Tag: gender equality
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.
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?
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 25th and 75th 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.
Women Entrepreneurs in Belarus: Characteristics, Barriers and Drivers
This policy brief summarizes the results of the research on aspects of female entrepreneurship in Belarus. The aim of this work was to shed a light on what the features of female-owned business in Belarus are and whether there are any differences in the motives and barriers it faces compared with male-owned companies. Results show that female-owned companies are smaller in size, less likely to grow fast and less effective in the monetization and promotion of their innovative products and ideas. This is partly due to differences in social roles, motives, decision-making process and macroeconomic factors.
Women’s entrepreneurship is not just a question of gender equality but one of the sources for the sustainable economic development of the country. The presence of women among decision makers is beneficial for companies’ performance, effectiveness and innovativeness, and impacts the growth of profitability of the company (Akulava, 2016; Noland et al., 2016).
Little is known about the state of women’s engagement in economic governance in Belarus. According to the 5th wave of the BEEPS survey conducted by the World Bank, female top managers operate in around 32.7% of Belarus’ firms and 43.6% of firms have women among their owners (The World Bank, 2013). At the same time EBRD research shows that, on average, for every 10 men taking loans for the development of their own enterprise, only one woman did. Furthermore, the probability of loan rejection is 55% higher for women than for men in Belarus (these average numbers were presented by EBRD representatives during the conference “Business Territory: Women’s View”, Minsk, 2017). Unfortunately there is no information on the size and purpose of the loans, but potentially this may be a sign of discrimination and constraints on women’s economic activity.
We tried to expand the understanding of the role of women in Belarus’ private sector and to uncover individual, social, economic and cultural barriers that affect economic behavior and career choices of women, as well as introduce new drivers for female entrepreneurship in Belarus.
For this purpose we conducted interviews in 3 focus groups with the involvement of women entrepreneurs and also ran a survey that covered 407 owners and top decision-makers in the small and medium enterprises (SMEs).
The data analysis showed that around 30% of businesses belong to women (Table 1). Women tend to choose to operate in wholesale/retail trade, manufacturing, and medical/social services. Trade is the most popular with 28.9% of female-owned companies being part of this industry, while manufacturing stays second (10.1%). Trade also attracts the largest share of the male-owned companies (29.6%), next go manufacturing (23.9%) and construction (18.9%).
Table 1. Sectoral distribution by gender of the owner
| Female-owned | Male-owned | |
| Share in total sample (%) | 30.3 | 69.7 |
| Sectoral distribution | ||
| Trade | 29.0 | 29.6 |
| Manufacturing | 10.1 | 23.9 |
| Construction | 7.3 | 18.9 |
| Medical and social services | 8.7 | 1.3 |
| Hotel and catering | 8.7 | 2.5 |
| Transport | 7.3 | 10.1 |
| Other | 29.0 | 13.8 |
Innovative behavior changes slightly depending on the gender of the owner (33.3% of female- and 38.9% of male-owned companies have implemented innovations during the last 3 years). The measure of implemented innovative activities includes information on whether the company introduced any radical or incremental innovation (product/service/novelty in business processes/new strategy) during the last three years.An average female-owned firm grows much slower than male-owned business (Table 2). The annual sales gain and the sales gain over the last 3 years are 4 times and 2 times smaller respectively. The average number of employees is also smaller among female-owned companies (10 vs. 17 employees). On average, the owner of the male-owned firm has almost 15 years of relevant working and 13 years of managing experience. Similar characteristics for female owners are 12.8 and 9.7 respectively.
However, the realization of the implemented innovations as well as their relevance look more successful among the male-owned businesses. According to the answers in the survey, the profit share due to implemented innovations equals 28.8% among male-owned businesses and just 16.4% among female-owned. Thus, the major part of return is generated by the established business model and not the novelty.
Table 2. Business characteristics by gender of the owner
| Female-owned | Male-owned | |
| Sales growth 1yr (%) | 7.6 | 27.1 |
| Sales growth 3yr (%) | 18.4 | 36.1 |
| Size of the company (employees) | 10.6 | 17.3 |
| Age of the company (years) | 8.8 | 10.2 |
| Relevant experience of the owner (years) | 13 | 14.7 |
| Managing experience of the owner (years) | 9.7 | 12.8 |
| Owners with a higher education (%) | 91.3 | 86.2 |
| Implemented innovation (%) | 33.3 | 38.9 |
| Profit share of implemented innovations (%) | 16.4 | 28.8 |
One of the potential reasons for differences in characteristics and performance indicators between genders is self-selection, meaning that women are choosing less productive sectors in order to have more flexibility in balancing various social roles they play. In order to check for this, we compare the characteristics mentioned above in three different sectors (manufacturing, wholesale/retail trade and medical/social services) (Table 2a). The male-owned companies form the majority in the manufacturing sector, while medical/social services industry is mostly presented by female-owned business. Finally, the wholesale/retail trade sector is located somewhere in between and is well presented by both female- and male-companies.
Table 2a. Business characteristics by gender of the owner in manufacturing, wholesale/retail trade and medical/social services
| Wholesale/Retail Trade | Manufacturing | Medical and social services | ||||
| Female-owned | Male-owned | Female-owned | Male-owned | Female-owned | Male-owned | |
| Sales growth 1yr (%) | 9.8 | 31 | 2 | 26.2 | 10 | n/a |
| Sales growth 3yr (%) | 16.4 | 37.9 | 5.6 | 42.3 | 17.5 | n/a |
| Size of the company (employees) | 5.9 | 14 | 23.7 | 19.8 | 13 | 8.5 |
| Age of the company (years) | 8.8 | 7.8 | 16.1 | 9.2 | 12.6 | 16 |
| Relevant experience of the owner (years) | 13 | 13.8 | 15.3 | 14.8 | 15.2 | 16 |
| Managing experience of the owner (years) | 9.8 | 11.2 | 12.3 | 13.3 | 10.3 | 22 |
| Owners with a higher education (%) | 85 | 83 | 100 | 89.5 | 100 | 50 |
| Implemented innovation (%) | 35 | 34.1 | 57.1 | 57.9 | 16.7 | 50 |
| Profit share of implemented innovations (%) | 2.5 | 25 | 30 | 34.1 | n/a | n/a |
There are differences in size and age of the businesses subject to the industry of the businesses. However, controlling for industry does not reveal any significant changes in the picture in terms of companies’ performance and effectiveness. Male-owned firms are still growing faster and are more successful in promoting implemented innovations Thus, this is likely not an issue of self-selection but of the way male and female owners operate their businesses.
The analysis revealed a number of internal and external barriers creating obstacles for doing business that breaks down into the following categories: social roles, educational patterns, decision-making process and general macroeconomic factors.
Women’s social roles in Belarus
Women in Belarus are mainly at the wheel of domestic responsibilities, which are rarely shared with male partners. According to the survey results, 40% of female and just 9% of male entrepreneurs are responsible for at least 75% of family duties (Table 3). 37% of female and only 0.74% of male owners said that they are in charge for taking care of kids. The same is true for the responsibility to stay at home when kids are sick (32.6% vs. 1.28).
Table 3. Distribution of domestic responsibilities by gender of the owner
| Women | Men | |
| Family duties | ||
| less than 25% | 10.91 | 37.5 |
| around 50% | 49.10 | 53.5 |
| more than 75% | 40.00 | 9.00 |
| Kids | ||
| taking care of kids | 36.96 | 0.74 |
| staying at home, when kids are sick | 32.61 | 1.48 |
At the same time, participants of the focus groups admitted that particularly childbirth motivated them to start their own business with flexible working hours and the possibility to work from home, which is generally not possible in corporate business in Belarus. Thus balancing between family and business becomes challenging, impacting career decisions. That motive also appeared in the survey where on average 13% of female and 2.5% of male owners started businesses in order to combine work with parenting. This trend does not change much if we control for industry.
Education
There is no significant gender difference in the educational level of business owners. According to the survey data, 91.3% of female and 86.2% of male owners have a university degree or higher. However, the established social role models of Belarusian women influence both their career and educational choices. Usually girls tend to choose education in arts and humanities, law or economics, rarely going to technical universities. Lack of technical background further prevents their access into hi-tech profitable industries.
Business and economic environment
During the interviews, women stated that “Both men and women businesses face generally the same obstacles in starting up, operational management and strategic development. But in an unfriendly environment – mostly men survive”. Similar messages were obtained from the survey, with almost no significant difference in the estimation of barriers was revealed. The main external barriers mentioned were government control (32.2% of female and 29.3% of male owners), administrative burden (44.1% vs. 41.1%) and tax system (33.5% and 30.5%) (Table 4). Almost all barriers were equally mentioned by the respondents except for corruption. Corruption is the only obstacle that differs between men and women, pointed out by 50% of women, while just 12% of men considered it a problem. We interpret it as women being more risk-averse and less likely do bold and dangerous actions in business like bribing. That corresponds to the literature, which finds women more risk-averse than men (Castillo and Freer, 2018; Croson and Gneezy, 2009).
Table 4. Main obstacles and motives for doing business by gender of the owner
| Women | Men | |
| Main barriers | ||
| Government control | 32.2 | 29.3 |
| Administrative burden and legal system | 44.1 | 41.1 |
| Tax system | 33.5 | 30.5 |
| Corruption | 49.7 | 11.8 |
| Human capital | 16.1 | 17.1 |
| Unfair competition | 28.5 | 26.9 |
| Motivation to start-up business | ||
| Sudden business opportunity | 47.8 | 42.8 |
| Willingness to earn more | 29 | 34.6 |
| No chance to continue the previous activity | 14.5 | 13.2 |
| Improvement of state’s attitude to entrepreneurs | 13 | 13.2 |
| Possibility to combine work and parenting | 13 | 2.5 |
Conclusion
The statistical evidence showed that female-owned businesses are smaller in size and grow more slowly compared with male-owned competitors. There are no signs of gender differences in entrepreneurial innovativeness. However, the monetization of implemented innovations is more successful among male-owned companies.
Altogether, the barriers of female entrepreneurship in Belarus are associated with the huge burden of household duties and childcare; hindered access to technical and business education; lack of managerial experience and industry knowledge. The existing exogenous barriers, excessive control, contradictory regulations and unfriendly entrepreneurial ecosystems are seen as additional constraints and contribute to the quality and dynamics of female business.
The obtained results confirm the necessity for adding a gender perspective to SME’s policy support in Belarus as well as for taking it into account when estimating the potential effects of business support programs and policies.
Further research of women entrepreneurship, collection of reliable statistics, comparison of the results with other transition countries are vital. These will give an encouragement to new gender specific initiatives and will contribute to economic growth and innovative perspectives of Belarus.
References
- Akulava, M. (2016a). Gender and Innovativeness of the Enterprise: the Case of Transition Countries. Working Paper No. 31.
- Castillo, M. and M. Freer. (2018). Revealed differences. Journal of Economic Behavior & Organization, 145: 202-217.
- Croson, R. and U. Gneezy. (2009). Gender Differences in Preferences. Journal of Economic Literature, 47(2): 448-474.
- Noland, M., Moran, T. and B. R. Kotschwar. (2016). Is gender diversity profitable? Evidence from a global survey. Peterson Institute for International Economics. Working Paper No. 16-3.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Economic Gender Equality Issues in Transition Economies
Until a couple of decades ago, gender was almost a non-topic within development economics.[1] But in the 1990s research gradually showed that gender inequality could have substantial impact on macroeconomic outcomes. At the same time it became clear that women and men were hit differently by economic shocks.[2] These insights triggered an unprecedented focus on gender both in research and at the policy level – see Duflo (2012) for a brilliant overview with a developing country focus. The largest collective action process in history targeted at reducing world poverty, the Millennium development goals, focused on gender inequalities in several dimensions when enacted in year 2000.[3]
In the so-called transition economies, economic gender issues came on the agenda in the late 1990s as it became evident that the transition process had affected men and women differently – see e.g. Dijkstra (1997) – and that these growing gender inequalities had important humanitarian and economic costs. For instance, in many transition economies men’s mortality skyrocketed in the 1990s while the gender wage gap rapidly increased.[4] In particular, Pastore and Verashchagina (2011) show that the gender wage gap in Belarus doubled during the decade from 1996 to 2006, partly as a result of women’s increased segregation into low-wage industries.
From a gender perspective, the Soviet model had focused on full employment for both men and women, but without aspiring to dismantle traditional gender roles. Women therefore tended to work full time alongside with men, while remaining primary caretakers of children and household. The differences in gender equality were, however, significant across the Eastern and Central European countries already before the transition process started. It is thus essential to carry out country-specific analysis of gender equality so as to fully account for context-specific institutional, economic and cultural aspects.
This paper aims to provide a short overview of research on economic gender inequality that might be of particular relevance to transition economies. Given the extensive literature on gender inequality on the one hand and transition economies on the other, this report hopes to serve as an introduction and therefore provides extensive references to the literature to ease further reading.
The structure of the paper is as follows. Section 2 presents the efficiency gains associated with gender equality; while the subsequent section examines education from a gender perspective. Section 4 reports on the research on gender differences in the labour market, while the following section exposes how gender stereotypes lead to less competent politicians, missing women, etc., while stereotypes at the same times can be changed quickly. The report ends with an overview of current research and policy relevant questions for transition economies.
Research based on economic gender equality
Had gender equality been a universally accepted goal, no further arguments would have been needed to promote it. In this report, the presumption is that men and women are equally worthy of human rights and civil liberties. Given conflicting policy goals, scarce resources and a lack of women decision-makers, more knowledge about the economic gains associated with gender equality is needed. Furthermore, research on the economic impact of gender inequality might not only provide arguments for promoting gender equality, but can also ease the formulation of actual policies by suggesting mechanisms through which gender equality and economic development are linked.
Economists’ argument for gender equality
From an economic point of view, the main argument to strive for gender equality is that men and women on average have the same cognitive and non-cognitive abilities. Few scientists would today question the statement that the differences within genders with respect to abilities are larger than the differences across genders. In other words, men and women are in terms of innate productive capacities more similar than men among men and women among women are. As long as we define our productive capacity only in terms of brains, most would also agree on the productive equality of men and women. But brawn is often raised as a divisive trait that makes men on average more productive than women. Galor & Weil (1996) even posits that there is no reason for women to enter the formal labour market as long as brawn is more important than brains in production as an explanation as to why women were not on the formal labour market in big numbers until the event of industrialization. Albeit seductive, this line of argument has several fundamental flaws.
First of all, no formal labour market existed before the industrial revolution. In agrarian economies everyone works – men, women and children – but are seldom paid with a monetary salary and have no formal contract regulating pay and work hours. With industrialization men came to constitute the majority of the workforce early on as a consequence of women being the main caretakers, and hence not being able to work far from home once they became mothers (until the children themselves were old enough to work). Moreover, social norms prescribing women to stay at home further impeded mothers to work during certain historical phases. Ultimately, there are few occupations – historically and especially now – that were too brawn-intensive for women. Rather social norms assigned occupations according to one of the genders and occupation-specific technologies developed accordingly. As a first step in the overview on the mechanisms of economic gender inequality, follows in the next section an exposition on its relation to economic development.
Engendering economic development
Two flagship reports from the World Bank (2001, 2012A) were exclusively dedicated to the role of women in economic development.[5] The point of departure for both reports was the strong correlation between any measure of gender equality and economic development (measured for instance as GDP per capita). While it is clear that gender equality in education and formal labour force participation enhance economic growth – see e.g. Klasen (1999) and Klasen and Lamanna (2009) – it is also clear that sustained economic growth generates a new demand for women’s human capital and indirectly promotes gender equality. From a policy perspective the direction of causality is not unimportant in the short and medium run. In the very long run it is unlikely that a high-income economy can flourish without utilizing the female half of the country’s productive capacity.
Recent research – as Bandiera and Natraj (2013) and Cuberes and Teignier (2014) – indicate that the methodological problems are such that it is challenging to draw policy conclusions on the link between gender equality and economic development based on cross-country studies, and that country-specific analyses are needed to be able to formulate precise policy conclusions.
In the transition economies, gender equality varies greatly along with economic standard. There are clearly efficiency gains to be made by increasing gender equality, but each country needs to perform an analysis of which factors are most crucial to improve. For instance, Hsieh, Hurst, Jones och Klenow (2016) calculates that 15-20 per cent of GDP per capita growth during the period 1960 to 2008 can be attributed to the increased efficiency in the allocation of talent in the American economy. This increase in efficiency is mainly explained by the improved allocation of women’s talents according to Hsieh, Hurst, Jones och Klenow (2016). In a closely related study, Cuberes och Teignier (2016), it is estimated that the OECD’s GDP per capita is 15 per cent lower at present compared to a situation without gender segregation on the labour market and where equally many women and men become entrepreneurs.
In the following, the main gender differences that are central for gender equality and economic efficiency (and thereby growth) are discussed. Out of these, it has been viewed as a first priority to assure that girls and boys both get primary and possibly secondary and tertiary education. Secondly, from an economic standpoint, women’s activity on the formal labour market is essential for sustained economic development. Thirdly, gender norms and their relevance for a wide spectrum of economic (and political) issues are discussed.
Men and women’s education
At the beginning of the 1990s, there were few gender differences in terms of level of education and the labour force was highly educated in most transition economies, although there are considerable regional differences. Gender segregation in terms of field of study was relatively low and gender differences in math performance small. While in most transition countries there has been a feminization of higher education – in line with the trend in most countries in the world – in other transition economies the increase in economic gender inequalities post 1991 has led to a widening of the gender gaps in both primary and secondary schooling.[6]
While it is debated – see for instance Breierova and Duflo (2004) – that girls’ education is more important than boys’ education for economic growth, it is uncontested that a gender gap in basic education harms future possibilities of a gender equal labour market and economic gender equality in a broad sense.
On a more positive note, the general math-intensity of education in transition countries is still associated with a relatively small gender gap in math performance. In some countries, girls even have a relative advantage in math relative to boys according to Unicef (2013). This becomes of special interest, since recent research has pointed to the importance of math-intensive higher secondary studies for future labour market outcomes – see Buser, Niederle and Oosterbeek (2014). This research also suggests that young women in the Netherlands (and in other European countries) are disadvantaged by their lack of math and science interests. More generally, there is an extensive literature on the existence of stereotype threat of women in mathematics, implying that especially the most talented women shy away from mathematics due to the fear of being found lacking in terms of mathematical performance – see e.g. Spencer, Steele and Quinn (1999).[7]
In most developed countries, math-intensive sciences, engineering and computer science are heavily male-dominated fields of higher education, maybe partly as a consequence of the predominant norm of math being a “male” subject. Thus, there is ample scope to promote women in IT and technology (by more research and explicit policy) in transition economies, where the preconditions for women entering these fields are generally more advantageous. At present Mexico and Greece have the largest share of women graduates in computing (around 40 per cent) according to OECD (2014). Transition countries have the potential to reach similar levels.
Women and men in the labour market
In this section, the overall findings regarding women’s labour force participation (and how it relates to economic development) and the gender wage gap are reviewed. Gender segregation on the labour market is only briefly discussed, but the following section reviews some evidence on vertical segregation. (Gender segregation varies across cultural and technological context and thus requires a more in-depth analysis.)
Development and women’s labour force participation
Women’s labour force participation has been shown to be sensitive to production technology. Research indicates that married women’s labour force participation is U-shaped of over the industrialization process – as first documented in Goldin (1994) and in Mammen and Paxson (2000) in a developing country-context. The line of arguments goes as follows. Before industrialization, most economies had a limited formal labour market. This does not imply that men and women do not work, but rather that they work in self-subsidence farming, or in the informal labour market. As economies develop, the labour force participation of married women tends to decrease for two main reasons. As production moves out of the homes, it becomes more difficult for women to combine work and the care for children. While in agricultural economies, children simply follow the mother when she works, this becomes unfeasible as production occurs in factories and under regulated conditions both because it is practically difficult to find someone to mind the children but also socially unacceptable often for a woman to leave home and children. Moreover, as economies develop there is a strong income effect, which makes it economically possible for married women not to work. Therefore, there is a decline in married women’s labour force participation as an industrialization process occurs. As the economy continues to develop the substitution effect comes into play. By this time, both men and women are more educated and eventually the family’s loss of well-educated married women’s salary becomes notable. Therefore, as the return on education increases with industrialization, the labour force participation of married women increases.
Women’s labour force participation in general has been shown to be sensitive to the introduction of new technology and new medicines. Greenwood, Seshadri and Yorukoglu (2005) indicate that the washing machine and the vacuum cleaner made home production less time-consuming, thereby freeing up time for women to dedicate more time to formal labour market work. Moreover, Goldin and Katz (2002) and Bailey (2006) show how the introduction of the Pill made it possible for women to control and plan their fertility and thereby made labour market work more feasible. Furthermore, Albanesi and Olivetti (2016) suggest that medical progress that led to improved maternal health in the US during the period 1930-1960 positively affected women’s labour force participation. Even though technological breakthroughs might come at a specific point in time, Fogli and Veldkamp (2011) has shown that it takes time for a change in social norms to occur. More precisely, their research shows how women’s labour market entry is closely related to the spread of information from working to non-working women at the local level.
Summing up, while it is clear that there is an overall tendency of women’s labour force participation increasing as a country develops into an industrialized economy with a well-developed service sector, this development is far from automatic or linear. Therefor it is important to identify country-specific conditions, technologies and norms that might enhance or hinder women to enter the labour force.
Gender wage gap
A persistent overall gender wage gap is often mistakenly interpreted as a prime indicator of women being discriminated against in the labour market. While a gender wage gap within a specific occupation in a sector might suggest the existence of discrimination, the overall wage gap is often more of an indication of gender segregation on the labour market or of low female labour force participation.
Even though a large gender wage gap is not synonymous with gender discrimination, it is associated with economic inefficiency. By simulating a theoretical growth model of the American economy, Cavalcanti and Tavares (2016) calculate that GDP per capita in the US would be 17 per cent higher if the US would have the same (relatively low) gender wage that Sweden has.
At an international level the trends in the gender wage gap appears to be related to several differences between men and women on the labour market. One correlation in international cross-country comparisons – that for long puzzled researchers – is that countries with high female employment rates tend to have higher gender wage gaps than countries with a lower female employment rate. The expectation would, if anything, be the reversed: in countries with a high share of women in formal employment, women are more emancipated and thus do not accept a considerable gender wage gap. But Olivetti and Petrongolo (2008) convincingly show that more than half of this cross-country correlation is due to selection. In countries with a high gender employment gap, such as southern Europe and Ireland, there is a selection of high-skilled women into the labour market resulting in a relatively high average wage for women, and thus in a comparatively low gender wage gap. Another potential mechanism explaining why the gender wage gap is smaller in for instance Scandinavia than in the UK and the US would be that the overall wage distribution is more compressed and thereby the gender wage gap is mechanically smaller – see Blau and Kahn (2003).
Even in countries with small gender employment gaps, women on aggregate tend to work fewer hours on the formal labour market. Recent research in Olivetti and Petrongolo (2016) suggests that for industrialized countries it is the growth in the service sector that drives the number of hours women are working. It is further shown that half of the variation in female working hours across industrialized countries is explained by the share of the service sector.
But even as men and women work to the same extent and the same hours, in most countries occupational gender segregation on the labour market is widespread. Horizontal segregation signifies that men and women tend to work within different occupations and even sectors, while the vertical segregation implies that women to a less extent than men tend to be managers. In the next section we will examine some of the costs related to vertical gender segregation.
Gender stereotypes, political quotas and missing women
For a long time, women were underrepresented in politics around the world. This constituted a democratic problem since it implied that half of the constituency in a country was not represented politically. Therefore, quotas for women at different levels in politics have been introduced around the world with considerable success. Pande and Ford (2011) review the evidence on the Indian case, where quotas have been shown not only to increase the representation of women but also to dismantle the negative stereotypes towards female politicians – see Beaman et al (2009). As suggested in Besley et al (2017), the introduction of gender quotas in politics can considerable also improves the quality of politicians. With an exceptionally rich dataset, Besley et al (2017) show that the voluntary quota, implying that every second candidate to the local elections in Sweden in the mid 1990s was a female politician, increased the average competence of politicians. This was achieved by the quota allowing for competent women to be elected and by less competent male politicians not being re-elected.
Even though quotas to increase the share of women on corporate boards are more controversial – despite several European countries having implemented them (see European Commission, 2015)– there is ample evidence that the social norm envisioning the leader/executive to be a man further cements vertical gender segregation – see e.g. Babcock and Laschever (2003) and Reuben et al (2012). Changing leadership norms is indeed a most important measure for increasing economic efficiency at the firm and societal level. Sekkat, Szafarz and Tojerow (2015) investigate which governance characteristics at the firm level are most likely to yield a female CEO in a vast sample of developing countries and find that a female dominant shareholder as well as the firm being foreign-owned are most conducive to women at the corporate top.
Generally, gender norms are known to be persistent and difficult to change. But there are examples where stereotypes change quickly, such as when the introduction of cable television to remote rural villages in South India almost instantly wiped out the traditional son preference with the introduction of more modern gender norms – see Jensen and Oster (2009). Unfortunately, son preferences can also be intensified due to worsening economic conditions, as for instance happened in South Caucuses after the breakup of the USSR. Georgia, Azerbaijan and Armenia all experienced a significant decline in fertility after 1990 and a sharp increase in the de facto son preference, measured as of the average share of boys to girls at birth. Research – see Das Gupta (2015), Dudwick (2015), and Ebenstein (2014) – suggest that this is the outcome of a combination of factors that all concurred to emphasize sons’ larger economic capability in helping their parents economically. In times of economic crises, increased availability of ultrasound technology and abortion together with having fewer children per family, the traditional preference for sons, at least temporarily, peaked to Chinese levels (after the One-Child policy).
Economic gender analysis in transition economics
In the following, the need for sex-disaggregated data and country-specific research are discussed, as well as recent policy work on gender equality.
Data
The prerequisite for well-informed research and policy is data availability. At the international level an impressive effort has been made during the last decades to create sex-disaggregated data, and there are now many gender databases as, for instance, the World Bank’s Gender data portal (http://datatopics.worldbank.org/gender/). While there are surveys such as the Life in Transition Survey (LiTS, http://www.ebrd.com/what-we-do/economic-research-and-data/data/lits.html), Demographic and Health Services (DHS, http://dhsprogram.com) and others being made, there is still a lack of gender-disaggregated data in most transition economies.
The national Statistics Bureau should have the mission of collecting and reporting sex-disaggregated data. Moreover, it is excellent if all interesting gender statistics regularly are published in an overview report to increase accessibility both for the general public but also for policy-makers. In Sweden, Statistics Sweden biannually since 1984 publishes “Women and Men in Sweden – Facts and Figures” (http://www.scb.se/en_/Finding-statistics/Publishing-calendar/Show-detailed-information/?publobjid=27675), a much appreciated publication. Since 1989, the Swedish government publishes, in an Appendix to its annual Autumn Budget, an overview of the “Economic Allocation of Resources between Men and Women”, where both past policy and current statistics are presented. Initially, the intention was to in this way guarantee the production of sex-disaggregated statistics that was necessary for the formulation of gender-sensitive economic policies.
An even more ambitious step would be to create longitudinal micro-datasets where individuals are followed in terms of family, education, work, health and other characteristics so as to be able to fully evaluate the effect of economic policy.
Country-specific research
Gender-specific analysis of labour market conditions and economic outcomes exist for several countries, see e.g. Khitarishvili (2016). However, there is a vast array of dimensions and mechanisms within the field of research about economic gender equality in need of further investigation, particularly incorporating deep knowledge about country-specific economic circumstances.
As discussed in Section 2, the correlation between gender equality and economic development is generally strong but the direction of causality is unclear. There is therefore scope to analyse the precise nature of the gender inequality within each transition economy with respect to the driving forces of economic growth. Are there, for example, any differences in accumulation of human capital at young age between men and women? Are women able to capitalize on their human capital in the labour market? Are there regulations in place impeding women to work in certain sectors and how is the availability of childcare? Is male mortality higher than female mortality – as has been the case in some transition countries in recent years?
In Section 3 about gender inequality in human capital, there are several dimensions that need country-specific contextualization. Higher education has generally undergone a feminization during recent decades in many transition economies, but not in all. To map such trends, it is essential both to analyse whether the economy capitalizes on women’s newly gained human capital and to study why men are becoming less present in higher education. Moreover, by field of study, transition economies have been exceptionally gender equal in math from an international perspective. One could try to exploit such an advantage by channelling women into programming and IT. This could provide transition economies with a considerable comparative advantage by them using their talent pool better than most countries.
Regarding gender inequality in the labour market, there are a number of interesting research projects that must be pursued at the country level as exemplified in Section 5. For instance, in Moldova there is only a tiny gender gap in labour force participation. While this can pass as an indication of a gender equal labour market, in reality it masks a highly (horizontally and vertically) gender segregated labour market, which might also be one explanation of Moldova’s elevated rates of human trafficking – see further World Bank (2014).
Policy
Gender inequality has been perceived as one of the most important dimension to both investigate and address by part of the international organizations working with development assistance. Three major policy areas can be identified, beyond the policy initiatives addressing basic health, violence against women and trafficking: a) the labour market; b) norms; and c) political representation. Regarding gender inequalities in the labour market, the trend is now for a deeper analysis attempting to identify the mechanisms at work in the labour market – see for instance Morton et al (2014).
The policy work on social norms is innovative and often uses surveys and interviews to map gender-specific stereotypes and expectations in order to provide a background and explanation for the wide gender differences in economic outcomes. World Bank (2012B) constitutes such an example, where gender norms are contextualized and at the same time put into a cross-country perspective. Here the attempts of involving men by at least mapping their attitudes are well on their way.
Lastly, there is a considerable amount of policy work – hand in hand with the extensive research on the topic – on women’s low degree of political representation. Introducing quotas for women in parliament is not enough to assure women’s political representation as overly evident in the report by the European Commission on the topic (European Commission, 2015). Further policy work is of the essence to support and ease the implementation of quotas and other measures to assure women’s political representation actually improves.
Concluding remarks
This report touches upon main gender issues in transition economies with a focus on economic dimensions, but essential human rights issues as equal access to health care and legislation, and policies against trafficking are, of course, presupposed. Ultimately gender equality is not a women’s issue. But women are the most engaged so far and efforts must continue to involve men and make them active stakeholders.
Even with the best intentions, it remains crucial to formulate actions on the basis of research. Given that economic resources for policy interventions are limited and that we strive for having policy-impact, continuous effort has to be made to let research inform policy on how to best use available resources.
References
Albanesi, S., and C. Olivetti (2016). “Gender Roles and Medical Progress”. Journal of Political Economy 124(3): 650-695.
Alesina, Alberto, Giuliano Paola and Nathan Nunn (2013). “On the Origins of Gender Roles: Women and the Plough”, Quarterly Journal of Economics 128(2): 469-530.
Babcock, Linda and Sara Laschever (2003). Women Don’t Ask: Negotiation and the Gender Divide. Princeton University Press, Princeton.
Baden, Sally (1993). “The Impact of Recession and Structural Adjustment on Women’s Work in Selected Developing Countries”. Institute of Development Studies, University of Sussex, BRIDGE Report 15.
Bailey, Martha J. (2006). “More Power to the Pill: The Impact of Contraceptive Freedom on Women’s Lifecycle Labor Supply”. Quarterly Journal of Economics 121(1): 289-320. Uppdatering “Erratum and Addendum,”, September 2009.
Beaman, Lori, Chattopadhyay, Raghabendra, Duflo, Esther, Pande, Rohini and Petia Topalova (2009). “Powerful Women: Does Exposure Reduce Prejudice?”. Quarterly Journal of Economics 124: 1497-1540.
Bandiera, Oriana and Ashwini Natraj (2013). “Does Gender Inequality Hinder Development and Economic Growth? Evidence and Policy Implications”. World Bank Research Observer 28(2): 2-21.
Becker, Gary S., Hubbard, William H. J. and Kevin M. Murphy (2010). “The Market for College Graduates and the Worldwide Boom in Higher Education of Women”. American Economic Review 100(2): 229-33.
Besley, Tim, Folke, Olle, Persson, Torsten and Johanna Rickne (2017). “Gender Quotas and the Crisis of the Mediocre Man: Theory and Evidence from Sweden”. American Economic Review 107(8): 2204-42.
Bhattacharya, Jay, Gathmann, Christina and Grant Miller (2013). “The Gorbachev Anti-Alcohol Campaign and Russia’s Mortality Crisis”. American Economic Journal: Applied Economics 5(2): 232-60.
Blau, Francine and Lawrence M. Kahn, 2003. “Understanding International Differences in the Gender Pay Gap”. Journal of Labor Economics 21: 106-144.
Boserup, Ester (1970). Woman’s Role in Economic Development. London: George Allen & Unwin.
Breierova, Lucia and Esther Duflo (2004). “The Impact of Education on Fertility and Child Mortality: Do Fathers Really Matter Less Than Mothers?”. NBER Working paper 10513.
Buser, Thomas, Niederle, Muriel and Hessel Oosterbeek (2014). “Gender, Competitiveness, and Career Choices”. Quarterly Journal of Economics 129(3): 1409-1447.
Cavalcanti, T. och J. Tavares, 2016. “The Output Cost of Gender Discrimination: A Model-Based Macroeconomic Estimate”. Economic Journal 126: 109–134.
Cuberes, David and Marc Teignier (2014). “Gender Inequality and Economic Growth: a critical review”. Journal of International Development 26: 260–276.
Cuberes, D. och M. Teignier, 2016. “Aggregate Effects of Gender Gaps in the Labor Market: A Quantitative Estimate”. Journal of Human Capital 10(1): 1-32.
Das Gupta, Monica (2015). “’Missing Girls’ in the South Caucasus Countries: Trends, Possible Causes, and Policy Options”. Policy Research Working Paper 7236. Washington, D.C.: World Bank Group.
Djikstra, Geske, A. (1997). “Women in Central and Eastern Europe: A Labour Market Transition” in Djikstra, Geske and Janneke Plantega (eds.). Gender and Economics. London: Routledge.
Dudwick, Nora (2015). “Missing Women in the South Caucasus: Local Perceptions and Proposed Solutions”. Washington, DC: World Bank Group.
Duflo, Ester (2012). “Women Empowerment and Economic Development”. Journal of Economic Perspectives 50(4): 1051-1079.
Ebenstein, Avraham (2014). “Patrilocality and Missing Women”. Mimeo, Hebrew University of Jerusalem.
Elborgh-Woytek, Katrin et al. (2013). “Women, Work, and the Economy: Macroeconomic Gains from Gender Equity”. IMF Staff Discussion Notes No. 13/10.
European Commission (2015). “Gender Balance on Corporate Boards Europe is Cracking the Glass Ceiling”. http://ec.europa.eu/justice/gender-equality/files/womenonboards/factsheet_women_on_boards_web_2015-10_en.pdf
European Commission (2015). “Women in Power and Decision-Making in the Eastern Partnership Countries”. http://eige.europa.eu/sites/default/files/documents/gender_equality_and_decision_making_in_eap_countries_2015_-_report_and_annex_one_file.pdf
Fogli, Alessandra and Laura Veldkamp (2011). “Nature or Nurture? Learning and the Geography of Female Labor Force Participation”. Econometrica 79: 1103–1138.
Galor, Oded and David N. Weil (1996). “The Gender Gap, Fertility, and Growth“. American Economic Review 86(3): 374-38.
Goldin, C., 1994. “The U-shaped Female Labor Force Function in Economic Devlopment and Economic History”. NBER Working Paper 4707.
Goldin, Claudia and Larry F. Katz (2002). ”The Power of the Pill: Oral Contraceptives and Women’s Career and Marriage Decisions”. Journal of Political Economy 110(4): 730-770.
Greenwood, J. Seshadri, A. and M. Yorukoglu (2005). ”Engines of Liberation”. Review od Economic Studies 72(1): 109-133.
Hsieh, C.-T., Jones, C. I., Hurst, E. och P. J. Klenow (2016). ”The Allocation of Talent and U.S. Economic Growth”. Mimeo. Older version in NBER Working paper 18693.
Jensen, Robert and Emily Oster (2009). “The Power of TV: Cable Television and Women’s Status in India”. Quarterly Journal of Economics 124: 1057-94.
Kabeer, Naila (2003). Gender Mainstreaming in Poverty Eradication and the Millennium Development Goals – A handbook for policy-makers and other stakeholders. International Development Research Centre, Ottawa.
Kazandjian, Romina, Kolovich, Lisa, Kochhar, Kalpana and Monique Newiak (2016). “Gender Equality and Economic Diversification”. IMF Working Paper 16/140.
Khitarishvili, Tamar (2016). “Gender Dimensions of Inequality in the Countries of Central Asia, South Caucasus and Western CIS”. Levy Economics Institute Working Paper 858.
Klasen, Stephan (1999). “Does Gender Inequality Reduce Growth and Development? Evidence from Cross-Country Regressions”. Background paper for Engendering Development, World Bank, Washington DC.
Klasen, Stephan and Francesca Lamanna (2009). “The Impact of Gender Inequality in Education and Employment on Growth: New Evidence for a Panel of Countries”. Feminist Economics 15(3): 91-132.
Mammen, K. and C. Paxson (2000). “Women’s Work and Economic Development”. Journal of Economic Perspectives 14: 141-164.
Morton, Matthew, Klugman, Jeni, Hanmer, Lucia and Dorothe Singer (2014). Gender at Work : A Companion to the World Development Report on Jobs. Washington, DC: World Bank Group.
OECD (2015). Education at a Glance 2015: OECD Indicators. OECD Publishing, Paris.
Olivetti, Claudia and Barbara Petrongolo (2008). “Unequal Pay or Unequal Employment? A Cross-Country Analysis of Gender Gaps”. Journal of Labor Economics 26: 621-654.
Olivetti, C. and B. Petrongolo (2016). “The Evolution of Gender Gaps in Industrialized Countries”. forthcoming Annual Review of Economics.
Pande, Rohini and Deanna Ford (2011). “Gender Quotas and Female Leadership: A Review”. Background Paper for the World Development Report on Gender
Pastore, Francesco and Alina Verashchagina (2011). “When Does Transition Increase the Gender Wage Gap?”. Economics of Transition 19(2): 333-369.
Reuben, Ernesto, Rey-Biel, Pedro, Sapienza, Paola and Luigi Zingales (2012). “The Emergence of Male Leadership in Competitive Environments”. Journal of Economic Behavior and Organization 83(1): 111–117.
Sekkat, Khalid, Szafarz, Ariane and Ilan Tojerow (2015). “Women at the Top in Developing Countries: Evidence from Firm-Level Data”. IZA Discussion paper 9537.
Spencer, Steven J., Steele, Claude M. and Diane M. Quinn (1999). “Stereotype Threat and Women’s Math Performance“. Journal of Experimental Social Psychology 35: 4–28.
UNICEF (2013). Equity in Learning? A Comparative Analysis of the PISA 2009 Results in Central and Eastern Europe and The Commonwealth of Independent States. Geneva: United Nations Children’s Fund.
World Bank (2001). Engendering Development – Through Gender Equality in Rights, Resources and Voice. Washington, DC.
World Bank (2012A). World Development Report 2012: Gender Equality and Development. Washington, DC.
World Bank (2012B). On Norms and Agency Conversations about Gender Equality with Women and Men in 20 Countries. Washington, DC.
World Bank (2014). “Moldova: Gender Disparities in Endowments and Access to Economic Opportunities”. Report 76077-MD, Washington, DC.
[1] The exception was the seminal Boserup (1970).
[2] See for instance Baden (1993).
[3] See Kabeer (2003) for an overview of research in development economics and policy experience relevant to the achievement of the Millennium Development Goals from the perspective of gender equality.
[4] Research – see Bhattacharya, Gathmann and Miller (2013) – however suggests that it might have been changing alcohol policy rather than transition per se that caused the sudden increase in mortality.
[5] The IMF has published a number of reports recently, such as Elborgh-Woytek et al (2013) and Kazandjian, Kolovich, Kochhar and Newiak (2016).
[6] See for instance, Becker et al (2010) and OECD (2015).
[7] Stereotype threat is defined as when an individual perceives to be ”at risk of confirming, as a self-characteristic, a negative stereotype about one’s social group” in the seminal paper by Steele and Aronson (1995).
Traces of Transition: Unfinished Business 25 Years Down the Road?
This year marks the 25-year anniversary of the breakup of the Soviet Union and the beginning of a transition period, which for some countries remains far from completed. While several Central and Eastern European countries (CEEC) made substantial progress early on and have managed to maintain that momentum until today, the countries in the Commonwealth of Independent States (CIS) remain far from the ideal of a market economy, and also lag behind on most indicators of political, judicial and social progress. This policy brief reports on a discussion on the unfinished business of transition held during a full day conference at the Stockholm School of Economics on May 27, 2016. The event was organized jointly by the Stockholm Institute of Transition Economics (SITE) and the Swedish Ministry for Foreign Affairs, and was the sixth installment of SITE Development Day – a yearly development policy conference.
A region at a crossroads?
25 years have passed since the countries of the former Soviet Union embarked on a historic transition from communism to market economy and democracy. While all transition countries went through a turbulent initial period of high inflation and large output declines, the depth and length of these recessions varied widely across the region and have resulted in income differences that remain until today. Some explanations behind these varied results include initial conditions, external factors and geographic location, but also the speed and extent to which reforms were implemented early on were critical to outcomes. Countries that took on a rapid and bold reform process were rewarded with a faster recovery and income convergence, whereas countries that postponed reforms ended up with a much longer and deeper initial recession and have seen very little income convergence with Western Europe.
The prospect of EU membership is another factor that proved to be a powerful catalyst for reform and upgrading of institutional frameworks. The 10 countries that joined the EU are today, on average, performing better than the non-EU transition countries in basically any indicator of development including GDP per capita, life expectancy, political rights and civil liberties. Even if some of the non-EU countries initially had the political will to reform and started off on an ambitious transition path, the momentum was eventually lost. In Russia, the increasing oil prices of the 2000s brought enormous government revenues that enabled the country to grow without implementing further market reforms, and have effectively led to a situation of no political competition. Ukraine, on the other hand, has changed government 17 times in the past 25 years, and even if the parliament appears to be functioning, very few of the passed laws and suggested reforms have actually been implemented.
Evidently, economic transition takes time and was harder than many initially expected. In some areas of reform, such as liberalization of prices, trade and the exchange rate, progress could be achieved relatively fast. However, in other crucial areas of reform and institution building progress has been slower and more diverse. Private sector development is perhaps the area where the transition countries differ the most. Large-scale privatization remains to be completed in many countries in the CIS. In Belarus, even small-scale privatization has been slow. For the transition countries that were early with large-scale privatization, the current challenges of private sector development are different: As production moves closer to the world technology frontier, competition intensifies and innovation and human capital development become key to survival. These transformational pressures require strong institutions, and a business environment that rewards education and risk taking. It becomes even more important that financial sectors are functioning, that the education system delivers, property rights are protected, regulations are predictable and moderated, and that corruption and crime are under control. While the scale of these challenges differ widely across the region, the need for institutional reforms that reduce inefficiencies and increase returns on private investments and savings, are shared by many.
To increase economic growth and to converge towards Western Europe, the key challenges are to both increase productivity and factor input into production. This involves raising the employment rate, achieving higher labor productivity, and increasing the capital stock per capita. The region’s changing demography, due to lower fertility rates and rebounding life expectancy rates, will increase already high pressures on pension systems, healthcare spending and social assistance. Moreover, the capital stock per capita in a typical transition country is only about a third of that in Western Europe, with particularly wide gaps in terms of investment in infrastructure.
Unlocking human potential: gender in the region
Regardless of how well a country does on average, it also matters how these achievements are distributed among the population. A relatively underexplored aspect of transition is to which extent it has affected men and women differentially. Given the socialist system’s provision of universal access to education and healthcare, and great emphasis on labor market participation for both women and men, these countries rank fairly well in gender inequality indices compared to countries at similar levels of GDP outside the region when the transition process started. Nonetheless, these societies were and have remained predominantly patriarchal. During the last 25 years, most of these countries have only seen a small reduction in the gender wage gap, some even an increase. Several countries have seen increased gender segregation on the labor market, and have implemented “protective” laws that in reality are discriminatory as they for example prohibit women from working in certain occupations, or indirectly lock out mothers from the labor market.
Furthermore, many of the obstacles experienced by small and medium-sized enterprises (SMEs) are more severe for women than for men. Female entrepreneurs in the Eastern Partnership (EaP) countries have less access to external financing, business training and affordable and qualified business support than their male counterparts. While the free trade agreements, DCFTAs, between the EU and Ukraine, Georgia, and Moldova, respectively, have the potential to bring long-term benefits especially for women, these will only be realized if the DCFTAs are fully implemented and gender inequalities are simultaneously addressed. Women constitute a large percentage of the employees in the areas that are the most likely to benefit from the DCFTAs, but stand the risk of being held back by societal attitudes and gender stereotypes. In order to better evaluate and study how these issues develop, gendered-segregated data need to be made available to academics, professionals and the general public.
Conclusion
Looking back 25 years, given the stakes involved, things could have gotten much worse. Even so, for the CIS countries progress has been uneven and disappointing and many of the countries are still struggling with the same challenges they faced in the 1990’s: weak institutions, slow productivity growth, corruption and state capture. Meanwhile, the current migration situation in Europe has revealed that even the institutional development towards democracy, free press and judicial independence in several of the CEEC countries cannot be taken for granted. The transition process is thus far from complete, and the lessons from the economics of transition literature are still highly relevant.
Participants at the conference
- Irina Alkhovka, Gender Perspectives.
- Bas Bakker, IMF.
- Torbjörn Becker, SITE.
- Erik Berglöf, Institute of Global Affairs, LSE.
- Kateryna Bornukova, Belarusian Research and Outreach Center.
- Anne Boschini, Stockholm University.
- Irina Denisova, New Economic School.
- Stefan Gullgren, Ministry for Foreign Affairs.
- Elsa Håstad, Sida.
- Eric Livny, International School of Economics.
- Michal Myck, Centre for Economic Analysis.
- Tymofiy Mylovanov, Kyiv School of Economics.
- Olena Nizalova, University of Kent.
- Heinz Sjögren, Swedish Chamber of Commerce for Russia and CIS.
- Andrea Spear, Independent consultant.
- Oscar Stenström, Ministry for Foreign Affairs.
- Natalya Volchkova, Centre for Economic and Financial Research.
Does Gender Matter for the Innovativeness of SMEs?
This policy brief summarizes the results of an on-going research project on the gender aspect of companies’ innovativeness in transition countries. The aim of this work is to examine whether there is a gender gap in innovative behavior within the sector of small and medium-sized enterprises (SMEs). The results suggest that the propensity to innovate is higher among companies with a presence of a female owner. This finding preserves for 5 measures of innovativeness. Thus, female involvement in business might be beneficial for the innovative sustainable development of economy.
The role of small and medium-sized enterprises (SMEs) has increased lately and they are considered one of the main engines of economic growth (Radas and Bosic, 2009). Research on transition economies and development has emphasized the need for strong a SME sector, since it often acts as the backbone of the economy (Lukasc, 2005) and is the largest contributor of employment (Omar et al., 2009). Another important channel through which the SME sector contributes to development is through their innovative activities. Sustainable economic development requires competitive and successful industries. Being innovative is one way to achieve this goal. However, the innovativeness of sectors and industries depends not only on the actions of the largest companies, but also on the SME sector and individual entrepreneurs. Indeed, the latter are often argued to be more dynamic and more ambitious (Chalmers, 1989; Li and Rama, 2015).
The decision to follow an innovative strategy often depends on the company’s leader, their experience and other managerial characteristics. However, the experience of the leader is not the only factor affecting managerial actions – gender also appears to matter (Daunfeldt and Rudholm, 2012). In the absence of clear answers and knowledge about female managerial characteristics, including their innovativeness (Alsos et al., 2013), it is difficult to evaluate their role in modernizing the business society and to distinguish their competitive advantages or disadvantages over male managers and business owners.
The role becomes even more ambiguous for the transition, post-communist economies. The labor market under USSR officially provided equal rights to women. However, in practice women were treated differently than men. While women often had to do the same work as men, the patriarchal society remained with men being regarded as the main decision makers, and women being fully responsible for housework and childcare. This can explain the low presence of women in top-managerial positions and women’s weaker business ties and networks (Welter et al., 2004).
The question of gender and innovation in entrepreneurship has recently starting to attract attention. Earlier, innovativeness was strongly connected and associated with high-tech companies. Thus, innovation research mostly focused on technology-based and capital-intensive industries (Dauzenberg, 2012; Marlow and McAdam, 2012). As a result, innovation behavior in less capital-intensive SMEs was almost entirely overlooked. This can also explain the lack of focus on gender, as men usually dominated the capital-intensive industries (Ljunggren et al., 2010). In an ongoing research project, I am trying to expand the understanding of gender differences in innovation and SME entrepreneurship with a focus on transition economies and the CIS block in particular.
The idea is to estimate owners’ and CEOs propensity to implement innovations in the organization. The specification of the model follows the literature and uses a probit technique that allows for an estimation of these propensities while taking into account other influencing factors and individual characteristics of firms, their owners and CEOs, which likely affect innovative decisions. The data I use come from the 5th wave of the Business Environment and Enterprise Performance Survey (BEEPS) conducted in 2012-2013. The final dataset covered 5254 SMEs from 30 European and East Asia countries.
The main variable of interest is the innovativeness of the enterprise, proxied by 5 different indicators. The measures of implemented innovative activities are: 1) whether the firms introduced a new product or service during the last 3 years; 2) whether there was any new production process implemented; 3) whether there were any spending on research and development; 4) whether were was an introduction of a new marketing strategy and method; and 5) whether an enterprise implemented new methods in operational management. The usage of 5 indicators instead of one allows me to see whether there is any specific feature of innovativeness that differs by gender.
The list of control variables covers information on the gender of the CEO and owners, number of years of experience of the CEO, age of the firm, type of ownership, focus on internal and external markets, as well as the usage of foreign technologies and certification. I also have information on the share of skilled labor force, the share of females in the organization, and whether the organization bears additional costs on external consulting services and training of employees. Information on industry, country, size of the organization and type of residence is also available.
Unfortunately, the data lacks information on the number of owners, which will prohibit me from estimating the clear gender effects and limits the analysis to the effect of gender diversity among owners.
The obtained results (see Table 1) show that having a female as the only, or one of the, owner(s) increases the propensity of going into uncertainty and implementation of a new good/service by 4.5% in the CIS region and 6.7% in the non-CIS block. However, the effect of having a female CEO is insignificant. This finding contradicts the literature on gender differences in the willingness to take on risk (Wagner, 2001; He et al., 2007; Eckel et al., 2008; Croson and Gneezy, 2009) that mostly demonstrates that women, on average, are more risk-averse than men.
A similar effect is observed for the implementation of a new business process or marketing strategy. The only insignificant difference is the spending on R&D in CIS countries and new managerial methods in non-CIS block. However, these measures of innovativeness raise doubts regarding its applicability for SME sector. A shift from high-intense productions towards services makes it less useful to spend enormous sums of money on technological research. Instead, other innovative actions like the development of human capital are of greater importance.
Table 1. Propensity to innovate
Source: Author’s own estimation.
Conclusion
The results show that having a female owner or gender diversity in the ownership structure positively affects the propensity of the organization to follow innovative behaviors and strategies. Therefore, promoting female entrepreneurship and gender equality in ownership seem positive for increasing the innovativeness of companies, and the economy in general, in both the CIS and non-CIS block.
▪
References
- Alsos, G.A., Hytti, U., and Ljunggren, E. 2013.Gender and Innovation: State of the Art and a Research Agenda.International Journal of Gender and Entrepreneurship, 5(3):236-256.
- Chalmers, N. 1989. Industrial Relations in Japan: The Peripheral Workforce. London: Routledge.
- Croson, R. and Gneezy, U. 2009. “Gender Differences in Preferences”.Journal of Economic Literature.Volume 47, #2.
- Daunfeldt, S., O., and Rudholm, N., (2012). Does gender diversity in the boardroom improve firm performance? Department of Economics, Dalarna University, SE-781 88 Borlänge, Sweden; and HUI Research, SE-103 29 Stockholm, Sweden.
- Dautzenberg, K. 2012. Gender differences of business owners in technology-based firms.International Journal of Gender & Entrepreneurship,4:79–98.
- Eckel, C. and Grossman, P. 2008. “Men, Women and Risk Aversion: Experimental Evidence”. Handbook of Experimental Economic Results.Elsevier.Volume 1, #7.
- He, X., Inman, J.J. and Mittal, V. (2007), “Gender jeopardy in financial risk taking”, Journal of Marketing Research, 44: 414-24.
- Li, Y., and Rama, M. 2015. Firm Dynamics, Productivity Growth, and Job Creation in Developing Countries: The Role of Micro- and Small Enterprises. The World Bank Research Observer, 30: 3-38.
- Ljundggren, E., Alsos, G.A., Amble, N., Ervik, R., Kvidal, T., Wiik, R. 2010. Gender and innovation: Learning from regional VRI projects. Nordland Research Institute, Norway.
- Lukacs, E. 2005. The economic role of SMEs in world economy, especially in Europe. European Integration Studies, 4(1): 3-12.
- McAdam, M. and Marlow, S. 2008.The Business Incubator and the Female High-Technology Entrepreneur: A Perfect Match? Paper presented at the 2008 International Council for Small Business World Confrence, recipient of the 2008 Best Paper Award for Women Entrepreneurship.
- Omar, S. S., Arokiasamy, L., & Ismail, M. 2009. The background and challenges faced by the small and medium enterprises. A human resources development perspectives. International Journal of Business and Management, 4(10): 95-102.
- Radas, S., and Božić, Lj. 2009.The Antecedents of SME Innovativeness in an Emerging Transition Economy. Technovation, 29: 438-450.
- Wagner, M.K. (2001), “Behavioral characteristics related to substance abuse and risk-taking, sensation-seeking, anxiety sensitivity and self-reinforcement”, Addictive Behaviors , Vol. 26, pp. 115-20.
- Welter, F., Smallbone, D., Isakova, N., Aculai, E. and Schakirova, N. 2004. Social Capital and Women Entrepreneurship in Fragile Environments: Does Networking Matter? Paper presented at Babson College-Kauffman Foundation Entrepreneurship Research Conference, University of Strathclyde.
Gender and Development: the Role of Female Leadership
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.
What Expansion of Mandatory Schooling Can and Cannot Do in Conservative Muslim Societies
New research shows expanding mandatory schooling in conservative Muslim societies have broad positive effects on female empowerment but is not enough to overcome the significant barriers to female entry in the labor force.
Does expansion of public education empower women? A large literature documents the positive effects of education on women’s economic and social outcomes in developed countries, but we know less about its causal effects on women’s empowerment in Muslim societies where women’s participation in the labor market is limited and they often do not have control over their earnings or their own bodies (Doepke et al 2012). In fact, even though female education has been successfully expanding in many majority-Muslim countries, the number of legal rights enjoyed by women is few relative to men, and female labor-force participation remains low (UNDP 2005). The lack of a corresponding labor-force participation effect raises concerns over the efficacy of expanding education as a means of improving women’s rights in Muslim societies. On the other hand, education has been shown to have many important non-pecuniary effects outside the labor market, such as in health, marriage, and parenting style (Oreopolous and Salvanes 2011) and to the extent that these effects help empower women, they may constitute alternative mechanisms through which education may lead to women’s empowerment (even in the absence of large labor market returns). However, most of this research comes from countries and societies that are not majority-Muslim and where women do work to a larger degree. As such, disentangling non-pecuniary returns to education from its labor market (and thus pecuniary) returns is particularly challenging in most settings and whether education may empower women in the Muslim world remains an open question.
Even though scholars debate the fundamental causes for the severe degrees of gender inequality in Muslim societies, most posit a nexus of patriarchal culture, strong religious values, and restricting social norms as proximate explanatory factors. Historically, Lewis (1961) claims women’s status was “probably the most profound single difference” between Muslim and Christian civilizations. In more contemporary cross-country studies, Fish (2002) documents a negative cross-country correlation between having an “Islamic religious tradition” and female empowerment, while Barro and McCleary (2006) also show that Muslim countries tend to exhibit higher degrees of religious participation and beliefs. Comparing the effects of a business training program on female entrepreneurship among Hindu and Muslim women in India, Field et al (2010) find evidence in line with significantly stricter constraints to female labor-force participation among Muslim women. To the extent that barriers to entry due to religious values restrain women’s rights, an integral outcome of empowerment is therefore a woman’s ability to independently assert her own beliefs.
In a recent paper, Selim Gulesci and I exploit an extension of compulsory schooling in Turkey to estimate the causal effect of schooling on female empowerment (Gulesci and Meyersson 2014). Compulsory schooling laws have been extensively used to estimate returns to education in Western countries on labor market outcomes (Angrist and Krueger, 1991, Oreopoulos 2006), health and fertility (McCrary and Royer 2011, Lleras-Muney 2005, Black et al 2008) among others. We follow a similar strategy to provide meaningful causal parameters for the effect of a year of schooling on outcomes related to social status of women in Turkey, a majority-Muslim country.
In 1997, Turkey’s parliament passed a new law to increase compulsory schooling from 5 to 8 years. By this law, individuals born on or after September 1986 were bound to complete 8 years of schooling, whereas those born earlier could drop out after 5 years. Using the sample of ever-married women from the 2008 Turkish Demographic Health Survey (TDHS) we are able to observe outcomes 10 years after the law change was implemented.
We adopt a regression discontinuity (RD) design assigning treatment based on whether an individual’s month-and-year of birth was before or after the September 1986 threshold. As such, our identification strategy entails comparing cohorts born one month apart and relies on the assumption that these two groups should exhibit no systematic differences other than being subject to different compulsory schooling laws. We can thus calculate an RD treatment effect, illustrative of the causal effect of education for individuals born around the threshold.
Analysis of the sample of ever-married women focuses the RD treatment effects on a subset of the population that tends to be demonstratively poorer and more socially conservative, i.e. the very subpopulation that the reform was aimed at. In a comparison of ever- and never-married women, the reform only affected education among the former, and as a result, the exclusion of non-married women effectively means exclusion of non-compliers with the reform. This is a likely consequence of ex post single women being more likely to have attended school longer regardless of expanding reforms. We also show that the probability of selection into the married sample is not affected by the law.
Our results are as follow. First, we show the effect of the reform on women’s years of schooling. As a result of the reform, women’s average years of schooling increased by one year, and completion rates for junior-high (secondary) and high school completion increased by 24 and 8 percentage points (ppt) respectively. There is no significant impact of the reform on men’s schooling on average (mainly because the average man’s schooling in Turkey around the age threshold was already at a relatively high level). Thus, the reform effectively served to reduce the education gender gap by half.
Second, our RD estimates reveal that this additional year of schooling had significant secularizing effects. Ten years after the reform was implemented, and relative to sample means, women were 10 percent (8 ppt) less likely to wear a headscarf, 22 percent (10 ppt) less likely to have attended a Qur’anic study center and 18 percent (7 ppt) less likely to pray regularly.
Third, we find no evidence of schooling on the timing of either marriage or birth, nor on the number of children. We do however find significant effects on women’s decision rights with regards to both marriage and fertility decisions; a reform-induced year of schooling results in a 10 ppt (20 percent relative to the sample mean) increase in the likelihood of having a say in the marriage decision, and a 10 ppt (12 percent) increase in the likelihood of having a say in the type of contraceptive method adopted. We further find a reducing effect of schooling on the likelihood that a bride price was received by the women’s parents from their husband’s family upon their wedding.
Fourth, we document less pronounced and largely imprecise impacts on women’s labor market outcomes. Although our estimates indicate positive effects on non-agricultural employment in general, and self-employment in particular, these estimates are sensitive to the specification used. At the same time, we show significant positive effects of schooling on household wealth, largely driven by appliances related to women’s role as housewives. We are unable to explain this by observable increases in spousal quality, measured as husband’s years of schooling.
Altogether, our results indicate significant empowering effects of education, but whereas we document precise effects on decision rights, household wealth, and measures of social and religious conservatism, we fail to find equally concise effects on spousal and labor force outcomes. This prevents an interpretation relying exclusively on either labor market or assortative matching in the marriage market as the main channel of empowerment. In fact, an examination of heterogeneous effects reveal diverging effects depending on how socially conservative women’s backgrounds are; in rural areas, education pre-dominantly allows increased freedom to be more secular, greater decision rights over marriage, and less traditional marriages. In urban areas, education has similar effects, but also leads to increased labor force participation. We interpret this as increased education, and its associated bargaining power in the household, leading to different allocations depending on the preexisting level of women’s rights. Education may thus have only a partial effect on employment, as religious or cultural barriers to entry prevent women from realizing larger gains of education through the labor market.
Our paper adds to the research literature by providing meaningful causal parameters for the effect of a year of schooling on both social and religious outcomes for women in a majority-Muslim country. The findings point to a set of returns to schooling that take into context the socially conservative nature of the Turkish society where policies to increase schooling ultimately seem to improve women’s status (as captured by higher decision-making power and household wealth) but are unable to meaningfully break down the barriers that women face in entering the labor market, particularly in more conservative rural communities. While still having important empowerment consequences for women’s empowerment in Muslim societies, education may not be a magic bullet toward full emancipation. Policies hoping to achieve female empowerment will thus require complementary reforms in health and the labor market to address barriers to entry more directly.
References
- Denisova, I., and S.Commander, S.Commander and I. Denisova (2012), ‘Are skills a constraint on firms? New evidence from Russia’, EBRD and CEFIR/NES, mimeo
- Hausmann, R., and Klinger, B., (2007), “The Structure of the Product Space and the Evolution of Comparative Advantage”, CID Working Paper No. 146
- Volchkova, N., Output and Export Diversification: evidence from Russia, CEFIR Working Paper, 2011
- Angrist, Joshua D. and Alan. B. Krueger, 1991, “Does Compulsory Schooling Attendance Affect Schooling and Earnings?” Quarterly Journal of Economics, 106(1): 979-1014.
- Barro, Robert and Rachel McCleary, 2006, “Religion and Economy”, Journal of Economic Per- spectives, 20(2): 49-74.
- Black, Sandra, Paul Devereux, and Kjell G. Salvanes, 2008, “Staying in the Classroom and out of the Maternity Ward? The Effect of Compulsory Schooling Laws on Teenage Births”. Economic Journal, 118(530): 1025-54.
- Doepke, Matthias, and Michelle Tertilt, 2009, “Women’s Liberation: What’s in it for Men?”, Quarterly Journal of Economics, 124: 1541-91.
- Field, Erika, Seema Jayachandran and Rohini Pande, 2010, “Do Traditional Institutions Constrain Female Entrepreneurial Investment? A Field Experiment on Business Training in India”, American Economic Review Papers and Proceedings, 100: 125-29.
- Gulesci, Selim, and Erik Meyersson, 2014, “For the Love of the Republic – Education, Secularism, and Empowerment”, working paper.
- Lewis, Bernard, 1961, “The Emergence of Modern Turkey”, Oxford University Press: London.
- McCrary, Justin, 2008, “Manipulation of the Running Variable in the Regression Discontinuity
- Design: A Density Test,” Journal of Econometrics, 142(2): 698-714.
- Lleras-Muney, Adriana, 2005, “The Relationship between Education and Adult Mortality in the United States,” Review of Economic Studies, 21(1): 189-221.
- Oreopolous, Phillip, 2006, “Estimating Average and Local Average Treatment Effects of Education when Compulsory Schooling Laws Really Matter ”, American Economic Review, 96(1): 152-175.
- Oreopolous, Philip and K. G. Salvanes, 2011, “Priceless: The Nonpecuniary Benefits of Schooling”, Journal of Economic Perspectives, 25(1): 159-184.
- UNDP, 2005, “Arab Human Development Report 2005 – Towards the Rise of Women in the Arab World”.




