Tag: gender economics

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

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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.

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

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

Introduction

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

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

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

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

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

Labor market highlights

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

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

Source: Geostat

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

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

Source: Geostat

Remote work: a burden or a blessing for women?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

On the road to recovery

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

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

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

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

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

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

Conclusion

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

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

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

References

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

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

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.

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  • 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.