Tag: Gender Inequality Index

Gender Equality and Women’s Economic Empowerment in Times of Crisis

Posted on January 22, 2024 | FROGEE Brief, Policy Brief

On October 19-20, 2023, the International School of Economics at Tbilisi State University Policy Institute (ISET Policy Institute), in partnership with the Forum for Research on Gender Economics (FROGEE), organized the conference “Gender Equality and Women’s Economic Empowerment in Times of Crisis”. The conference addressed critical issues surrounding gender equality and women’s economic empowerment. By bringing together academics and practitioners from various sectors it served as a dynamic platform for knowledge sharing and collaboration on actionable solutions and commitments to address multifaceted challenges faced by women globally. This policy brief outlines the keynote, academic and other presentations and discussions featured at the conference.

Introduction

Gender equality and women’s economic empowerment are vital issues that have gained increasing global attention in recent years. Their significance is even more pronounced in times of crisis, such as during economic downturns or global health emergencies. Such challenging circumstances often exacerbate existing gender disparities and vulnerabilities, making it crucial to address the specific challenges women face in accessing economic opportunities and resources. Discussions on these matters delve into the complex intersection of gender equality and economic empowerment and how empowering women economically can contribute to more resilient and equitable societies.

The October 19-20 conference was aimed at examining and addressing the various aspects of gender equality and female empowerment. The conference begun with opening introductions by Tamar Sulukhia, Eva Atterlöv and Kaori Ishikawa (see the participant list at the end for all associations). Following the opening remarks were two distinctive keynote presentations, a policy panel discussion, and academic presentations. This policy brief summarizes the key takeaways from the conference.

Keynote Addresses

The conference’s first keynote speaker, Elizabeth Brainerd, deliberated on the impact of World War II on marriage and fertility among Russian women. Brainerd show that the war affected these women’s lives for decades, leading to lower rates of marriage and fertility and higher out-of-wedlock births and divorce rates in urban areas than would have been the case in absence of the war. These effects were likely exacerbated by a war and post-war institutional environment that encouraged nonmarital births (in part by expanding the child benefit program) and increased the cost of binding commitments through marriage, particularly for men (absolving fathers of any financial or legal responsibility for children fathered outside marriage). As shown by Brainerd the shock to sex ratios in the Soviet Union due to World War II was among the largest experienced by any country in the twentieth century. In this sense, the effect on Russian women and men was unique and arguably not directly relevant to other countries or time periods. Yet, highly unbalanced sex ratios characterize many populations – whether due to war, immigration and emigration, or preferences for sons etc., – and the analysis can therefore shed light on the effects of sex ratio imbalance also in other contexts. Brainerd’s work supports the conclusion that sex ratios matter for marital and fertility outcomes, both on the marriage market itself and within marriage. The insights from the Soviet Union also highlights that the institutional context matters for determining both the size and direction of the sex ratio’s impact on marriage markets and family formations.

In the conferences second keynote presentation, Maria Floro discussed the findings from a time-allocation survey in Georgia. Evident from the results, women’s work differs from men’s in the sense that women more often perform unpaid household tasks, and since they are primarily responsible for household and caregiving duties, including childcare and elderly care. Such combined responsibilities, coupled with working in typically low-paid jobs can negatively affect women’s physical and mental wellbeing. As the data shows, 66 percent of Georgia’s population engage in unpaid domestic work, with women (88.3 percent) and men (39.6 percent) participating at starkly different rates. Rural women’s participation is the highest, at 90,3 percent. On average, the Georgian population spends 2.1 hours per day on unpaid domestic services for household and family members – with a large gender disparity. In general, the time spent per day by men is 0.7 hours while, in contrast, the time spent by women on these activities is 5 times higher in rural areas (3.6 hours) and 4.7 times higher in urban areas (3.2 hours). Women working full time spend 2.7 hours per day on unpaid domestic services, five times higher than the 0.5 hours spent by men working full time. For all areas of residence, the time spent on unpaid domestic services by women increases with age up until 64 years of age when the numbers drop. Further, women’s time spent on unpaid caregiving work (0.9 hours per day) is 4.5 times higher than the time spent by men. Even for full time working women, the daily time spent on unpaid caregiving work (0.6 hours) is three times higher than that of their male counterparts (0.2 hours). Women who have completed a higher level of education spend higher time on unpaid caregiving services (0.9-1.1 hours per day) than those with a lower level of education (0.4-0.7 hours per day). The difference in women’s and men’s time spent on unpaid caregiving work is greatest for Georgians aged 25-44. Such unequal sharing of household and caregiving responsibilities limits women’s job prospects and is a major reason behind their low participation rate in the labor force, as well as the gender pay gap.

The South Caucasus Gender Equality Index

Following the keynote presentations, Davit Keshelava, presented the ISET Policy Institute’s most recent work on the South Caucasus Gender Equality Index (SCGEI). The index, developed by ISET Policy Institute in close collaboration with Swiss Cooperation Office in Georgia and updated on an annual basis, draws inspiration from the European Institute for Gender Equality’s Gender Equality Index. It comprises of six domains: work, money, knowledge, time, power, and health, alongside eleven subdomains and nineteen indicators.

The index is calculated for three South Caucasus countries, Georgia, Armenia, and Azerbaijan, and nine benchmark countries: Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, and Slovenia. The 2023 edition, mainly based on data from 2021-2022, reveals that within the South Caucasus Armenia is ahead concerning gender equality in the work domain, while Georgia trails behind its regional counterparts. Gender equality in the work domain is lower in the South Caucasus (64.0) than in the baseline countries (67.3).

Georgia stands out as the South Caucasus leader in gender equality within the money domain but significantly trails the baseline countries (South Caucasus – 51.1 vs. baseline countries – 80.5). This discrepancy is the most prominent across all six domains. Azerbaijan leads in the knowledge domain (with Armenia displaying the greatest inequality), yet the South Caucasus slightly outpaces baseline countries in this domain (South Caucasus – 59 and baseline countries – 58.8). This is however the sole equality domain where the South Caucasus surpasses the benchmark countries.

Georgia and Armenia exhibit higher equality in the power domain than Azerbaijan while, in the time domain, Georgia takes the lead in the South Caucasus. In the health domain, Armenia leads in equality, although the difference in index values is marginal.

In the overall index, Georgia emerges as the regional leader in gender equality (60.4), followed by Armenia (57.5) and Azerbaijan (53.0). However, South Caucasus countries as a whole have a lower index (55.4) than the baseline countries (64.1).

Panel Discussion: Topics and Takeaways

The SCGEI presentation was followed by a policy panel discussion, moderated by Tamar Sulukhia and including the panelists Nino Okribelashvili, Nino Chelidze, Nani Bendeliani and Nino Lortkipanidze. The panelists discussed gender inequalities in different areas such as within academia and the tech industry as well as the role of women during crises and the progress made in Georgia towards ensuring gender equality.

Nino Okribelashvili deliberated on the role of women in academia emphasizing that gender inequalities in higher education attainment become obvious when looking at the representation of women across different fields of science. The share of women in subjects such as social work, education and nursing is more than 80 percent, while it is 20 percent in subjects such as computer science, electrical engineering and mechanical engineering. Science, technology, engineering, and mathematics (STEM) oriented institutions are still generally perceived as male dominated. The second glaring gap concerns the representativeness of women in higher rank and leadership positions in academia, where women remain underrepresented in academic and professorial positions across all subjects.

While Nino Okribelashvili discussed the role of women in academia in general, Nino Lortkipanidze focused specifically on the tech industry. She discussed the industry’s potential to create job opportunities for women through various strategies and initiatives such as STEM education and training, diverse hiring practices, leadership development and flexible work policies – including remote work possibilities. Lortkipanidze emphasized that with the right support and opportunities, the rapidly growing tech industry could allow working mothers to thrive in their careers while also enjoying the advantages of a family-friendly work environment.

Shifting the focus to women in times of crisis, Nino Chelidze emphasized the aggravated impact of war on women using the example of the Nagorno-Karabakh conflict. Chelidze highlighted the need for urgent, coordinated action from the donor community to address the challenges of internally displaced persons, most of whom are women and children.

The panel discussion wrapped up with Nani Bendeliani highlighting Georgia’s advancements in gender equality and female empowerment over the past three decades. Bendeliani mentioned different institutional mechanisms adopted in the country for the advancement of women alongside legislative initiatives implemented in different areas concerning for instance maternity and paternity leave, changes to the labor code and the election code. According to Bendeliani, the progress towards gender equality is visible but slow, with available data and multiple assessments showing there is still much to be done.

Academic Presentations

The remainder of the conference was comprised of several academic sessions all contributing to the overall theme of multifaceted gender-related issues. The topics, as detailed below, were: gender disparities in the labor market, violence against women, gender dynamics during the Covid-19 pandemic, the gender divide in education, women in academia and female empowerment and access to services.

Gender Disparities on the Labor Market

The presenters focused on gender disparities on the labor market, exploring aspects such as the implications of labor protection regulations on both men and women, biases and discrimination in employment and wage negotiation, and the impact of female labor force participation on the advancement of women’s rights.

In his presentation, Michal Myck outlined the consequences of labor protection policies in Poland for employees within four years of retirement (regulation that protects them against layoffs, a lowering of their wages or adjustment of their responsibilities). Preliminary results indicate no economically or statistically significant adverse impacts on the employment of men and women approaching labor protection eligibility. These findings suggest that either the anticipated negative effects are absent, or that any concerns employers may have harbored regarding prospective employment protection were counteracted by robust labor demand during the reform period. The general conclusion is that extending protection to specific groups of workers, both men and women, does not necessarily lead to the adverse outcomes often highlighted in standard economic theory.

While Michal Myck focused on labor protection regulations, Francisco Lagos addressed the topic of weight-related employment discrimination and its impact on hiring outcomes. In an experiment, job applications accompanied either by a facial photo of a normal-weight person or by a photo of the same person manipulated to look overweight were sent out to real job opening across 12 occupations in Spain. The results reveal a significant disparity in callback rates for weight-manipulated male applicants, who received fewer callbacks compared to their normal-weight counterparts, with a more pronounced effect in female-dominated occupations. Conversely, weight-manipulated female applicants experienced a slight increase in callbacks, particularly in female-dominated fields. For men, the weight manipulation effect is attributed to the overweight making them appear less attractive, which translates into an attractiveness wage premium. On the contrary the findings for women suggest evidence of an attractiveness penalty, which is also combined with a weight penalty.

The topics of discrimination and biases were also central to Ramon Cobo Reyes Cano’s presentation, which outlined the results of a field experiment on anticipated discrimination and wage negotiation. The findings show that female applicants ask for a lower salary than male applicants in the baseline treatment group – when the full name of the applicant is visible. In the main treatment group, when the gender of the applicant was no longer visible to the employer, the wage requested by female applicants increased by 86 percent, whereas male applicants’ wage requests were 18 percent lower. Evidently, the gender gap in requested wages completely disappears (and even slightly reverses) when the applicants know that their sex is not visible for the potential employer.

The presentations on gender inequalities in the labor market were concluded by Nisar Ahmad, who empirically investigate the impact of women’s labor force participation on women’s rights. In general, female labor force participation has a positive effect on women’s rights in countries with at least some legal economic rights for women. In countries where women’s rights are extremely limited or non-existent, female labor force participation has a negative or negligible impact on women’s rights.

Violence Against Women

In the academic session devoted to violence against women, the presenters elaborated on the primary factors influencing such violence in various countries at different time periods, including during the Covid-19 pandemic.

Monika Oczkowska explores how social norms, values, and stereotypes determine beliefs about abuse, including recognition of abuse, what is considered as abuse, whether abuse is ever justified, and societal consent towards gender-based discrimination. In countries where gender inequality is rampant, reported rates of abuse in standard surveys are sensitive to the socio-economic status and beliefs about gender norms of the participants, highlighting a high scale of variation in the perception of gender-based discrimination in Central and Eastern Europe.

These findings are in line with the results presented by Salome Gelashvili, who consider potential determinants of gender-based violence (GBV) in South Caucasus. According to the research, key factors contributing to GBV in Armenia, Azerbaijan and Georgia include alcohol abuse, social stigma, being a member of a marginalized groups, a pervasive patriarchal culture, adherence to traditional gender roles, a high level of bureaucracy when reporting GBV to the police, generally weak legal support, limited awareness about various forms of GBV, and economic factors such as financial dependence on an abusive partner.

Similar outcomes, but with more emphasis put on norms and the patriarchal system, were found by Reina Shehi, who assesses gender-based violence in Albania. The results show that the patriarchal system and gender-based norms are the two main factors contributing to gender-based violence. However, there is a growing awareness of the importance of patriarchal institutions and gender norms when addressing GBV in Albania.

Violence against women increase in times of crisis, as shown by Velan Nirmala, who studies women’s empowerment and intimate partner violence (IPV) in India. The findings reveal that, regardless of socio-economic factors, the main types of IPV during the Covid-19 lockdown were physical and emotional violence. The results also highlight that a large majority of victims, regardless of education, wealth, region, household structure, religion, and caste, do not disclose the abuse due to societal taboos.

Gender Dynamics During the Covid-19 Pandemic

The unequal effect from the Covid-19 pandemic was further examined in an academic session in which the presenters keyed in on repercussions of the pandemic on women in terms of employment outcomes, decisions related to time allocation, and the division of unpaid household labor.

Nabamita Dutta presented work on gender inequality in employment during Covid-19 related lockdowns in India. The results show that during the pandemic, women were, in general, 8 percent less likely to be employed than men. While return migrants generally suffered less in terms of finding alternative jobs, being a female return migrant, increased the probability of joblessness to about 17 percent. For female return migrants belonging to marginalized castes, the probability of joblessness was about 10 percent, an interesting result considering that women belonging to marginalized castes (but not being return migrants) experience a higher likelihood of being unemployed then women that are not part of marginalized castes.

Anne Devlin further elaborated on this topic, assessing the economic impact of the Covid-19 pandemic on people living in disadvantaged areas in Ireland. The results indicate that Pandemic Unemployment Payment (PUP) rates were higher in more deprived areas during lockdown periods and that woman, on average, receive PUP for a slightly longer duration than men. Further, female unemployment has a negative and statistically significant relationship with the length of PUP claims. The findings show that average PUP durations tend to be shorter in areas with a higher share of individuals with lower education levels, and in areas with historically higher levels of female unemployment.

Jacklyn Makaaru Arinaitwe presented work on how gender, culture, norms, and practices contributed to the unequal distribution of unpaid care work during Covid-19 in Uganda. The findings reveal that there are policy gaps in addressing the issue, as current policies don’t acknowledge the value of unpaid care work at a personal and national level. This lack of recognition and failure to come up with new ways to reduce or share women’s disproportionate burden of unpaid care work creates obstacles to girls’ education and hinder women’s economic empowerment in Uganda.

Also, on the topic of the Covid-19 pandemic impacts on women, Alessandro Toppeta presented work on the impacts of the pandemic on the role of parental beliefs in England. The results show that parents believe that the time they spend with their children is more valuable and less risky than the time children spend in formal childcare or with friends and that parents’ beliefs can predict the choices they make in investing time with their children. Further, the findings align with previous indications of the increased burden on women’s time experienced during the pandemic being a consequence of limited availability of alternative childcare options.

The Gender Divide in Education

Within the topic of gender in education, the presenters delved into the connection between education and gender roles and the importance of parental education for children’s education.

Sumit S. Deole presented work on the causal impact of education on gender role attitudes based on evidence from European datasets. The results suggest that an additional year of education prompts egalitarian gender role attitudes. Furthermore, the impact of increases in education is particularly prominent among women and, to some extent, in urban areas.

Fethiye Burcu Türkmen-Ceylan focus specifically on the importance of maternal education for children’s education in Turkey. Preliminary results indicate that maternal education has a distinctive positive impact on households’ budget allocation for children’s education among Turkish households.

Saumya Kumar also presented work on the importance of maternal education, considering the impacts of paternal education as well. The presented research finds that both maternal and paternal education reduce the gender gap in educational enrollment. However, having an educated mother is more important when it comes to increasing girls’ enrollment as compared to boys’ enrollment. The research also indicates that as mothers’ education levels rise, there is a greater increase in spendings on education for both boys and girls.

Further on the gender divide within education, Lubna Naz deliberated on how drought affects school attendance in rural Pakistan. The income decline caused by drought leads to a four-month decrease in schooling for all children, and a six-month decrease for boys. Asset ownership also has a negative impact on school attendance, suggesting a possible reverse causality or Simpson’s paradox. The combined effect of asset ownership and drought, however, has a positive impact on school attendance, Naz concluded.

Women in Academia

Gender inequalities are apparent also in the academic sphere. Liis Roosaar’s research looks into the impact of having children on women’s careers within academia. Roosaar find that becoming a mother doesn’t impact earnings per hour, but that mother’s do work fewer hours. More than four years after having a child, women in academia have lost the equivalent of two years of full-time work. Interestingly, men don’t face the same reduction in work hours after becoming fathers. The study also reveals that the career setback for women in academia after having a child is shorter compared to the general population. However, female academics experience a decline in citations as a consequence of the reduced working hours.

Barbara Będowska-Sójka’s research on women in academia focus on female representation on editorial boards of finance journals. According to Będowska-Sójka women account for 20 percent of all editors on average, with considerable variance between countries. When it comes to editor’s affiliations they are strongly concentrated in the United States, and to a lesser extent in the United Kingdom. Additionally, a small number of extremely well-connected editors sit on many boards. The gender ratio is consistent in substructures for editors that are better connected (have so-called a high degree of centrality in terms of network analysis) or editors who serve on a large number of boards, yet men outnumber women.

Female Empowerment and Access to Services

Although their research focuses on distinct topics, Fazle Rabbi and Ulrich Wohak both presented research on the overarching theme of women’s empowerment and enhanced access to goods and services.

In his paper, Fazle Rabbi and his co-authors consider a new way to support marginalized individuals, most of whom are women, through the introduction of a new donation model where development agencies provide goats to project beneficiaries. Goat ownership might help beneficiaries generate income and devote more time to education. The research results show that the proposed donation model significantly enhances the economic empowerment of participants, providing them a steady income, better access to education, and more access to the financial system – with the results being more pronounced for women.

Ulrich Wohak evaluated tampon tax reforms (efforts to reduce the taxation of menstrual hygiene products, including tampons, pads, and menstrual cups) as a means to address gender-based tax discrimination. Using transaction-level scanner data, the study finds that when countries lower their standard VAT rates, the extent to which these reductions are passed on to consumers ranges from 57 percent to 119 percent.

Concluding Remarks

The ISET conference “Gender Equality and Women’s Economic Empowerment in Time of Crisis” brought together diverse voices, perspectives, and expertise from various sectors to engage in discussions and knowledge sharing on how to advance gender equality in times of normality and in times of crises. The conference also served as a platform to inspire actionable solutions and commitments to address the multifaceted challenges women face worldwide.

List of Participants

Alessandro Toppeta – Assistant Professor at SOFI, Stockholm University, Sweden. “Parental Beliefs, Perceived Health Risks, and Time Investment in Children: Evidence from COVID-19” (in collaboration with Gabriella Conti and Michele Giannola).
Anne Devlin – Research Fellow, Economic and Social Research Institute, Ireland. “The Impact of COVID-19 on Women’s Employment in Ireland” (in collaboration with Adele Whelan, Seamus McGuinnes, Paul Redmond).
Aswathi Rebecca Asok – PhD Fellow, University of Portsmouth, United Kingdom. “Unveiling Gendered Dimensions of “Volunteerism”: The COVID-19 Story of Kerala, India”.
Barbara Będowska-Sójka – Head of Department, Poznań University of Economics and Business, Poland. “Editorial boards of finance journals: the gender gap and social networks” (in collaboration with Claudia Tarantola, C., Mare, C., Ozturkkal, B., Paccagnini, A., Perri, R., Pisoni, G., Shala, A., Skaftad´ottir, H., K.).
Davit Keshelava – Lead Economist, ISET Policy Institute.
Elizabeth Brainerd – Susan and Barton Winokur Professor of Economics and Women’s, Gender and Sexuality Studies, Brandeis University.
Eva Atterlöv – Deputy Head of Development Cooperation, Embassy of Sweden.
Fazle Rabbi – Deputy Head of School of Business, Crown Institute of Higher Education, Australia. “From Goats to Education: An Innovative Approach to Community Empowerment” (in collaboration with Laurel Jackson and Zahid Hasan).
Fethiye Burcu Türkmen-Ceylan – Research Fellow, Ahi Evran University, Turkey. “Educate a Woman, And You Educate a Generation: How Does Maternal Education Affect Intro Household Resource Allocation for Education among the Children?” (in collaboration with Ulucan, H., Çakmak, S.).
Francisco Lagos – Professor of Economics, Georgetown University, USA. “Weight, Attractiveness, and Gender when Hiring: a Field Experiment in Spain” (in collaboration with Catarina Goulão, Juan Antonio Lacomba, and Dan-Olof Rooth).
Jacklyn Makaaru Arinaitwe – Director, Ace Policy Research Institute, Uganda. “Gender, culture, norms, and practices that promote gender gaps in the allocation of time to unpaid domestic work in the context of COVID-19 in Uganda” (in collaboration with Twinomugisha David).
Kaori Ishikawa – UN Women Country Representative to Georgia.
Liis Roosaar – Lecturer at the Chair of Economic Modelling, University of Tartu, Estonia. “Child penalty in academia: Event study estimate” (in collaboration with Jaan Masso, Jaanika Meriküll, Kärt Rõigas, and Tiiu Paas).
Lubna Naz – Associate Professor, Institute of Business Administration. Pakistan. “Left High and Dry: Gendered impacts of Drought on school attainment in Rural Pakistan”.
Maria Floro – Professor Emerita Economics, American University in Washington, DC.
Michal Myck – Director, Centre for Economic Analysis (CenEA), Poland. “Pre-retirement employment protection: no harm when times are good” (in collaboration with Paweł Chrostek, and Krzysztof Karbownik).
Monika Oczkowska – Senior Research Economist, CenEA, Poland. “Patterns of harassment and violence against women in Central and Eastern Europe. The role of the socio-economic context and gender norms in international comparisons” (in collaboration with Kajetan Trzcinski and Michal Myck).
Nabamita Dutta – Professor of Economics, University of Wisconsin-La Crosse, USA. “Lockdown and Rural Joblessness in India: Gender Inequality in Employment?” (in collaboration with Kar, S.).
Nani Bendeliani – Project Analyst, UN Women Georgia.
Nino Chelidze – Program Director of Women’s Initiative for Security and Equity at Mercy Corps.
Nino Lortkipanidze – Women in Tech Ambassador for Georgia and Chief Innovation Officer at The Crossroads.
Nino Okribelashvili – Vice Rector for Research at Ivane Javakhishvili Tbilisi State University.
Ramon Cobo Reyes Cano – Professor of Economics, Georgetown University, USA. “Anticipated Discrimination and Wage Negotiation: A Field Experiment” (in collaboration with Gary Charness and Simone Meraglia).
Reina Shehi – Primary Appointment Lecturer, Epoka University, Albania. “Patterns of Geographic Gender-Based Violence in Albania” (in collaboration with Endi Tirana and Ajsela Toci).
Salome Gelashvili – Lead Economist, ISET Policy Institute, Georgia. “Gender-based violence in the South Caucasus” (in collaboration with Lobjanidze, G., Seturidze, E., Shubitidze I.).
Saumya Kumar – Assistant Professor (Economics), University of Delhi, India. “Gender Differential in Parental Investment in Education: A Study of the Factors Determining Children’s and Adolescents’ Educational Investment in India” (in collaboration with Jawaharlal Nehru).
Sumit S. Deole – Scientific Assistant, Trier University, Germany. “The Causal Impact of Education on Gender Role Attitudes: Evidence from European Datasets” (in collaboration with Zeydanli, T.).
Tamar Sulukhia – Director ISET and ISET Policy Institute.
Ulrich Wohak – Teaching and Research Associate, Vienna University of Economics and Business, Austria. Free the Period? Evaluating Tampon Tax Reforms using Transaction-Level Scanner Data (in collaboration with Kinnl, K.).
Velan Nirmala – Professor of Economics, Pondicherry University, India. “Women Empowerment and Intimate Partner Violence in India” (in collaboration with Lusome, R).

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

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

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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.
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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.
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ILO, 2020. “Survey of Women Leading Micro, Small and Medium Businesses About the Main Challenges They Face as a Result of the Coronavirus Crisis.”
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Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

How Should Policymakers Use Gender Equality Indexes?

Posted on November 13, 2018 | Policy Brief, Policy Papers

We look at the development of gender inequality in transition countries through the lens of the Gender Inequality Index (GII), which aims to capture overall gender inequality. Extending the measure back to 1990, we look at the development of the overall index as well as that of its components. We show that, even though gender inequality in transition countries for the most part has decreased since 1990, once overall development is taken in account these countries appear to fare better in 1990 than today. We also caution against relying exclusively on composite indexes to understand patterns of gender inequality. While the desire of policy makers to get one number that captures gender inequality development is understandable, weak correlations of the GII with other indexes (over years when multiple gender inequality indexes exist) as well as across sub-indexes suggests that such an approach has limitations. Finally, we emphasize the need to understand levels as well as trends and underlying mechanisms to better inform policy to improve gender equality.

On Measuring Progress

When studying economic development, or any issue really, one faces the challenge not only of finding the right way to identify and measure what are often complex changes, but also of communicating the bottom line efficiently. This naturally leads to the search for a single metric according to which we can rank progress and follow it over time. In the realm of economic development the standard measure is GDP growth. But, of course, focusing only on GDP leaves out many important dimensions of development, such as health and education.[1] In an attempt to capture these dimensions, while still arriving at a single number that measures development, the Human Development Index (HDI) was developed in the late 1980s. Since then, a number of alternative indexes capturing additional aspects of human wellbeing have been suggested; see the report by the “Commission on the Measurement of Economic Performance and Social Progress” (Stiglitz, Sen and Fitoussi, 2009).

Just as for overall development, there is great interest in single measures that capture the gender dimension of this development. Over the past decades a number of such “gender equality indexes” have been developed by international organizations such as the UNDP, the EIGE (European Institute for Gender Equality) and the WEF (World Economic Forum), to name a few.

These measures receive a lot of attention and in particular the reporting of country rankings tends to have an influence on political and policy discussions. The various indexes proposed differ in what dimensions they include (as will be explained below) and, much as a consequence of this, in the time periods they can cover. In some cases (as will also be shown below) it is possible to extend the time coverage of the indexes, but most of the times it is hard to recover the underlying data.

In this brief we summarize what the most popular indexes tell us about the development of gender equality in transition countries, contrasting these to Western European countries.[2] Whenever we have been able to find the underlying data, we also add to publicly available measures by extending indexes back to early 1990s. We then comment on the development of gender equality in transition countries and, perhaps most importantly, on why an indexes-based analysis should be interpreted with some care.

Gender Equality Before 1990

As has often been pointed out, the Soviet Union and many of the countries in Eastern and Central Europe were, at least in some dimensions, forerunners in terms of promoting gender equality (e.g., Brainerd, 2000; Pollert, 2003; Campa and Serafinelli, 2018). This was mainly due to the high participation of women in the labor market as well as the (official) universal access to basic health care and education.

However, some scholars have suggested that not all aspects of gender equality were as advanced in the countries in the Soviet Union and in Central and Eastern Europe (Einhorn, 1993; Wolchik and Meyer, 1985). Even though women were highly integrated in the labor market, they were also still expected to take care of child rearing and house work (UNICEF, 1999). The gender pay gap and gender segregation in the labor market was also similar to levels found in OECD countries. In addition, despite the high number of women in representative positions in communist party politics, women were rarely found in positions of real power in the political sphere (Pollert, 2003).

Generally speaking, while the communist regimes succeeded in promoting women’s access to the labor market and tertiary education, they failed to eliminate patriarchy (LaFont, 2001). Such a dichotomy gives rise to a broad set of questions regarding gender equality in transition countries as well as the measurement of gender equality in this context. What happened to gender equality, in relation to economic growth, during the transition, when new governments often broke with the tradition of promoting women’s employment and education? Did gender equality enhanced by communism leave a legacy or did underlying patriarchic values characterizing many of the communist societies come to dominate? How should we regard developments of indexes that try to weight several components within a context, such as that of transition countries, where these components may move in different directions from each other, given the dichotomy characterizing gender relations?

The Different Indexes

There are several different indexes that are often quoted in policy discussions. Two important measures are the Gender Development Index (GDI) and the Gender Inequality Index (GII), both calculated by the UNDP and reported annually in the Human Development Report (HDR). A third, more recent index that has received increasing attention is the World Economic Forum’s global Gender Gap Index (GGI), which is published in the yearly Gender Gap Report. These three can serve as illustrations of what gender equality indexes typically try to capture.

The Gender Development Index (GDI) essentially measures gender differences in the Human Development Index (HDI). The HDI in turn aims to capture achievements in three basic dimensions of human development: health (measured by life expectancy), knowledge (measured by expected and mean years of schooling) and living standards (measured by GNI per capita). The GDI then basically tries to assess the relative performance in these three dimensions for men and women respectively. If health (or education, or income) in the population on average goes up, this improves the HDI. But to the extent that the improvements are felt differently by men and women, this will show in the GDI. There are several potential problems with the measurement of this index, especially when it comes to dividing GNI per capita between men and women (see e.g. Dijkstra and Hanmer, 2000); on the other hand, the index offers a transparent way to connect gender inequality to the HDI measure.

The other UNDP measure, the Gender Inequality Index (GII), was reported for the first time in the 2010 Human Development Report. It was created to address some of the perceived shortcomings of its forerunner, the Gender Empowerment Index (GEM) which had been introduced together with the GDI in 1995 (see e.g., Klasen and Schuler, 2011 for problems with GDI as well as GEM). The GII measures gender inequalities in three dimensions of human development: 1) reproductive health, measured by maternal mortality and adolescent birth rates; 2) empowerment, measured by representation in parliament and secondary education among adults; and 3) economic status, measured by labor force participation. As with the GDI, the areas of health, education, and economic empowerment are present, but the index also considers some aspects of health that are more directly relevant for women, and includes a component trying to capture political participation. The economic measure of labor force participation is also somewhat easier to interpret (and measure) than GNI divided between men and women. As for the GDI, GII country-values from 1995 are available on the UNDP website. Conveniently for our purpose, most of the underlying data that the index is based on are also made available from the UNDP for the years 1990, 1995, 2000, 2005, and every year between 2010 and 2015, with the only exception of female seat share in parliaments in 1990[3]. We downloaded the latter from the World Bank indicators database[4]. We also added information on the share of women in the 1990 Polish Parliament, from the Inter-Parliamentary Union[5], and on the share of women in the 1990 Georgian “Supreme Council,” from Beacháin Stefańczak and Connolly (2015).

A third more recently developed index is the Global Gender Gap Index. This covers areas of political empowerment, health and survival, economic participation and educational attainment, as measured using 14 different variables. An indicator is available for each of the sub areas covered, which are then weighted together in an overall indicator of the gender gap. The Global Gender Gap Index is clearly more detailed and provides a more nuanced picture of existing gender gaps compared to the GDI or the GII. But this amount of detail also comes with potential costs; it is more difficult to interpret the overall index as there are more underlying components that may change simultaneously, and it is also more difficult to reconstruct the index back in time.

What Does the GII Index Tell Us About Gender Equality in Transition Economies?

Among the above mentioned indexes, we focus on the GII here. Extending this measure when possible allows us to study gender inequality starting from 1990 for a limited set of countries (we expand the sample of countries when looking at different dimensions of the GII separately below)[6]. Figure 1 reports values for the index in box plots, which show the index median, maximum, minimum, 75^th and 25^th percentile for two groups of countries: transition countries and Western-European countries. When interpreting Figure 1, recall that higher GII values imply more inequality.

Figure 1. The Gender Inequality Index in transition countries and Western Europe, 1990-2015

Source: Own calculations based mainly on UNDP data.

Figure 1 shows that based on the GII, median gender inequality is larger in transition countries than in Western Europe and has been so throughout the entire period since 1990. In both regions the index shows a decreasing trend, after an initial increase in 1995 in the transition countries. Below we will show that this is mainly due to a drop in female representation in national parliaments. The variance of the index scores has declined over time in Western Europe, while it remained mostly unchanged in the transition countries[7].

This first piece of evidence from the data is somewhat at odds with the common notion that transition countries enjoy relatively low level of gender inequality. However, two qualifications are in order here. First, transition and Western European countries are generally at different levels of development. Figure 2 displays the country groups performance in relation to their level of human development. This is done by measuring the difference between their GII ranking and their HDI ranking among all the countries with non-missing GII values in the years considered. The larger the difference, the worse the group performance in terms of gender inequality in relation to its level of development.

Figure 2. Difference between Gender Inequality Index ranking and Human Development Index ranking in transition countries and Western Europe, 1990-2015

Source: Own calculations based mainly on UNDP data.

The trends of transition countries and Western Europe are now opposite. In the former group, in 1990 the median standing in terms of gender equality was better than that in human development; this difference appears to have narrowed over time, and it is close to zero in 2015. Western European countries have instead improved their gender equality in relation to their level of overall human development over the period studied. Put differently, the gains in human development made by former socialist countries since the transition have not translated into comparable gains in gender equality as measured by the GII index.

Second, it is also important to emphasize that, as noted above, according to several scholars the socialist push in favor of gender equality was directed only to certain spheres of women’s lives, namely their economic empowerment. This suggests that a composite index can mask important contrasting patterns among its components.

In Figures 3 to 5 we document that different variables indeed paint quite diverging pictures of gender inequality in transition countries.

Figure 3. Development of adolescent births and maternal mortality, 1990-2015

Figure 4. Development of secondary education and share of women in parliament, 1990-2015.

Figure 5. Labor force participation, 1990-2015

Source: Own calculations based mainly on UNDP data.

In each figure we display box-plots for the three areas covered by the GII: health (measured by teenage births and maternal mortality), empowerment (measured by secondary education and share of women in Parliament) and labor force participation. Looking at the different variables separately also allows us to increase the number of countries significantly, since for many countries only the seat share of women in parliaments is missing in 1990.

As the figures show transition countries in 1990 displayed relatively low levels of gender inequality in labor force participation and secondary education. Over the last 25 years, they have kept improving the latter, while the former has stalled, resulting in Western European countries displaying a higher median level of gender equality in labor force participation for the first time around 2010. Reproductive health, while improving since the transition, is still far from converging to Western European standards. Finally, political representation appears to be responsible for the increase in inequality immediately after the transition that we have noted in Figure 1. While it is hard to compare the meaning of representation in the context of 1990 totalitarianisms to that of the democratic regimes emerged later, during the regime change women de facto lost descriptive representation, which was sometime guaranteed in socialist times by gender quotas (Ostrovska, 1994).

In conclusion, breaking down the GII by its components shows that, while Western European countries have invariantly improved their levels of gender equality since 1990, the trend in transition countries depends on the measure one looks at: women maintained but did not improve their relative status in the labor force, they gained more equality in education and especially in terms of reproductive health, and lost descriptive political representation.

What Does the GII Index (And Other Indexes) Not Tell Us?

The conclusion in the previous paragraph raises the question of which other areas of progress, stagnation or deterioration in gender equality in transition countries that might be overlooked in the GII index. Above, we have summarized two more indexes, the GDI and the Gender Gap Index, which focus on additional dimensions of gender inequality but are more limited in terms of time availability. For the time over which there is overlap between the available indexes, the correlation between the GII index and the GDI and the Gender Gap Index respectively, is roughly 0.60. Interestingly, such correlation is higher in the sample of western European countries (0.64 and 0.68 respectively); when the sample is limited to transition countries, the correlations are down to 0.40 and 0.50 respectively.

Several factors might account for the differences across indexes. Unlike the GII, both the GDI and the Gender Gap Index, for instance, include measures of income inequality. On the other hand, the GDI, as pointed out above, does not account for issues related to reproductive health and political representation. The Gender Gap Index is the only one to include, among the health measures, sex-ratios (typically defined as the ratio of male live births for every 100 female births). This turns out to be especially important for some of the transition countries: in the most recent Gender Gap Report, Georgia, Armenia and Azerbaijan remain among the worst-performing countries globally on the Health and Survival sub-index, due to some of the highest male-to-female sex ratios at birth in the world, just below China’s. This goes hand in hand with very high scores in terms of gender equality in enrolment in tertiary education, for which each of these countries ranks first (at par with a few other countries), having completely closed the gender gap. In fact, women are more likely to be enrolled in tertiary education than men.

The relatively low correlation among the different indexes for the group of transition countries also deserves special attention, because it might be a direct consequence of the peculiar history of women’s rights and empowerment in the region. Since some dimensions of gender equality were fostered through a top-down approach, rather than as the result of demands and needs expressed by an organized society, it is more likely that over the last thirty years elements of modernization coexisted with more traditional forms of gender inequality.

Finally, it is worth pointing out that none of the above indexes accounts for important dimensions of gender inequality such as,: gender violence, division of chores in the household, political representation at the local level, and the presence of women in STEM’s professions (where the largest job creation might happen over the next couple of decades). Once more, some of these measures might be particularly relevant for transition countries. Just to mention one example, gender violence is an urgent issue in a few of the countries in the area[8]. A case in point in this respect is Moldova: in 2017, the country ranked 30th out of 144 countries in the Gender Gap Index. Its rank for the sub-index called “Economic Opportunity and Participation” was 11[9]. The country performs especially well in terms of economic opportunity and participation because women not only participate in the labor market in almost equal rates as men, but they are also relatively fairly represented in professions traditionally less feminized elsewhere, such as “professional and technical workers” and “legislators, senior officials and managers.” At the same time, gender violence appears quite prevailing in Moldova: according to the UN, in 2014 “lifetime prevalence of psychological violence” in Moldova was of 60%. Official country statistics also report that the percentage of ever-partnered women aged 15-65 years experiencing intimate partner physical or sexual violence at least once in their lifetime in 2011 was 46%[10].

While limited in scope, the example above illustrates how some of the available indexes might not capture some important drivers of gender inequality in the region.

Conclusion

In this policy brief, we have reviewed some of the available gender inequality indexes that are commonly used in policy discussion as well as in policy-making.

We have then discussed gender inequality in transition countries focusing on one of these indexes, the Gender Inequality Index, whose span we have extended to the beginning of the transition period. Our analysis has highlighted some points to be mindful of when using comprehensive indexes to discuss gender inequality, especially in transition countries:

It can be fruitful to analyze gender inequality indexes in relation to levels of development. Some issues related to gender inequality, such as maternal mortality, are potentially addressed with a comprehensive strategy aimed at overall development. Conversely, other drivers of gender inequality, such as women’s political empowerment or gender violence, might require more targeted policy interventions, since they do not necessary go hand in hand with overall development.
While comprehensive indexes can be useful in terms of effective communication, it is often difficult to compress all the potential forms that gender inequality can take into a single index, especially over time. This is due to both conceptual issues and data limitations. Moreover, even when this is done, a comprehensive index can overshadow important sources of gender inequality if it is composed of sub-indexes that move in opposite directions.
The previous point can be especially relevant in the context of transition countries, which historically experienced a top-down approach to gender equality, the results of which in the long-term appear to be major advancements in some dimensions of women’s empowerment and contemporary potential backlash in other dimensions. In the context of transition countries, for instance, it has been argued that low levels of female representation in political institutions can be the result of women’s large participation to the labor market while division of roles in the household remained traditional. In the words of anthropologist Suzanne LaFont, “Women have been and continue to be overworked, and their lives have been over-politicized, the combination of which has led to apathy and/or the unwillingness to enter the male dominated sphere of politics. Many post-communist women view participation in politics as just one more burden.”[11] In such a context, average values of an index on gender equality might mask high achievements in economic empowerment coexisting with lack of political representation.
Identifying policies to address gender inequality in transition countries might be especially difficult because, depending on the dimension that one focuses on, the challenge at hand is different: in terms of education and employment, the policy goal appears to be maintaining current levels of equality or increasing them from relatively high initial points; the type of policies to do so are likely different than those used in Western European countries in the last 30 years, where the challenge was rather how to increase equality from relatively much lower levels. Conversely, in other dimensions the challenge is how to make major leaps forward, which move transition countries closer to Western European standards: this is the case for sex-ratios, for instance, and reproductive health more in general. The importance of initial levels and trends for policy implications also showcases how crucial it is to acquire more historical knowledge of policies, institutions, and statistics.

Overall, policy discussions and policy-making should go beyond mere descriptions of what indexes and related international comparisons tell us about gender inequality. A better knowledge and understanding of all of the drivers of gender inequality, of their historical evolution, and of their connections both with overall development and among them, is crucial to give sound policy recommendations.

References

Beacháin Stefańczak, K.Ó. and Connolly, E.(2015), ‘Gender and political representation in the de facto states of the Caucasus: women and parliamentary elections in Abkhazia’. Caucasus Survey, 3(3), pp.258-268.
Brainerd, E. (2000), ‘Women in Transition: Changes in Gender Wage Differentials in Eastern Europe and the Former Soviet Union’, Industrial and Labor Relations Review, 54 (1), pp. 138-162.
Campa, P. and Serafinelli, M. (2018), ’Politico-economic Regimes and Attitudes: Female Workers under State-socialism’, Review of Economics and Statistics, Forthcoming.
Dijkstra, A. and L. Hanmer (2000), ‘Measuring socio-economic gender inequality: towards an alternative for UNDP’s Gender-related Development Index’, Feminist Economics, Vol. 6, No. 2, pp. 41-75.
Einhorn, B. (1993), Cinderella goes to market: citizenship, gender, and women’s movements in East Central Europe, London: Verso.
Klasen, S. and Schuler, D. (2011) Reforming the Gender-Related Development Index and the Gender Empowerment Measure: Implementing Some Specific Proposals. Feminist Economics. (1) 1 – 30
LaFont, Suzanne (2001), ‘One step forward, two steps back: women in the post-communist states.’ Communist and post-communist studies 34(2), pp. 203-220.
Ostrovska, I. (1994). Women and politics in Latvia. Women’s Studies International Forum 2, 301–303.
Pollert, A. (2003), ‘Women, work and equal opportunities in post-Communist transition’, Work, Employment and Society, Volume 17(2), pp. 331-357.
Stiglitz, Joseph, Amartya Sen, and Jean-Paul Fitoussi (2009). `The measurement of economic performance and social progress revisited.’ Reflections and overview. Commission on the Measurement of Economic Performance and Social Progress, Paris.
Tur-Prats, Anna (2018). Unemployment and Intimate-Partner Violence: Gender-Identity Approach. GSE Working Paper No. 1564
Unicef. Women in transition. 1999.
UN. The World’s Women 2015.
Wolchik, S. L. and Meyer, A.G. (1985), Women, State and Party in Eastern Europe, Durham, NC: Duke University Press.

Footnotes

[1] In contrast to a common perception, economists are generally well-aware of the limitations of GDP as a measure of welfare. In fact, the reference manual of national accounts, the SNA 2008, makes this explicit in stating that there is “no claim that GDP should be taken as a measure of welfare and indeed there are several conventions in the SNA that argue against the welfare interpretation of the accounts”.
[2] By “transition countries,” we refer to all countries that were part of the Soviet Union plus the Central and Eastern European countries that were heavily influenced by the Soviet Union before 1990 (not including Albania and former Yugoslavia). Starting from this, we – as will be made clear below – sometimes limit the set of countries further depending on data availability.
[3] http://hdr.undp.org/en/data
[4] https://data.worldbank.org/indicator/SG.GEN.PARL.ZS
[5] http://archive.ipu.org/parline-e/reports/2255_arc.ht
[6] For Western Europe these countries are: Austria, Belgium, Cyprus, Denmark, Finland, France, Greece, Iceland, Italy, Luxembourg, Malta, Netherlands, Norway, Portugal, Spain, Sweden, and Switzerland. The transition countries are: Armenia, Bulgaria, Georgia, Hungary, Poland, Romania, Russian Federation.
[7] The outlier among Western countries is Malta.
[8] While explaining the sources of gender violence in the region is beyond the scope of this report, incidentally we notice that, according to recent research, female economic empowerment in a context where patriarchal values are dominant might backfire against women in the form of increased gender violence. See Tur-Prats, 2018.
[9] http://reports.weforum.org/global-gender-gap-report-2017/dataexplorer/#economy=MDA
[10] UNFPA (2015). Combatting Violence against Women and Girls in Eastern Europe and Central Asia. https://eeca.unfpa.org/en/publications/combatting-violence-against-women-and-girls-eastern-europe-and-central-asia
[11] LaFont, Suzanne (2001). One Step Forward, Two Steps Back: Women in the Post-Communist States. Communist and Post-Communist Studies, Vol. 34, pp 208.

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 Gaps in Transition – What do we learn (and what do we not learn) from gender inequality indexes?

Posted on November 12, 2018 | Policy Brief

20181112 Gender Gaps in Transition Image 01

We look at the development of gender inequality in transition countries through the lens of the Gender Inequality Index (GII), which aims to capture overall gender inequality. By extending the measure back to 1990, we show that even though gender inequality in transition countries for the most part has decreased since the fall of the iron curtain, once overall development is taken into account, transition countries did better in relation to other countries in terms of rank differences before transition. We, however, caution against relying exclusively on composite indexes to understand patterns of gender inequality. While the desire of policy makers to get one number that captures gender inequality development is understandable, weak correlations across different overall indexes, as well as across different sub-indexes that make up each index, suggest that such an approach has limitations.

Indexes of gender inequality

In the public debate of socio-economic issues there is an understandable interest in single measures that summarize complex issues, describe historical developments and allow international comparisons. The use of GDP to measure economic development is the most immediate example of this way of proceeding. The same applies to gender inequality. Over the past decades a number of “gender equality indexes” have been developed by international organizations such as the UNDP, the EIGE (European Institute for Gender Equality) and the WEF (World Economic Forum), to name a few. These measures receive a lot of attention and in particular the reporting of country rankings tends to have an influence on political and policy discussions.

In this brief, we study the development of the Gender Inequality Index (GII) in transition countries, contrasting these to Western European countries. By transition countries, we refer to all countries that were part of the Soviet Union plus the Central and Eastern European countries that were heavily influenced by the Soviet Union before 1990 (not including Albania and former Yugoslavia). Whenever we have been able to find the underlying data, we extend the GII measure back to the early 1990s. This extension allows us to measure the development of gender inequality through the lens of a single index since the beginning of the transition. We then discuss what the GII tells us about gender inequality in transition, but also – perhaps more importantly – what it does not tell us. Our analysis is discussed as well as shown in some more detail in our forthcoming companion FREE Policy Paper.

The Gender Inequality Index

The GII was reported for the first time in the 2010 Human Development Report. It measures gender inequalities in three dimensions of human development: 1) reproductive health, measured by maternal mortality and adolescent birth rates; 2) empowerment, measured by representation in parliament and secondary education among adults; and 3) economic status, measured by labor force participation.

GII country-values from 1995 are available on the UNDP website. Conveniently for our purpose, most of the underlying data that the index is based on are also made available from the UNDP for the years 1990, 1995, 2000, 2005, and every year between 2010 and 2015, with the only exception of the female seat share in Parliament in 1990. Using the UNDP data, and data on the female seat share in Parliament in 1990 from additional sources (see the FREE Policy Paper for a list of sources), we obtain values for the GII from the beginning of the transition in 1990 until 2015.

What does the GII index tell us about gender equality in transition economies?

Figure 1 reports values for the GII index in box plots, which show the index 25^th and 75^th percentile (respectively bottom and top of the box), its median (horizontal line in the box), its maximum and minimum (whiskers), and outliers (dots) for two groups of countries: transition countries and Western-European countries. We have reconstructed the values of the GII index for a limited set of countries within these groups (see the note to Figure 1 for the list of countries). When interpreting Figure 1, recall that higher GII values imply more inequality.

Figure 1. The Gender Inequality Index in transition countries and Western Europe, 1990-2015

Source: Own calculations based mainly on UNDP data. The transition countries are: Armenia, Bulgaria, Georgia, Hungary, Poland, Romania, and the Russian Federation. For Western Europe the countries are: Austria, Belgium, Cyprus, Denmark, Finland, France, Greece, Iceland, Italy, Luxembourg, Malta, the Netherlands, Norway, Portugal, Spain, Sweden, and Switzerland.

Figure 1 shows that based on the GII, median gender inequality is larger in transition countries than in Western Europe and has been so throughout the entire period since 1990. In both regions, the index shows a decreasing trend, after an initial increase in 1995 in the transition countries. As we show in the Policy Paper, this decrease is mainly due to a drop in female representation in national parliaments. The variance of the index scores has declined over time in Western Europe, while it remained mostly unchanged in the transition countries.

The evidence from the GII is somewhat at odds with the common notion that transition countries enjoy relatively low level of gender inequality. However, it is important to notice that transition and Western European countries are generally at different levels of development. Figure 2 displays the country groups’ performance in relation to their level of human development. This is done by measuring the difference between their GII ranking and their Human Development Index ranking (HDI) among all the countries with non-missing GII values in the years considered. The HDI is an UNDP-developed measure of overall human development. See the policy paper for details about its measurement. The larger the difference between GII- and HDI-ranking, the worse the group performance in terms of gender inequality in relation to its level of development.

Figure 2. Difference between Gender Inequality Index ranking and Human Development Index ranking in transition countries and Western Europe, 1990-2015

Source: Own calculations based mainly on UNDP data.

The trends between transition countries and Western Europe are now opposite. In 1990, the median standing in terms of gender inequality was better than that in human development for transition countries, and the relative level of gender inequality was lower than in Western Europe. The (negative) difference between GII and HDI ranking however appears to have narrowed over time, and it is close to zero in 2015. Western European countries have instead improved their gender equality ranking in relation to their ranking in terms of human development over the period studied. Put differently, the ranking improvement in terms of human development in former socialist countries since the transition have not translated into comparable gains in gender equality ranking as measured by the GII index.

It is also important to emphasize that, according to several scholars, a dichotomy in terms of gender relations existed in transition countries during the socialist period. This is because on one hand the socialists put substantial into effort to empower women economically (see e.g. Brainerd, 2000; Pollert, 2003; Campa and Serafinelli, 2018), but on the other hand they failed to eliminate patriarchy (LaFont, 2001). This suggests that a composite index can mask important contrasting patterns among its components. In the Policy Paper we uncover such contrasting patterns. By looking separately at the different components of the GII index, we show that while Western European countries have invariantly improved their levels of gender equality since 1990, the trend in transition countries depends on the measure one looks at: Women maintained, but did not improve, their relative status in the labor force. They gained more equality in education and especially in terms of reproductive health, and lost descriptive political representation.

Conclusion

In this policy brief we have studied the development of gender inequality in transition countries through the lens of the Gender Inequality Index, whose span we have extended to the beginning of the transition period. We have shown that, based on this index, gender inequality has decreased since 1990 in transition countries, a trend which is common to that in Western Europe. However, once the changes in overall development during this period are taken into account, it appears that transition countries fared better in 1990 than today. Our analysis thus shows that analyzing gender inequality indexes in absolute terms and in relation to levels of development can deliver different conclusions. The factors that account for these differences should be kept in mind in policy discussions and policy-making. Some issues related to gender inequality, such as maternal mortality, are potentially addressed with a comprehensive strategy aimed at overall development. Conversely, other drivers of gender inequality, such as women’s political empowerment, do not necessary go hand in hand with overall development, and might therefore require more targeted policy interventions.

We have also cautioned the reader about the limitation of using comprehensive indexes to describe developments in gender inequality. A comprehensive index can overshadow important sources of gender inequality if it is composed of sub-indexes that move in opposite directions. This point can be especially relevant in the context of transition countries, which historically experienced a top-down approach to gender equality, the results of which in the long-term appear to be major advancements in some dimensions of women’s empowerment and contemporary potential backlash in other dimensions. It has been argued, for instance, that low levels of female representation in political institutions in transition countries can be the result of women’s large participation in the labor market while the division of roles in households remained traditional. In the words of anthropologist Suzanne LaFont (2001), “Women have been and continue to be overworked, and their lives have been over-politicized, the combination of which has led to apathy and/or the unwillingness to enter the male dominated sphere of politics. Many post-communist women view participation in politics as just one more burden”. In such a context, average values of an index of gender equality might mask high achievements in economic empowerment coexisting with lack of political representation.

References

Brainerd, E. (2000), ‘Women in Transition: Changes in Gender Wage Differentials in Eastern Europe and the Former Soviet Union’, Industrial and Labour Relations Review, 54 (1), pp. 138-162.
Campa, P. and Serafinelli, M. (2018), ’Politico-economic Regimes and Attitudes: Female Workers under State-socialism’, Review of Economics and Statistics, Forthcoming.
LaFont, Suzanne (2001), ‘One step forward, two steps back: women in the post-communist states.’ Communist and post-communist studies 34(2), pp. 203-220.
Pollert, A. (2003), ‘Women, work and equal opportunities in post-Communist transition’, Work, Employment and Society, Volume 17(2), pp. 331-357.

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.