Project: FREE policy paper
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.
Whistleblower Protections but no Rewards: EU Commission Proposes a New Directive
On the 17th of April 2018 the European Commission adopted a package of measures to increase protections for whistleblowers (European Commission Newsroom, 2018). This is good news, as whistleblower protection in Europe has been uneven and in some member states non-existent. Transparency International (2013) rated a disappointing four European countries as having adequate or extensive protection. In a report by Wolfe et al (2014), several European countries, including Germany, France and Italy, were judged to have inadequate laws with respect to several aspects of whistleblower protection, although France and Italy recently improved them considerably. Corruption, fraud of various types, and related forms of economic crime are widespread almost everywhere in the world (See e.g. Dyck et al 2014, and Global Crime Survey 2016). Criminal organizations such as drug cartels, have become increasingly sophisticated and their ability to use the international financial markets has made it ever more difficult for law enforcement agencies to discover them with more traditional law enforcement tools (see e.g. Radu 2016 for an overview). Incentivizing whistleblowers through protection and rewards can prove effective at getting information on these hard-to-detect crimes. Whistleblower protection is central for ensuring democratic values such as freedom of speech and fair elections, and recent cases also suggest that it may be central for protecting investigative journalists and their sources.
The Need for Protection and Possibly Rewards
On February 26th 2018 Ján Kuciak, a Slovakian journalist, was murdered in his home for investigating political connections to organized crime in the heart of Europe (Washington Post, 2018); Daphne Caruana Galizia was killed on 16th of October 2017 by a car bomb while she had been writing about corruption in Malta in connection with the Panama papers (Financial Times, 2018a); Maria Efimova, an employee at a private bank that claimed that her employer had illegally moved funds for Maltese politicians, is under an arrest warrant from Malta and Cyprus on seemingly unrelated charges (The Guardian, 2018); and Hervé Falciani, who blew the whistle on the bank he was working for in Switzerland that helped clients evade billions of dollars in taxes, was arrested in April in Spain after an arrest warrant issued by Switzerland on March 19th, though he has now been released on bail (Financial Times, 2018b).
While some EU countries recently improved whistleblower protection, some seem to be heading in the opposite direction. An extreme example is Germany. A provision packed into the German Data Retention Framework of 2015 allows for prison sentences of up to 3 years for the handling of “stolen data”, and journalists are no longer protected against search and seizure (European Digital Rights, 2017). This provision was included despite Germany’s problems with underreporting of corporate crime. On the need of whistleblowing in the country, consider Volkswagen’s emissions scandal in 2015 when the public learned that the company had installed defeat devices in millions of diesel cars to ‘cheat’ on environmental emissions standards and increase pollution all over the world. The response of management was to blame a set of “rouge engineers” (Congressional Hearing, 2015), while we now know that power points on how to circumvent U.S. emissions tests by a top technology executive circulated within the company as early as 2006 (New York Times, 2016). Excess diesel emissions were associated 38 000 premature deaths in 2015 (Anenberg et al, 2017), implying that whistleblowing could have saved thousands of lives, yet the wrongdoing went on for close to a decade without anyone blowing the whistle. Cheating on emissions tests also turned out to be an industry wide phenomenon.
Germany also has a history of treating whistleblowers poorly. Consider for example the case where a German nurse brought a complaint to her employer in December of 2004 over poor treatment of patients, and she was fired in January 2005. Her employer cited repeated illness as the reason for being fired, the nurse claimed that it was retaliation for speaking out about poor conditions. The nurse then filed a complaint in German Labor Court which was dismissed in August 2005. She then brought the claim to the European Convention of Human Rights, alleging that her right to expression under article 10 of the European Convention of Human Rights had been violated by her employer. She won that case in 2011, and Germany was ordered to pay the nurse 10 000 Euro in non-pecuniary damages, and 5000 for costs and expenses (Heinish V Germany 2011).
Large firms do not appear to be doing better. Even after the Siemens scandal in 2008, when the company was discovered pursuing a long-term, extensive and systematic strategy of bribing foreign governments and purchasing agencies, and promises about a drastic change in corporate governance. Recent cases suggest that the corporate culture at Siemens has not improved. Meng-Lin Liu, a compliance officer at Siemens China, brought attention to alleged kickbacks paid in connection with equipment sales to army hospitals in China to the chief financial officer for healthcare in China. He was fired after reporting internally and filed a claim alleging violations of the Foreign Corrupt Practices Act. Siemens lawyers argued that since he was no longer an employee, he was not entitled to protection under Dodd-Franks definition of “whistleblower” (Forbes, 2014).
The situation in such an important European country like Germany suggests that protection applying across all member states is needed, and the experience of other countries further suggest that protection may not be enough. In the UK, the country recognized to have some of the best protections in the EU (Wolfe 2014, Transparency International 2013), whistleblowers are still experiencing pushback. The recent case of Jes Staley, Barclays Bank’s CEO is enlightening. He ordered his security team to unveil the identity of an uncomfortable whistleblower, going so far as to request video footage of the person who bought the postage for the letter. Yet, the Financial Conduct Authority and the Prudential Regulation Authority (FiCA & PRA) decided to just fine him £642 000 – a small fraction of his pay package that year (Reuters, 2018). Cases like this suggest that the US Congress was right in pushing for rewards. The mild sanctions established by the UK regulators sent a loud and clear message to prospective whistleblowers: even in the UK, where protection was judged as high in the above-mentioned reports, a CEO that violates the law trying to uncover someone reporting his potential mismanagement (probably not to give him a premium), will just have to pay a mild fine, if he is caught of course!
In the following we review the new proposal for whistleblower protections and argue that evidence from the US suggests that financial incentives for whistleblowers may still be needed to ensure an adequate level of reporting. We then consider objections to monetary rewards which are praised by regulators in the US, while EU agencies remains hesitant. Finally, we conclude with suggestions on how to improve the European legislation.
The EU Proposed Directive Versus US Developments
The new Directive includes mandatory establishment of internal reporting channels for firms with more than 50 employees that should allow for anonymous claims (Article 5). It includes prohibition against a wide range of retaliation (Article 14); and the burden of proof is reversed in case of alleged retaliation (Article 15). Who counts as a whistleblower under the Directive is defined widely to encompass subcontractors, trainees, and people associated with a wrongdoing firm in a “work-related context” (Article 2).
The Directive is bound to improve the situation for whistleblowers given the current uneven protection. It bears similarities with the US Sarbanes-Oxley act of 2002 (SOX), but it goes beyond SOX in that it applies more broadly. Since SOX, the legal debate in the US has increasingly focused on rewards to whistleblowers as protections alone are often insufficient to ensure an adequate level of reporting.
After the financial crisis, the US concluded in the Dodd-Frank Act of 2008 that protections were insufficient, and that above and beyond protections, Dodd-Frank allows for rewards to whistleblowers who report wrongdoings in securities trading where the sanction against the wrongdoing party exceeds 1$ million.
The use of rewards was not unfamiliar to the US before Dodd-Frank. They had formerly concluded that in the tax area, whistleblowers who report tax evasion should be eligible for rewards through the Tax Relief and Health Care Act of 2006 which established the Internal Revenue Service “Office of the Whistleblower”. Although previously to 2006 whistleblowers could receive rewards at the IRS, this was entirely up to the agency’s discretion.
In the procurement area, whistleblowers are also eligible for rewards in the US under the False Claims Act (FCA) enacted in 1863. The commitment to rewards was reaffirmed in 1986 when revisions to the act reinvigorated the whistleblower or “qui tam” provisions of act (for an overview of reward programs, see Nyreröd & Spagnolo 2017).
Despite being regarded as having some of the best whistleblower protections in the world (see e.g. Wolfe et al 2014), the US did not settle for protections alone in key regulatory areas. The new EU directive does not address rewards at all which is unfortunate given their law enforcement potential if they are coupled with independent and competent judicial institutions.
Although the US experiment with whistleblower rewards is working, the only EU institution to evaluate reward policies to our knowledge is the UK’s PRA & FiCA on the request of the UK parliament. Their assessment concludes strongly against rewards, yet they do not provide any evidence to back up their negative assessment and make claims that later evidence has refuted. In the following, we review the concerns raised by critics of reward programs, primarily the PRA & FiCA.
Evidence on the Effectiveness of Rewards
Under reward programs in the U.S whistleblowers can receive a percentage of the fine imposed on the wrongdoing firm or person. The range is usually between 15-30% of the sanctions against the firm, and of the money recovered. The exact reward percentage within the range is determined by how central the whistleblowers information was to unearth and sanction the wrongdoing.
One fundamental concern with rewards is their cost effectiveness. Some argue that they can come with a costly government structure and that they attract a lot of meritless claims by opportunist employees, which increase the administrative costs (PRA & FiCA 2014, Ebersole 2011).
On the other hand, many argue that they can be a cost-effective tool in an age when governments are looking for austere economic policies (Engstrom 2014). Some argue that they are at least as efficient as classical “command and control” methods of enforcement, such as selecting random persons or firms for audit. We evaluate cost-effectiveness with respect to three important effects: deterrence, increased quality of claims, and increase quantity of claims.
A significant part of determining cost-effectiveness is the extent to which whistleblowing has any significant deterrence effects on future misbehavior. Johannesen & Stolper (2017) found that whistleblowing had deterrence effects in the off-shore banking sector. They studied the stock market reaction before and after the whistleblower Heinrich Kieber leaked important tax document from the Liechtenstein based LGT Bank. They found abnormal stock returns in the period after the leak, and the market value of banks known to derive some of their revenues from offshore activities decreased.
Wilde (2017) also provide evidence that whistleblowing deters financial misreporting and tax aggressiveness. Using a dataset of retaliation complaints filed with OSHA between 2003 through 2010 on violations of paragraph 806 which outlaw’s retaliation against employees who provide evidence of fraud, he found that firms subject to whistleblower allegations exhibited decreases in financial misreporting and tax aggressiveness.
As for experimental evidence, Abbink and Wu (2017) conducted laboratory experiments studying collusive bribery, corruption, and the effects of whistleblower rewards on deterrence. They find that amnesty for whistleblowers and rewards strongly deter illegal transactions in a one-shot setting, but in repeated interaction the deterrence effect is limited. Their results support a reward mechanism, especially for petty forms of bribery (which are more like one-shot games).
Bigoni et al (2012) conducted laboratory experiments on leniency policies and rewards as tools to fight cartel formation. They find that rewards financed by the fines imposed on the other cartel participants had a strong effect on average price (returning it to a competitive level). In the model setting, this implies that rewards have a deterring and desisting effect on cartel formation.
Another central question is whether rewards increase the quality and quantity of claims. PRA & FiCA (2014) writes that “There is as yet no empirical evidence of incentives leading to an increase in the number or quality of disclosures received by regulators” (PRA & FiCA 2014, p.2).
As for increased quality, there is evidence suggesting that this claim is untrue. Dyck et al (2010) compared whistleblowing in the health care sector where rewards are available through the FCA with non-healthcare sectors where they are not. They found that 41% of fraud cases are detected by employees in the healthcare sector. That number was only 14% for other sectors, a difference highly statistically significant (at the 1% level) despite a small sample size (Dyck et al 2010, p. 2247).
More recently, Call et al (2017) examined empirically the link between whistleblowing and (i) penalties, (ii) prison sentences, and (iii) duration of regulatory enforcement actions for financial misrepresentation. They found that whistleblowers’ involvement in financial misrepresentation enforcement actions was correlated with higher monetary sanctions for the wrongdoing firm and increased jail time for culpable executives. They also found that enforcement proceedings began quicker, and further that whistleblower involvement increased the likelihood that criminal sanctions were imposed by 8.58%, and that criminal sanctions were imposed against the targeted wrongdoer increased by 6.64%.
Another highly contested point is the relation between the quantity and quality of claims and regulatory effectiveness. Some argue that rewards may attract a lot of meritless claims by employees who are either malicious or hope to reap some reward (PRA & FiCA 2014, Ebersole 2011). This does seem to have been the case with some reward programs, but not to the extent many opponents of rewards argue, and this effect does not render rewards a futile or ineffective policy approach, see Nyreröd & Spagnolo (2017) for a thorough discussion.
There are, however, valuable lessons to be learned from the quantity of claims received and the percentage of claims determined to have merit from, for example, the IRS Whistleblower Office. At the IRS there has been a significant backlog of claims, and an exceedingly small number of claimants receive rewards. The IRS program, under 7623(a), does not have a threshold for claims to be considered, and the vast majority of claims fall under 7623(a). These are lessons for optimal design, but not an insurmountable obstacle for effective reward programs. One way around this problem is to have a threshold for claims to be considered. Another is the FCA model, where persons pursue litigation on their own if the Department of Justice declines to join, thereby taking on the risks and costs of losing in court.
Concerns over administrative burden and costly government structures are not salient enough to warrant a rejection of reward policies, as benefit in deterrence and quality outweigh the administrative costs of reviewing even large quantities of incorrect claims.
Entrapment and Malicious Claims
Another central concern has been that “Some market participants might seek to ‘entrap’ others into, for example, an insider dealing conspiracy, to blow the whistle and benefit financially”, FiCA & PRA (2014).
There are presently good ways of preventing this issue, which does not seem to have been salient in the U.S. experience with these policies. Regarding the FCA, for example, when the relator (whistleblower) initiated or planned the wrongdoing, courts can reduce the reward below 15% as they see fit (False Claims Act, 31 U.S.C. §3730 (d) (3)). The IRS has similar restrictions that in cases where the whistleblower planned and initiated the tax evasion, they may considerably reduce or deny any reward. If the whistleblower is convicted of criminal conduct related to the suit, then they should deny her any reward (Internal Revenue Code, 26 U.S.C §7623 (b) (3)).
These restrictions on reward payouts is probably the reason why, judging from the reports by the U.S agencies, entrapment has not emerged as a salient issue in the US experience with the various programs. As for evidence, the National Whistleblower Center (2014) claims they did not find a single case of entrapment in over 10 000 cases in which the planner and initiator of the wrongdoing received an award. Of course this does not exclude the possibility that a poorly run European agency/regulator might mismanage the whistleblower program to the point where this indeed becomes an issue; a sufficiently incompetent administration can generate problems even with the most robust and effective tools.
A related concern is that financial incentives could encourage employees to submit fraudulent claims, e.g. to “fabricate claims of wrongdoing for personal profit” (Howse & Daniels 1995, p.540, see also Rose 2014, p.1283). A similar concern is that: “Financial incentives might lead to more approaches from opportunists and uninformed parties passing on speculative rumors or public information. The reputation of innocent parties could be unfairly damaged as a result” (PRA & FiCA 2014, see also Vega 2012, p.510). There is also the fear that opportunistic whistleblowers will force “corporations into financial settlements in order to avoid the adverse reputational and related effects caused by highly public, albeit ill-founded, accusations” (Howse & Daniels 1995, p.526/27).
Although evidence on this is hard to find, judging from the reports of agencies, fraudulent and malicious has not been a significant issue. This is probably because fraudulent reporting is a crime, and a whistleblower who report fraudulent information exposes him or herself to a legal fight with the falsely accused employer and to sanctions against perjury and defamation. Indeed, in the case of the IRS, the information is submitted under penalty of perjury (Internal Revenue Code, 26 U.S.C §7623 (b)(6)(C)), which is also the case of the SEC if the whistleblower is represented by an attorney (Exchange Act, U.S.C 78u-6(h)). In the case of the FCA, should the whistleblower lie to the court, he risks felony charges punishable by up to five years in jail for perjury, and the possibly of being convicted of other crimes related to lying under oath. Further, the FCA has a reverse fee-shift for obviously frivolous claims (Engstrom 2016, p.10).
Whether fraudulent claims are a concern for the efficacy of a whistleblower reward program depends to a large extent on the precision of the court system. Buccirossi et al. (2017) analyze this concern within a formal economic model. They show that fraudulent reports are entirely irrelevant for countries with sufficiently precise/competent court systems, provided strong sanctions against perjury, defamation and lying under oath are there to balance the incentives generated by large bounties. Where the judicial system makes a lot of mistakes, instead, this may not be sufficient for the scheme to have crime deterrence effects, which may make it preferable not to introduce large rewards for whistleblowers.
Conclusions
Some suggest that the European hesitation over improving whistleblower protection and considering rewards may have partially historical roots, as both Nazi Germany and Soviet Russia relied heavily on citizens reporting on one another (Givati 2016, p.26.). But the lack of voices speaking out against what the Nazi’s were doing should suggest the opposite, and it is not clear how these parallels should be drawn when we are talking about rewarding whistleblowers in the financial offices of private corporations.
It is also the case that most valuable information to law enforcement is often in the hands of higher-ups in the organization, those who have more to lose in the case of whistleblowing (Engstrom 2016), and for whom protections would be an insufficient compensation relative to their current position and salary. The blunt tool that is horizontal protection for whistleblowers who report violations of EU law could be coupled with precise tools such as rewards for violations of specific EU laws whose undermining can be particularly detrimental to financial stability or the environment.
If European countries and their regulatory and law enforcement institutions are not capable of having an open and honest debate, competently based on the available evidence from rigorous research and from previous experiences in other countries, then they would hardly be able to competently design and properly administer a system of rewards for whistleblowers. As argued in Buccirossi et al. (2017), in countries with weak institutions high powered tools like whistleblower rewards should better be avoided, as in the hand of incompetent law makers and corrupt regulators they would likely produce more damage than good.
References
- Abbink, Klaus & K. Wu. 2013. “Reward Self-Reporting to Deter Corruption: An Experiment on Mitigating Collusive Bribery”, Monash University Discussion Paper 42/13, 2013.
- Anenberg, S. 2017. “Impacts and mitigation of excess diesel-related NOx emissions in 11 major vehicle markets”, Nature 545, 467-471.
- Bank of England: Prudential Regulations Authority & Financial Conduct Authority. 2014.” Financial Incentives for Whistleblowers”, available at: https://www.fca.org.uk/news/financial-incentives-for-whistleblowers
- Berghoff, H. 2017. “´Organized irresponsibility´”? The Siemens corruption scandal of the 1990s and 2000s”, Business History, DOI: 10.1080/00076791.2017.1330332
- Bigoni, M., C. Le Coq, S. Fridolfsson and G. Spagnolo. 2012. “Fines, Leniency and Rewards in Antitrust”, RAND Journal of Economics, 43(2), 368-390.
- Buccirossi P, Immordno G, and Spagnolo G. 2017. “Whistleblower Rewards, False Reports, and Corporate Fraud”, Stockholm Institute of Transition Economics Working Paper No.42.
- Congressional Hearing (2015) of Volkswagens head of American Operations Michael Horn, October.
- Dyck, A. Morse, A. Zingales, L. 2010. ”Who Blows the Whistle on Corporate Fraud?”, The Journal of Finance, Vol.65, No.6, pp.2213-2253.
- Dyck, A. Morse, A. Zingales, L. 2013. ”How Pervasive is Corporate Fraud?”, Rotman School of Management Working Paper no.2222608.
- Ebersole, D. 2011. “Blowing the Whistle on the Dodd-Frank Whistleblower Provisions”, 6 Ohio St. Entrepen. Bus. L. J. 123.
- Engstrom, D. 2016. “Bounty Regimes”, in RESEARCH HANDBOOK ON CORPORATE CRIMINAL ENFORCEMENT AND FINANCIAL MISDEALING (Jennifer Arlen ed., Edward Elgar Press, forthcoming 2016)
- Engstrom, D. 2014. “Private Enforcement’s Pathways: Lessons from Qui Tam Litigation”, Columbia Law Review, Vol.114, December, No.8.
- European Commission. 2018. “Proposal for a DIRECTIVE OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL on the protection of persons reporting on breaches of Union law”, available at: https://ec.europa.eu/info/publications/annexes-proposal-directive-protection-persons-reporting-breaches-union-law_en
- European Commission Newsroom. 2018. “Robust protections for whistleblowers across EU: commission proposes new rules” available at: http://ec.europa.eu/newsroom/just/item-detail.cfm?item_id=620400
- European Digital Rights. 2017.“Germany: fighting anti-whistleblower provision” available at: https://edri.org/germany-fighting-anti-whistleblower-provision/
- Givati, Y. 2016. “A Theory of Whistleblower Rewards.” Journal of Legal Studies, 45, 2016.
- Heinish V Germany. 2011. European Court of Human Rights.
- Howse, R., Daniels, R. J. 1995. “Rewarding Whistleblowers: The Costs and Benefits of an Incentive-Based Compliance Strategy.” 525-549. Retrieved from: http://repository.upenn.edu/law_series/4
- Jahmani, Y. Dowling, W. 2008. “The Impact of Sarbanes-Oxley Act”, Journal of Business & Economic Research, Vol 6, Number 10.
- Johannesen, Niels and Stolper, Tim B.M. 2017. “The Deterrence Effect of Whistleblowing – An Event Study of Leaked Customer Information from Banks in Tax Havens”, Working Paper of the Max Planck Institute for Tax Law and Public Finance No. 2017-4. Available at SSRN: https://ssrn.com/abstract=2976321 or http://dx.doi.org/10.2139/ssrn.2976321
- National Whistleblower Center. 2014. “The Importance Of Whistleblower Rewards in
- Combating International Corruption.” Available at: https://www.whistleblowers.org/storage/docs2/anti-corruption-report.pdf
- Nyreröd, T. Spagnolo, G. 2017. “Myths and Numbers on Whistleblower Rewards”, SITE Working Paper Series no.44, available at: SSRN: https://ssrn.com/abstract=3100754
- Vega, M. 2012. “Beyond Incentives: Making Corporate Whistleblowing Moral in the New Era of Dodd-Frank Act ‘Bounty Hunting’”, Connecticut Law Review, Vol. 45.
- Jaron H. Wilde. 2017. “The Deterrent Effect of Employee Whistleblowing on Firms’ Financial Misreporting and Tax Aggressiveness”, The Accounting Review, In-Press.
- Call, Andrew C. and Martin, Gerald S. and Sharp, Nathan Y. and Wilde, Jaron H. 2017. “Whistleblowers and Outcomes of Financial Misrepresentation Enforcement Actions”, available at SSRN: https://ssrn.com/abstract=2506418 or http://dx.doi.org/10.2139/ssrn.2506418
- Wolfe, S. et al. 2014. “Whistleblower Protection Laws in G20 Countries, priorities for Action”, Available at <http://schd.ws/hosted_files/16iacc/0b/IACC%20whistleblower%20improvements%209.3.15.pdf>
- Radu, P. 2016. “Follow the Money: A Digital Guide for Tracking Corruption”, International Center for Journalists, Romanian Centre for Investigative Journalism. Avaliable at: https://www.icfj.org/sites/default/files/Follow_Money.pdf
- Financial Times. 2018a. “Maltese journalist Caruana Galizia was assassinated, says her son”, available at: https://www.ft.com/content/d410b136-b34b-11e7-a398-73d59db9e399
- Financial Times .2018b. “HSBC whistleblower Hervé Falciani arrested in Spain”, available at: https://www.ft.com/content/f662b04e-3830-11e8-8b98-2f31af407cc8
- Forbes .2014. “SEC ready to rumble in Siemens whistleblower case” available at: https://www.forbes.com/sites/erikakelton/2014/03/04/sec-ready-to-rumble-in-siemens-whistleblower-case/#17a3cda856c4
- The Washington Post. 2018. “Police believe a journalist was killed for reporting on fraud in the heart of Europe”, available at: https://www.washingtonpost.com/news/worldviews/wp/2018/02/26/police-believe-a-journalist-was-killed-for-reporting-on-fraud-in-the-heart-of-europe/?noredirect=on&utm_term=.cac1bdef7f00
- The Guardian. 2018. “Malta corruption whistleblower hands herself in to police”, available at: https://www.theguardian.com/world/2018/mar/20/malta-corruption-whistleblower-maria-efimova-hands-herself-in-police
- New York Times. 2016. “VW Presentation in ’06 Showed How to Foil Emissions Tests” available at: http://www.nytimes.com/2016/04/27/business/international/vw-presentation-in-06-showed-how-to-foil-emissions-tests.html?smid=tw-share&_r=1
Disclaimer: Opinions expressed in policy papers and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Remaining Challenges for Faster Growth in CESEE
Between 1995 and 2016, per capita GDP levels in Europe have converged, as countries that had lower income levels in 1995 on average have seen faster growth rates between 1995 and 2016 (Figure 1).
Figure 1
Income differentials between CESEE and Germany have narrowed significantly during this time. If we look at CESEE as a whole, in 1995 GDP per capita of CESEE was only a third of Germany. By 2016 it has increased to almost half. If we look at individual countries, all countries in CESEE have seen faster GDP growth than in Germany, but there have been important cross-country differences. For example, growth has been relatively rapid in the EU New Member States and very slow in Ukraine.
Nevertheless, CESEE is still much poorer than Germany. The richest country in CESEE – Slovenia – has the income level per capita Germany had in 1990 (Figure 2). Poland is as rich as Germany was in the late 1970s. And Ukraine, which in early transition had similar level of income to Poland, is now as rich as Germany was in the early 1950s.
Figure 2
CESEE is poorer both because labor productivity is lower and a smaller share of the population works. GDP per capita is the product of GDP per worker and the employment to population rate:
In 2015, labor productivity in CESEE was still well below that in Germany and the Netherlands (Figure 3, x-axis). Employment rates were also lower, but those differences were less pronounced (Figure 3, y-axis).
Figure 3
Differences in employment rates are, however, more pronounced if we take into account that in CESEE a higher share of the population is of working age. The employment to population rate is the product of the employment to working age population [1] rate:
The share of the working age population in CESEE is relatively high (Figure 4), although it is now declining. The employment to working age ratios in CESEE are well below those in Germany (Figure 5); only the Baltics come close.
Figure 4
Figure 5
It will be challenging to further increase the employment to total population rate, given the impact of aging and the already relatively low level of unemployment. The decline of the working age population will accelerate in the next decade (Figure 6) as the baby-boom generation is retiring; in a number of countries the working age population is set to decline by more than 1 percent annually. [2] If the share of the working age population that works remains constant, the share of the employment to total population rate will fall sharply. At the same time, the unemployment rate in many countries is already close to pre-crisis lows (Figure 7). It will therefore be key to increase labor force participation rates, which in most countries are still below those of Germany, particularly those of women (Figure 8).
Figure 6
Figure 7
Figure 8
A higher capital stock may be even more important than raising the employment rate. There is a strong correlation between the level of capital stock per capita and GDP per capita (Figure 9, left panel). The relationship between the employment rate and GDP per capita is much weaker (Figure 9, right panel). Further convergence of CESEE will thus require capital deepening. As of 2015, the capital stock per capita in CESEE region is on average only a quarter of that in Germany.
Figure 9
Figure 10
Figure 11
Figure 12
Unfortunately, the growth of the capital stock per capita has slowed (Figure 10), which reflects the decline in investment rates. Investment rates are low compared with other emerging market countries (Figure 11). Saving rates are low too (Figure 12), which suggests that a rebound of investment could lead to a re-emergence of high current account deficits, unless savings increases as well. Yet it may be challenging to boost saving. With labor markets tightening, wages shares are likely to increase, which is likely to reduce corporate profits. Indeed, in a number of countries this is already happening (Figure 13). Household savings are difficult to influence. Boosting public savings would help, yet even though unemployment rates are falling, few countries plan a meaningful fiscal tightening (Figure 14).
Figure 13
Figure 14
TFP growth has slowed as well. TFP growth has recovered somewhat in recent years, but it is still much slower than in the pre-crisis years (Figure 15). The TFP slowdown might be a result of both the decrease of productivity in main trading partners and unfinished post-crisis adjustment.
The IMF’s CESEE Regional Economic Issues have identified several factors that might restrain productivity and investment. The May 2016 and November 2016 IMF CESEE Regional Economic Issues [3] analyzed several areas where reforms are needed in CESEE, and recommended to improve institutions to boost productivity. The May 2016 REI suggested the largest efficiency gains might come from increasing protection of property rights, upgrading legal systems and other government services. In this context, the November 2016 REI discussed the need to improve public investment management and tax administration. Given the large gaps in infrastructure and capital stock to Western Europe, improving the efficiency of public investment by improving its allocation and the implementation of frameworks and procedures could boost potential growth significantly. Regarding tax administration, reducing compliance gaps, would help improve tax collection, which could generate more fiscal revenues and allow for higher public investment.
Figure 15
In short, further catch-up is possible but challenging. Labor force participation could be further increased, which would also help to offset declining share of working age population. A slowdown or even reversal of net emigration would also contribute. The capital stock is relatively low, and higher investment is needed especially in infrastructure, but raising the saving rate will be a challenge. Since the crisis the TFP has slowed considerably, and re-igniting TFP growth will be crucial for boosting growth. For all this, improving the quality of institutions and legal frameworks will help.
Bas Bakker is the IMF’s Senior Resident Representative for Central and Eastern Europe; Marta Korczak and Krzysztof Krogulski are economists in the IMF’s regional office for Central and Eastern Europe in Warsaw. The views expressed in this paper are those of the authors and do not necessarily represent those of the IMF or IMF policy. Comments by [Jorg Decressin] on an earlier version are gratefully acknowledged.
[1] The working age population is the population ages between 15 and 64.
[2] In many countries, demographics pressures have been exacerbated by the net emigration. A reduction in emigration, or even reversal, would also help. See IMF Staff Discussion Note “Emigration and Its Economic Impact on Eastern Europe” available at https://www.imf.org/external/pubs/ft/sdn/2016/sdn1607.pdf
[3] In many countries, demographics pressures have been exacerbated by the net emigration. A reduction in emigration, or even reversal, would also help. See IMF Staff Discussion Note “Emigration and Its Economic Impact on Eastern Europe” available at https://www.imf.org/external/pubs/ft/sdn/2016/sdn1607.pdf
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.
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[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).
Avoiding Corruption and Tax Evasion in Belarus’ Construction Sector
This brief summarizes our research on the problem of corruption and tax evasion in the construction sector in Belarus. We conducted a survey of construction companies, asking them to estimate the extent of different dimensions of tax evasion and corruption within the sector. The results show the most problematic directions in the sphere. Based on international experiences, we develop recommendations of how to reduce corruption and tax evasion in construction of Belarus.
Shadow economy and the construction sector
The problem of a shadow economy is real for many countries in the world. Many countries try to minimize the level of this illegal activity. But it is very difficult to liquidate tax evasion or envelope wages fully.
In Belarus there is a lot of discussion about corruption and tax evasion limitation. The country ranked 79th in the Corruption Perception Index 2016. The situation in Belarus is much better then in Russia or Kazakhstan, but worse than in Sweden, Finland and Switzerland.
There is lack of systematically updated knowledge about the situation with corruption and tax evasion in the different economic spheres of Belarus. At the same time, there are sectors, which are more prone to develop a shadow economy. One of them is the construction sector. Multilevel chains of relations between contractors and subcontractors, numerous suppliers, and complicated procedures for facility acceptance create possibilities for illegal schemes.
Construction plays an important role in national production. In 2016, the construction sector corresponded to more than 6% of Belarusian GDP. In 2014, this indicator was above 10%. The decline can be explained by a reduction of preferential lending in housing construction and a recession in the economy. Despite the reduction in the share of GDP, around 8% of the total labor force works in construction. More than 90% of the legal entities in the sphere are presented by privately owned enterprises [8].
Taking into account the importance of construction it is necessary to emphasize that reducing the size of the shadow economy could create a better business environment, reduce companies’ expenditures for resolving issues in informal ways, and increase budgetary revenues.
In this brief we present a short summary of our research “Problems of corruption and tax evasion in construction sector in Belarus”, which is forthcoming in the International Journal Entrepreneurship and Sustainability Issues. The project was made in the framework of the project “Corporate engagement in fighting corruption and tax evasion”, financed by the Nordic Council of Ministries.
Method
In order to understand the main issues and challenges in construction sector, we surveyed 50 Belarusian construction companies. We took 20 companies from Minsk and its surrounding region, and 6 organizations from each Belarusian region (Brest, Grodno, Vitebsk, Gomel, and Mogilev). The survey was based on the method used in Putnins and Sauka (2016). This method includes a questionnaire, which helps understanding the actual situation with the shadow economy in the sector. The questions of the survey were divided into three parts.
The first part included neutral questions about economic characteristics of the company, such as number of employees, profit level, the year of establishment, wage levels, and form of ownership.
The second part include more sensitive questions, but which can help us understanding the most problematic issues concerning to corruption and tax evasion. These questions concern such indicators as the level of underreported business income, the degree of underreported number of employees, the percentage of revenue that firms pay in unofficial payments to ‘get things done’, and main barriers to business development. In order to make the answers easier for participants, all the questions deal with the situation in the sector as a whole, and not the company in particular.
The third part of questions concerns the situation in public procurement, and includes the perception of main problems in the sphere.
Survey results
The first part of the survey shows that there has been a decline in many of the economic indicators during the last two years. This may be one factor stimulating the sector’s development of informal activities. Indeed the results of the second part of survey demonstrate that level of shadow economy has significant dimensions. More then 60% of the respondents agree that some firms in the sector received hidden income. More than 50% of the interviewed companies believe that some organizations in the construction sector hire part of their employees unofficially. Wages in “envelopes” is also a problem for the construction companies.
Unregistered firms are a big threat to having a well-developed construction sector. More than 60% of the interviewed companies agree with the existence of unregistered companies. Such non-official organizations create unfair competition in the sector and decrease the level of budget revenues. Many of the unregistered companies work in the sphere of home improvements and renovations.
Figure 1. Estimation of the approximate level of hidden salaries (“wages in the envelopes”) in construction industry
Notes: X-axis is the percentage of respondents that agree with the statement. Source: Results of the survey
The survey results allow us to conclude that the state budget loses part of its corporate income taxes, taxes on wages and social contributions due to the existence of hidden incomes, wages in envelopes, and unregistered companies and employees.
The last, but not the least, question in the second part of the survey was about main obstacles and barriers for operating in the construction sphere. Most of the respondents underlined three groups of barriers. One of them is the administrative challenge, including high level of taxation, inconsequent business legislation, and attitude of the government towards business in general. The second barrier includes economic problems such as lack of funds for business investments, payment behavior of clients, low product or service demand from customers, low access to credits, and inflation. The third group of problems in the construction sector is related to the shadow economy. A large part of the enterprises experiences a problem of high competition from illegal business and corruption. At the same time, a positive thing is that the majority of respondents does not consider crime and racketeering as a threat for the sector.
Figure 2. Estimation of approximate share of unregistered firms production in the total output in construction industry
Notes: The X-axis is the percentage of respondents that agree with the statement. Source: Results of the survey
In the third part of the survey, companies were asked about their participation in public procurement tenders. About 42% of all respondents did not have this experience over the past two years. One of the questions was about competition among construction companies. About 40% of all respondents underlined that they have lost at least one public tender because of unfair competition. Given that only 58% of the companies participated in tenders, we can conclude that unfair competition is a widespread problem for the majority of public procurement auction participants. Imperfect legislation is another problem for the companies. 46% of all respondents believe that the quality of legislation in the sphere is unsatisfactory. Only 12% of the companies did not see any problems in the national legislation.
At the end of the interview, companies were asked to list three main problems in the sphere of public procurement. The answers are shown in Figure 3.
Figure 3. Main problems that companies face when participating in public procurement tenders
Notes: The X-axis is the percentage of respondents that agree with the statement. Source: Results of the survey
The most common answer was corruption. Unfair competition and nepotism were also quite common problems in the public procurement sphere. Among administrative barriers, companies emphasized the complexity of documentation preparation and imperfect legislation. Important economic problems were inflation and unequal conditions for public and private enterprises.
International experiences and recommendations in fighting corruption and tax evasion in the construction sector
Corruption and tax evasion can be stimulated by different factors. One of the main preconditions of the shadow economy in the Belarusian construction sector is inconsistent and frequently changing legislation. For example, public procurements are regulated by the Presidential Decree (Ukaz) on procurement of goods (works, services) in construction. However, this regulation document expires at the end of 2018. Before 2017, such operations were regulated by several legislative acts. Developing understandable and sustainable legislation, which creates clear rules for participants of the market, is very important to increase transparency and openness of the market [11; 12; 13; 15; 18].
Another problem concerns the relations of contractors and sub-contractors. In many cases negotiations between parties are closed and non-transparent. So, it is very difficult to estimate the effectiveness of costs and proper use of funds.
Modern E-Government system adoption can support increased transparency between contractors and sub-contractors, as well as improve the quality of state services. One of the directions in this sphere is the transition towards full electronic document management. [3; 4; 6].
Another risk is related to public procurement procedure. Direct communications between public tender participants and organizers create possibilities for unfair competition. There is substantial international evidence showing that full digitalization of the process would improve the transparency of the public procurement procedure [3; 4; 21]. For example, good reference points for implementation of such digitalization can be the Georgian or Ukrainian experiences of electronic tenders. These two countries have relatively similar institutional environment and heritage as Belarus.
The problem of tax evasion is often related with payments in cash. Such transactions are less transparent and visible for authorities. According to national legislation operations between legal entities should be in cashless form. But there are exceptions to the rule [20]. In this regards the level of tax evasion would be decreased if payments in cash will be minimized.
Another concern is the efficiency of the public procurement procedures. During public procurement auctions in construction, price plays the most important role. The share of “Bid Price” criterion in total volume of all criteria can be up to 50%. The project with the lowest price has the best chance to win the tender. This is not always reasonable. Moreover, some companies hire disabled people that allow them to obtain preferential treatment in the public procurement procedure – for example, apply special correction indicators to the final price. In many cases it is better to install more expensive but high efficiency (more qualitative or ecological) equipment instead of buying cheap but low quality ones. Of course, even in EU legislation, the cost or price of projects is a very important criterion. But then it is often defined as a price-quality ratio. In this regards, the quality of the project can be estimated from the environmental, qualitative or social side [12; 19].
One more issue according to survey results is the problem of unregistered labor force in construction. It can be partly resolved by ID card implementation for all workers and employers in construction sector. In Finland, for example, all workers in construction must have such cards during workdays. Tax authorities can check the availability of the cards at any time [17].
Conclusion
Our survey of Belarusian construction companies confirmed wide exposure of the sector to tax evasion and corruption. The majority of the respondents agreed that some companies hire unregistered workers, pay wages in envelopes, or have hidden income. The most common answer to the main problems in the public procurement sphere was corruption. Based on international experience and national peculiarities, it is advisable to propose the following measures to reduce corruption and tax evasion in construction sector:
- Adoption of sustainable legislation.
- E-Government system development.
- Modernization of the electronic tender system to require no direct contacts between organizers and tender participants.
- Reduction of the possibilities of making payments in cash.
- Implementation of a price-quality ratio as one of the main criteria for choosing the winner of tenders.
- Introduction of ID cards for all employees and employers in the construction sector.
These and other measures are likely to significantly improve the business environment in the construction sector.
References
[1] Anderson, E. 2013. Municipal “Best Practices”: Preventing Fraud, Bribery and Corruption, International Centre for Criminal Law Reform and Criminal Justice Policy. Available on the Internet:http://icclr.law.ubc.ca/sites/icclr.law.ubc.ca/files/publications/pdfs/Municipal%20Best%20Practices%20-%20Preventing%20Fraud%2C%20Bribery%20and%20Corruption%20FINAL.pdf.
[2] Fazekas, M., Toth, I.J., King, L.P. 2013. Corruption manual for beginners: “Corruption techniques” in public procurement with examples from Hungary, Working Paper series: CRCB-WP/2013:01 Version 2.0, Budapest, Hungary. Available on the Internet: http://www.crcb.eu/wp-content/uploads/2013/12/Fazekas-Toth-King_Corruption-manual-for-beginners_v2_2013.pdf.
[3] Krasny, A. 2014. Georgia E-Government. Available on the Internet: https://www2.deloitte.com/content/dam/Deloitte/ua/Documents/public-sector/e-government/Electronic%20government%20of%20Georgia.pdf.
[4] Luzgina, A. International experience of the e-Government System development/ A. Luzgina //Journal of the Belarusian State University. Economics. – Minsk, 2017. – P.76-83.
[5] Luzgina, A., Laukkanen E., Larjavaara I., Viavode I., Volberts J. ,Corporate engagement in fighting corruption and tax evasion in construction sector”, forthcoming in “Entrepreneurship and sustainability issues”
[6] Naumov, A. 2014. Georgia E-experience for Belarus. Available on the Internet: http://e-gov.by/best-practices/elektronnyj-opyt-gruzii-dlya-belarusi.
[7] Official website of Transparency International. Available on the Internet: https://www.transparency.org/.
[8] Official website of Belarusian National Statistical Committee. Available on the Internet: http://www.belstat.gov.by.
[9] Official website of the European Commission. Available on the Internet: https://ec.europa.eu/commission/index_en.
[10] On procurements of goods (works, services) [Electronic source] // Decree of the President of the Republic of Belarus/ 20.10.2016 # 380. Rus.: О закупках товаров (работ, услуг) при строительстве, Указ Президента Республики Беларусь от 20.10.2016, №380. – Mode of access: http://www.pravo.by/document/?guid=3871&p0=P31600380.
[11] On public procurements of goods [Electronic source] // Law of the Republic of Belarus/ 13.07.2012, # 419-З. Rus.: О государственных закупках товаров, работ услуг Закон Республики Беларусь от 13 июля 2012 г. № 419-З. – Mode of access: http://www.pravo.by/document/?guid=3871&p0=h11200419&p1=2.
[12] On organization and conduct of the procurement of goods (works, services) procedures and settlements between customer and contractor in facilities construction [Electronic source] // Resolution of the Council of Ministers of the Republic of Belarus / 31.12.2014, # 88.: Rus: Об организации и проведении процедур закупок товаров (работ, услуг) и расчетах между заказчиком и подрядчиком при строительстве объектов, Постановление Совета Министров Республики Беларусь №88 от 31.12.2014. – Mode of access: http://www.pravo.by/document/?guid=3871&p0=C21400088.
[13] Putnis, J.T., Sauka, A. 2016. Shadow economy index for the Baltic countries 2009 – 2016. The Center for Sustainable Business at SSE Riga. – 47 p.
[14] Pelipas, I., Tochitskaya, I. 2016. Problems of corruption in the assessments of small and medium enterprises. Available on the Internet:
[15] Procurement in construction, what has been changed since January 1, 2017. Available on the Internet: http://www.mas.by/ru/news_ru/view/zakupki-v-stroitelstve-chto-izmenilos-s-1-janvarja-2017-goda-852/
[16] Preventing corruption in public procurements. 2016. OECD Publishing. Available on the Internet: http://www.oecd.org/gov/ethics/Corruption-in-Public-Procurement-Brochure.pdf.
[17] Briganti, F., Machalska, M., Steinmeyer, Heinz-Dietrich, Buelen, W. 2015. Social Identity cards in the European construction industry, edited by Buelen W. Available on the Internet: http://www.efbww.org/pdfs/EFBWW-FIEC%20report%20on%20social%20ID%20cards%20in%20the%20construction%20industry.pdf.
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Cross-Country Differences in Convergence in CESEE
Since 1989, there have been large differences in the convergence of the income levels of the former communist countries in CESEE with those in the US. Most Central European countries have seen a sharp rise in relative incomes, but many countries in former Yugoslavia and the CIS have not—indeed, some countries, including Moldova and Serbia, are now poorer than they were in 1989 (Figure 1).
Figure 1. Transition outcomes
Figure 2. GDP level in Poland and Ukraine
The difference between Ukraine and Poland is particularly stark. In 1989, both had similar income levels, but Poland is now more than three times as rich (Figure 2). As a result, cross-country income differences in CESEE remain large. In 1989, the Czech Republic, Russia, Slovenia and Croatia had the highest income per capita in 1989, about 4 times as high as in Albania and Moldova, the poorest in the group. Twenty-six years later, the differences are even larger. GDP per capita in Slovenia is 6 times as high as in Moldova (Figure 3).
Figure 3. Cross-country income differences
What Explains Convergence Differences?
These differences in convergence do not seem to reflect data problems. True, GDP statistics in 1989 were not very good. It is hard to measure value added when prices are not quite right. Moreover, GDP at that time was probably not a good indicator or of consumer welfare. Much of what was produced was not wanted by consumers (e.g. military expenditures) and/or of low quality. Nevertheless, these issues apply to all post-communist countries in the regions—it is not clear that some countries suffered from data problems more than others.
Indeed, more direct measures of economic activity also suggest large initial output falls and large cross-country differences. Between 1990 and 1995 electricity consumption per capita fell by almost 40 percent in Ukraine and Moldova. By then electricity consumption in Poland had nearly recovered to the 1990 level (Figure 4).
Figure 4. An alternative measure of decline in economic activity
Instead, several factors seem to have a played a role:
- The speed of transition to a market economy
- War and conflicts
- Boom-busts
- EU Membership
- Whether transition has been completed
Countries that reformed early had a shorter and shallower post-transition recession. The lower the EBRD transition index in 1995 (i.e., the less the economy was reformed), the sharper the output decline between the beginning of the transition and 1995 (Figure 5).
Figure 5. Market reforms and post-transition recession
Why was this? In late 1989, a fierce debate broke out over what came to be called gradualism versus shock therapy. Many gradualists argued that the structural flaws of the economy would frustrate attempts at liberalization, and therefore that reforms should be implemented in a gradual, sequenced way. But for others—including key figures such as Leszek Balcerowicz in Poland—understanding the nature of the problem meant the opposite: reform was a seamless web that could only succeed if all the changes happened together, because liberal prices, improved governance, and a stable economic and financial environment were needed to reinforce one another; little could be achieved with a partial reform. The evidence from the past 25 years has vindicated the seamless web theory of transition. There is no doubt that some reforms took much longer than anticipated, including privatization, both of banks and companies. But it seems clear that the countries that made sweeping changes, and that kept at reform and stabilization have done well.[2] Countries that followed a more gradual path suffered from the decline of the old industries and did not get the boost from the growth of new firms. And in some countries bouts of macroeconomic instability repeatedly undermined reforms and sapped political momentum.
Weaker growth in the early transition years was not compensated by faster growth later. Countries, where output declines were deeper in early 1990s, did not see more rapid growth in subsequent years (Figure 6).
Figure 6. Permanent output losses in the early transition
Wars and conflicts also played an important role. It is striking that the five countries with the lowest growth all had a war or serious conflict between 1990 and 2015 (Figure 7).
Figure 7. Wars and conflicts impact on long-term growth
Avoiding boom-busts helped boost longer-term growth. Steady growth rates seem to be more conducive to higher long term growth than booms followed by busts. Between 2002 and 2008, Romania had capital inflows fueled boom and grew much faster than Poland, but thereafter it suffered a deep bust, and between 2002 and 2015, Poland has grown faster (Figure 8).
Figure 8. The hare and the tortoise
EU accession was a powerful catalyst for reforms and upgrading of institutional frameworks. CESEE countries that joined the EU were required to bring their regulations and institutions up to Western European standards. There is a striking difference in the level of EBRD transition indicators between EU countries and non-EU countries (Figure 9).
Figure 9. EU accession as a reform catalyst
Thus, prospects of EU Membership have led to more reforms and, as a consequence, to stronger growth (Figure 10).
Figure 10. Market reforms and changes in income levels
Countries that upgraded their institutions to EU standards saw a decline in cross-country income differences. Countries that joined the EU in 2000s show clear pattern of convergence. The difference between Bulgaria and Slovenia has narrowed by 15 percent of Slovenia’s GDP since the former begun EU accession negotiations in 2000 (Figure 11, right panel). Similarly, a group of candidate and potential candidate countries, including Croatia (which joined the EU only in 2013) have converged as well (Figure 11, left panel).
Figure 11. Convergence within CESEE regions

Source: Total Economy Database and IMF staff calculations. Note: The EU has recognized Bosnia and Herzegovina as potential EU candidate countries.
By contrast, there was no convergence among the European CIS-countries. Russia, the richest of CIS countries grew by only 0.6 percent annually since 1989, while output per capita declined in Moldova and Ukraine. Only Belarus achieved growth rates comparable to non-CIS countries, but its largely unreformed economy may have approached the limits of the current extensive growth model (Figure 12).
Figure 12. Convergence in the European CIS region
Countries that have a more completed transition are richer. There is a strong correlation between progress in market reforms and a country’s income level (Figure 13).
Figure 13. Market reforms and income level
Similarly, richer countries have a more vibrant private sector (Figure 14).
Figure 14. Market reforms and private sector share in the economy
Correlation does of course not mean causality but is it telling that there is no highly reformed poor country.
Convergence Post-2009 Crisis
Post-2009, catch-up has slowed down. Pre-crisis, convergence was rapid and widespread. In some countries, the GDP per capita gap to the US narrowed by more than 12 percentage points in 2003-08. Since 2010 only two-thirds of countries in the region have continued to catch-up with the US, while Ukraine and Slovenia saw a widening of income differences (Figure 15). And if we include the 2009 crisis, which was deeper in CESEE than in Western Europe, convergence has been even less.
Figure 15. Convergence pace pre- and post-crisis
More recently, there have also been large differences across regions: while the CIS was in recession, the non-CIS countries doing much better.
- The CIS countries suffered from falling commodity prices, and from the impact of sanction on Russia.
- By contrast, the non-CIS countries saw a gradual acceleration of GDP growth, on the back of a pick-up of domestic demand in the euro area. Labor markets in many EU New Member States (NMS) are tightening rapidly, and unemployment is quickly approaching pre-crisis lows, though GDP growth rates are well below those in the pre-crisis years.
How can we boost Convergence going forward?[3]
GDP per capita is the product of GDP per worker (labor productivity) and the share of the population that works (the employment rate):
Low GDP per capita can thus be the result of both low labor productivity and a low employment rate. In CESEE, both factors play a role:
- In most CESEE countries, the employment rate is below that in Western Europe (Figure 18). Low employment rates are a particular problem in SEE and some CIS countries.
- The labor productivity gap with Western Europe is still large, even though it has declined in the past twenty years.
Figure 16. Big differences in growth among regions
Figure 17. Labor markets in EU new member states
Figure 18. Labor utilization and productivity
To raise labor productivity more investment is needed. The capital stock per worker in a typical CESEE economy is only about a third of that in advanced Europe. Domestic saving rare are too low in most the region; policies should, therefore, focus on institutional reforms that reduce inefficiencies and increase returns on private investment and savings.
Boosting total factor productivity (TFP) is important as well. CESEE countries have to address structural and institutional obstacles that prevent efficient use of available technologies or lead to an inefficient allocation of resources. The recent IMF CESEE report suggests the largest efficiency gains are likely to come from improving the quality of institutions (protection of property rights, legal systems, and healthcare); increasing the affordability of financial services (especially for small but productive firms), and improving government efficiency.
Conclusion
Since the fall of communism, there have been large differences in the convergence of income levels with the US among CESEE countries. Much of these differences reflect differences in policies. Countries that reformed more and earlier saw faster growth than countries that reformed less or later. Macro-stability also helped, and countries that avoided boom-busts tended to grow faster.
Continued convergence will require a higher investment, higher TFP, and higher employment rates. The capital stock per worker is still below that in Western Europe. Higher investment rates will require higher saving rates, lest large current account deficits emerge anew. Addressing structural and institutional obstacles would also help convergence, as it will support higher labor force participation and allow for a more efficient allocation of resources.
Notes and References
- [1] Bas B. Bakker is the Senior Resident Representative and Krzysztof Krogulski an economist in the IMF’s Regional Office for Central and Eastern Europe in Warsaw. The views expressed in this paper are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
- [2]This is not to say that the rapid and seamless approach was without problems, notably large losses of output and high unemployment in the short run. Thus, reform will always have to worry about the social safety net and, under some circumstances, may benefit from external assistance, which is where the IMF and others can come in.
- [3]The IMF addressed this question in depth in the spring 2016 issue of “CESEE Regional Economic Issues.”
Disclaimer: Opinions expressed in policy papers and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.







































