Tag: Labor force participation

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

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


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.


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.


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.

Vaccination Progress and the Opening Up of Economies

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In this brief, we report on the FREE network webinar on the state of vaccinations and the challenges ahead for opening up economies while containing the pandemic, held on June 22, 2021. The current state of the pandemic in each respective country was presented, suggesting that infection rates have gone down quite substantially recently in all countries of the network, except in Russia which is currently facing a surge in infections driven by the delta-version of the virus. Vaccination progress is very uneven, limited by lacking access to vaccines (primarily Ukraine and Georgia) and vaccine scepticism among the population (primarily in Russia and Belarus but for certain groups also in Latvia, Poland and to some extent Sweden). This also creates challenges for governments eager to open their societies to benefit their economies and ease the social consequences of the restrictions on mobility and social gatherings. Finally, the medium to long term consequences for labour markets reveal challenges but also potential opportunities through wider availability of workfrom-home policies. 


In many countries in Europe, citizens and governments are starting to see an end to the most intense impact of the Covid-19 pandemic on their societies. Infection and death rates are coming down and governments are starting to put in place policies for a gradual opening up of societies, as reflected in the Covid-19 stringency index developed by Oxford University. These developments are partially seasonal, but also largely a function of the progress of vaccination programs reaching an increasing share of the adult population. These developments, though, are taking place to different degrees and at different pace across countries.  This is very evident at a global level, but also within Europe and among the countries represented in the FREE network. This has implications for the development within Europe as a whole, but also for the persistent inequalities we see across countries.   

Short overview of the current situation

The current epidemiological situation in Latvia, Sweden, Ukraine, and Georgia looks pretty similar in terms of Covid-19 cases and deaths but when it comes to the vaccination status there is substantial variation.

Latvia experienced a somewhat weaker third wave in the spring of 2021 after being hit badly in the second wave during the fall and winter of 2020 (see Figure 1). The Latvian government started vaccinating at the beginning of 2021, and by early June, 26% of the Latvian population had been fully vaccinated.

Sweden, that chose a somewhat controversial strategy to the pandemic built on individual responsibility, had reached almost 15 thousand Covid-19 deaths by the end of June of 2021, the second highest among the FREE network member countries relative to population size. The spread of the pandemic has slowed down substantially, though, during the early summer, and the percentage of fully vaccinated is about to reach 30% of the population.

Figure 1. Cumulative Covid-19 deaths 

Source: Aggregated data sources from the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, compiled by Our World in Data.

Following a severe second wave, the number of infected in Ukraine started to go down in the winter of 2020, with the total deaths settling at about 27 thousand in the month of February. Then the third wave hit in the spring, but the number of new daily cases has decreased again and is currently three times lower than at the beginning of the lastwave. However, a large part of the reduction is likely not thanks to successful epidemiological policies but rather due to low detection rates and seasonal variation

In June 2021, Georgia faces a similar situation as Ukraine and Latvia, with the number of cumulative Covid-19 deaths per million inhabitants reaching around 1300 (in total 2500 people) following a rather detrimental spring 2021 wave. At the moment, both Georgia and Ukraine have very low vaccination coverage relative to other countries in the region(see Figure 5).

In contrast to the above countries, Russia started vaccinating early. Unfortunately, the country is now experiencing an increase in the number of cases (as can be seen in Figure 2), contrary to most other countries in the region. This negative development is likely due to the fact that the new Covid-19 delta variant is spreading in the country, particularly in Moscow and St. Petersburg. Despite the early start to vaccinations, though, the total number of vaccinated people remains low, only reaching 10.5% of the population.

Figure 2. New Covid-19 cases

Source: Aggregated data sources from the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, compiled by Our World in Data.

In some ways similar to Sweden, the government of Belarus did not impose any formal restrictions on individuals’ mobility. According to the official statistics, in the month of June, the rise in the cumulative number of covid-19 deaths and new daily infections has declined rapidly and reached about 400 deceased and 800 infections per one million inhabitants, respectively. Vaccination goes slowly, and by now, around 8% of the population has gotten the first dose and 5% have received the second.

There were two major waves in Poland during the autumn 2020 and spring 2021. In the latter period, the country experienced a vast number of deaths.  As can be seen in Figure 3, the excess mortality P-score – the percentage difference between the weekly number of deaths in 2020-2021 and the average number of deaths over the years 2015-2019 – peaked in November 2020, reaching approximately 115%. The excess deaths numbers in Poland were also the highest among the FREE Network countries in the Spring of 2021, culminating at about 70% higher compared to the baseline. By mid-June, the number of deaths and cases have steeply declined and 36% of the country’s population is fully vaccinated.

Figure 3. Excess deaths

Turning to the economy, after a devastating year, almost all countries are expected to bounce back by the end of 2021 according to the IMF (see Figure 4). Much of these predictions build on the expectations that governments across the region will lift Covid-19 restrictions. These forecasts may not be unrealistic for the countries where vaccinations have come relatively far and restrictions have started to ease. However, for countries where vaccination rates remain low and new variations of the virus is spreading, the downside risk is still very present, and forecasts contain much uncertainty.

 Figure 4. GDP-growth

Vaccination challenges

Since immunization plays such a central role in re-opening the economy and society going back to normal, issues related to vaccinations were an important and recurring topic at the event. The variation in progress and speed is substantial across the countries, though.

Ukraine and Georgia are still facing big challenges with vaccine availability and have fully vaccinated only 1.3% and 2.3% of the population by the end of June, respectively. Vaccination rates have in the recent month started to pick up, but both countries face an uphill battle before reaching levels close to the more successful countries.

Figure 5. Percent fully vaccinated

Other countries a bit further ahead in the vaccine race are still facing difficulties in increasing the vaccination coverage, though not so much due to lack of availability but instead because of vaccine skepticism. In Belarus, a country that initially had bottleneck issues similar to Ukraine and Georgia, all citizens have the opportunity to get vaccinated. However, Lev Lvovskiy, Senior Research Fellow at BEROC in Belarus, argued that vaccination rates are still low largely because many Belarusians feel reluctant towards the vaccine at offer (Sputnik V).

This vaccination scepticism turns out to be a common theme in many countries. According to different survey results presented by the participants at the webinar, the percentage of people willing or planning to get vaccinated is 30% in Belarus and 44% in Russia. In Latvia, this number also varies significantly across different groups as vaccination rates are significantly lower among older age cohorts and in regions with a higher share of Russian-speaking residents, according to Sergejs Gubins, Research Fellow at BICEPS in Latvia.

Webinar participants discussed potential solutions to these issues. First, there seemed to be consensus that offering people the opportunity to choose which vaccine they get will likely be effective in increasing the uptake rate. Second, governments need to improve their communication regarding the benefits of vaccinations to the public. Several countries in the region, such as Poland and Belarus, have had statements made by officials that deviate from one another, potentially harming the government’s credibility with regards to vaccine recommendations. In Belarus, there have even been government sponsored disinformation campaigns against particular vaccines. In Latvia, the main problem is rather the need to reach and convince groups who are generally more reluctant to get vaccinated. Iurii Ganychenko, Senior Researcher at KSE in Ukraine, exemplified how Ukraine has attempted to overcome this problem by launching campaigns specifically designed to persuade certain age cohorts to get vaccinated. Natalya Volchkova, Director of CEFIR at NES in Russia, argued that new, more modern channels of information, such as professional influencers, need to be explored and that the current model of information delivery is not working.

Giorgi Papava, Lead Economist at ISET PI in Georgia, suggested that researchers can contribute to solving vaccine uptake issues by studying incentive mechanisms such as monetary rewards for those taking the vaccine, for instance in the form of lottery tickets. 

Labour markets looking forward

Participants at the webinar also discussed how the pandemic has affected labour markets and whether its consequences will bring about any long-term changes.

Regarding unemployment statistics, Michal Myck, the Director of CenEA in Poland, made the important point that some of the relatively low unemployment numbers that we have seen in the region during this pandemic are misleading. This is because the traditional definition of being unemployed implies that an individual is actively searching for work, and lockdowns and other mobility restrictions have limited this possibility. Official data on unemployment thus underestimates the drop in employment that has happened, as those losing their jobs in many cases have left the labour market altogether. We thus need to see how labor markets will develop in the next couple of months as economies open up to give a more precise verdict.

Jesper Roine, Professor at SITE in Sweden, stressed that unemployment will be the biggest challenge for Sweden since its economy depends on high labor force participation and high employment rates. He explained that the pandemic and economic crisis has disproportionately affected the labor market status of certain groups. Foreign-born and young people, two groups with relatively high unemployment rates already prior to the pandemic, have become unemployed to an even greater extent. Many are worried that these groups will face issues with re-entering the labour market as in particular long-term unemployment has increased. At the same time, there have been more positive discussions about structural changes to the labour market following the pandemic. Particularly how more employers will allow for distance work, a step already confirmed by several large Swedish firms for instance.

In Russia, a country with a labour market that allowed for very little distance work before the pandemic, similar discussions are now taking place. Natalya Volchkova reported that, in Russia, the number of vacancies which assumed distance-work increased by 10% each month starting from last year, according to one of Russia’s leading job-search platforms HeadHunter. These developments could be particularly beneficial for the regional development in Russia, as firms in more remote regions can hire workers living in other parts of the country.

Concluding Remarks

It has been over a year since the Covid-19 virus was declared a pandemic by the World Health Organization. This webinar highlighted that, though vaccination campaigns in principle have been rolled out across the region, their reach varies greatly, and countries are facing different challenges of re-opening and recovering from the pandemic recession. Ukraine and Georgia have gotten a very slow start to their vaccination effort due to a combination of lack of access to vaccines and vaccine skepticism. Countries like Belarus and Latvia have had better access to vaccines but are suffering from widespread vaccine skepticism, in particular in some segments of the population and to certain vaccines. Russia, which is also dealing with a broad reluctance towards vaccines, is on top of that dealing with a surge in infections caused by the delta-version of the virus.

IMF Economic Outlook suggests that most economies in the region are expected to bounce back in their GDP growth in 2021. While this positive prognosis is encouraging, the webinar reminded us that there is a great deal of uncertainty remaining not only from an epidemiological perspective but also in terms of the medium to long-term economic consequences of the pandemic.


  • Iurii Ganychenko, Senior Researcher at Kyiv School of Economics (KSE/Ukraine)
  • Sergejs Gubins, Research Fellow at the Baltic International Centre for Economic Policy Studies (BICEPS/ Latvia)
  • Natalya Volchkova, Director of the Centre for Economic and Financial Research at New Economic School (CEFIR at NES/ Russia)
  • Giorgi Papava, Lead Economist at the ISET Policy Institute (ISET PI/ Georgia)
  • Lev Lvovskiy, Senior Research Fellow at the Belarusian Economic Research and Outreach Center (BEROC/ Belarus)
  • Jesper Roine, Professor at the Stockholm Institute of Transition Economics (SITE / Sweden)
  • Michal Myck, Director of the Centre for Economic Analysis (CenEA / Poland)
  • Anders Olofsgård, Deputy Director of SITE and Associate Professor at the Stockholm School of Economics (SITE / Sweden)

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.

From Partial to Full Universality: The Family 500+ Programme in Poland and Its Labour Supply Implications

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The implementation of the ‘Family 500+’ programme in April 2016 represented a significant shift in public support for families with children in Poland. The programme guaranteed 500 PLN/month (approx. 120 euros) for each second and subsequent child in the family and the same amount for the first child in families with incomes below a specified threshold. As of July 2019, the benefit has been made fully universal for all children aged 0-17, an extension which nearly doubled its total cost and benefited primarily middle and higher income households. We examine the labour market implications of both the initial design and its recent fully universal version. Using the discrete choice labour supply model, we show that the initial Family 500+ benefits generated strong labour supply disincentives and were expected to result in the withdrawal of between 160-200 thousand women from the labour market. The recent removal of the means test is likely to nullify this negative effect, leading to an approximately neutral impact on labour supply. We argue that when spending over 4% of GDP on families with children, it should be possible to design a more comprehensive system of support, which would be more effective in reaching the joint objectives of low child poverty and high female employment combined with higher fertility rates.


Following the 2015 parliamentary elections in Poland the ruling Law and Justice Party was quick to fulfill their campaign promise of implementing a generous quasi-universal family support programme. In April 2016, all families began receiving PLN 500 (approx. 120 euros) per month for each second and subsequent child, while households that passed an income means test were granted the same amount for their first or only child.  At a cost of nearly PLN 22 billion (5.2 billion euros, approx. 1.1% of GDP) per year, the Family 500+ benefit became the flagship reform of the Law and Justice government’s first term.

With new elections approaching in October this year, the government announced a significant expansion of the programme in May, which made it fully universal. The extended programme is nearly twice as expensive with an additional cost of PLN 18.3 billion (4.3 billion euros) per year, valuing the whole package at over 2% of GDP. This takes the total value of financial support for families with children, including family benefits and child-related tax breaks, to 4% of GDP and it means that as far as family support is concerned, the ruling party has brought Poland from one of the lowest-spending countries in the EU to one of the highest over the course of 4 years.

The initial design of the benefit had a significant impact on childhood poverty in Poland, with an absolute and relative decrease from 9.0 to 4.7 percent and 20.6 to 15.3 percent respectively between 2015 and 2017 (GUS, 2017). While a more targeted design could have made a far greater impact, these changes still reflect a significant improvement in the material situation of families with children. The policy may have also had a modest upward effect on fertility rates in the first years following its implementation, although this is difficult to assess given the parallel roll out of several other fertility-oriented policies and other changes which could have played a role in family decisions. Simultaneously, as argued in the ex-ante analysis by Myck (2016) and ex-post analysis by Magda et al. (2018), these positive outcomes came at the cost of reduced female labour market participation. This reduction primarily affected women with both lower levels of education and living outside of large urban areas (Myck and Trzciński, 2019).

The Family 500+ Reform: Design and Distributional Implications

The initial Family 500+ programme directed funds to 2.7 million families in addition to any already existing financial support and has been excluded from other means-tested support instruments.  Since families that had a net income of less than PLN 800 per month per person could receive the benefit for the first or only child, the policy had a distinct redistributive element and meant that  the bottom half of the income distribution received nearly 60% of the funds. However, the design was characterised by clear labour market disincentive effects, which were particularly strong for second earners and single parents.

In a one-child household (53.3 percent of families with children, GUS, 2016) with the first earner bringing in an income equivalent to 125% of the national minimum wage, the second earner needed only to earn PLN 940 per month in order for the family to cross the means test threshold and stop receiving the Family 500+ benefits. The benefit design is presented in Figure 1 in the form of budget constraints for the first earner (Case A) and the second earner (Case B) in a couple with one child. In the latter case the first earner is assumed to receive earnings equivalent to 125% of the minimum wage. The disincentive effects of the means test are clear in both cases and we can see that for the second earner, the benefit withdrawal comes at a very low income level – far below the national minimum wage of PLN 2100 per month. The “point withdrawal” of the benefit implied that it was enough for the family to marginally exceed the means test threshold for it to completely lose eligibility for the Family 500+ support for the first child.

The expansion of the Family 500+ programme, which came into effect in July 2019, eliminated the means-tested threshold thus making the policy fully universal. It came, however, at the cost of the redistributive character of the programme. Over 32% of the additional expenditure resulting from the universal character of the policy has been passed on to the top quintile of the income distribution and in its new version, the bottom half of households only receive 45 percent of all spending. The expansion of the programme is thus unlikely to further reduce child poverty significantly and – since its beneficiaries are mainly families with middle and high incomes – it is not expected to bring noticeable changes in fertility levels.

Figure 1: Family budget constraints for the first and second earner

Source: Authors’ calculations using the SIMPL microsimulation model.

Partial and Full Universality of the Family 500+ Programme and the Implications on Female Labour Supply

With the use of modelling tools to simulate the labour market response to changes in financial incentives to work, we have updated the initial simulations of Myck (2016) using the latest pre-reform data and examined the simulated labour supply decisions to the expanded fully universal programme, as if it were implemented instead of the initial version of the benefit. The analysis was conducted with data from the 2015 Polish Household Budget Survey, a detailed incomes and expenditure survey conducted annually by the Polish Central Statistical Office.

Table 1: Effects of the initial and the expanded Family 500+ programme on female labour supply

Results of the simulations are presented in Table 1. Simulations were conducted separately for single women, and under two scenarios for women in couples assuming that both partners adjust their behaviour (Model A) and that the labour market position of the male partner is unchanged (Model B).  The simulated labour supply response to the initial reform confirms the magnitude of earlier results and suggests an equilibrium effect of 160-200 thousand women leaving the labour force. This is also consistent with results presented by Magda et al. (2018), who found that female labour market participation decreased by approx. 100 thousand women after the policy had been in place for one year.

However, as we can see in the right-hand part of Table 1, the response to a fully universal design – modelled as if it was introduced in 2016 instead of the means-tested version – is essentially neutral. For single mothers the reduction is only about 3000, while for women in couples, the model suggests a small positive reaction under the Model A specification and a small negative one under Model B. In total, the universal design of Family 500+ benefits can be described as labour supply neutral. Since the reaction has been modelled on pre-reform data, and because some women have already withdrawn from the labour market after the introduction of the initial benefit design in 2016, the remaining uncertainty is whether the new set of incentives will motivate these mothers sufficiently to return to work.


The introduction and subsequent expansion, of the Family 500+ programme has substantially increased financial resources of families with children in Poland. The policy rollout of the initial, partially universal programme has seen substantial changes in the level of child poverty in Poland and may have contributed to a modest increase in fertility in the initial years following the introduction of the reform. The means-tested design of the benefit, however, incentivised a significant number of women to leave the labour market. One year after the introduction of the policy approximately 100,000 women were estimated to have left the labour market (Magda et al. 2018), while the equilibrium effect of the policy suggested long-run implications of over 200,000 (Myck, 2016). The updated simulation results using the latest available data suggest slightly lower, though still substantial equilibrium implications of the initial partially universal design of the Family 500+ programme in the range of between 160,000-200,000. However, as we show in our latest analysis, these labour market consequences could be reversed after the expansion of the programme to a fully universal set-up. The simulated effects of the universal design of the programme, which has been in place in Poland since July 2019, modelled as if it was implemented instead of the initial means-tested version, are broadly neutral for female labour supply. The only question is how likely the mothers who left employment in response to the initial policy will return to work given the new set of financial incentives. Considering these positive implications of the fully universal programme, one has to bear in mind that the extended programme, which will cost over PLN 40 bn per year (approx. 2% of GDP), is unlikely to contribute to the other key objectives set by the government, namely reducing child poverty and increasing fertility. Including the Family 500+ programme, the Polish government currently spends about 4% of GDP on direct financial support for families with children. Given the design of the policies which make up this family package, it seems that the joint objectives of higher fertility, reduced poverty and higher female employment could be achieved more effectively under a reformed structure of support that would be better targeted at poorer households, include specific employment incentives, and incorporate support for childcare, early education and long-term care.


This brief summarizes the results presented in Myck and Trzciński (2019). The authors gratefully acknowledge the support of the Swedish International Development Cooperation Agency, Sida, through the FROGEE project. For the full list of acknowledgements see Myck and Trzciński (2019).


  • Goraus, K. and G. Inchauste (2016), “The Distributional Impact of Taxes and Transfers in Poland”, Policy Research Working Paper 7787, World Bank.
  • GUS (2016), “Działania Prorodzinne w Latach 2010-2015, Główny Urząd Statystyczny Polish Central Statistical Office, Warsaw.
  • GUS (2017), “Zasięg ubóstwa ekonomicznego w Polsce w 2017r.”, Główny Urząd Statystyczny – Polish Central Statistical Office, Warsaw.
  • Magda, I., A. Kiełczewska, and N. Brandt (2018), “The Effects of Large Universal Child Benefits on Female Labour Supply”, IZA Discussion Paper No. 11652, IZA-Bonn.
  • Myck, M. (2016), “Estimating Labour Supply Response to the Introduction of the Family 500+ Programme”, Working Paper 1/2016, CenEA. Jacobson, L., LaLonde, R. and Sullivan, D. (1993). “Earnings losses of displaced workers”, American Economic Review, 83, pp. 685–709.
  • Myck, M. and Trzciński, K. (2019) “From Partial to Full Universality: The Family 500+ Programme in Poland and its Labor Supply Implications”, Ifo DICE report 3 / 2019.

How Should Policymakers Use Gender Equality Indexes?

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, 75th and 25th 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.


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.


  • 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.


  • [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.

Paid Work after Retirement – Does Quality of Your Main Job in the Past Matter?

20171204 Paid Work after Retirement Image 01

In this brief, we summarize the results of a recent analysis focused on identifying the key determinants of engagement in paid work after retirement based on life histories data from the Survey of Health, Ageing and Retirement in Europe (SHARE). We find a strong link between the probability of work after retirement and indicators of quality of work prior to labor market exit, such as high physical and psychosocial demands, lack of control or receiving adequate social support. These results suggest a potentially important role of job-quality regulations. We find no significant association with past experience of adequate rewards with respect to efforts in the main job, which suggests that involvement in paid work after retirement may to a lesser extent be driven by financial concerns. This might mean that policy initiatives targeted at higher level of labor market activity among retirees should stress non-material aspects of employment in later life.

The collection of data in the 7th wave of the Survey of Health, Ageing and Retirement in Europe (SHARE) proceeded in 2017, and the Centre for Economic Analysis (CenEA) has recently published a report based on information collected in previous waves of the survey. The report entitled “The Polish 50+ generation in the European context: activity, health and wellbeing” examined among other issues the determinants of labor market activity of people aged 50+ with a special focus on Poland (Myck and Oczkowska, 2017).

SHARE is a panel survey conducted every two years and focuses on health conditions, material situation and social relations of the population aged 50 years and older. In 2017, in the 7th Wave, interviews were conducted with over 80,000 participants in 26 European countries and Israel. While the survey usually focuses on contemporary conditions of respondents, the interviews in Wave 3 (the SHARE-Life conducted in 2008-2009) is concerned with respondents’ life histories and topics such as family history, mobility and work histories.

In this brief, we draw on one of the chapters from the report and present results of a analysis that combines information on the quality of the main job of the respondents’ working careers, with information on engagement in paid work among retired individuals to examine key determinants of undertaking paid work after labor market exit.

Work histories in SHARE

The life-history interview includes a series of 12 questions evaluating effort-reward imbalance in the main job of individuals’ working careers (Siegrist and Wahrendorf, 2011; Siegrist et al., 2004; 2014). Based on these questions, five dimensions of the quality of the workplace were identified: physical and psychosocial demands, control, social support and reward (see Table 1). Figure 1 presents an example of the distribution of answers to one of the questions used to define these dimensions, which asked about the extent to which the respondents’ main jobs was physically demanding. Generally, men’s past main job is more often described as physically demanding than women’s. While less than half of respondents in France and Sweden claimed physically strenuous main job, the respective measure in Poland and Greece was as high as 75%.

Table 1. Dimensions of job quality

Dimension SHARE Questionnaire Items
Physical demands

– „My job was physically demanding.”

– „My immediate work environment was uncomfortable (for example, because of noise, heat, crowding).”

Psychosocial demands – „My work was emotionally demanding.”

– „I was exposed to recurrent conflicts and disturbances.”

Control – „I was under constant time pressure due to a heavy workload.”

– „I had very little freedom to decide how to do my work.”

Social support at work – „I received adequate support in difficult situations.”

– „There was a good atmosphere between me and my colleagues.”

– „In general, employees were treated fairly.”


– „I had an opportunity to develop new skills.”

– „I received the recognition I deserved for my work.”

– „Considering all my efforts and achievements, my salary was adequate.”

Notes: answer categories: “strongly agree, agree, disagree, strongly disagree”. Source: adapted from Siegrist and Wahrendorf (2011).

Figure 1. “My job was physically demanding”

Notes: includes wave 3 respondents with at least 10 years of seniority who retired by the time of wave 6; weighted. Source: own calculation based on SHARE data waves 3 (2008-2009) and 6 (2015).

Following Wahrendorf and Siegrist (2011), for the purpose of further analysis, we construct five measures of workplace quality based on the questions listed in Table 1. For each dimension of job quality, we calculate a sum-score of answers (from 1 “strongly agree” through 2 “agree”, 3 “disagree” to 4 “strongly disagree”) to selected questions, and identify the upper (lower) tertile of observations. We create five binary indicators (with 1 meaning “yes”) describing the quality of work in the sense of high physical or psychosocial demands, lack of control, and adequate social support or adequate reward. The results are presented in Figure 2 in association with the frequency of paid work after retirement.

Figure 2. Associations between quality of work in the past and frequency of paid work after retirement

Notes: includes wave 3 respondents with at least 10 years of seniority who retired by the time of wave 6 from selected countries (CZ, FR, DE, GR, PL, ES, SE); weighted. Source: own calculation based on SHARE data waves 3 (2008-2009) and 6 (2015).

In most cases the percentage of retirees engaged in paid work was significantly higher among those positively evaluating the quality of their past workplace. The only dimension where no significant difference was found in the level of involvement in paid work was between the retirees who estimated rewards at work as adequate to their efforts and those who assessed them otherwise.

What determines paid work after retirement?

The role of the five measures of job quality was further examined using models of probability of paid work after retirement. Apart from quality indicators regarding the main job, controls included total labor market experience, unemployment incidence, as well as detailed demographics and information concerning current health status and material conditions. Odds ratios were estimated separately for men and women from a group of selected countries: Czech Republic, France, Germany, Greece, Poland, Spain and Sweden.

Higher education is positively associated with the odds of employment after retirement, but have the opposite effect for age, poor health and living in rural areas. Each additional year of labor market experience increases the odds of working after retirement, but we find no significant effect of unemployment episodes.

Both men and women without experience of high physical demands and lack of control in their main job have higher odds of working after retirement than those who declared such experiences. For example, men who did not experience highly, physically demanding main jobs have 1.4 times higher odds of work after retirement compared to those who did. The respective odds for those who did not experience lack of control are 1.9. On the other hand, high psychosocial demands and adequate social support have significant influence only among retired women. Women who did not report high psychosocial demands had 1.25 times higher odds of work after retirement, while those who received adequate support in their past job had 1.5 times higher odds. We find no significant effect of the experience of adequate rewards with respect to efforts in the main job, and similarly no significant association between material conditions and employment of retirees. Both of these may imply that involvement in paid work after retirement is to a lesser extent driven by financial concerns.

Further discussion and policy implications

Differences in the degree of engagement in paid work after retirement with respect to the assessment of past job quality suggest a potentially important role of job quality regulations. At the same time, lack of significant association between the material situation and paid work after retirement implies that policy initiatives targeted at higher levels of labor market activity among retirees may benefit from stressing the non-material aspects of employment in later life.

Results point to a strong link between quality of work in the past and probability of work after retirement, which is in line with what other studies have showed: e.g. that low quality of work in the past strongly correlates with the desire to retire as soon as possible (e.g. Dal Bianco et al., 2014). Given the demographic pressure on public finances observed or expected in many developed countries, and foreseen reductions in the generosity of pension benefits, increasing the level of engagement in paid work after labor market exit may become an important policy challenge. The results summarized in this brief suggest that governments should, on the one hand, pay attention to the labor market conditions faced by those currently employed, and on the other hand focus on a broad set of incentives to encourage employment among older generations, going beyond financial remuneration.








Gender and Development: the Role of Female Leadership

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This policy brief reports on a discussion of the role of female leadership in development held during a full day conference at the Stockholm School of Economics on June 16, 2014. The event was organized jointly by the Stockholm Institute of Transition Economics (SITE) and the Swedish Ministry for Foreign Affairs, and was the fourth installment of Development Day – a yearly development policy conference. It is well known that women fall behind men on many markers of welfare and life opportunities, both in developed and developing countries. For most indicators, though, such as education and labor force participation, both the absolute and relative position of women tend to improve with economic development. However, in some areas the beneficiary effect of raising incomes is less clear. Access to leadership positions and decision-making roles are examples of such areas. To discuss this question, the conference brought together a distinguished and experienced group of policy oriented scholars and practitioners from government agencies, international organizations, civil society and the business community.