obtain more favorable indicators through successive iterations.
Conclusion
Setting up an EPRR system is one way to contribute to the implementation of the equal pay for equal work principle.
Designing the Georgian Model for the Implementation of an Equal Pay Review and Reporting Methodology generated several useful insights that might prove valuable for policymakers in Georgia and other developing countries:
1) The EPRR instrument can be utilized for the analysis of gender pay gaps within companies with more than 50 employees. Within smaller companies, evaluating the gender pay gap significantly increases the costs to society, while providing rather limited additional information.
2) The decisions about whether to provide the analytical part of the tool to companies, and whether reporting should be voluntary or mandatory should be taken jointly. If the goal is to provide an instrument to the agency enforcing the equal pay for equal work principle and to facilitate appeals from workers, the tool should be made mandatory. However, in this case, companies should only provide the input data, without having access to the part of the tool that assesses pay gaps at the job level. On the other hand, if the goal of the reform is to support willing companies in their efforts to eliminate unequal pay for equal work conditions, a non-mandatory form may be preferable. In this instance, companies should have access to the full version of the tool. This would allow them to better understand the dynamics that lead to unequal pay and thus put in place internal remedial actions.
3) If the goal is to provide a tool to the agency enforcing the equal pay for equal work principle, it is crucial that any gaps in the associated legislation are closed. As such, the enforcing agency should be capable of sanctioning failures to provide the required data, and prosecuting violations of the equal pay for equal work principle.
Finally, it is important to note that testing the application of the equal pay for equal work principle at the company level through an EPRR system, while useful for identifying potential causes of the gender pay gap and the existence of gender disparities within companies, is just a first step in a longer and more complex process. Once disparities are identified, both companies and enforcing agencies should follow up with additional research and analysis to determine whether these disparities are linked to discriminatory practices, and what type of remedial options could be adopted.
References
- Equileap. 2021. Gender equality global report & ranking. Equileap Research Paper. Available at: https://equileap.com/wp-content/uploads/2021/07/Equileap_Global_Report_2021.pdf
- Geostat. 2020. Business Sector in Georgia. Geostat. Available at: https://www.geostat.ge/media/35014/Krebuli-2020.pdf%20
- UN Women. 2020. Analysis of the Gender Pay Gap and Gender Inequality in the Labor Market in Georgia. Tbilisi: UN Women. Available at: https://georgia.unwomen.org/en/digital-library/publications/2020/03/analysis-of-the-gender-pay-gap-and-gender-inequality-in-the-labor-market-in-georgia
- UN Women. 2021. Assessment of the models for the implementation of the models for the implementation of the Equal Pay Review and Reporting (EPRR) methodology in Georgia. Tbilisi: UN Women. Available at: https://iset-pi.ge/en/publications/research-reports/3020-assessment-of-the-models-for-the-implementation-of-eprr-methodology-in-georgia
- WGEA. 2019. International Gender Equality Reporting Schemes. Workplace Gender Equality Agency Annual Report. Available at: https://www.wgea.gov.au/publications/international-gender-equality-reporting-schemes
- WEF. 2021. Global Gender Gap Report 2021. The World Economic Forum. Geneva, Switzerland. Available at: https://www.weforum.org/reports/ab6795a1-960c-42b2-b3d5-587eccda6023
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.
Food Security in Times of Pandemic in Georgia
The lockdowns and trade restrictions related to the COVID-19 pandemic resulted in shortages of some major food commodities on international and local markets. In this policy brief, we discuss and analyze Georgia’s response to the crisis in terms of food security and agricultural policy. Furthermore, we provide recommendations to ensure fewer disruptions in food supply chains and low volatility in food prices.
Background
COVID-19 has posed significant risks to the food security of many countries including Georgia. Lockdowns and pandemic-related trade restrictions across the world have resulted in shortages of some major food commodities on international and local markets (e.g. sunflower oil shortage in Russia). As of October 16, 2020, according to a World Bank report, 62 jurisdictions have executed a total of 62 export controls in food commodities since the beginning of 2020 (Table 1).
Table 1. Total number of new export controls and import reforms in the food sector globally since January 2020, by month.

Source: World Bank Group, Global Alert Team, 2020
Most of the interventions have involved import reforms with the largest number of new regulations imposed in March-April. On August 18, 2020, the Eurasian Economic Commission announced an EAEU import tariff quota on certain agricultural goods, valid for 2021. Turkey has also conducted a price stabilization policy by announcing purchasing prices for apricots, paddy, and dried raisin. On August 5, 2020, the government of Turkey introduced additional customs duties on certain agricultural products including chocolate, pasta, and some food preparations. It also eliminated import duties on wheat and barley in October.
Given that Georgia is a net importer of food, and in light of the trade restrictions imposed by its major trade partners, food security moved up on Georgia’s agricultural policy agenda. In order to weaken the adverse impact of the pandemic, keep food prices stable, and reduce input prices for farmers, the state designed the following set of measures:
- 10M Georgian lari (GEL) from the Ministry of Environmental Protection and Agriculture (MEPA) budget were allocated to subsidize imports of 9 food products: pasta, buckwheat, vegetable oil, sugar, wheat, wheat flour, milk powder, and beans (Legislative Herald of Georgia, 2020). The program subsidized importers’ additional costs resulting from exchange rate fluctuations and was implemented between March 15-May 15;
- Additional 16M GEL were allocated for purchasing sugar (5,000 tons), vegetable oil (1,500 thousand liters), and pasta (500 tons) stocks from private companies;
- An anti-crisis plan, “Caring for Farmers and Agriculture”, was presented by the state on March 12. The plan entailed two forms of aid: direct assistance to farmers and sectoral support. Some of the support measures included the distribution of so-called “agricultural cards”– subsidies for cattle-breeding and land cultivation services for smallholder farmers (registered farms with plots in the range of 0.25-10 ha); provision of cheap diesel fuel for farmers; nullification of costs of land reclamation services; provision of agricultural loans and insurance; grants for machinery, equipment, and cooperatives.
Results of Government Interventions
As of October 9, 2020, state support schemes had the following results:
- Up to 165,000 farmers had been granted agricultural cards. The size of the subsidy exceeded 28.9M GEL;
- Under the agro-diesel program (which subsidized fuel prices for agro-producers) 122,000 beneficiaries received discount cards on 32,000 tons of agro-diesel;
- More than 17,000 policies had been issued and 18,000 hectares (around 2% of agricultural land) had been insured under the agro-insurance program. The value of the insured crop exceeded 160M GEL;
- Across different regions of Georgia, 255 applications for modernization of the dairy sector were approved. In total, 12.4M GEL were spent on this program;
- 2,215 agro-loans had been issued with a 6-month interest rate covered by the state. The total amount of loans exceeded 40M GEL, including the co-financing of interest rates, which exceeded 3.3M GEL.
While many farmers have benefited from state support programs, these programs were not directly focused on the main consequences of the pandemic. The major threats posed by the pandemic – disruptions in food supply chains leading to decreased sales of agricultural products and price volatility – were not sufficiently addressed by the state support programs. According to the Georgian Farmers’ Association (GFA), 55% of surveyed farmers and agricultural business representatives encountered complications with product realization due to pandemic-related restrictions. Most farmers depend on the HoReCa (hotels, restaurants, and cafés) and hospitality sector, and their products are largely procured for accommodation and food facilities. 60% of those surveyed claimed that they were simply unable to sell their products due to the closure of hotels, restaurants, and cafés.
Food Price Dynamics
During March-May 2020 – the first months of the pandemic – food prices in Georgia showed upward trends on both a month-on-month and year-on-year basis (Figure 1).
Figure 1. Month-on-month and year-on-year changes in food prices

Source: GeoStat, 2020
The main explanation is likely the depreciation of the GEL against the US dollar: during March-May 2020, the GEL depreciated against the USD by 15.8% from 2.71 to 3.14 compared to March-May 2019 (National Bank of Georgia, 2020). As Georgia is a net importer of food commodities, the depreciation of the GEL put upward pressure on food prices. To limit the GEL depreciation and its impact on food prices, the Government of Georgia subsidized additional costs of importers of major food commodities arising from exchange rate fluctuations. The price restraint mechanism involved negotiating with food importers to not increase prices of their commodities and setting the exchange rate of the GEL against the USD at 3, while the Government of Georgia subsidized the corresponding difference between the actual and fixed exchange rates. Despite minimizing the effects of GEL depreciation, food prices in Georgia experienced a significant increase during the observed period: disruptions in supply chains associated with the COVID-19 pandemic led to food shortages that further increased food prices.
In April, annual food price inflation marked its highest level at 16.1% during March-August 2020. Since then, annual food price inflation has been decreasing as farming activities resumed after COVID-19-related restrictions were relaxed and seasonal (locally produced) agricultural products appeared on the market. Accordingly, food prices started to decrease on a monthly basis.
However, with very few exceptions, prices for major food commodities that were subsidized by the state during March-May increased for both month-over-month and year-on-year comparison (Table 2). On a monthly basis, the biggest price changes were observed for sugar; while on annual basis prices for buckwheat increased the most.
Table 2. Year-on-year changes in prices of major food commodities, March-September 2020

Source: GeoStat, 2020
While food prices could have increased even more in the absence of subsidies, it appears that the state measures did not fully reach their objectives and could not fully overshadow the adverse impact of the pandemic and GEL depreciation.
Recommendations
The pandemic has shown the need for increasing the level of food security in Georgia. Given the multidimensional nature of food security, a longer-term policy should consider not only an increase in domestic production of key food commodities but also a diversification of import markets to ensure low volatility in food supply and prices. As an immediate response to the pandemic, it is recommended to:
- further subsidize farm inputs in order to reduce the current costs of production;
- support farmers in selling their produce;
- develop state programs that strengthen local producers;
- focus on diversification of import markets for food commodities which constitute a high share of households’ consumption basket.
References
- GeoStat (National Statistics Office of Georgia), 2014. “Agricultural Census of Georgia“, Tbilisi, Georgia.
- Georgian Farmers’ Association, 2020. “The effects of COVID-19 on farmers and agriculture”, available only in Georgian.
- GeoStat, 2020. Statistics of food prices, retrieved from: https://www.geostat.ge/en/modules/categories/26/cpi-inflation
- Government of Georgia, 2020. “Ordinance of the Government of Georgia on subsidizing prices of major food commodities”, Legislative Herald of Georgia, available only in Georgian.
- National Bank of Georgia, 2020. Statistics of exchange rates, retrieved from: https://www.nbg.gov.ge/index.php?m=582
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.
COVID-19 | The Case of Georgia
Introduction
Georgia has close to 4 million inhabitants. It borders Russia, Azerbaijan, Armenia and Turkey, which are also its main trading partners. The capital and largest city is Tbilisi with about 1,5 million inhabitants. Agriculture and the tourism sector dominate the local economy.
Georgia reported its first case of Covid-19 on February 27, 2020 and its first deaths on April 6, 2020. The government reacted quickly, banning direct flights from China in late January 2020 and imposing severe travel restrictions even within the country in March 2020. Schools and universities were closed on March 11, 2020. The government banned all larger public gatherings on March 21, 2020, the same day when the country declared the state of emergency. The four major cities of Georgia – Tbilisi, Batumi, Kutaisi and Rustavi – were put under lockdown on April 15, 2020.
As of May 8, 2020, Georgia reported a total of 9 fatalities, suggesting that the virus has quite successfully been contained so far. A breakdown of the healthcare system seems unlikely at the moment. Economically, the situation is more heterogenous. Georgia’s public finances are in a tolerable enough shape to handle a crisis. The public debt to GDP ratio is not very high (44.9% in 2018), and the government budget deficit is also below 3% of GDP. Georgia’s financial system has been praised as one of the strongest among in the ECA region. However, annual inflation in January-February was 6.4%, which is significantly higher than the target level of 3%. Georgia is facing uncertainties in terms of inflationary expectations, and this limits the National Bank of Georgia’s (NBG) ability to stimulate the economy under the current circumstances. Most probably, NBG will not cut the policy rate to avoid provoking further currency depreciation and stoking inflationary expectation even further. Moreover, a major weakness in the Georgian economic system lies in its lack of a broad social safety net infrastructure, which could help support afflicted groups during downturns. Finally, another risk is the substantial informal sector: workers in these sectors are hard to reach via conventional policy measures.
Below, we outline how the Georgian economy has been affected by Covid-19 and what the policy responses have been so far. We will also discuss several economic scenarios and explain which further policy options are thinkable.
How Does the Covid-19 Crisis Affect the Georgian Economy?
Demand Side Effects
- A decline in domestic consumption resulting from behavioural and policy changes is to be expected on the demand side – i.e. people staying home as a precaution or because they are required to. In addition, currency depreciation and possible price spikes (due to herding behaviours and potential disruptions in supply chains) are also expected to have a negative effect on consumption and investment.
Household consumption accounts for 66.7% of the Georgian GDP (Geostat, 2018). A significant reduction in household consumption (e.g. spending on transportation, clothing, electronics, and domestic services) would therefore result in an overall slowdown of GDP growth. A slowing of internal demand would hit people working in the informal sector particularly hard; namely, those without a regular salary (e.g. temporary workers, taxi drivers, and other self-employed service sector workers) and small and micro business-owners. Their situation is worsened still because the government’s fiscal stimulus and assistance is unlikely to reach them directly. They are also not expected to benefit from the extra liquidity injected into the financial system, as they will not qualify for bank loans to cover temporary income losses. Another vulnerable group are the formal sector workers employed in companies that face a dramatic decline in their usual economic activities (restaurants, hotels, the entertainment industry, transport, etc.). These companies are likely to put their workers on unpaid leave or simply fire them. Moreover, the slump in household demand will also be made worse by the fact that most families are likely to have limited savings and, therefore, their capacity to smooth consumption is limited. Hence, the crisis may cause a significant drop in well-being and, possibly, further deterioration in individuals’ physical and mental health, alongside the direct impacts of Covid-19
- A decline in domestic investment because uncertainty and deteriorating business sentiments will stall business investment decisions. Expectations of a global recession could become self-fulfilling if ‘business-as-usual’ does not resume in the next few months. If companies expect a slowdown in demand, they will also delay investment, and GDP will decline further. Investment (gross fixed capital formation) accounts for approximately 28% of Georgia’s GDP. Thus, the Georgian government has announced capital spending to combat the expected drop in private investment.
- A decline in tourism and related business seems inevitable as tourism arrivals and receipts are expected to decrease sharply as a result of the numerous travel bans, and due to precautionary behavior. According to our preliminary calculations, the Georgian economy lost between 3-9% of potential tourism revenue in February. Since the tourism sector accounts for 6% of Georgia’s GDP (GNTA 2018), a direct hit to the industry will substantially impact GDP. In table 1, we work out GDP losses associated with the following scenarios:
Table 1: Net effect of the coronavirus crisis on tourism in Georgia

Note: after each period indicated in the scenarios, tourism is assumed to immediately recover to 2019 levels.
Source: Geostat, NBG, authors’ calculations.
- The spillover effect on other sectors: a drop in demand for goods and services in the region, in China, the EU, and the US – will affect the overall economy via trade and production linkages.
While it is difficult to predict how Georgia’s economy will react to a global shock of such magnitude, some preliminary estimations may already be made. Georgia’s growth rate over the last 20 years correlates notably to several neighboring economies. One of the greatest correlations is, unsurprisingly, with Russian economic growth. Russia’s growth is also highly correlated with other countries, reflecting global economic linkages. These correlations are reported in table 2 below:
Table 2: Correlations of growth rates
| Table 2 | Georgia | Russia | Armenia | Turkey | China | Kazakhstan | Italy | Germany | France | US | Israel | Ukraine |
| Georgia | 1.00 | 0.87 | 0.88 | 0.66 | 0.58 | 0.81 | 0.67 | 0.74 | 0.85 | 0.69 | 0.77 | 0.73 |
| Russia | 1.00 | 0.90 | 0.60 | 0.73 | 0.83 | 0.64 | 0.67 | 0.82 | 0.63 | 0.79 | 0.91 |
Source: World Bank, authors’ calculations.
In order to explore how a slowdown across major world economies will affect Georgia, we have followed three economic scenarios relating to major world economies, as reported by Orlik et al. (2020). The numbers reflect growth rate changes relative to the baseline (no virus outbreak).
Table 3: Coronavirus effect on growth rates.
| Table 3. Coronavirus effect on growth rates | Real GDP annual growth change in 2020 compared to the baseline scenario, pp | Real GDP growth, % in 2020, assuming a 5% baseline | |||
| Russia | Germany | US | Georgia | Georgia | |
| Scenario A: Outbreak causes localized disruption | -0.9 | -1.2 | -0.2 | -1.09 | 3.91 |
| Scenario B: Widespread contagion | -3 | -2.8 | -1.3 | -3.09 | 1.91 |
| Scenario C: Global pandemic | -4.8 | -3.6 | -2.4 | -4.55 | 0.45 |
Source: Orlik et al. (2020); authors’ calculations.
- A decline in trade is likely and it is possible to find certain similarities between the current situation and the economic slowdown in the Eastern Europe and Central (EECA) region in 2014-2017, caused by a drop in oil prices and global appreciation of the US dollar. The latter resulted in a sharp decline of external demand, falling commodity prices and regional currency crises, which equally affected the Georgian economy. The country’s goods exports fell by 23%, while imports contracted by 15% in 2015. Trade was only restored to the 2014 level by 2018. While, the forthcoming crisis is expected to not only have stronger negative impacts on external demand, but also disruptions in the production value chains, affecting Georgia’s trade in more severe ways. Trade of all commodities, except food and medicine, is projected to decline, depending on the duration of the shock.
- A decline in Foreign Direct Investment (FDI) is to be expected since foreign investors prefer to invest in safe assets. Additionally, currency depreciation expectations will negatively affect FDI. The FDI in Georgia amounted to 1,267.7 mln. USD in 2019 (7.1% of GDP).
- A decline in remittance inflows seems likely: since all countries will suffer economically in the aftermath of the health and oil price crises, we expect significant slowdown in remittance inflows from the rest of the word. The remittances decline will hit Georgia particularly hard as it is among the top receiver countries of foreign transfers. For instance, in 2019, money transfer inflows accounted for 9.8% of GDP. Various scenarios for just how much Georgia is set to lose in monetary inflows is presented in table 4 below:
| Table 4. Net change in money transfers inflow in 2020 due to coronavirus (Mln. USD) | ||
| Scenario 1: 10% decrease of net money transfers in the remaining months of the year (March-December) | Scenario 2: 30% decrease of net money transfers in the remaining months of the year (March-December) | Scenario 3: 50% decrease of net money transfers in the remaining months of the year (March-December) |
| -114 | -372 | -629 |
| Net change in consumption spending due to money transfers decline* | ||
| -570 | -1,857 | – 3,146 |
| Net change as a share of household total real consumption spending** | ||
| +0.3% | -2.6% | -5.5% |
* $1 of transfers is assumed to become $0.8 equivalent of consumption spending.
** USD/GEL exchange rate is assumed to equal to the official exchange rate as for March 20th (3.1818) in the remaining months of the year (March-December). Inflation is assumed to be 6% in 2020.
Source: Geostat, NBG, authors’ calculations.
Supply Side Effects
- Production disruptions may occur on the supply side. Domestic production suffers as a result of forced business closures and the inability of workers to get to work, as well as disruptions to trade and business as a result of border closures, travel bans, and other restrictions on the movement of goods, people, and capital (in the PRC as a whole fell to 50%–60% of normal levels but is now normalizing, after the introduction of extremely restrictive measures that – so far – no country in the West has been able/willing to mimic. However, in the absence of such restrictions, the crisis may be prolonged, and production might be hard to restart quickly). The overall impact on production may be mitigated by the fact that in some sectors (particularly in manufacturing) production can be ramped up in later periods to compensate for lower production (providing closures do not last too long).
- Long-term economic effects need to be taken into account. Covid-19 will impact health via mortality and morbidity, and through changes in (and the diversion of) healthcare expenditure.
Currency Depreciation
The expected decline of tourist inflows, remittances, and exports as a result of reduced foreign demand from Georgia’s trading partners and low world oil prices have already affected the lari exchange rate (mostly through expectation channels). On the other hand, due to restrictions on air travel, the outflow of currency from Georgia to foreign countries will be reduced (the import of tourism services will be lower), which will have a positive effect on the exchange rate. Another positive factor may be that Georgia’s reliance on remittances from oil-exporting countries (like the Russian Federation) has been significantly reduced in recent years.
What Has Been Done to Address the Covid-19 Crisis?
The Government of Georgia timely started applying measures to address dramatic impacts on various market participants:
Businesses
- Restructuring loans for businesses affected by the crisis;
- Companies that operate in the tourism industry: hotels and restaurants, travel agencies, passenger transportation companies, site-seeing companies, arts and sports event organizers, etc., will have their property and personal income taxes deferred by the Georgian government for four months;
- Doubling the volume of VAT refunds to companies, with the aim of supplying them with working capital;
- Designing a state program to co-finance interest payments on bank loans by hotels with 4-50 rooms, throughout the country, for the next six months.
Workers
- Loan payment deferrals for three months;
- Personal income taxes deferred for employees in the tourism industry.
The Health Care System
- No new measures are planned at this point.
The Financial System
- Easing lending restrictions for commercial banks;
- NBG has not cut policy rates and is unlikely to do so given the risks of inflation.
Other Measures
- Boosting capital expenditure (CapEx) projects with the aim of providing additional economic incentives;
- Governmental price fixing for specific products (rice, pasta, sunflower oil, flour, sugar, wheat, buckwheat, beans, milk powder and its products) by subsidizing corresponding businesses.
Will the Current Measures Be Sufficient?
Given the rapidly changing scope of the crisis, the short answer is simple – probably not. As the forecast seems pessimistic, it is the role of the fiscal stimulus and, where possible, the monetary policy to help soften the economic shock.
It is evident that the measures adopted by the government as well as private commercial banks in Georgia will not be able to directly reach a sizeable group of the population affected by the shock – i.e. those unemployed due to Covid-19; those working in the informal sector; people with low income; or households that are very reliant on remittances transfers. It is important for the government to connect with these groups quickly, not only for humanitarian reasons, but also in the interest of a broader development agenda. In case of relatively prolonged quarantine sizable part of the population will no longer be able to support themselves and their families in coming months.
What More Can Be Done?
We broadly outline the additional monetary and fiscal policy measures that may be considered:
More Forceful Fiscal Intervention:
As previously mentioned, Georgia’s systemic weakness lies in its lack of a broad social safety net infrastructure, which could help target and support afflicted groups during downturns. An unemployment benefits system, which in other countries acts as an “automatic stabilizer” and reduces and mitigates the effect of economic downturns, simply does not exist in Georgia. Yet even with an unemployment benefits system in place, the sizeable informal economy would prevent such a system from effectively easing labor market tensions. In the current situation, the government should attempt to provide cash relief for workers in the informal sector, for the low-income self-employed, and for independent contractors. These groups of workers are the most vulnerable to income flow reduction during the crisis, furthermore, they are unlikely to have access to sick leave benefits or to take advantage from cheaper bank credit.
Based on the experience of other countries, the government perhaps should consider the following measures in addition to current measures:
- Providing low interest emergency loan/cash advances to affected adults, or direct cash payments to affected households, in particular households with the elderly and children. These measures are valuable as they can quickly reach afflicted groups. Unfortunately, this solution is not well-targeted and risks wasting government funds on those who are not disadvantaged.
- Simply providing “helicopter money”, or cash transfers to households below a certain income threshold (similar measures are being considered in the US) may be an option, but this measure is subject to the same concerns as above. However, the advantage is that cash transfers allow households to optimize their expenditure and do not distort consumption choices.
- Another form of wide-reaching support could be state subsidies to help support utility payments for a limited time. These measures, equally, are not well-targeted, nevertheless there may be methods to direct them towards the households which need them the most.
- Measures to encourage companies to not cut employment in the months following the crisis: following the example of other countries, Georgia may support salary payments for companies, on the condition that they do not reduce employment or force workers to take unpaid leave.
Naturally, none of the proposed measures are perfect as they cannot specifically target those most affected by the crisis, yet they may act as a short-term second-best solution. As these examples show, Georgia should consider to develop a targeted social safety net system in the future. Such a system can make the country more resilient in the face of future crises and unexpected emergencies.
Monetary Policy
While other countries push for fiscal stimulus and monetary expansion, Georgia is facing uncertainties in terms of inflationary expectations. As discussed, this limits NBG’s ability to stimulate the economy under the current circumstances. Annual inflation in January-February was at 6.4%, significantly higher than the 3% target. Going forward, a sharp decline in aggregate demand would reduce the pressure on inflation, while a depreciating nominal effective exchange rate will exert upward pressure. Therefore, the possibility to reduce the monetary policy rate depends on which effect will dominate in the future. In the meantime, NBG has approached the IMF to increase access to funding under its Extended Fund Facility program (NBG). Alongside the additional funds from other international donors, this will positively affect the economy, strengthen the nominal effective exchange rate and, consequently, curb inflation.
In addition to the measures already announced, NBG has the option of decreasing the minimum reserve requirements for deposits attracted in a foreign currency. This will stimulate FX lending and economic activity, without creating depreciation or inflationary expectations.
Overall, the Georgian government responded very timely and efficiently to contain the virus outbreak, earning well-deserved plaudits from the international community and approval from the general public. However, as the scope of the crisis continues to change rapidly, additional measures might soon be needed. As the economic landscape becomes more uncertain, the government needs to ensure that emergency economic stimulus measures directly reach the people most affected by the crisis.
Disclaimer
This policy brief was first published as an ISET policy note on March 25, 2020 under the title “The Economic Response to COVID-19: How is Georgia Handling the Challenge?“. This brief is an adaption of the original note and is published with the consent of the authors.
References
CIA World Fact Book, 2020. “Georgia”.
The Guardian, 2020. “How UK government could support people as coronavirus spreads”.
Imeson, Michael, 2019. “Georgian banks gather rewards for resilience”. The Banker.
Lomsadze, Giorgi, 2020. “Georgia gets rare plaudits for coronavirus response“. Eurasianet.
Migration Policy Institute, 2020. “Global Remittances Guide”.
Orlik, Tom; Jamie Rush; Maeva Cousin and Jinshan Hong, 2020. “Coronavirus Could Cost the Global Economy $2.7 Trillion. Here’s How”. Bloomberg.
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 Georgian Tax Lottery of 2012 – A Quantitative and Qualitative Evaluation
This policy brief is based on preliminary findings of research that assesses the 2012 Georgian Tax Lottery by Larsen et al. (2019). Tax lotteries are seen as a way to relatively easily augment public revenue while also increasing compliance. Tax lotteries are constructed so that consumers are nudged to ask for a receipt when making a purchase. This receipt contains information which can also be used as a lottery ticket with the possibility of winning prizes. Such tickets also leave traces of transaction records that allow revenue authorities to audit vendors. Given this background, the aim of this paper is to provide a broad, multi-methodological and socio-economic assessment of Georgia’s tax lottery experience in 2012.
Introduction
A well-designed tax system improves economic efficiency, facilitates economic growth and social welfare, (Besley & Persson, 2013). Yet, curbing tax evasion remains one of the key challenges for policy makers, and institutions in charge of revenue administration are experimenting with diverse set of instruments to increase tax compliance and thus revenue.
In addition to the traditional audit-sanctioning mechanism, the taxation literature emphasizes the role of consumers in facilitating tax compliance of businesses. The government can create direct monetary incentives for consumers to request receipts. Turning a receipt into a lottery ticket with a chance of winning a pre-determined prize is an example of such an incentive. The tax lottery motivates and rewards those consumers who become part in the efforts to fight tax evasion by requesting receipts while making purchases. Given that audit-sanctioning mechanisms are very costly for the government, clever usage of a “zero cost policy”, such as tax lotteries, might be advisable (Fabbri & Hemels, 2013).
The aim of this paper is to provide an assessment of the Georgian tax lottery experience in 2012 using both quantitative and qualitative methodologies. The two methodological approaches complement each other and help to investigate the tax lottery from different angles.
The Georgian Tax Lottery
The Georgian Revenue Service (GRS) introduced a tax lottery starting in spring 2012, which was planned to run until January 1, 2013. The aim of the lottery was to popularize the already introduced General Packet Radio Services (GPRS) -based cash registers and make sure that they were used by vendors. Such registers would allow the GRS to gather information about business activities online daily. This, in turn, was due to an effort to fight the shadow economy and be able to audit business revenue, when payments were made by cash. The lottery would thus motivate consumers to ask for receipts. As a communicative resource, the lottery aimed to increase awareness of asking for receipts, as well as to develop a positive attitude in Georgian society towards GRS in the background of harsh fiscal reforms.
In order to participate, customers had to buy goods or services from a vendor who had a GPRS-based cash register. The receipt could be checked for win immediately by mobile phone. The Georgian Tax Lottery was a chance to win money for every customer purchasing anything from groceries, to shoes and hair care. The winning prizes were 10, 20, 50, 100, 10,000 and 50,000 GEL[1]. The 10,000 GEL prizes were awarded once a month while 50,000 GEL prizes were given quarterly.
The lottery ended prematurely on grounds of inefficiency on November 12, 2012 when a new government was elected.
Multi-Method Approach
For the assessment of the tax lottery in Georgia, we employed a multi-method approach combining a qualitative assessment built on an ethnographic approach with quantitative regression-based methods; following the ethnographic approach, we collected opinions, experiences, and views on the tax lottery from the perspective of participating and non-participating businesses, consumers as well as other stakeholders.
The quantitative assessment of the paper investigates whether the existence of the lottery affected businesses’ total revealed turnovers through the facilitation of a receipt-requesting norm. The data for the quantitative analysis conducted in this paper was provided by the GRS. The latter was collected from the daily reports of the GRS system, for two years, 2012 and 2013. The data includes variables, such as the unique cash register identifier, the year and the week of a purchase and address (city and municipality) and the total turnover of the cash register reported through GPRS. GRS also provided the dataset with detailed information on winning tickets. The latter includes daily information on the number of winning tickets and the aggregate daily monetary amount of the prizes.
Three different specifications of linear regression models were run separately on the aggregate country level data. The model-specifications differ in a way that each uses different dependent variables – aggregate weekly sales, average weekly sales per register and number of registers reporting any sales.
Preliminary Results
Table 1: Regression Results of the aggregated analysis on a country level

As may be inferred from the country level regression results reported in Table 1, for all the econometric specifications the ‘lottery’ variable is significant at 1% level. The regression results show that during the weeks of the lottery (weeks 16-46) the aggregate weekly sales are on average 33,363 GEL higher than in the non-lottery weeks (11% more than in non-lottery weeks, based on the log linear model). When looking at the year effect of 2012 in non-lottery weeks, the effects are positive, significant, and, on average, amount to 38,813 GEL. This means that aggregate weekly sales in the non-lottery weeks of 2012, exceed aggregate weekly sales in 2013, on average, by 38,813 GEL. While in this simple model we do not explicitly control for the macroeconomic environment, GDP in 2013 grew by 3.4% while inflation stood close to 0%. These macroeconomic outcomes strengthen predictions of the econometric analysis.
When looking at the average sales per register as the dependent variable instead of aggregate weekly sales, the results are compatible with the results of the first model. There is on average a 282 GEL (7.7%) increase in average turnover during the lottery weeks compared to the non-lottery weeks; and average weekly sales in non-lottery weeks of 2012 exceed average weekly sales in 2013 by 458 GEL, on average. In addition, the positive effect and significance of the year 2012 variable shows that controlling for the non-lottery weeks, something was still driving sales up. This could be the long-term effect of the lottery weeks that continued even after the termination of the lottery; hence some evidence of habit formation.
A similar regression is done with the weekly number of cash registers reporting their income as a dependent variable. The outcome illustrates that during the lottery weeks of 2012, the average number of reported cash registers is 3,199 units (4%) more than those in non-lottery weeks, which is quite compatible with the results reported by the first and second regressions.
Conclusion
Despite seemingly positive results, the lottery was prematurely terminated after parliamentary elections in November 2012. Interviews with stakeholders revealed that the public budget that was allocated for the lottery was deemed insufficient to keep the chances of winning high enough and therefore interest and participation from public had decreased significantly from around 2 mln out of 2.5-2.8 mln receipts checked daily in the first months of the lottery to only 300,000 by the end of the lottery. However, there was a lack of financial resources or interest from the new government to invest additional resources to increase the budget and effectiveness of the lottery.
Regardless of its premature termination lottery itself was thought to have influenced social norms and also started a discussion about tax compliance. The tax lottery also aimed to improve citizens’ attitude towards the GRS. A qualitative analysis, based on multi-ethnographic approach through which we have collected media articles, reports, and other materials expressing views on the Georgian tax lottery, however, showed that strategies of “love and fear” are difficult to make work in combination, and we find it hard to say that citizens’ views of the GRS improved due to the lottery itself. Perhaps even the contrary could be proposed. In terms of an increased trust to the GRS, we conclude with our methodological point that a tax lottery cannot be assessed as an isolated event. Previous and other activities that the revenue services engage in that have an impact on taxpayers and on societal tax, compliance have to be taken into consideration. Fear and unjust treatment especially linger in people’s perceptions.
References
- Besley, T., & Persson, T. (2013). Taxation and development. In Handbook of public economics (Vol. 5, pp. 51-110). Elsevier.
- Fabbri, M., & Hemels, S. (2013). ‘Do you want a receipt?’ Combating VAT and RST evasion with lottery tickets. Intertax, 41(8), 430-443.
- Larsen, L., Arakelyan, R., Gogsadze, T., Katsadze, M., Skhirtladze, S., & Muench, N. (2019). The Georgian Tax Lottery of 2012. A Multi-Methodological Assessment. International School of Economics at TSU, Tbilisi, Republic of Georgia.
- Marcus, G. E. (1995). Ethnography in/of the world system: The emergence of multi-sited ethnography. Annual review of anthropology, 24(1), 95-117.
[1] The exchange rate for a Georgian Lari, GEL, is about 3.0 GEL to 1 EUR.
Agricultural Exports and the DCFTA: A Perspective from Georgia
On June 27, 2014, Georgia and the EU signed an Association Agreement (AA) and its integral part – the Deep and Comprehensive Free Trade Area (DCFTA). In this policy brief, we discuss the changes and analyze the agricultural exports statistics of Georgia since 2014. Furthermore, we will provide the recommendations to capitalize on the opportunities that the DCFTA offers to Georgia.
Georgia is a traditional agrarian country, where agriculture constitutes an important part of the economy. 36.6% of the country’s territory are agricultural lands and 48.2% of the Georgian population live in villages. Although 55% of population are employed in agriculture, Georgia’s agriculture accounts for only 15.8% of its GDP (Geostat, 2019). Agricultural exports constitute an important part of Georgia’s economy, accounting for about 25-30% of total exports.
On June 27, 2014, Georgia and the EU signed an Association Agreement (AA) and its integral part, the Deep and Comprehensive Free Trade Area (DCFTA). On July 1st, 2016, the DCFTA fully entered into force. The DCFTA aims to create a stable and growth-oriented policy framework that will enhance competitiveness and facilitate new opportunities for trade. The DCFTA widens the list of products covered by the Generalized System of Preferences+ (GSP+) and sets zero tariffs on all food categories (only garlic is under quota), including potentially interesting products for Georgian exports – wine, cheese, berries, hazelnuts, etc. (Economic Policy Research Center, 2014).
As July 2018 marked only two years since the implementation of the DCFTA between Georgia and EU, valuable conclusions on its impact cannot be formulated yet. In this policy brief, we will give an overview of Georgia’s agricultural trade statistics, particularly, we will focus on agricultural exports and provide recommendations for capitalizing on opportunities offered by the DCFTA.
Georgia’s agricultural trade
Despite its potential and natural resources, Georgia is a net importer of agricultural products. In 2018, Georgia’s agricultural exports increased by 23.2% (181 million USD), while the respective imports grew by only 15.5% (179 million USD) compared to 2017. Therefore, the trade balance (the difference between exports and imports) remained almost unchanged at (-394) million USD (Figure 1).
Figure 1: Georgia’s Agricultural Trade (2014-2018)

Source: Geostat, 2019
Out of the sharp increase in agricultural exports, 100 million USD are attributed to tobacco and cigars. Since Georgia cultivates very little tobacco, the growth was instigated mostly from the import, slight processing and re-export of tobacco products. Consequently, the export of tobacco and cigars increased by 240% in 2018, and it currently holds second place (after wine) in Georgia’s total food and agricultural exports. It should be mentioned that wine exports contributed to 26 million USD in export growth.
Over the last five-year period, the top export countries for Georgia were mainly neighboring counties (Azerbaijan, Russia, Armenia, Turkey); for imports, we see the same neighboring countries as well as China and Ukraine. Observing the trade statistics over the years, 45% of Georgia’s agricultural exports were destined for markets in countries of the former Soviet Union, so-called Commonwealth of Independent States (CIS), while the EU’s share in Georgia’s total agricultural exports was 24%.
Trade relationships between Georgia and the EU
The EU is one of Georgia’s largest trade partners. The EU’s share of total Georgian imports was 28% in 2018, and for exports, 24%. Total exports have been more or less stable since 2014, except for 2016, when an 11% decrease was observed (Figure 2). Specifically, for agriculture, in 2017, the EU’s share of Georgian imports was 22%, and its share of exports was 19%. During the same period, the top export products were hazelnuts (shelled), spirits obtained by distilling grape wine or grape marc, wine, mineral and aerated waters and jams, jellies, marmalades, purées or pastes of fruit.
Figure 2: Total and Agricultural Exports to the EU (2014-2018)

Source: Geostat, MoF, 2019
In 2015 (before the full enforcement of the DCFTA), Georgia’s agricultural exports to EU countries (including the United Kingdom) increased by 20% compared to the previous year. This positive trend remained in 2016, when the same indicator increased by 5%. In 2017, which was quite a bad year in terms of harvest in Georgia, we observed a 38% decrease in the country’s agricultural export to the EU (Figure 2). This decrease was mainly caused by a significant decrease (64%) in hazelnut exports during the same period. The reason for such a large decrease is that hazelnut production suffered from various fungal diseases due to unfavorable weather conditions in 2017. The Asian Stink Bug invasion worsened the situation, and in the end, hazelnut exports dropped dramatically in both value and quantity. In 2018, Georgia’s agricultural export in EU slightly increased by 6% compared to 2017.
Trade relationships between Georgia and CIS countries
It is interesting to observe agricultural trade within the same time period with CIS countries. In 2018, the CIS’ share of Georgian imports was 51%, and its share of exports was 60%. The top export products to CIS countries were wine, mineral and aerated waters, spirits obtained by distilling grape wine or grape marc, hazelnuts (shelled), and waters, including mineral and aerated, with added sugar, sweetener or flavor, for direct consumption as a beverage. As we can see in both EU and CIS countries, the top export products are more or less the same. However, the main export destination market for Georgian hazelnuts are EU countries, but wine is mostly exported to the CIS countries.
Figure 3: Agricultural Exports to CIS Countries (2014-2018)

Source: Geostat, MoF, 2019
Due to the worsened economic situation in CIS countries, Georgia’s agricultural exports to these countries decreased by 37% in 2015. Such a sharp decrease was mainly driven by a significant decrease in the export of alcoholic and non-alcoholic beverages, hazelnut, and live cattle. However, since 2015, Georgia’s agricultural exports to CIS countries have been increasing; we observed a slight 2% increase in the value of agricultural exports in 2016, while the same indicator was 37% in 2017 (Figure 3). That was mainly caused by the increased exports of alcoholic and non-alcoholic beverages (wine by 61%, spirits by 28%, mineral and aerated waters by 22%). In 2018, Georgia’s agricultural export in CIS countries increased by 12% compared to 2017.
Conclusion
Despite its potential and comparative advantage in agriculture, Georgia is still a net importer of agricultural products and has negative trade balance (-394 mn USD). Two years after the DCFTA came into force, it is challenging to know its impact on Georgia’s agricultural trade due to the insufficient passage of time since. Notwithstanding, we can formulate some conclusions from trade statistics. The diversity of the destinations for Georgia’s agricultural exports has not changed through the years. Georgia’s agricultural exports has increased to the EU, but at a quicker pace to CIS too. Furthermore, Georgia’s share of agricultural exports to CIS countries is still significant (60%).
While it is obvious that Georgia needs to diversify its agricultural export destination markets, there are several challenges facing small and medium size farmers and agricultural cooperatives in Georgia that are not specific to implementation of the DCFTA. As the previous regime (GSP+) with the EU already covered most products, the DCFTA did not represent a significant breakthrough. On the path to European integration, the biggest challenge for Georgia is to comply to non-tariff requirements such as food safety standards and SPS measures. The attention should be paid on providing consultations to farmers regarding certification processes and standards and better information sharing (e.g. developing online platforms).
In Georgia, agri-food value chains are not well-developed and lack coordination among different actors. In order to capitalize on opportunities offered by the DCFTA, government and private sector should work together to improve logistics infrastructure. There is a need for upgrading at every stage of export logistics: warehousing, processing, labeling, regional consolidation, final customer services. In this regard, there are high approximation costs for business that should be considered as long-term investment to modernize agriculture and improve food the safety system in the country. This would boost the export potential not only to the EU, but to other countries with similar requirements as well.
References
- ISET Policy Institute, 2016. “DCFTA Risks and Opportunities for Georgia”
- Economic Policy Research Center, 2014. “Agreement on the Deep and Comprehensive Free Trade Area and Georgia”. Available only in Georgian
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.