Tag: Gender

Gender-Based Violence in Conflict

Posted on May 30, 2022 | Policy Brief

The eruption of war exposes women to increased gender-based violence, in the immediate conflict area as well as in the countries where they seek refuge. Acknowledging the specific conflict-related risks that women face is important, in order to target interventions, especially considering that the actors that sit at peace negotiation tables are predominantly or exclusively men. In this policy brief, we discuss the implications of conflict for gender-based violence, with a special focus on the ongoing war in Ukraine. We also outline some policy interventions that might help mitigate the risks that women face, holding those responsible to account, and building a more gender-equal society from the reconstruction efforts. Our discussion draws from existing academic literature and inputs from the special panel session on conflict during the FROGEE conference “Economic and Social Context of Domestic Violence”.

Gender-Based Violence During Conflicts

During war, as in peacetime, women are exposed to different forms of violence, and to a different extent, as compared to men. In other words, there are gender-specific aspects of conflict-related violence, both in immediate conflict areas and in the places where affected populations might seek refuge.

One form of violence against women in conflict areas is sexual violence and rapes perpetrated by combatants. Scholars and policy analysts tend to portray this violence as a weapon of war (Eriksson and Stern, 2013), meaning that it is a way of humiliating and demoralizing the enemy as individuals and as communities. Differently put, the narrative that portrays sexual violence as, for instance, the consequence of unmet sexual needs among soldiers is increasingly less accepted. Sexual violence against women perpetrated by armed forces in conflict areas is tragically prevalent. While proper quantification of the phenomenon is hard for obvious reasons, it is estimated for example that at least 500,000 women were raped during the Rwandan genocide, and 50,000 during the war in Bosnia (Guarnieri and Tur-Prats, 2022).

Another form of gender-based violence in conflict is that women who are uprooted by war tend to confront a high risk of sexual violence during their journey away from home and in the places where they seek refuge. Vu et al. (2014) estimate, through meta-analysis, that approximately one in five refugees or displaced women in complex humanitarian settings experienced sexual violence. The study also highlights the need for more data to shed light on the characteristics of perpetrators. The presence of aid workers among them appears to persist through several humanitarian crises (Reis, 2021).

Further, women and children fleeing war areas are vulnerable to the risk of trafficking and exploitation for sexual or other work (as highlighted in the FROGEE conference panel). Traffickers and criminal organizations tend to exploit the combination of a mass movement of people in precarious economic situations and the decreased scrutiny generated by the humanitarian emergency.

Finally, war heightens the risk of intimate partner violence (IPV) in conflict areas as well as among refugees and displaced individuals, by causing stress, trauma, economic hardship and increased substance abuse, all of which lead to deterioration in mental health and the quality of relationships (Conference panel). An actual or perceived sense of impunity can also undermine victims’ propensity to report IPV at such a time. A systematic review of the published literature on gender-based violence in conflict finds that estimated rates of IPV across most studies are much higher than the rates of rape and sexual violence perpetrated outside the home (Stark and Ager, 2011).

The consequences of conflict on IPV can be long-lasting. Evidence from post-genocide Rwanda shows that women who married after the conflict were more likely to be victims of spousal abuse; skewed sex ratios that reduced women’s bargaining power in the marriage market appear to be the relevant channel (La Mattina 2017). Another important factor is posttraumatic stress disorder (PTSD) among veterans: a study of US military personnel shows that assignment to combat in the Global War on Terrorism is associated with higher incidence of domestic violence and lower relationship quality (Cesur and Sabia, 2016). The increased availability of small weapons can also lead to more frequent or more violent instances of domestic abuse (Conference panel).

The War in Ukraine

Reports from the US State Department and Amnesty international document episodes of sexual violence from armed conflict actors in Donetsk and Luhansk since the start of the conflict in 2014 (Amnesty International, 2020). Both Russian and Ukrainian military were involved, speaking to the tragedy that the population close to the “contact area” have witnessed since 2014.

At present, growing evidence is emerging that Ukrainians, especially but not exclusively women and girls, are victims of rape, gang-rape and forced nudity perpetrated by Russian military troops invading the country (United Nations). It is notoriously difficult to collect and verify data and facts on sexual violence during wartime, but these early accounts, and the experience from previous conflicts, call for a high level of scrutiny and readiness to help. Research also suggests some potential factors that aggravate the prevalence of sexual violence in conflict. Guarnieri and Tur-Prats (2020) show that armed actors who hold more gender-unequal norms are more likely to be perpetrators of sexual violence, and that the incidence of sexual violence is highest when the parts in conflict hold gender norms that differ substantially (Guarnieri and Tur-Prats, 2022). Survey data show that the share of people who appear to hold gender-unequal norms in Russia remained high over the years, based on questions on the effectiveness of women and men as political or business leaders (Figures 1 and 2), or the desirability of women earning more than their husbands (not shown).

Figure 1. Men make better political leaders than women do, % agreement

Source: World Value Survey

Figure 2. Men make better business executives than women do, % agreement

Source: World Value Survey

Evidence on the evolution of norms in Ukraine is more mixed (see Figures 1 and 2). All in all, surveys of gender-role attitudes suggest that gender stereotypes persist in Russian society, but it is not obvious that the prevailing gender norms are starkly different between Russia and Ukraine. On the other hand, attitudes toward IPV in the two countries might be evolving differently, at least among the respective elites, based on the fact that legislation on domestic violence recently changed in opposite direction in the two countries. Specifically, Russia decriminalized minor forms of domestic violence in early 2017. Conversely, Ukraine strengthened the legal response to domestic violence in early 2019, in particular making minor but systematic domestic violence criminally punishable, and extending criminal punishment beyond physical violence to include emotional and economic violence.

As a consequence of the war, almost 13 million Ukrainians have left their homes since Russia invaded on Feb. 24, 2022, according to the United Nations. Almost all of them are women and children, since men and boys aged 18 to 60 are required to stay in Ukraine to defend the country. Women traveling alone with their children, especially when fleeing to foreign countries where they often have no connections, are clearly at risk of assault and exploitation. Such risk is heightened by the exceptional speed of the refugee influx, whereby an impromptu response from the host countries is by necessity reliant on individual independent participation. Private hosts have spontaneously been opening their homes to accommodate for days or even weeks Ukrainians fleeing the war. Proper vetting of these offers is made difficult by the sheer number of people who are being welcomed in bordering countries, for instance Poland, as well as by the exceptional response from private individuals. Within a little more than a month from the start of this crisis there had already been a few episodes of sexual violence against Ukrainian refugees in their host countries (specifically in Poland and Germany).

While the current death toll in the war in Ukraine is unlikely to lead to dramatically skewed sex-ratios, this aspect might become more relevant as events evolve, in light also of the fact that nearly the universe of those who fled the country so far consists of women and children.

Finally, in the post-conflict period, the presence of small weapons, which have been made available to civilians to defend the country, is an additional risk factor for IPV (Conference panel).

What Can Be Done?

Academics, international organizations, activists and female politicians from Ukraine have made specific requests to improve the system of protection and accountability in the face of sexual violence against women living in or fleeing from conflict zones. These suggestions include ensuring that the system of transitional justice that will govern the post-conflict period establishes proper investigation and punishment of every form of sexual violence performed by armed actors during the war. To this end, some steps have already been taken. The UN Resolution in favor of the creation of an International Commission of Inquiry refers explicitly to the need to recognize the gender dimension of violations and abuses.

Beyond the horizon of the war, the safety of Ukrainian women in their homes relies on the protection offered by State legislation against domestic violence. In this respect, the Ukrainian government has recently taken a few measures in what the international community deems to be the “right direction”. A very important reform taken in the summer of 2021 allows for the military to be prosecuted for domestic violence on a general basis rather than on the basis of the disciplinary statute as it was before. This is especially important in light of the findings of increased risk of domestic violence in families of veterans (Cesur and Sabia, 2016). However, some critical aspects remain. In the current context, a crucial factor might be the limit of 6 months to prosecute the crime from the occurrence of the violence. An extension of such a period at a time when the normal functioning of many institutions is suspended or subject to delays can attenuate the perception of impunity that the exceptionality of the circumstances creates.

When it comes to refugees, there is as mentioned a need for better vetting of private hosts, although the urgency of action that the current circumstances require makes this a particularly challenging task. State effort in this direction has been complemented by civil society initiatives. For example, in Sweden, Facebook groups that lined up to coordinate the offer of housing are now organizing themselves to create a system for verifying housing and hosts.

Ukrainian politicians have also asked Western countries to be prepared to offer expertise on how to support survivors of rape and other sexual violence in conflict.

Other experts recommend reliance on cultural and linguistic mediators to help refugee women access services for victims of IPV that are already offered by local actors in their temporary host country (Conference panel).

In the longer term, guaranteeing economic safety for refugees is also an effective measure to reduce their vulnerability to exploitation from sex-traffickers and criminal organizations.

Finally, yet importantly, the involvement of women in peace negotiation processes should be sought after. Echoing the discussion on women’s scarcity in leadership positions in peacetime, the gender-unequal composition of peace delegations poses an issue of equality, representativeness, and efficiency (Bertrand 2018). Interestingly, it has been noted that a more truthful narrative of war, which recognizes women’s role not only as victims but also as perpetrators (and the converse for men, although proportions are clearly unbalanced in both cases), might help pave the way for higher female representation at negotiation tables (Conference panel). Relatedly, the European Institute for Gender Equality proposes gender mainstreaming of all policies and programs involved in conflict resolution processes (EIGE). The international community should also consider gender mainstreaming of reconstruction programs, to help build a more gender-equal post-conflict Ukraine.

References

Amnesty International. (2020). Not a Private Matter. Domestic and Sexual Violence against Women in Eastern Ukraine.
Baaz, M. E., and Stern, M. (2013). Sexual violence as a weapon of war?: Perceptions, prescriptions, problems in the Congo and beyond. Bloomsbury Publishing.
Bertrand, M. (2018). Coase lecture–the glass ceiling. Economica, 85(338), 205-231.
Cesur, R., and Sabia, J. J. (2016). When war comes home: The effect of combat service on domestic violence. Review of Economics and Statistics, 98(2), 209-225.
Guarnieri, E., and Tur-Prats, A. (2022). Cultural distance and conflict-related sexual violence. Mimeo
Reis, C. (2021). Sexual abuse during humanitarian operations still happens. What must be done to end it. The Conversation, October 5 2021. https://theconversation.com/sexual-abuse-during-humanitarian-operations-still-happens-what-must-be-done-to-end-it-169223
Stark, L. and Ager, A. (2011). A systematic review of prevalence studies of gender-based violence in complex emergencies. Trauma, Violence, & Abuse, 12(3), pp.127-134.
Vu, A., Adam, A., Wirtz, A., Pham, K., Rubenstein, L., Glass, N., Beyrer, C. and Singh, S. (2014). The prevalence of sexual violence among female refugees in complex humanitarian emergencies: a systematic review and meta-analysis. PLoS currents, 6.

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.

Understanding the Economic and Social Context of Gender-based and Domestic Violence in Central and Eastern Europe – Preliminary Survey Evidence

Posted on May 11, 2022 | FROGEE Brief, Policy Brief

20220511 Economic and social context of domestic violence Image 02

This brief presents preliminary findings from a cross-country survey on perceptions and prevalence of domestic and gender-based violence conducted in September 2021 in eight countries: Armenia, Belarus, Georgia, Latvia, Poland, Russia, Sweden and Ukraine. We discuss the design and content of the study and present initial information on selected topics that were covered in the survey. The collected data has been used in three studies presented at the FROGEE Conference on “Economic and Social Context of Domestic Violence” and offers a unique resource to study gender-based violence in the region.

While the COVID-19 pandemic has amplified the academic and policy interest in the causes and consequences of domestic violence, the Russian invasion of Ukraine has tragically reminded us about the gender dimension of war. There is no doubt that a gender lens is a necessary perspective to understand and appreciate the full consequences of these two ongoing crises.

The tragic reason behind the increased attention given to domestic violence during the COVID-19 lockdowns is the substantial evidence that gender-based violence has intensified to such an extent that the United Nations raised the alarm about a “shadow pandemic” of violence against women and girls (UN Women on-line link). Already before the pandemic, one in three women worldwide had experienced physical or sexual violence, usually at the hands of an intimate partner, and this number has only been increasing. The tragic reports from the military invasion of Ukraine concerning violence against women and children, as well as information on the heightened risks faced by war refugees from Ukraine, most of whom are women, should only intensify our efforts to better understand the background behind these processes and study the potential policy solutions to limit them to a minimum in the current and future crises.

The most direct consequences of gender-based and domestic violence – to the physical and mental health of the victims – are clearly of the highest concern and are the leading arguments in favour of interventions aimed at limiting the scale of violence. One should remember though, that the consequences and the related social costs of gender-based and domestic violence are far broader, and need not be caused by direct acts of physical violence. Gender-based and domestic violence can take the form of psychological pressure, limits on individual freedoms, or access to financial resources within households. As research in recent decades demonstrates, such forms of abuse also have significant consequences for the psychological well-being, social status, and professional development of its victims. All these outcomes are associated with not only high individual costs, but also with substantial social and economic costs to our societies.

This policy brief presents an outline of a survey conducted in eight countries aimed at better understanding the socio-economic context of gender-based violence. The survey, developed by the FREE Network of independent research institutes, has a regional focus on Central and Eastern Europe, with Sweden being an interesting benchmark country. The data was collected in September 2021 in Armenia, Belarus, Georgia, Latvia, Poland, Russia, Sweden and Ukraine. The socio-economic situation of all these countries irrevocably changed with the Russian invasion of Ukraine on 24 February 2022, the ongoing war, and its dramatic consequences. The world’s attention focused on the unspeakable violence committed by the Russian forces in Ukraine, the persecution in Belarus and Russia of their own citizens who were protesting against the invasion, and the challenges other neighbouring countries have faced as a result of an unprecedented wave of Ukrainian refugees. This change, on the one hand, calls for a certain distance with which we should judge the survey data and the derived results. On the other hand, the data may serve as a unique resource to support the analysis of the pre-war conditions in these countries with the aim to understand the background driving forces behind this dramatic crisis. In as much as the gender lens is necessary to comprehend the full scale of the consequences of both the COVID-19 pandemic and the war in Ukraine, it will be equally indispensable in the process of post-war development and reconciliation once peace is again restored.

Survey Design, Countries, and Samples

The survey was conducted in eight countries in September 2021 through as a telephone (CATI) survey using the list assisted random digit dialling (LA-RDD) method covering both cell phones and land-lines, and the sampling was carried out in such a way as to make the final sample representative of the respective populations by gender and three age group (18-39; 40-54; 55+). The collected samples varied from 925 to 1000 individuals. The same questionnaire initially prepared as a generic English version was fielded in all eight countries (in the respective national languages). The only deviations from the generic version were related to the education categories and to a set of final questions implemented in Latvia, Russia and Ukraine with a focus on the evaluation of national IPV legislation.

Table 1 presents some basic sample statistics, while Figure 1 shows the unweighted age and gender compositions in each country. The proportion of women in the sample varies between 49.4% in Sweden and 55.0% in Belarus, Russia and Ukraine. The average sample age is between 43 (Armenia) and 51 (Sweden), while the proportion of individuals with higher education is between 29.3% in Belarus and 55.4% in Georgia. The highest proportion of respondents living in rural areas could be found in Armenia at 62.9%, while the lowest was in Georgia at 24.1%. Figure 1 illustrates good coverage across age groups for both men and women.

Table 1. FROGEE Survey: samples and basic demographics

Source: FROGEE Survey on Domestic and Gender-Based Violence.

Figure 1. FROGEE Survey: gender and age distributions

Source: FROGEE Survey on Domestic and Gender-Based Violence.

Socio-economic Conditions and Other Background Characteristics

To be able to examine the relationship between different aspects of domestic and gender-based violence to the socio-economic characteristics of the respondents, an extensive set of questions concerning the demographic composition of their household and their material conditions were asked at the beginning of the interview. These questions included information about partnership history and family structure, the size of the household and living conditions, education and labour market status (of the respondent and his/her partner) and general questions concerning material wellbeing. In Figure 2 we show a summary of two of the latter set of questions – the proportion of men and women who find it difficult or very difficult to make ends meet (Figure 2A) and the proportion who declared that the financial situation of their household deteriorated in the last two years, i.e. since September 2019, which can be used as an indicator of the material consequences of the COVID-19 pandemic. We can see that the difficulties in making ends meet are by far lowest in Sweden, and slightly lower in the other EU countries (Latvia and Poland). The differences are less pronounced with regard to the implication of the pandemic, but also in this case respondents in Sweden seem to have been least affected.

Figure 2. Making ends meet and the consequences of COVID-19

a. Difficulties in making ends meet

b. Material conditions deteriorated since 2019

Source: FROGEE Survey on Domestic and Gender-Based Violence.

Perceptions and Incidence of Domestic and Gender-Based Violence and Abuse

Frequency of differential treatment and abuse

The set of questions concerning domestic and gender-based violence started with an initial module related to the different treatment of men and women, with respondents asked to identify how often they witnessed certain behaviours aimed toward women. The questions covered aspects such as women being treated “with less courtesy than men”, being “called names or insulted for being a woman” and women being “the target of jokes of sexual nature” or receiving “unwanted sexual advances from a man she doesn’t know”, and the respondents were to evaluate if in the last year they have witnessed such behaviours on a scale from never, through rarely, sometimes, often, to very often. We present the proportion of respondents answering “often” or “very often” to two of these questions in Figure 3A (“People have acted as if they think women are not smart”) and 3B (“A woman has been the target of jokes of a sexual nature”). We find significant variation across these two dimensions of differential treatment, and we generally find that women are more sensitive to perceiving such treatment. It is interesting to note that the proportion of women who declared witnessing differential treatment in Sweden is very high in comparison to for example Latvia or Belarus, which, as we shall see below, does not correspond to the proportion of women (and men) witnessing more violent types of behaviour against women.

Figure 3. Frequency of differential treatment (often or very often)

a. People have acted as if they think women are not smart

b. A woman has been the target of jokes of a sexual nature

Source: FROGEE Survey on Domestic and Gender-Based Violence.

Questions on the frequency of witnessing physical abuse were also asked in relation to the scale of witnessed behaviour. Here respondents were once again asked to say how often “in their day-to-day life” they have witnessed specific behaviours. These included such types of abuse as: a woman being “threatened by a man”, “slapped, hit or punched by a man”, or “sexually abused or assaulted by a man”. The proportion of respondents who say that they have witnessed such behaviour with respect to two of the questions from this section are presented in Figure 4. In Figure 4A we show the proportion of men and women who have witnessed a woman being “slapped, hit or punched” (sometimes, often or very often), while in Figure 4B being “touched inappropriately without her consent”. Relative to the perceptions of differential treatment the incidence of a woman being hit or punched (4A) declared by the respondents seems more intuitive when considered against the overall international statistics of gender equality. The proportions are lowest in Sweden and Poland, and highest in Armenia and Ukraine. However, the perception of inappropriate touching by men with respect to women (Figure 4B) shows a similar extent of such actions across all analysed countries.

Figure 4. Frequency of abuse (sometimes, often or very often)

a. A woman has been slapped, hit or punched by a man

b. A woman has been touched inappropriately, without her consent, by a man

Source: FROGEE Survey on Domestic and Gender-Based Violence.

Perceptions of abuse

The questions concerning the scale of witnessed behaviours were complemented by a module related to the evaluation of certain behaviours from the perspective of their classification as abuse and the degree to which certain types of gender-specific behaviours are acceptable. Thus, for example respondents were asked if they consider “beating (one’s partner) causing severe physical harm” to be an example of abuse within a couple (Figure 5A) or if “prohibition to dress as one likes” represents abuse (Figure 5B). This module included an extensive list of behaviours, such as “forced abortion”, “constant humiliation, criticism”, “restriction of access to financial resources”, etc. As we can see in Figure 6, with respect to the clearest types of abuse – such as physical violence – respondents in all countries were pretty much unanimous in declaring such behaviour to represent abuse. With respect to other behaviours the variation in their evaluation across countries is much greater – for example, while nearly all men and women in Sweden consider prohibiting a partner to dress as he/she likes to be abusive (Figure 5B), only about 57% of women and 36% of men in Armenia share this view.

The questionnaire also included questions specifically focused on the perception of intimate partner violence. These asked respondents if they knew about women who in the last three months were “beaten, slapped or threatened physically by their intimate partner”, and the evaluation of how often intimate partners act physically violent towards their wives.

Figure 5. Perceptions of abuse: are these examples of abuse within a couple?

a. Beating causing severe physical harm

b. Prohibition to dress as one likes

Source: FROGEE Survey on Domestic and Gender-Based Violence.

A further evaluation of attitudes towards violent behaviour was done with respect to the relationship between a husband and wife and his right to hit or beat the wife in reaction to certain behaviours. In Figure 6 we show the distribution of responses regarding the justification for beating one’s wife in reaction to her neglect of the children (6A) or burning food (6B). The questions also covered such behaviour as arguing with her husband, going out without telling him, or refusing to have sex. As we can see in Figure 6, once again we find substantial country variation in the proportion of the samples – both men and women – who justify such violent behaviour within couples. This was particularly the case when respondents were asked about justification of violent behaviour in the case of a woman neglecting the children. In Armenia as many as 30% of men and 22% of women agree that physical beating is justified in those cases. These proportions are manyfold greater than what can be observed in countries such as Latvia, where 3% of men and women agreed that abuse was justifiable under these circumstances, or Sweden, where only 1% of men and women agreed.

Figure 6. Perceptions of abuse: is a husband justified in hitting or beating his wife

a. If she neglects the children

b. If she burns the food

Source: FROGEE Survey on Domestic and Gender-Based Violence.

Seeking help and the legal framework

The final part of the questionnaire focused on the evaluation of different reactions to incidents of domestic and gender-based violence. Respondents were first asked if a woman should seek help from various people and institutions if she is beaten by her partner – respondents were asked if she should seek help from the police, relatives or friends, a psychologist, a legal service or if, in such situations, she does not need help. In Figure 7 we show the proportion of people who agreed with the last statement, i.e. claimed that it is only the couple’s business. The proportions of respondents who declare such an attitude is higher among men than women within each country, and is highest among men in Armenia (48%) and Georgia (25%). Again, these proportions are in stark contrast to men in Sweden, or even Poland, where only 4% and 8% of men agreed, respectively. Nevertheless, looking at the total survey sample, a vast majority believe that a woman who is a victim of domestic violence should seek help outside of her home, indicating that at least some forms of institutionalised support for women are popular measures with most people.

Figure 7. Proportions agreeing that domestic violence is only the couple’s business

Source: FROGEE Survey on Domestic and Gender-Based Violence.

The interview also included questions on the need for specific legislation aimed at punishing intimate partner violence and on the existence of such legislation in the respondents’ countries. The latter questions were extended in three countries – Latvia, Russia and Ukraine – to evaluate the specific sets of regulations implemented recently in these countries and to facilitate an analysis of the role IPV legislation can play in reducing violence within households. Legislation on domestic violence is relatively recent. During the last four decades, though, changes accelerated in this respect around the world. Legislative measures have been introduced in many countries, covering different aspects of preventing, protecting against and prosecuting various forms of violence and abuse that might happen within the marriage or the family. Research strives to offer evaluations on what legal provisions are most effective, in a setting in which statistics and information are still far from perfect, and as a consequence of the dearth of strong evidence the public debate on the matter is often lively. For legislation to have an effect on behaviour through shaping the cost of committing a crime, on the one hand, and the benefit of reporting it or seeking help, on the other, or more indirectly through changing norms in society, information and awareness are key. For how can deterrence be achieved if people do not know what the sanctions are? And how can reporting be encouraged if victims do not know their rights? The evidence on legislation awareness is unfortunately quite scarce. A survey of the criminology field (Nagin, 2013) concludes that this is a major knowledge gap.

Figure 8 shows the proportions of answers to questions concerning the need for and existence of legislation specifically targeted towards intimate partner violence. We can see that while support for such legislation is quite high (Figure 8A), it is generally lower among men (in particular in Armenia, Russia and Belarus). Awareness of existence of such laws, on the other hand, is much lower, and it is particularly low among women. It should be pointed out that all countries have in fact implemented provisions against domestic violence in their criminal code, but only around half of the population, sometimes much fewer, are aware of that.

Figure 8. Need for and awareness of IPV legislation

a. State should have specific legislation aimed at punishing IPV

b. Country has specific legislation aimed at punishing intimate partner violence

Source: FROGEE Survey on Domestic and Gender-Based Violence.

Recent reforms of DV legislation that were implemented in Russia in 2017, in Ukraine in 2019 and in Latvia just a few months ago (at the time of the survey, the changes were at the stage of a proposal) were the subject of the final survey questions in these countries. We find that awareness of these recent reforms is very low in all three countries, and knowledge about the reform content (gauged with the help of a multiple-choice question with three alternative statements) is even lower. Our analysis suggests that gender and family situation are the two factors that most robustly predict support for legislation, while education and age are associated with awareness and knowledge of the reforms. Minority Russian speakers are less aware of the reforms in both Ukraine and Latvia, in Ukraine are also less likely to answer correctly about the content of the reform, and in Latvia are less supportive of DV legislation in general.

Analyses of this type are useful for policy design, to better understand which groups lack relevant knowledge and should be targeted by, for example, information campaigns to combat DV, such as those many governments around the world implemented during the covid-19 pandemic.

Future Work Based on the Survey

The above is just a small sample of the rich source of information that has resulted from conducting the survey. Already from this simple overview we can see some interesting results. There are, for example, clear differences between men and women in perceptions of how common certain types of abusive behaviour are. However, for many questions differences between countries are larger than those between men and women within a country. Interestingly such differences are also different depending on the severity of the abuse or violence. In Sweden the perception of women being victims of less violent abuse is higher than in some other countries where instead some more violent types of abuse are reported as being more common. This could, of course, be due to actual differences in actual events but it is also possible that there are differences in what types of behaviour are considered to represent harassment and abuse in different societies. More careful data work is needed to try to answer questions like this and many others. Currently there are a number of ongoing research projects based on the survey results, three of which will be presented at the FREE-network conference on “Economic and Social Context of Domestic Violence” in Stockholm on May 11, 2022. Our hope is that this work will help in taking actions to prevent gender-based abuse and domestic violence based on a better understanding of underlying cross-country differences in social norms and attitudes and their relation to socio-economic factors.

About FROGEE Policy Briefs

FROGEE Policy Briefs is a special series aimed at providing overviews and the popularization of economic research related to gender equality issues. Debates around policies related to gender equality are often highly politicized. We believe that using arguments derived from the most up to date research-based knowledge would help us build a more fruitful discussion of policy proposals and in the end achieve better outcomes.

The aim of the briefs is to improve the understanding of research-based arguments and their implications, by covering the key theories and the most important findings in areas of special interest to the current debate. The briefs start with short general overviews of a given theme, which are followed by a presentation of country-specific contexts, specific policy challenges, implemented reforms and a discussion of other policy options.

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.

Social Norms, Conspiracy Theories and Vaccine Scepticism: A Snapshot from the First Year of the Covid-19 Pandemic in Poland

Posted on April 19, 2022 | FROGEE Brief, Policy Papers

20220419 Social Norms and Vaccine Scepticism Image 05

In January 2022, Poland experienced the highest rate of SARS-CoV-2 transmission since the beginning of the COVID-19 pandemic. Considering the widespread consensus among experts about the efficacy of vaccines in preventing hospitalisation and death resulting from the virus, low vaccination rates and widespread anti-vaccine sentiments in Poland are of great concern. We use data from the DIAGNOZA+ Survey to demonstrate the relationship between various demographic characteristics, opinions around certain gender norms, the propensity for conspiratorial thinking, concern about the pandemic, and vaccine scepticism. While controlling for exogenous demographic characteristics, we measure the strength of the relationship between various beliefs that people hold and how they feel about the COVID-19 vaccine. Our analysis indicates that while respondents who hold more traditional views on gender roles are 6 percentage points less likely to get vaccinated, those who agree with a variety of conspiratorial statements are 43 percentage points less likely to vaccinate against COVID-19.

Introduction

As of January 2022, Europe finds itself well into the 4^th wave of the COVID-19 pandemic, with some countries, including Poland, experiencing the highest rates of transmission since the virus was first detected. There are a few tools available to policymakers and healthcare professionals for combating the spread of the virus, ranging from preventative measures to strict social lockdowns aimed at reducing interpersonal interaction. A comprehensive literature review of 72 academic studies conducted by the BMJ found that the implementation of preventative measures such as hand washing, mask wearing, and social distancing decreased the risk of transmission by 53% (Talic et al., 2021). But even though such measures reduce transmission, the shortcomings in adherence and enforcement make high vaccination rates much more effective in diminishing the risk of hospitalization and death (Moline et al., 2021). With a consensus among experts reaffirming the effectiveness of vaccines in minimising the more severe cases of COVID-19 illness, the widespread availability of the vaccine has become the most effective and cost-efficient tool in limiting morbidity while avoiding future instances of economically unsustainable lockdowns. The drawbacks of the alternative scenario have already been made evident in 2020, before the development and distribution of COVID-19 vaccines. Over the course of the year, hospital capacities were overwhelmed in many countries around the world, leading to significant spikes in excess deaths. Poland saw an increase of over 18% in all-cause mortality in 2020 (OECD, 2021), the fourth-highest in the OECD and second-highest in the European Union (Eurostat, 2021).

Considering the central role that prevalent vaccination plays in combating the impact of COVID-19, it is important to understand the underlying factors and demographic characteristics of individuals who are driving the low vaccination rates in countries such as Poland. With this in mind, we use an online survey: DIAGNOZA+ (DIAGNOZA Plus, 2020-2021), conducted on a representative sample of adults in Poland throughout the pandemic, allowing for the identification of characteristics that are most strongly correlated with vaccine scepticism. This kind of analysis can provide useful indicators for the targeting of certain policies and information campaigns that encourage vaccinations, and thereby suppress future outbreaks of SARS-CoV-2, as well as any other future pandemics. Below, we first outline the key features of the DIAGNOZA+ data, describe the methodology adopted in this study, and present results on the relationship between key demographic characteristics, social norms, views of respondents, and attitudes towards COVID-19 vaccination. We show a strong correlation between traditional family values, conspiratorial views, and reservations relating to the vaccination programme. Having traditional family values (expressed by about 40% of the sample) is associated with an over 10 percentage point (p.p.) lower probability to declare a willingness to get vaccinated. This drops to about 6 p.p. when we extend the model to account for conspiratorial thinking, which strongly dominates the relationship. Individuals who express strong conspiratorial and anti-establishment views (about a quarter of the sample), conditional on other demographic characteristics, were more than 40 p.p. less likely to declare a willingness to get vaccinated.

Methodology

The following analysis is based on data from DIAGNOZA+, an online survey collected in seven waves over the course of the COVID-19 pandemic (DIAGNOZA Plus, 2020-2021). The panel survey was conducted with the purpose of assessing changes in the labour market situation of adults in Poland between April 2020 and July 2021. The survey consistently included standard questions on individual and household characteristics such as age, gender and education, as well as questions on as well as questions about the respondent’s labor market status, hours worked, and financial situation. Waves 3 and 4 included additional modules where respondents were asked to express their opinions on a variety of statements surrounding gender norms such as “In general, fathers are as well suited to look after their children as mothers”, “A pre-school child is likely to suffer if his or her mother works” and “When jobs are scarce, men should have more right to a job than women”. The questions were answered on a scale of 1 (strongly agree) to 4 (strongly disagree). For the analysis, these categorical variables are dichotomised, with a value of 1 assigned to responses 1 and 2 (strongly agree or agree) and a value of 0 assigned to responses 3 and 4 (disagree or strongly disagree). Thus, for each question, we develop a binary variable that categorises respondents as either having a progressive or traditional reaction to each particular gender norms statement.

In consecutive waves, the same respondents were asked questions surrounding their willingness to vaccinate against the virus (in wave 5) and their trust in experts and the government response to the COVID-19 pandemic (in wave 6). For this analysis, we select questions that may influence an individual’s likelihood to vaccinate, starting with their level of concern about the pandemic or their fear of the virus itself. Furthermore, we identify individuals with a high predisposition for conspiratorial beliefs based on information from wave 6. Each variable included in this module is converted into a binary measure of agreement or disagreement, as outlined above for the social norms questions. We consider seven statements from the survey related to conspiratorial views, including “Secret organisations influence political decisions” or “I trust my intuition more than the so-called experts” (see the full list of statements in Figure 2). For each of them, the variable is converted into a binary measure of agreement or disagreement, similarly to the social norms questions above. Those who agreed or strongly agreed with all seven statements are classified as having conspiratorial views.

Due to sample attrition and after dropping respondents who did not answer one (or more) of the questions needed for our analysis, the sample reduces to 726 individuals (see table A1 in the Annex). Although each wave of the DIAGNOZA+ survey is carefully weighted to ensure population representativeness of the survey, these cross-sectional weights are only relevant to each independent wave of the survey. Therefore, for our sample, we develop frequency weights by sex and age using population data from Statistics Poland (Statistics Poland, 2021), which are utilised throughout the analysis. Given the low number of participants in the oldest age groups (those above 60 years old), we limit the sample to individuals aged between 21 and 60. Unfortunately, calibrating the weights according to additional characteristics such as education and municipal population is not feasible with a sample of this size. Clearly, the requirement of consistent consecutive participation in at least three waves of the survey has implications for its representativeness. For example, after the sample of respondents that participated in wave 6 is cut to include only those who also participated in waves 3, 4 and 5, we observe a bias in favour of conspiratorial views among the remaining observations, indicating that individuals who hold these views were more likely to continue their participation in the survey. For example, while 18.1% of the total cross-sectional sample of individuals in wave 6 hold conspiratorial views, the proportion is 23.4% in the sample we analyse (falling slightly to 23.2% when weights are applied). From this perspective, while indicative of existing correlations, the results ought to be treated with some caution.

Limiting the sample to respondents who answered all sets of questions across several rounds of the survey allows us to study vaccine scepticism and respondents’ susceptibility to conspiracy theories in relation to a number of personal characteristics. Furthermore, we consider the relationship between a respondent’s attitudes towards certain social norms (asked in waves 3 and 4), their individual response to COVID-19 (asked in wave 5), and their trust in the government’s response to the pandemic (asked in wave 6). We begin the analysis by assessing the relationship between respondents’ demographic characteristics and their opinions on gender roles, their propensity to hold conspiratorial beliefs, and their concern about the pandemic. This is followed by two models measuring respondents’ willingness to vaccinate. In the first of these models, demographic characteristics and traditional family values are used as explanatory variables, while in the second model conspiratorial views are included as well. Finally, we conclude with a summary of results and policy considerations.

Survey Results

Traditional Family Values in Poland

The respondents of the DIAGNOZA+ survey vary, on average, in the ‘traditionality’ of their attitudes towards gender and family depending on the selected indicator. The shares of answers to the three questions about gender norms are presented in Figure 1. The results demonstrate that progressive views on gender norms in Poland were more common in relation to the workplace than the home and family. For example, the statement to which most respondents were opposed was “When jobs are scarce, men have more right to a job than women”, with 37.2% of respondents disagreeing and 50.3% of respondents strongly disagreeing. On the other hand, slightly fewer respondents disagreed (50.5%) or strongly disagreed (34.8%) with “In general, fathers are not as well suited to look after their children as mothers”. Finally, respondents were most ‘traditional’ in their views in reaction to the statement “A pre-school child is likely to suffer if his or her mother works”, with 28% agreeing and 10% strongly agreeing. There is a natural correlation between these different views, and in our analysis, we examine the significance of different combinations of the three indicators. Given the relatively small sample, only the last indicator proved to be significantly related to our main outcome of interest and we use this one to represent the view on the ‘progressive-traditional’ spectrum

Figure 1. Gender norms in the survey sample

Source: DIAGNOZA+ survey, waves 3 and 4. Note: Data weighted using weights generated from Statistics Poland’s data on population by sex and age. Sample limited to individuals aged 21-60. The statement “In general, fathers are as well suited to look after their children as mothers” from the questionnaire was adjusted in the graph for better readability.

Conspiratorial Views

In wave 6 of the DIAGNOZA+ survey respondents were asked seven different questions relating to trust in government, politicians, media, and the recommendations of experts. As shown in Figure 2, for five out of the seven statements, a majority of respondents agreed or strongly agreed that the government or media are dishonest, intentionally share misinformation, or have ulterior motives. Nearly three quarters of respondents agreed that “politicians and the media deliberately hide certain information”. This result supports data published by the OECD in 2020 showing that, out of the 38 member countries, Poland had the second-lowest trust in government, with only 27.3% of the population expressing confidence (OECD, 2022). However, the DIAGNOZA+ survey goes further to find that nearly half of respondents in our sample reported that they trust their own intuitions more than the experts during the pandemic, while the least widespread belief out of the seven was that “secret organisations influence political decisions”. Still, even this statement, which suggests deep-seeded nefarious behaviour behind the scenes of government, found 39.8% of respondents to be in agreement. Note that we aim to identify individuals who have a general propensity for conspiratorial thinking, rather than those who simply find some of the statements particularly compelling. To this end, we only categorise those respondents who agreed with all seven statements as having a high propensity for conspiratorial thinking, which was the case for 23.2% of our sample after reweighting.

Figure 2. Conspiratorial beliefs and trust in authority

Source: DIAGNOZA+ survey, wave 6. Note: Data weighted using weights generated from Statistics Poland’s data on population by sex and age. Sample limited to individuals aged 21-60.

Analysis

Table 1 presents regression results on the relationship between specific beliefs reported in the different waves of the survey and a number of individual characteristics. We show these results for three dependent variables: traditional family values, as defined by the opinion that a pre-school child is likely to suffer if his or her mother works; propensity for conspiratorial views, which identifies the respondents that agreed with all seven statements presented in Figure 2; and concern about the pandemic, a binary variable that identifies individuals who expressed great worry or fear about the pandemic. The results indicate that parents who live with their children are 10.1 p.p. more likely to hold traditional family values. After controlling for age, gender and education, living in a small town or village is associated with a 10.9 p.p higher probability of ascribing to more traditional gender norms, while individuals holding a tertiary degree are 18 p.p. less likely to agree that “a pre-school child is likely to suffer if his or her mother works” compared to those with primary education. Interestingly, neither age nor gender significantly correlates with family values, suggesting that the DIAGNOZA+ survey did not capture an intergenerational or gender-driven divide on these issues. This might relate to the online nature of the survey and the implied sample selection, in particular among older individuals.

Table 1. Regression results on views and attitudes

Standard errors in parentheses. * p < 0.1, ** p < 0.05, *** p < 0.01. Note: Data weighted using weights generated from Statistics Poland’s data on population by sex and age. Sample limited to individuals aged 21-60. Estimates using the linear probability model.

The results presented in Table 1 also demonstrate a relationship between some demographic characteristics and the likelihood to hold conspiratorial views (as defined by expressing agreement to the seven related statements in wave 6). A number of characteristics strongly correlate with conspiratorial thinking: being a parent living with their children aged 0-17, and living in small cities, towns and villages. Each of these characteristics is associated with a higher probability of believing in secret organisations and mistrusting experts. A number of characteristics strongly correlate with conspiratorial thinking: holding such views are 9.3 p.p. more likely among parents living with their underaged children and 10 p.p. more likely among individuals living in smaller towns or villages compared to those living in cities of over 500 thousand inhabitants. Higher education is strongly negatively correlated with the likelihood of holding conspiratorial views – those with tertiary education are 14.5 p.p. less likely to have these views compared to individuals with primary education.

One simple explanation for the increased vaccination rates among certain demographic groups in Poland could be that some segments of the population are more worried about the virus, and thus choose to take greater precautions. The analysis presented in Table 1 demonstrates that people were increasingly likely to be concerned about the pandemic in higher age groups. When asked “To what extent are you concerned about the COVID-19 pandemic?”, the probability of expressing serious concern increases progressively with age. This is an intuitive result considering the strong relationship between age and the severity of COVID-19 symptoms and the associated risk of mortality (CDC, 2021). Respondents aged between 31 and 40 were 10 p.p. more likely to report being very concerned or frightened than respondents between the age of 21 and 30, while in the age groups 41-50 (12.6 p.p.) and 51-60 (21.4 p.p.) the probability was even higher. There is also a weak but positive correlation (7.7 and 8.6 p.p.) between living in a city with a population of 10,000 to 500,000 inhabitants and expressing fear about the pandemic, as compared to respondents who lived in cities with a population of more than 500,000 people. The relationships between the remaining demographic characteristics and the probability of being seriously concerned about the pandemic are not statistically significant. Below, we use this data to examine the link between people’s beliefs and the likelihood of getting vaccinated.

Vaccine Scepticism, Demographic Characteristics and Conspiratorial Views

In light of the widespread scientific consensus on the safety and effectiveness of COVID-19 vaccines, low vaccination rates in Poland are difficult to explain. In this section, we analyse to which extent they may be driven by the underlying beliefs, on top of the socio-demographic characteristics. Overall, 54% of respondents in the selected sample from the DIAGNOZA+ survey planned to be or had already been vaccinated. Thus, the survey sample closely reflects the actual proportion of the population that was fully vaccinated in Poland as of January 2022. (ECDC, 2022). In Model A of Table 2, we present the relationship between the response to the question “Do you plan to get vaccinated against COVID-19 or are you already vaccinated?” and traditional family values, alongside the usual demographic characteristics. We find that those in the 51-60 age group were 14.5 p.p. more likely to plan to vaccinate than those aged between 21 and 30. This also reflects the higher level of concern about the virus expressed by those over the age of 50, as presented in Table 1, and the risk of serious illness associated with increasing age. However, the relationship between age and the probability of vaccination was much weaker than the relationship between age and the probability of expressing general concern about the pandemic, implying that concern does not translate directly into a willingness to vaccinate. We also find that tertiary education has a particularly strong effect, and respondents who have a university degree were much more likely (17.7 p.p.) to get vaccinated than those with less than secondary education.

Through this analysis we also discover several less intuitive relationships between individual characteristics and the propensity to vaccinate. We find that women are 11.5 p.p. less likely to plan to vaccinate against COVID-19 than men. Moreover, individuals living in a city with less than 500,000 inhabitants were much less likely to vaccinate, with the strongest correlation (-23.5 p.p.) observed for respondents living in medium-sized cities of 100,000 to 500,000 people. However, a strong relationship can also be seen for smaller cities of 10,000 to 100,000 inhabitants (-19.3 p.p.) and small towns and villages (-17.2 p.p.). Respondents’ expressions of traditional family values are also a strong predictor of their propensity to vaccinate. After controlling for gender, age, education and municipality size, those categorised as holding traditional views are 10.6 p.p. less likely to plan to vaccinate against COVID-19. Our findings demonstrate that while population density, education, age and gender, are all strong indicators of vaccine scepticism in Poland, so is the degree of traditionalism in people’s beliefs.

Table 2. Regression results on vaccination: probability of being vaccinated or planning to get vaccinated

A commonly cited explanatory factor for vaccine scepticism is the susceptibility to conspiratorial beliefs, as well as scepticism towards information disseminated by figures of authority (Hornsey et al., 2018). Thus, in Model B, we seek to identify a relationship between conspiratorial beliefs and scepticism towards the COVID-19 vaccine in Poland. When adding to our model a binary indicator for agreement with all seven of the conspiratorial statements included in the survey, we find that those who agreed across the board were 43.3 p.p. less likely to get vaccinated. Therefore, it seems that the propensity for conspiratorial thinking is a very strong correlate of willingness to vaccinate, and the characteristic most strongly associated with vaccine scepticism. The impact of the demographic factors goes in the same direction for both models, although the scale diminishes in Model B after controlling for conspiratorial views, reflecting the higher propensity of older individuals to hold such views. Furthermore, the effect of traditional family values is much weaker in Model B, suggesting a positive correlation between traditional family values and conspiratorial beliefs (Figure A1 in the Annex shows how values and views in the analysis views overlap with each other). This is in line with past research that ties traditional moral values and conservatism with conspiratorial beliefs, both before and during the COVID-19 pandemic (Pennycook et al., 2020; Romer and Jamieson, 2021).

One explanation for the strong relationship between conspiratorial beliefs and vaccine scepticism could be that respondents who do not trust the media and figures of authority believe that the dangers of the pandemic have been exaggerated and would thus not be concerned about its consequences. We account for this possibility in Model C by including the indicator for fear of the pandemic. We find that those who are very concerned or frightened are 21.1 p.p. more likely to vaccinate than those who are not. However, including this variable in the model has little effect on the estimates of the relationship between traditional gender views or conspiratorial thinking and the likelihood to vaccinate. Further research is needed to understand what is driving these relationships in this particular context. These findings demonstrate that while individuals that believe in conspiracies are the most susceptible to vaccine scepticism, other elements such as fear of the pandemic, education attainment, and where people live play an important role as well.

Conclusion

By January 2022 most European countries have reached a plateau in their vaccination rates, with free vaccines readily available since the summer months of 2021 to all those who are willing to take them. Not only have the high rates of hospital admissions among the non-vaccinated population proven the epidemiological models about the efficacy of vaccines in reducing hospitalisation and death to be true (a study in the United States showed a more than tenfold reduction in the risk of each measure; Scobie et al., 2021), but disparities between countries in the proportion of the population that is vaccinated have created a natural experiment that further substantiates this hypothesis. Poland, a country with a vaccination rate that is 15 p.p. lower than neighbouring Germany, had virtually the same number of cases per 100,000 people in the first two weeks of December, but almost threefold the number of deaths from COVID-19 (ECDC, 2021). Due to the burden COVID-19 related hospitalisations place on healthcare systems, the issues arising from the significant scale of vaccine scepticism are not only related to physical well-being, but also directly impact economic and fiscal stability.

Despite a fairly small sample size available for our analysis from the DIAGNOZA+ survey, a number of important correlations are identified in this study. We find that people living in cities and towns smaller than 500,000 people are less likely to vaccinate than those living in big cities. We show that women, those with less than secondary education, and young people are less likely to be vaccinated. Moreover, those believing that pre-school-aged children suffer when their mothers work are less likely to vaccinate compared to those with more progressive gender views. The most significant predictor of vaccine scepticism, however, is whether a respondent expressed low trust in authority and belief in the conspiracy theories presented in the survey, which was the case for 23.2% of the sample. These individuals are more than 40 p.p. less likely to express willingness to get vaccinated than the rest of the population. This suggests that the low rate of vaccination in Poland can, in part, be attributed to widespread distrust of government, the media, and scientific experts. Poland has already suffered the consequences of the high magnitude of anti-vaccine sentiments in the population, with the severity of the fourth wave of COVID-19 being one of the harshest in Europe (ECDC, 2021). If the government intends to prevent future outbreaks and protect the healthcare system and the economy, it must present a consistent, clear, and transparent message about the safety and efficiency of vaccines to minimise the misinformation that is driving vaccine scepticism among certain demographic groups.

References

Centers for Disease Control and Prevention, (2021). Hospitalization and Death by Age.
DIAGNOZA Plus, (2021). https://diagnoza.plus/
European Centre for Disease Prevention and Control, (2021). Data on 14-day notification rate of new COVID-19 cases and deaths
Eurostat, (2021). Excess mortality by month.
Hornsey, M., Harris, E., &. Fielding, K., (2018). “The psychological roots of anti-vaccination attitudes:
A 24-nation investigation”, American Psychological Association.
Moline H. et al., (2021). “Effectiveness of COVID-19 Vaccines in Preventing Hospitalization Among Adults Aged ≥65 Years – COVID-NET, 13 States, February-April 2021”, Morbidity and Mortality Weekly Report.
Organisation for Economic Co-operation and Development, (2021). “The impact of COVID-19 on health and health systems”.
Organisation for Economic Co-operation and Development, (2022). “Trust in Government, OECD data”.
Pennycook, G., Cheyne J.A., Koehler, D., & Fugelsang, J.(2020). “On the belief that beliefs should change according to evidence: Implications for conspiratorial, moral, paranormal, political, religious, and science beliefs”, Judgement and Decision Making
Romer D. & Jamieson K. H., (2021). “Conspiratorial thinking, selective exposure to conservative media, and response to COVID-19 in the US”, Social Science & Medicine
Scobie H. et al., (2021). “Monitoring Incidence of COVID-19 Cases, Hospitalizations, and Deaths, by Vaccination Status — 13 U.S. Jurisdictions, April 4–July 17, 2021”, Morbidity and Mortality Weekly Report.
Statistics Poland, (2021). “Demographic Yearbook of Poland 2021”.
Talic S. et al., (2021). “Effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality: systematic review and meta-analysis”, The BMJ.

Annex is available in the PDF version.

Disclaimer

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

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

Posted on April 11, 2022 | Policy Papers

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.
Sostero, Matteo; Milasi, Santo; Hurley, John; Fernancez Macias, Enrique; and Martina Bisello, 2020. “Teleworkability and the COVID-19 crisis: a new digital divide?”, JRC Working Papers Series on Labour, Education and Technology, 2020/05.
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.
UN Women, 2020. “Rapid Gender Assessment of the Covid-19 Situation in Georgia”.
UN Women, 2021. “Women’s Entrepreneurship Expo 2021 report”.
UNIDO, 2020. “Assessment of the impact of Covid-19 outbreak on Women and youth entrepreneurs in the manufacturing sector and manufacturing-related services.

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

Female Entrepreneurs in Transition: Social Norms, Double Burden and the Next Generation

Posted on December 6, 2021 | Policy Brief

Photo Of People Doing Handshakes representing Belarusian higher education

Nowadays, it is evident that equal participation of both men and women in entrepreneurial activity can boost the world economy, create more diverse teams, and decrease social inequality. While the subject of women-led enterprises is widely discussed and explored, the portraits of women who stand behind these companies are still not complete. This brief focuses on the social aspects a businesswoman faces in a transition economy such as Belarus: Who is she? What are her social roles? And how do entrepreneurial families differ from average families in Belarus?

Introduction

Female entrepreneurship is widely discussed as one of the potential engines of sustainable economic growth (World Bank, 2018; IFC, 2017). This brief utilizes a recent wave of the Global Entrepreneurship Monitor survey to shed light on the key aspects of female entrepreneurship in Belarus – a transition economy with a relatively short history of private entrepreneurship. It looks at the social status and social norms surrounding female businesses to better understand the current situation and future trends in this part of Belarusian society.

The data for the analysis is provided by the Global Entrepreneurship Monitor (GEM) surveys conducted in the summer of 2019:

Survey of the adult population of Belarus (GEM APS): 2002 respondents aged 18 to 64.
Survey of entrepreneurs based on GEM APS: 208 business owners (107 men and 101 women).

Women Are More Willing to Study Hard

Following a long-standing tradition, women in Belarus are likely to obtain higher education. Based on the GEM surveys of the adult population, 35% of respondents have completed a bachelor’s degree (42% of women versus 27% of men) and 1.5% have completed a master’s degree. Among entrepreneurs, 60% of respondents have the first stage of higher education and 15% have the second stage. While most of the interviewed entrepreneurs have higher education (bachelor’s degree), women are more inclined to continue their studies: 19% of female and 11% of male entrepreneurs choose to enroll in master’s programs.

Access to business education is not a problem in Belarus: almost half of the respondents claim that their education is related to the business they run. A similar fraction also report participating in business training programs (with no significant gender differences). A third of respondents report having had a mentor who helped them start a business (42% and 58% of men and women, respectively). Entrepreneurs in Belarus are not inclined to be members of business associations or (in)formal self-support groups for entrepreneurs.

Are Female Entrepreneur Families More Equal?

Most often, an entrepreneur is married and has 1-2 children under 18 years old (this pattern being the same across genders). The majority of Belarusian families are of the so-called “Soviet” type, in which the most important woman’s role is to be a mother and “keep home”. At the same time, it is perfectly normal for women to have a paid job. In the case of preparing food, cleaning the house, and washing clothes, a comparable share of male entrepreneurs and men in the general population answer that most of these responsibilities are usually carried by women (65-68%). In contrast, half of the female entrepreneurs report having an equal distribution of these household duties [Figure 1]. We observe similar patterns in the caretaking of children: 68% of women entrepreneurs claim to have an equal distribution versus 44% of non-business women. This greater intra-family equality of women-entrepreneurs can be partially explained by the fact that businesswomen earn more than Belarusian women do on average.

Figure 1. How do you and your spouse/partner divide the task of cleaning the house and washing clothes?

Source: based on GEM APS 2019

According to data on the daily time use of the population collected by the National Statistics Committee for 2014-2015, women spend twice as much time as men on housekeeping and childcare. But, surprisingly, only 40-45% of women note that the traditional distribution of social roles in the family imposes an unfair constraint on women’s work and career possibilities. Therefore, we document a trend towards equal relations between spouses in households where the wife is an entrepreneur. At the same time, even a typical businesswoman bears a large burden of unpaid work.

A Successful Woman is a Happy Mother and a Wife

The respondents were asked a rather controversial question of what defines a “successful woman” [Figure 2]. Both entrepreneurs and the general population of Belarus were in solidarity in understanding a successful woman primarily as a happy wife and mother (75% of respondents). In second place, in terms of importance, respondents answered that a woman should be an educated and highly qualified professional (about 50% men and 60% women). Only 23% of male and 42% of female entrepreneurs agreed with the statement that a successful woman is, first of all, a successful entrepreneur. Remarkably, 46% of men in the general population survey completely or to a greater extent disagree with this statement, at the same time, 67% of those with children would like their daughter to run a business.

Figure 2. A successful woman is first of all a/an..

Source: Author’s calculations based on GEM APS 2019

Parental Entrepreneurship or Are There Any Predispositions to Become an Entrepreneur?

According to the research on parental entrepreneurship, the probability that children in entrepreneurial families will also have a career in business is 30-200% above that of children from non-entrepreneurial families (Lindquist et al., 2015). In the case of Belarus, half of the surveyed entrepreneurs indicated that their fathers were employees, while 5-10% and 17-25% reported having fathers in business and leadership positions. By comparison, out of the 2000 respondents in the general population survey, 4-8% and 14-15% reported having fathers in business and leadership positions, respectively. As the difference is not very significant, parental entrepreneurship cannot play a decisive role in becoming an entrepreneur. This fact can be explained by the relative juvenility of Belarussian businesses, the absence of entrepreneurship in the USSR, and the attitude of society towards entrepreneurship in the 90s.

Nevertheless, the Belarusian business environment is changing as well as the social attitude. Among the 2000 respondents in the general population survey, about 68% would like their daughter to own a business, and 82% want such a future for their son. Among entrepreneurs, aspirations about their children’s future are rather predictable: a third of respondents do not make plans for their children and the majority of the remaining want their children to run their own business. Moreover, among those having preferences for their children’s future, both male and female entrepreneurs reached almost 100% consensus regarding their sons. When it comes to their daughters, 95% of women and 80% of men prefer a future in business while 15% of men would like to see their daughter become a homemaker.

Conclusion

Several key findings can be noted when comparing women entrepreneurs in Belarus with those who are not in business. Entrepreneurs are more likely to obtain higher education, both first and second stage; household chores more equally shared in families with women entrepreneurs. Female entrepreneurs more often want a future in business for their children, especially their daughters. Based on the above, it can be expected that a greater involvement of women in business can positively affect the state of gender equality in Belarus and the quality of human capital.

Nowadays, the promotion of entrepreneurship (let alone female entrepreneurship) is not a priority of the current Belarusian government, and independent development actors, who used to support it in the past, are out of the country. For the future, however, I will outline some general recommendations for developing female entrepreneurship (based on Akulava et al., 2020). With regard to education, the popularization of STEM programs among women can positively affect female involvement in entrepreneurial activity. Additionally, promoting examples of successful women-led enterprises will help combat stereotypes and inspire women to venture into entrepreneurship. Last but not least, an equal division of domestic responsibilities will allow women to spend more time on their careers.

References

Aginskaya, Hanna; and Maryia Akulava, 2018. “Women Entrepreneurs in Belarus: Characteristics, Barriers and Drivers“, Free Network.
Akulava, Maryia; Myck, Michal; and Jesper Roine, 2020. “Transition and Beyond: Women on the Labour Market in the Context of Changing Social Norms“, Free Network FROGEE.
Belstat, 2015. „How do we use our time“, Statistical bulletin, National Statistical Committee of the Republic of Belarus (in Russian).
IFC, 2020. “Women’s entrepreneurship in Belarus”.
IFC, 2017. “Investing in Women: New Evidence for The Business Case”.
Lindquist, Matthew J.; Sol, Joeri; and Mirjam Van Praag, 2015. “Why Do Entrepreneurial Parents Have Entrepreneurial Children?”, Journal of Labor Economics, Vol. 33, No. 2 (April 2015), pp. 269-296.
World Bank, 2018. “An Operational Guide to Women’s Entrepreneurship Programs in The World Bank”.

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

Posted on November 3, 2021 | Policy Brief

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.

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

Posted on September 28, 2021 | Policy Papers

20210928 Female Representativeness and Covid-19 Policy Responses Image 01

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

Introduction

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

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

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

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

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

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

Covid-19 Policy Measurements

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

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

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

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

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

Figure 1. Stringency Index

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

Figure 2. Economic support index.

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

Figure 3. Containment & health index.

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

Female Representativeness: Layers and Indicators

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Discussion and Conclusions

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

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

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

References

Abrams, B. A., & Settle, R. F. (1999). Women’s suffrage and the growth of the welfare state. Public Choice, 100(3), 289-300.
Acker, J. (1992). From sex roles to gendered institutions. Contemporary sociology, 21(5), 565-569.
Aidt, T. S., & Dallal, B. (2008). Female voting power: the contribution of women’s suffrage to the growth of social spending in Western Europe (1869–1960). Public Choice, 134(3), 391-417.
Andersen, A. L., Hansen, E. T., Johannesen, N., & Sheridan, A. (2020). Pandemic, shutdown and consumer spending: Lessons from Scandinavian policy responses to Covid-19. arXiv preprint arXiv:2005.04630.
Bagues, M., & Campa, P. (2021). Can gender quotas in candidate lists empower women? Evidence from a regression discontinuity design. Journal of Public Economics, 194, 104315.
Ball, C. (2009). What Is Transparency? Public Integrity 11 (4): 293–308. doi:10.2753/PIN1099-9922110400.
Besley, T., & Coate, S. (1997). An economic model of representative democracy. The Quarterly Journal of Economics, 112(1), 85-114.
Besley, T., & Case, A. (2003). Political institutions and policy choices: evidence from the United States. Journal of Economic Literature, 41(1), 7-73.
Besley, T., Folke, O., Persson, T., & Rickne, J. (2017). Gender quotas and the crisis of the mediocre man: Theory and evidence from Sweden. American economic review, 107(8), 2204-42.
Borrelli, M. A. (2002). The first lady as formal advisor to the president. Women & Politics 24 (1), 25–45.
Brodeur, A., Gray, D., Islam, A., & Bhuiyan, S. (2020). A literature review of the economics of Covid-19. Journal of Economic Surveys.
Chappell, L., & Waylen, G. (2013). Gender and the hidden life of institutions. Public Administration, 91(3), 599-615.
Chappell, L. (2010). Comparative gender and institutions: Directions for research. Perspectives on Politics, 183-189.
Chattopadhyay, R., & Duflo, E. (2004). Women as policy makers: Evidence from a randomized policy experiment in India. Econometrica, 72(5), 1409-1443.
Coibion, O., Gorodnichenko, Y., & Weber, M. (2020). The cost of the Covid-19 crisis: Lockdowns, macroeconomic expectations, and consumer spending (No. w27141). National Bureau of Economic Research.
Davis, R. H. (1997). Women and power in parliamentary democracies: Cabinet appointments in Western Europe, 1968-1992, Volume 2. U of Nebraska Press.
Dixit, A. K. (2011). Lawlessness and economics. Princeton University Press.
Eagly, A. and M. Crowley (1986, November). Gender and helping behavior. a meta-analytic review of the social psychological literature.
Eagly, A. H., & Karau, S. J. (2002). Role congruity theory of prejudice toward female leaders. Psychological review, 109(3), 573.
Eagly, A. H., & Johannesen‐Schmidt, M. C. (2001). The leadership styles of women and men. Journal of social issues, 57(4), 781-797.
Eagly, A. H. (1987). Reporting sex differences. Eckel, C. and P. Grossman (1998). Are women less selfish than men? evidence from dictator experiments. Economic Journal 108 (448), 726–35.
Easterly, W. (2008). Institutions: Top down or bottom up?. American Economic Review, 98(2), 95-99.
Elson, D. (1999). Labor markets as gendered institutions: equality, efficiency and empowerment issues. World development, 27(3), 611-627.
Fox, R. L., & Schuhmann, R. A. (1999). Gender and local government: A comparison of women and men city managers. Public Administration Review, 231-242.
Franceschet, S. (2011). Gender policy and state architecture in Latin America. Politics & Gender, 7(2), 273.
Froehlich, L., Olsson, M. I., Dorrough, A. R., & Martiny, S. E. (2020). Gender at work across nations: Men and women working in male–dominated and female-dominated occupations are differentially associated with agency and communion. Journal of Social Issues, 76(3), 484-511.
Gidengil, E. (1995). Economic man—social woman? The case of the gender gap in support for the Canada-United States free trade agreement. Comparative Political Studies, 28(3), 384-408.
Glover, S. H., M. A. Bumpus, J. E. Logan, and J. R. Ciesla (1997). Re-examining the influence of individual values on ethical decision making. In: From the universities to the marketplace: the business ethics journey, 109–119.
Goertzel, T. (1983). The gender gap: Sex, family income and political opinions in the early 1980’s. JPMS: Journal of Political and Military Sociology 11 (2), 209.
Greif, A. (2006). Institutions and the path to the modern economy: Lessons from medieval trade. Cambridge University Press.
Grigoryan, A. & K. Khachatryan (2021). Covid-19 policy responses through the lenses of female political and social representation. Mimeo.
Gupta, R., Ghosh, A., Singh, A. K., & Misra, A. (2020). Clinical considerations for patients with diabetes in times of Covid-19 epidemic. Diabetes & metabolic syndrome, 14(3), 211.
Hartl, T., K. W. and E. Weber (2020, 4). Measuring the impact of the German public shutdown on the spread of Covid-19. Covid Economics 1 (11), 25-32.
Hawkesworth, M. (2003). Congressional enactments of race-gender: Toward a theory of raced-gendered institutions. American Political Science Review, 529-550.
Hyland, M., S. Djankov, and P. Goldberg. 2020. Gendered Laws and Women in the Workforce. American Economic Review: Insights, 2 (4): 475-90.
Hyland, M., S. Djankov, & P. Goldberg. 2021. Do Gendered Laws Matter for Women’s Economic Empowerment? Peterson Institute for International Economics Working Paper No. 21-5.
Iyer, L., Mani, A., Mishra, P., & Topalova, P. (2012). The power of political voice: women’s political representation and crime in India. American Economic Journal: Applied Economics, 4(4), 165-93.
Kong, E., & Prinz, D. (2020). Disentangling policy effects using proxy data: Which shutdown policies affected unemployment during the Covid-19 pandemic?. Journal of Public Economics, 189, 104257.
Krook, M. L., & Mackay, F. (2011). Introduction: Gender, politics, and institutions. In Gender, politics and institutions (pp. 1-20). Palgrave Macmillan, London.
Lott, Jr, J. R., & Kenny, L. W. (1999). Did women’s suffrage change the size and scope of government?. Journal of political Economy, 107(6), 1163-1198.
Lovenduski, J. (2005). Feminizing politics. Polity.
Mackay, F., Kenny, M., & Chappell, L. (2010). New institutionalism through a gender lens: Towards a feminist institutionalism?. International Political Science Review, 31(5), 573-588.
Mackay, F., & Waylen, G. (2009). Feminist institutionalism. Politics & Gender, 5(2), 237-237.
Miller, G. (2008). Women’s suffrage, political responsiveness, and child survival in American history. The Quarterly Journal of Economics, 123(3), 1287-1327.
OECD. (2014). Women, Government and Policy Making in OECD Countries: Fostering Diversity for Inclusive Growth. OECD. doi:10.1787/9789264210745-en.
Ones, D. S. and C. Viswesvaran (1998). The effects of social desirability and faking on personality and integrity assessment for personnel selection. Human Performance 11 (2-3), 245–269.
Reiss, M. C. and K. Mitra (1998). The effects of individual difference factors on the acceptability of ethical and unethical workplace behaviors. Journal of Business Ethics 17 (14), 1581–1593.
Reynolds, A. (1999). Women in the legislatures and executives of the world: Knocking at the highest glass ceiling. World Politics 51 (4), 547–572.
Rodriguez-Garcia, M. J. (2015). Local Women’s Coalitions: Critical Actors and Substantive Representation in Spanish Municipalities. European Journal of Women’s Studies 22 (2): 223–240. doi:10.1177/1350506814549424.
Rosenthal, C. S. (2000). Gender Styles in State Legislative Committees: Raising Their Voices in Resolving Conflict. Women & Politics 21 (2): 21–45. doi:10.1300/J014v21n02_02.
Svaleryd, H. (2009). Women’s representation and public spending. European Journal of Political Economy, 25(2), 186-198.
Wood, W., & Eagly, A. H. (2009). Gender identity. Handbook of individual differences in social behavior, 109-125.

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

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

Five Years in Operation: the Polish Universal Child Benefit

Posted on May 10, 2021 | Policy Brief

Family in the golden hour representing Child Benefits

Over the last five years, Polish families with children have been entitled to a relatively generous benefit of approximately €110 per month and child. Initially granted for every second and subsequent child in the family regardless of income and for the first child for low-income families, the benefit was made fully universal in 2019. With the total costs amounting to as much as 1.7% of Poland’s GDP, the benefit reaches the parents of 6.7 million children and significantly affects these families’ position in the income distribution. Its introduction has led to a substantial reduction in the number of children living in poverty. However, since families with children are more likely to be among households in the upper half of the income distribution, out of the total cost of the benefit, a proportionally greater share ends up in the wallets of high-income families. While the implementation of the benefit has significantly changed the scope of public support to families in Poland, there are many lessons to be learnt and some important revisions to be undertaken to achieve an effective and comprehensive support system.

Introduction

One of the principal commitments in the 2015 Polish parliamentary elections of the then-main opposition party – Law and Justice (Prawo i Sprawiedliwość, PiS), was introducing a generous child benefit. The purpose of this benefit was to support families and encourage higher fertility, which had been one of the lowest in the European Union for a long time. Following PiS’s electoral victory, the new government introduced a semi-universal child benefit of approximately €110 per month (exactly 500 PLN per month, thus the Polish nickname of “the 500+ benefit”) in April 2016. Initially, the benefit was granted for every second and subsequent child in the family regardless of income and for the first child in low-income families. Since July 2019 (nota bene three months before the next parliamentary elections), it was made universal – all parents with children under the age of 18 are entitled to 500PLN per month for every child. The benefit is relatively generous (for comparison, it accounts for 17.9% of the minimum wage in Poland in 2021), and universal coverage implies substantial costs for the government budget, totalling about 41bn PLN per year (1.7% of the Polish GDP).

Over the last five years, a number of analyses of the consequences of the benefit’s introduction have been conducted. These have encompassed a variety of socio-economic outcomes for Polish families with children – from a comprehensive assessment of these consequences (Magda et al. 2019) to analyses focused on specific effects of the benefit, such as the impact on women’s economic activity (Magda et al. 2018, Myck 2016, Myck and Trzciński 2019) or poverty (Brzeziński and Najsztub 2017, Szarfenberg 2017). The fifth anniversary of the benefit’s implementation seems to be a good opportunity for a summary and update of previous evaluations of the distributional consequences and financial gains for households resulting from this policy (an overview of all the previous CenEA analyses of the child benefit can be found in CenEA 2021). The results presented in this brief are based on analyses conducted using the Polish microsimulation model SIMPL on data from the 2019 CSO Household Budget Survey (more details in Myck et al. 2021). It should be noted that the analyses do not account for the impact of the Covid-19 pandemic on the material situation of households, as the data was collected before the outbreak. As previous studies suggest, the consequences for households of the pandemic and the series of resulting lockdowns varied greatly depending on various factors, such as the sources of income, sector, and form of employment, thus making it impossible to estimate precisely (Myck et al. 2020a).

The Child Benefit on Household Incomes

Due to its universal character, the distributional consequences of the child benefit payments are directly related to the position of households with children aged 0-17 in the income distribution relative to those without. As households with children are more likely to be in the upper half of the distribution (taking into account the demographic structure of households through income equivalisation), out of the total budget expenditure on the benefit, a proportionally greater share goes to high-income families (Table 1). Families with children in the two highest income decile groups (i.e., belonging to the 20% of households with the highest income) currently receive almost 25% of the total annual expenditure on the child benefit. On the other hand, among the 20% of households with the lowest incomes, families with children receive only 11.7% of the total annual cost of the benefit.

Table 1. Household gains resulting from the child benefit by income decile groups

Source: Myck et al. 2021. Notes: Income decile groups – ten groups each covering 10% of the population, from households (HH) with the lowest disposable income to the most affluent households, calculated on the basis of equivalised incomes.

Compared to the poorest 10% of households, families with children in the highest income decile receive 2.5 times more of the total funds allocated to the benefit.

It is also worth noting that the proportion of benefit in the disposable income is relatively evenly distributed if one considers all households in a given decile (with and without children). The proportional benefits in the first nine income deciles are in the range of 3.4% and 5.3% and only fall to 1.9% in the highest income group. A significant differentiation of the benefit in proportional terms can only be seen when accounting solely for households with children within each income decile. The benefit amounts to as much as 26.9% of the disposable income of households with children in the first decile, and the effect falls in subsequent groups – from 18.9% and 16.4% in the second and third deciles, to only 4.1% in the top decile.

The Child Benefit and the Position of Families With Children in the Income Distribution

Taking into account the magnitude of the policy, the position of families with children in the income distribution relative to other households may, to some extent, be the result of receiving the benefit itself. It is, therefore, reasonable to ask what role the benefit plays in shaping this relative position in the income distribution. Figure 1 presents the number of children under 18 in households by income decile groups when the benefit is included in total household income (left panel) and in a hypothetical scenario when the child benefit payment is withdrawn (right panel). As we can see, the withdrawal of the benefit would cause a substantial change in the relative position of families with children in the income distribution, significantly increasing the number of children in the lowest income groups. While in the current system, the poorest 10% of households include 342 thousand children aged 0-17, this number would be 553 thousand in a system without the benefit. However, the benefit also changes the relative position of high-income households with children. In the current system, the richest 10% of households include 762 thousand children. Subtracting the benefit from their household income would reduce this number to 687 thousand.

Figure 1. The child benefit and its impact on the position of families with children in the income distribution

Source: Myck et al. 2021.

Thus, even when taking into account the income distribution without the benefit, the number of children among the richest 10% of households is almost 25% higher than the number of children in the poorest 10% of households. Looking at the income distribution after including the benefit, there are more than twice as many children in the richest 10% of households than among the poorest 10%. This, in turn, inevitably means that, out of the total cost of the benefit, over twice as much money is transferred to households belonging to the richest deciles as compared to the funds transferred to families belonging to the poorest 10% of households.

Discussion

With the total costs amounting to 1.7% of Poland’s GDP, the child benefit introduced in April 2016 substantially raised the level of direct financial support for families with children. As shown in this brief, the benefit reaches the parents of 6.7 million children aged 0-17 and significantly affects the position of these families in the income distribution. While, on the one hand, a large proportion of families with children have incomes high enough to be in the highest income groups even without this support , the lowest decile group would include over 200 thousand more children in the absence of the benefit. This confirms that the child benefit alone contributes to a significant improvement in the material conditions of families with children and to a significant reduction in poverty (cf. Brzezinski and Najsztub, 2017; Szarfenberg, 2017). However, the scale of this reduction is modest given the size of the resources involved. This is not surprising given that the bulk of the total costs of the benefit comes from the 2019 program extension to cover all children regardless of family incomes, which largely ended up in the wallets of higher-income families (Myck et al. 2020b). One of the key goals of the benefit upon introduction was to increase the number of births in Poland by easing the material conditions of families with children. Yet despite a radical increase in the level of support, the number of births in Poland over the period 2017-2020 has essentially remained the same as that forecasted by the Central Statistical Office in its long-term population projection of 2014 (Myck et al. 2021). It is thus difficult to consider the benefit a success in terms of this major objective. Moreover, the withdrawal of the income threshold has largely eliminated the negative disincentive effects of the benefit with regard to employment (Myck and Trzcinski 2019). However, it is unclear whether the post-pandemic economic situation will allow for an increase in female labour force participation, which declined following the introduction of the benefit in 2016 (Magda et al., 2018).

The effects of every socio-economic programme should be assessed by comparing cost-equivalent alternatives. Despite all gains the “500+” child benefit has brought to millions of families in Poland over the last five years, the flagship programme of the ruling Law and Justice party does not fare well in this perspective. The need for change seems much broader than the reform of the benefit alone. The benefit was introduced on top of two other financial support mechanisms focused on families with children, namely family allowances and child tax credits, and the three elements have been operating in parallel since 2016. A number of suggestions on creating a streamlined, comprehensive system have been made a long time ago (e.g., Myck et al. 2016). However, a major restructuring of the entire support system with clearly defined socio-economic policy goals in mind seems all the more justified now, when many families may require additional assistance due to the difficult financial situation related to the Covid-19 pandemic.

Acknowledgement:

This Policy Brief draws on the CenEA Commentary published on 31.03.2021 (Myck et al. 2021). It has been prepared under the FROGEE project, with financial support from the Swedish International Development Cooperation Agency (Sida). The views presented in the Policy Brief reflect the opinions of the Authors and do not necessarily overlap with the position of the FREE Network or Sida.

References

Brzeziński, M., Najsztub, M. 2017. The impact of „Family 500+” programme on household incomes, poverty and inequality”, Polityka Społeczna44(1): 16-25.
CenEA 2021. Childcare benefit 500+ in CenEA analyses. https://cenea.org.pl/2021/04/06/childcare-benefit-500-in-cenea-analyses/
Magda, I., Brzeziński, M., Chłoń-Domińczak, A., Kotowska, I.E., Myck, M., Najsztub, M., Tyrowicz, J. 2019. „Rodzina 500+– ocena programu i propozycje zmian”. (“Child benefit 500+: the evaluation of the programme and suggestions for changes”), IBS report.
Magda, I., Kiełczewska, A., Brandt, N. 2018. “The Effects of Large Universal Child Benefits on Female Labour Supply”, IZA Discussion Paper No. 11652.
Myck, M. 2016. “Estimating Labour Supply Response to the Introduction of the Family 500+ Programme”. CenEA Working Paper 1/2016.
Myck, M., Król, A., Oczkowska, M., Trzciński, K. 2021. “Świadczenie wychowawcze po pięciu latach: 500 plus ile?”(„The child benefit after 5 years – 500 plus what?”), CenEA Commentary 31/03/2021.
Myck, M., Kundera, M., Najsztub, M., Oczkowska, M. 2016. „25 miliardów złotych dla rodzin z dziećmi: projekt Rodzina 500+ i możliwości modyfikacji systemu wsparcia” („25 billion PLN to families with children: Family 500+ programme and possible modifications of the family support system”), CenEA Commentary 18/01/2016.
Myck, M., Oczkowska, M., Trzciński, K. 2020a. “Household exposure to financial risks: the first wave of impact from COVID-19 on the economy”, CenEA Commentary 23/03/2020.
Myck, M., Oczkowska, M., Trzciński, K. 2020b. „Kwota wolna od podatku i świadczenie wychowawcze 500+ po pięciu latach od prezydenckich deklaracji” („Tax credit and child benefit 500+ after five years since electoral declarations”, in PL), CenEA Commentary 22/06/2020.
Myck, M., Trzciński, K. 2019. “From Partial to Full Universality: The Family 500+ Programme in Poland and its Labor Supply Implications”, ifo DICE Report 17(03), 36-44.
Szarfenberg, R. 2017. “Effect of Child Care Benefit (500+) on Poverty Based on Microsimulation”, Polityka Społeczna 44(1): 25-30.

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.

Economic Perspectives on Domestic Violence | Insights from the FROGEE Webinar | Part 1

Posted on October 26, 2020 | Policy Brief

Broken mirror with a man's hand representing domestic violence during COVID-19 pandemic frogee

The COVID-19 pandemic and the resulting lockdown restrictions have amplified the academic and policy interest in the causes and consequences of domestic violence. With this in mind, the FREE Network invited academic researchers to participate in an online workshop entitled “Economic perspectives on domestic violence“. This policy brief is the first in a series of two briefs summarizing the papers presented at the workshop. The current brief addresses the presentations that had a more general focus on domestic violence. The second brief will discuss the papers devoted to the domestic violence implications of the pandemic.

Introduction

Domestic violence (DV), as well as one of its main forms – intimate partner violence (IPV) – are societal issues of massive proportion. The World Health Organization estimates that 1 in 3 women across 80 countries worldwide are victims of IPV during their lifetime (WHO, 2013). IPV imposes huge costs on society: its victims, for instance, are estimated to be twice as susceptible to depression and alcohol abuse, and 16% more likely to give birth to a low birth-weight child (WHO, 2013).

IPV separates itself from other types of violent offenses in several aspects. To start with, the intimate victim-perpetrator relationship causes IPV to be vastly underreported. The victim may have feelings of shame, guilt, and self-blame, which could deter her from seeking support. Further, IPV and more generally DV cases also have high rates of attrition within the justice system. These distinct characteristics highlight the level of difficulty in developing policies aimed at helping victims of intimate partner abuse. The fact that the prevalence of IPV is widespread and at the same time vastly under-reported, casts doubt on the policy measures and legislation in place today.

This policy brief is the first in a series of two that summarizes the recent economic research on IPV presented in the workshop entitled “Economic Perspectives on Domestic Violence”. The workshop was organized as a part of the Forum for Research on Gender Economics (FROGEE) supported by the Swedish International Development Cooperation Agency (SIDA).

Economic Determinants of Domestic Violence

A number of presentations in the workshop were devoted to the economic determinants of domestic violence.

Andreas Kotsadam presented a paper on the relationship between women’s employment and IPV in Ethiopia. The link between the two is twofold: employment could increase women’s empowerment and, thereby, decrease IPV; however, the boost in empowerment could threaten the man’s status in (male-female) relationships, and lead to violent retaliation. Violence could also be used to extract economic resources from working women. To study which of these mechanisms prevail, the authors conducted an extensive field experiment collaborating with shoe and garment factories in Ethiopia. From a list of qualified job-candidates provided by employers, they randomly assigned 1500 equally qualified women living with partners to either getting a job (treatment group) or not (control group). Prior to treatment, women from both groups were interviewed and asked to answer various questions regarding intimate partner abuse. They were also called to a follow-up survey 6 months later. The statistical analysis of these answers fails to establish a causal link between employment status and the incidence of IPV.

Taking a more theoretical approach, Paul Seabright‘s preliminary work on the determinants of IPV offered a dynamic framework modeling how (unpredictable) economic circumstances and (predictable) individuals’ traits influence domestic violence, as well as formation and dissolution of partnerships. The model distinguishes individuals in their ability to control resources within relationships without the use of violence (“skills”), and in their costs of engaging in violence (“temperament”). The model assumes that individuals with more violent temperaments are on average endowed with lower skills. It predicts women’s income and their risk of IPV should be negatively correlated cross-sectionally, but that positive shocks in income should increase IPV for married women while decreasing it for women with easier exit options. The authors test the model on survey data from Brazil and data on randomized expansions of a food-program in Ecuador. The results support the cross-sectional prediction and confirm that the effect of income shocks depends on exit options, though does not support the prediction of an increase for married women.

Sonia Bhalotra’s presentation addressed the DV consequences of another type of economic shock, namely female and male unemployment, and also considered the role of unemployment benefits as a mitigating factor. By exploiting an extensive dataset covering every court case in Brazil between 2009 and 2017, and information on mass layoffs at the local level, the study finds that the probability of a male being prosecuted for a DV crime increases by 32% when he loses his job and persists at similar levels 4 years after. For female job-loss, the corresponding effect is significantly larger and amounts to 52%. Bhalotra and her co-authors argue that the fact that unemployment of either the man or the woman leads to an increase in domestic violence is consistent with unemployment constituting a negative shock to income and a positive shock to time spent at home. They further argue that the larger impact of female relative to male unemployment is potentially consistent with the “household bargaining model”, which encapsulates the idea that it becomes more difficult for a woman to leave a violent relationship when she is more economically dependent on her partner. Additional analysis shows that eligibility for unemployment insurance increases DV once benefits expire and that this is in turn a result of unemployment benefits increasing peoples’ time in unemployment.

The Role of Police

Part of the workshop was dedicated to the role of the criminal justice system. A fact that stresses the importance of studying police behavior is that domestic abuse cases generally suffer from high legal attrition and most of them are dropped before reaching the court. Variation in the characteristics of law enforcement could likely play a role in explaining differences in DV across contexts.

In this vein, Sofia Amaral introduced a study on the relationship between gender diversity of the police force and domestic violence in the UK. The gender-distribution within law enforcement is believed to directly influence DV in two ways: First, gender-based differences in attitudes and norms may influence police-handling in DV cases. Second, if the gender of the victim aligns with that of the officer, the victim may be more willing to cooperate and disclose evidence. The data shows that the total share of women in the police force is almost equal to that of men, but the tasks performed differ systematically across genders. Women are found to be overrepresented among call-handlers and underrepresented among first-response teams. For each position, Amaral and her co-authors investigate whether changes in gender-distribution influence the rate of legal attrition, rate of repeat victimization, and the amount of time spent at a scene (response duration). By analyzing police force and crime data the study shows that there are substantial efficiency gains from increasing gender diversity, particularly in first-response teams. An increase in the share of females in first-response teams increases response duration, reduces legal attrition, and decreases repeat victimization. There is an even larger effect when a female is the most experienced officer in the team. The gender of the call-handler has no significant effect on the outcomes of interest.

Along somewhat similar lines, Victoria Endl-Geyer presented research on the link between the quality of police response and DV in the UK. More specifically, the research explores how increased police response times, caused by police station closures in 2012, affected the rate of repeat victimization in DV cases. Faster police response times are believed to improve the victim’s cooperation: If the police are quick to arrive at the scene, the victim gets less time to revise the initial assessment that she needed support. The results show that faster police responses are associated with a higher conviction rate. However, they also increase the likelihood of repeat victimization. A potential explanation could be the so-called “reprisal effect” – the perpetrator retaliates with more violence as a response to being reported by his partner.

Criminalization

Many studies on IPV, including some that were presented at the workshop, highlight that an inherently good policy such as improving police response, sometimes leads to unintended negative consequences to victims. In the keynote speech, Leigh Goodmark addressed this topic by critically discussing the history, consequences, and alternatives to criminalization of IPV in the US. As suggested by her recent book, domestic violence has fallen in the US since the introduction of criminalization and mandatory arrest of IPV crimes. However, historical trends show that the overall crime rate has fallen to a greater extent. Goodmark provided several reasons why criminalization has likely been unsuccessful in deterring IPV. Some studies emphasize that it is the accountability and monitoring of perpetrators (even after incarceration) that has been effective in deterring IPV crimes and not the punishment itself. In fact, there are vast costs of DV criminalization occurring to victims of domestic abuse, such as financial instability caused by unemployment of (in many cases) the primary breadwinner in a household. Also, criminalization has been shown to exacerbate other correlates of IPV such as aggressive and hostile tendencies of the perpetrator. Goodmark proposed alternatives to DV criminalization that avoid such costs and thereby, are potentially more effective in reducing domestic abuse. First, there are solutions rooted in economics such as cash-transfer programs, employment training, and micro-financing. These types of measures can help to reduce the economic penalties of seeking support and strengthen the victim’s financial independence. Also, more social solutions were suggested such as community organizing, restorative justice, and community accountability. Moreover, Goodmark underlined the fact that individuals with adverse childhood experiences, often involving violence, are significantly more likely to commit violent crimes such as IPV. Identifying and intervening at an early age to educate these individuals about intimate relationships has been shown to be effective in dealing with the problem. In a nutshell, Goodmark stressed the importance of constructing a balanced policy approach that targets the origins of DV and argued that the time has come to reconsider punishing violence with more violence.

Reporting

Problems related to IPV misreporting were a recurring subject of discussion at the workshop. A lot of the previous research on IPV relies on direct surveys asking women whether they were a victim of different instances of IPV. The main problem associated with such surveys relates to accuracy: social factors such as stigma, shame, and/or self-blame, as well as privacy concerns, are likely to influence respondents’ answers. A practice that has proven successful for sensitive questions is the use of an indirect method called list experiments, where the structure of the survey mitigates much of the above concerns on the respondent’s side (see, e.g., https://blogs.worldbank.org/ impactevaluation/list-experiments-sensitive-questions-methods-bleg).

Veronica Frisancho presented a study on the gap in reporting originating from direct questionnaires vs. list experiments based on experimental evidence from Peru. The experiment considers two groups of 500 women each. Women in the first group participate in a survey that uses direct questionnaires, whereas those in the second group answer a survey using indirect questionnaires. Based on the answers, the authors obtain an IPV prevalence rate for each group and define under-reporting as the difference in prevalence between them, under the assumption that the rate of under-reporting in the presence of indirect questionnaires is minor. Unexpectedly, yet encouraging, they find no evidence of misreporting in the direct-questions method. However, when looking closer at different education levels, they find that under-reporting is significantly more prevalent for highly educated women. In other words, less educated women are more truthful when answering questions about IPV. Frisancho emphasized that these types of patterns make it more difficult to identify the most vulnerable groups, implying that direct methods could increase the risk of mistargeted policies.

More generally, there are several reasons why respondents may be less truthful when answering questions related to IPV. On the one hand, individuals may be aware that they are victims of abuse, but perhaps are unwilling to confess due to stigma. On the other hand, it could be that individuals fail to identify themselves as victims of abuse at all, and do not consider their relationship unhealthy. Against this background, Nishith Prakash presented preliminary results of an ongoing study on behavioral barriers to the demand for DV-support services. The baseline results of the survey indicate belief gaps among women who scored high on levels of abuse: a significant majority of abuse victims rated their relationship as healthy. While 46.43% of respondents report some form of physical, emotional, or sexual violence, the portion of those with the prior belief that they are in an abusive relationship is only 1%. The study also finds that stress about Covid-19 correlates with higher levels of self-blame, abuse, and lower levels of understanding of what abusive behaviors are.

The covid-19 pandemic and its massive repercussions on determinants of DV such as mobility, economic insecurity, and social isolation have offered new possibilities for researchers to study the underlying causes of DV, while also making DV research ever more important. The next policy brief in this series will summarize the presentations which were specifically devoted to the consequences of the pandemic on DV. On behalf of FROGEE and SITE, we would like to thank the speakers for their contributions to the understanding of this topic, which will be indispensable both to the academic community and to policymakers in their efforts to design more effective policies for the future. We would also like to thank SIDA for generous financial support.

References

WHO, Department of Reproductive Health and Research, London School of Hygiene and Tropical Medicine, South African Medical Research Council. “Global and regional estimates of violence against women”. Reference No. 978 92 4 156462 5. 2013.

List of Participants

Andreas Kotsadam, The Frisch Centre, Oslo University, EGAP, CESifo
Paul Seabright, Toulouse School of Economics, IAST
Sonia Bhalotra, University of Essex
Sofia Amaral, University of Munich, CESifo
Victoria Endl-Geyer, ifo Institute
Leigh Goodmark, University of Maryland
Veronica Frisancho, Inter-American Development Bank
Nishith Prakash, University of Connecticut

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.

Domestic Violence in the Time of Covid-19

Posted on October 12, 2020 | Policy Brief

Since the outbreak of Covid-19 in the spring of 2020, media outlets around the world have reported increases in domestic violence. United Nations secretary-general António Guterres has even referred to it as a “shadow pandemic”. Besides news outlets, academic researchers have also taken an interest in the issue, which is crucial if we are to draw the right conclusions from the patterns we see in the statistics. Preliminary evidence shows that the incidence of intimate partner violence has also increased in Sweden, notwithstanding the absence of a strict lockdown. This is likely related to the socio-economic changes brought about by the pandemic.

A Shadow Pandemic?

In response to the Covid-19 pandemic, governments around the world introduced a variety of measures aimed to stave off the contagion, and billions of worried people adapted their behavior and lifestyle. But did the pandemic, and the changes brought by it, also lead to an increase in domestic violence?

Were we to simply look at the number of domestic violence offenses reported over time, we would not be able to answer this question. Historical trends and seasonal patterns in domestic violence would confound this observation, while the crisis might affect the reporting of crimes independently of their occurrence. More rigorous statistical analysis is needed for understanding not only the true situation with domestic violence under the pandemic, but also the reasons behind it. Investigating the driving factors is crucial for informing policy reactions already in the short run — is it a loss of income that generates violence, or could it simply be increased exposure? Do we need more unemployment benefits or shelters for victims? Moreover, the rather special conditions created by the pandemic can contribute to our general understanding of how domestic violence occurs in relation to other societal dynamics, unveil some of the causal mechanisms that are still open questions in the literature and help to fight this issue further, even after the pandemic is over.

Socio-economic Theories of Violence

Within social science research, studies that focus on the relationship between domestic violence and factors at a societal level can be divided into several different branches. A large corpus of theories interprets violence as a result of power imbalance within households. This perspective is associated with explanations such as bargaining power, exit options, and status, theoretical concepts that are often embodied and approximated by observable factors such as (relative) education, income or employment status. For example, Aizer (2010) provides results in line with the bargaining power hypothesis showing that a decrease in the gender wage gap in the US is associated with a decrease in domestic violence against women. Along the same lines, Anderberg et al. (2016) use UK data to show that an increase in unemployment among men reduces the incidence of intimate partner violence (IPV) while an increase in unemployment among women increases it. In contrast, a study from Spain documents the opposite relationship in provinces characterized by stronger traditional gender roles (Tur-Prats, 2019). It finds that a decrease in female relative to male unemployment causes an increase in violence, which is more in line with the “backlash explanation” — when a woman improves her economic position and independence, the man in the household feels that his identity as breadwinner is threatened and retaliates with violence as a result. Studies such as Iyer et al. (2012) and Miller and Segal (2018) highlight the importance of improving the position of women in society, which can be achieved, for example, through role models and female representation in critical positions. They associate the proportion of women among elected politicians and among the police, in India and the United States respectively, with a significant increase in reports of crimes against women and at the same time a significant decrease in the incidence of such crimes.

An alternative interpretation of domestic violence puts more emphasis on its emotional and irrational nature. In this case, particular events or negative emotional shocks, such as an unexpected negative result of an important football match (Card and Dahl, 2011), are believed to trigger violent reactions in the heat of the moment. The likelihood of such incidents is exacerbated by stress and emotional climate within a household, which in turn are influenced by economic conditions or financial uncertainty. For example, several studies from developing countries associate improvements in general economic conditions with a reduction in domestic violence (Hidrobo et al., 2016; Kim et al., 2007; Haushofer et al., 2019).

Finally, there is a common perception that domestic violence increases during holidays and weekends as families spend more time together and potential victims are more isolated from their social networks, in line with the so-called exposure model in criminology. So far, research on this hypothesis is limited and incomplete. However, it is precisely one of the areas where studies from the recent months may fill the knowledge gap: the fact that lockdowns and work from home forced many families to spend more time together at home while retaining full wages, gives a unique opportunity to examine exposure in isolation from other economic factors.

The opposite of exposure is known as (self-) incapacitation theory: no aggression will occur while a (potentially violent) partner is occupied with something else, whether imposed or self-chosen. Several studies focusing on this hypothesis have documented that the incidence of violent crimes declines, on the street or in the home environment, when potential perpetrators are in school (Jacob and Lefgren, 2003), in prison (Levitt, 1996), at the cinema (Dahl and DellaVigna, 2009) and when they have access to a legal prostitution market (Cunningham and Shah, 2018; Ciacci and Sviatschi, 2018; Berlin et al., 2019). During a lockdown, the availability of such activities is restricted, both to violent people as well as potential victims.

Research on Domestic Violence During Covid-19

The list of studies analyzing data from the past few months is growing by the day. Although full consensus is yet to be reached, the results that have emerged point towards a few patterns: spikes in domestic violence can be credibly connected to strict limitations of movement, at least in some contexts (India, Ravindran and Shah, 2020; Peru, Agüero, 2020; 15 large US cities, Leslie and Wilson, 2020); unemployment could be an important mechanism (Bhalotra et al., 2020; in Canada, Beland et al., 2020 find no impact of unemployment or work arrangements per se, but do associate spikes in violence to financial difficulties); alcohol does not seem to amplify domestic violence during the pandemic, at least in some context (Silverio-Murillo and Balmori de la Miyar do not find any effect of the prohibition to sell alcohol in parts of Mexico City); and by and large barriers to reporting might be a serious issue (Spencer et al, 2020).

A selection of studies on domestic violence during the Covid-19 crisis, many of which are as yet unpublished, were presented at the recent FROGEE Workshop “Economic Perspectives on Domestic Violence”. Two FREE Policy Briefs summarizing the event are forthcoming.

Domestic Violence in Sweden During Covid-19

Studying Sweden against this background can be particularly interesting for at least two reasons. Sweden regularly occupies the top positions in international rankings of gender equality in many dimensions and is seen as having advanced progressive norms and attitudes in this area. As pointed out by the literature on the economic determinants of domestic violence, underlying norms and attitudes can play a significant role in shaping the impact of other factors, such as unemployment (Tur-Prats, 2019). Therefore, the Swedish case can offer a valuable comparison to studies focusing on countries that have different attitudes and norms.

According to estimates by the National Council for Crime Prevention (BRÅ), at least 7% of the Swedish population is exposed yearly to domestic violence, both men and women in roughly equal parts. However, women are much more likely to report recurring violence and to end up hospitalized.

When it comes to the particular situation of the Covid-19 crisis, Sweden is also close to unique in its contagion-management strategy. Swedish policy relied much more than elsewhere on voluntary participation and individual responsibility rather than coercion. Certainly, working from home when possible was encouraged, the use of public transport discouraged, and indoor events with more than 500, and thereafter 50 participants were forbidden, which included many sports and cultural events. In fact, the Google mobility index, based on location data from Google Account users, shows patterns of clear deviation from the baseline since week 11 of 2020, when the authorities declared a very high risk of community spread.

Figure 1. Mobility patterns in Sweden during Covid-19

Source: Author’s aggregation of Google mobility index. The lines show the deviation from baseline, in percentual terms, of total user presence in different urban areas by category.

The plots in Figure 1 show that the presence of Google Account users was about 10% higher in residential areas (the pink line) and much lower in workplaces, despite some variation over the period: the initial decline was roughly half as large as the impact of summer vacation, as shown by the blue line. Also, visits to retail centers and grocery stores, recreation places (such as restaurants, cinemas, and theaters), and transit stations decreased, especially during the beginning of the period. Mobility in parks and green areas, shown separately, follow to a larger extent a seasonal pattern.

Nevertheless, the general population was never forbidden or even discouraged from leaving their homes, which clearly makes a stark difference for many of the mechanisms that, based on the literature, we think could play a role in explaining domestic violence.

According to BRÅ, during the first half of 2020, there was a 1% increase in total reported crime compared to the same period of the previous year. However, there is wide variation among the crime categories: 9% more violent assaults against women were reported, and 4% more against men, but 6% fewer rapes of women and 9% fewer rapes of men. As discussed above, it is not straightforward to draw conclusions from simple comparisons over time. Preliminary analysis utilizing the variation in mobility patterns over weeks and municipalities reveals that a 10% increase in residential mobility is associated with a (lower bound) increase in reported non-battery crimes against women committed by an intimate partner by 0.015 crimes per 10,000 individuals (a sixth of the mean). The corresponding figure for a 10% reduction in mobility in retail and recreation areas and transit mobility is around 0.0025 additional crimes (3% of the mean) (see Figure 2). Crime categories include attempted or planned homicides; sexual molestations, sexual assaults, and rapes; violations of integrity and privacy (including limitation of freedom, coercion, threats, persecutions; battery crimes are not included for the time being because of a coding mistake in the police system pertaining this particular category).

Figure 2. Mobility patterns and IPV in Sweden during Covid-19 – non-battery crimes

Source: Author’s analysis. Crime data provided by the police, mobility index provided by Google.

We consider this a lower bound because of the voluntary nature of the Swedish ”lockdown” – if people have the freedom to choose, then it is reasonable to expect that individuals more exposed to the risk of domestic violence would decide to be less at home, which would reduce the strength of the relationship observed. In the opposite direction, we might be worried that when more people are at home, more crimes are reported by a third party, such as neighbors, and thus not implying that more crimes are being committed. However, we differentially see more reported crimes with a female victim than with a male victim, which is not necessarily easy for a third party to distinguish by the sounds. Therefore, it seems likely that, based on the changes in mobility patterns, IPV against women has increased in Sweden during the Covid-19 crisis. Other consequences of the crisis that might also play an important role in shaping IPV and domestic violence, including the huge increase in unemployment and changes in alcohol sales, remain to be investigated.

Conclusion

In conclusion, research from the past months finds some limited support for hypotheses originating from previous literature on the relationship between different socio-economic factors and domestic violence. When these factors were affected by the pandemic and the associated economic crisis, domestic violence responded as well, to a varying extent depending on the context. This can be seen as an indirect and hidden cost of the pandemic.

Preliminary evidence indicates a similar case for Sweden, notwithstanding the absence of a strict lockdown. This implies that a significant part of the changes in behavior, which in turn can be expected to affect domestic violence, have occurred as a response to the pandemic itself and not necessarily as a result of policy measures.

While the shock of the pandemic will help us to better understand some of the underlying mechanisms behind the phenomenon of domestic violence, many questions are still open, and it is important to look beyond the pandemic. Domestic violence existed before Covid-19 and will, unfortunately, remain part of our societies when the pandemic is over. Investigating and understanding its determinants is important in order to formulate proper policies to combat it during and after the crisis.

References

Agüero, Jorge M, 2020. “Covid-19 and the rise of intimate partner violence”. Unpublished.
Aizer, Anna, 2010. “The Gender Wage Gap and Domestic Violence.”, The American economic review, 100 (4), 1847-1859.
Anderberg, Dan; Helmut Rainer; Jonathan Wadsworth; and Tanya Wilson, 2016. “Unemployment and Domestic Violence: Theory and Evidence.”, The Economic Journal, 126 (597), 1947–1979.
Béland, Louis-Philippe; Abel Brodeur; and Taylor Wright, 2020. “The short-term economic consequences of Covid-19: exposure to disease, remote work and government response.” Unpublished.
Berlin, Maria P.; Giovanni Immordino, Francesco F. Russo and Giancarlo Spagnolo, 2020. “Prostitution and Violence. Empirical Evidence from Sweden”, Unpublished.
Berlin, Maria P.; and Manne Gerell, 2020. “Economic Determinants of Violence in the Home: The Case of Sweden During Covid-19”, Unpublished.
Bhalotra, Sonia; Damian Clarke; Emilia Brito; Pilar Larroulet; and Francisco Pino, 2020. “Impact of Covid-19 on Domestic Violence, Crime and Male and Female Time Use and Labor Supply: Evidence from Rolling Quarantines in Chile”, Unpublished.
Capaldi, Deborah M.; Naomi B. Knoble, Joann Wu Shortt, and Hyoun K. Kim, 2012. “A systematic review of risk factors for intimate partner violence.” Partner abuse 3, no. 2. 231-280.
Card, David; and Gordon B. Dahl, 2011. “Family violence and football: The effect of unexpected emotional cues on violent behavior.” The quarterly journal of economics. 126.1, 103-143.
Ciacci, Riccardo; and Maria Micaela Sviatschi, 2016. ”The Effect of Indoor Prostitution on Sex Crime: Evidence from New York City”, Columbia University Working Paper.
Cunningham, Scott; and Manisha Shah, 2017. “Decriminalizing indoor prostitution: Implications for sexual violence and public health.” The Review of Economic Studies, 85.3, 1683-1715.
Dahl, Gordon; and Stefano DellaVigna, 2009. “Does movie violence increase violent crime?”, The Quarterly Journal of Economics. 124.2 (2009): 677-734.
Haushofer, Johannes, Charlotte Ringdal, Jeremy P. Shapiro, and Xiao Yu Wang, 2019. “Income changes and intimate partner violence: Evidence from unconditional cash transfers in Kenya”, Unpublished.
Hidrobo, Melissa; Amber Peterman, and Lori Heise, 2016 “The effect of cash, vouchers, and food transfers on intimate partner violence: evidence from a randomized experiment in Northern Ecuador.” American Economic Journal: Applied Economics. 8, no. 3. 284-303.
Iyer, Lakshmi; A. Mani, P. Mishra, & P. Topalova, 2012.”The power of political voice: women’s political representation and crime in India.” American Economic Journal: Applied Economics 4.4, 165-93.
Jacob, Brian, A.; and Lars Lefgren, 2003. “Are Idle Hands the Devil’s Workshop? Incapacitation, Concentration, and Juvenile Crime.” American Economic Review, 93 (5): 1560-1577.
Kim, Julia C.; Charlotte H. Watts, James R. Hargreaves, Luceth X. Ndhlovu, Godfrey Phetla, Linda A. Morison, Joanna Busza, John DH Porter, and Paul Pronyk, 2007. “Understanding the impact of a microfinance-based intervention on women’s empowerment and the reduction of intimate partner violence in South Africa.” American journal of public health. 97, no. 10. 1794-1802.
Levitt, Steven D., “The Effect of Prison Population Size on Crime Rates: Evidence from Prison Overcrowding Litigation”. The Quarterly Journal of Economics, Volume 111, Issue 2, May 1996, Pages 319–351.
Leslie, Emily; and Riley Wilson, 2020. “Sheltering in place and domestic violence: Evidence from calls for service during COVID-19.” Unpublished.
Miller, Amalia R.; and Carmit Segal, 2018. “Do Female Officers Improve Law Enforcement Quality? Effects on Crime Reporting and Domestic Violence.” The Review of Economic Studies.
Ravindran, Saravana; and Manisha Shah, 2020. ”Unintended consequences of lockdowns: Covid-19 and the shadow pandemic.” Unpublished.
Silverio-Murillo, Adan; Jose Roberto Balmori de la Miyar; and Lauren Hoehn-Velasco, 2020. “Families under confinement: Covid-19, domestic violence, and alcohol consumption.” Unpublished.
Spencer, Melissa; Amalia Miller; and Carmit Segal, 2020. “Effects of the COVID-19 Pandemic on Domestic Violence in US Cities.” Unpublished.
Tur-Prats, Ana, 2019. “Family Types and Intimate Partner Violence: A Historical Perspective”. Review of Economics and Statistics, 101(5), 878-891.

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.