Project: FREE policy paper
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.
References
Albanesi, S., and C. Olivetti (2016). “Gender Roles and Medical Progress”. Journal of Political Economy 124(3): 650-695.
Alesina, Alberto, Giuliano Paola and Nathan Nunn (2013). “On the Origins of Gender Roles: Women and the Plough”, Quarterly Journal of Economics 128(2): 469-530.
Babcock, Linda and Sara Laschever (2003). Women Don’t Ask: Negotiation and the Gender Divide. Princeton University Press, Princeton.
Baden, Sally (1993). “The Impact of Recession and Structural Adjustment on Women’s Work in Selected Developing Countries”. Institute of Development Studies, University of Sussex, BRIDGE Report 15.
Bailey, Martha J. (2006). “More Power to the Pill: The Impact of Contraceptive Freedom on Women’s Lifecycle Labor Supply”. Quarterly Journal of Economics 121(1): 289-320. Uppdatering “Erratum and Addendum,”, September 2009.
Beaman, Lori, Chattopadhyay, Raghabendra, Duflo, Esther, Pande, Rohini and Petia Topalova (2009). “Powerful Women: Does Exposure Reduce Prejudice?”. Quarterly Journal of Economics 124: 1497-1540.
Bandiera, Oriana and Ashwini Natraj (2013). “Does Gender Inequality Hinder Development and Economic Growth? Evidence and Policy Implications”. World Bank Research Observer 28(2): 2-21.
Becker, Gary S., Hubbard, William H. J. and Kevin M. Murphy (2010). “The Market for College Graduates and the Worldwide Boom in Higher Education of Women”. American Economic Review 100(2): 229-33.
Besley, Tim, Folke, Olle, Persson, Torsten and Johanna Rickne (2017). “Gender Quotas and the Crisis of the Mediocre Man: Theory and Evidence from Sweden”. American Economic Review 107(8): 2204-42.
Bhattacharya, Jay, Gathmann, Christina and Grant Miller (2013). “The Gorbachev Anti-Alcohol Campaign and Russia’s Mortality Crisis”. American Economic Journal: Applied Economics 5(2): 232-60.
Blau, Francine and Lawrence M. Kahn, 2003. “Understanding International Differences in the Gender Pay Gap”. Journal of Labor Economics 21: 106-144.
Boserup, Ester (1970). Woman’s Role in Economic Development. London: George Allen & Unwin.
Breierova, Lucia and Esther Duflo (2004). “The Impact of Education on Fertility and Child Mortality: Do Fathers Really Matter Less Than Mothers?”. NBER Working paper 10513.
Buser, Thomas, Niederle, Muriel and Hessel Oosterbeek (2014). “Gender, Competitiveness, and Career Choices”. Quarterly Journal of Economics 129(3): 1409-1447.
Cavalcanti, T. och J. Tavares, 2016. “The Output Cost of Gender Discrimination: A Model-Based Macroeconomic Estimate”. Economic Journal 126: 109–134.
Cuberes, David and Marc Teignier (2014). “Gender Inequality and Economic Growth: a critical review”. Journal of International Development 26: 260–276.
Cuberes, D. och M. Teignier, 2016. “Aggregate Effects of Gender Gaps in the Labor Market: A Quantitative Estimate”. Journal of Human Capital 10(1): 1-32.
Das Gupta, Monica (2015). “’Missing Girls’ in the South Caucasus Countries: Trends, Possible Causes, and Policy Options”. Policy Research Working Paper 7236. Washington, D.C.: World Bank Group.
Djikstra, Geske, A. (1997). “Women in Central and Eastern Europe: A Labour Market Transition” in Djikstra, Geske and Janneke Plantega (eds.). Gender and Economics. London: Routledge.
Dudwick, Nora (2015). “Missing Women in the South Caucasus: Local Perceptions and Proposed Solutions”. Washington, DC: World Bank Group.
Duflo, Ester (2012). “Women Empowerment and Economic Development”. Journal of Economic Perspectives 50(4): 1051-1079.
Ebenstein, Avraham (2014). “Patrilocality and Missing Women”. Mimeo, Hebrew University of Jerusalem.
Elborgh-Woytek, Katrin et al. (2013). “Women, Work, and the Economy: Macroeconomic Gains from Gender Equity”. IMF Staff Discussion Notes No. 13/10.
European Commission (2015). “Gender Balance on Corporate Boards Europe is Cracking the Glass Ceiling”. http://ec.europa.eu/justice/gender-equality/files/womenonboards/factsheet_women_on_boards_web_2015-10_en.pdf
European Commission (2015). “Women in Power and Decision-Making in the Eastern Partnership Countries”. http://eige.europa.eu/sites/default/files/documents/gender_equality_and_decision_making_in_eap_countries_2015_-_report_and_annex_one_file.pdf
Fogli, Alessandra and Laura Veldkamp (2011). “Nature or Nurture? Learning and the Geography of Female Labor Force Participation”. Econometrica 79: 1103–1138.
Galor, Oded and David N. Weil (1996). “The Gender Gap, Fertility, and Growth“. American Economic Review 86(3): 374-38.
Goldin, C., 1994. “The U-shaped Female Labor Force Function in Economic Devlopment and Economic History”. NBER Working Paper 4707.
Goldin, Claudia and Larry F. Katz (2002). ”The Power of the Pill: Oral Contraceptives and Women’s Career and Marriage Decisions”. Journal of Political Economy 110(4): 730-770.
Greenwood, J. Seshadri, A. and M. Yorukoglu (2005). ”Engines of Liberation”. Review od Economic Studies 72(1): 109-133.
Hsieh, C.-T., Jones, C. I., Hurst, E. och P. J. Klenow (2016). ”The Allocation of Talent and U.S. Economic Growth”. Mimeo. Older version in NBER Working paper 18693.
Jensen, Robert and Emily Oster (2009). “The Power of TV: Cable Television and Women’s Status in India”. Quarterly Journal of Economics 124: 1057-94.
Kabeer, Naila (2003). Gender Mainstreaming in Poverty Eradication and the Millennium Development Goals – A handbook for policy-makers and other stakeholders. International Development Research Centre, Ottawa.
Kazandjian, Romina, Kolovich, Lisa, Kochhar, Kalpana and Monique Newiak (2016). “Gender Equality and Economic Diversification”. IMF Working Paper 16/140.
Khitarishvili, Tamar (2016). “Gender Dimensions of Inequality in the Countries of Central Asia, South Caucasus and Western CIS”. Levy Economics Institute Working Paper 858.
Klasen, Stephan (1999). “Does Gender Inequality Reduce Growth and Development? Evidence from Cross-Country Regressions”. Background paper for Engendering Development, World Bank, Washington DC.
Klasen, Stephan and Francesca Lamanna (2009). “The Impact of Gender Inequality in Education and Employment on Growth: New Evidence for a Panel of Countries”. Feminist Economics 15(3): 91-132.
Mammen, K. and C. Paxson (2000). “Women’s Work and Economic Development”. Journal of Economic Perspectives 14: 141-164.
Morton, Matthew, Klugman, Jeni, Hanmer, Lucia and Dorothe Singer (2014). Gender at Work : A Companion to the World Development Report on Jobs. Washington, DC: World Bank Group.
OECD (2015). Education at a Glance 2015: OECD Indicators. OECD Publishing, Paris.
Olivetti, Claudia and Barbara Petrongolo (2008). “Unequal Pay or Unequal Employment? A Cross-Country Analysis of Gender Gaps”. Journal of Labor Economics 26: 621-654.
Olivetti, C. and B. Petrongolo (2016). “The Evolution of Gender Gaps in Industrialized Countries”. forthcoming Annual Review of Economics.
Pande, Rohini and Deanna Ford (2011). “Gender Quotas and Female Leadership: A Review”. Background Paper for the World Development Report on Gender
Pastore, Francesco and Alina Verashchagina (2011). “When Does Transition Increase the Gender Wage Gap?”. Economics of Transition 19(2): 333-369.
Reuben, Ernesto, Rey-Biel, Pedro, Sapienza, Paola and Luigi Zingales (2012). “The Emergence of Male Leadership in Competitive Environments”. Journal of Economic Behavior and Organization 83(1): 111–117.
Sekkat, Khalid, Szafarz, Ariane and Ilan Tojerow (2015). “Women at the Top in Developing Countries: Evidence from Firm-Level Data”. IZA Discussion paper 9537.
Spencer, Steven J., Steele, Claude M. and Diane M. Quinn (1999). “Stereotype Threat and Women’s Math Performance“. Journal of Experimental Social Psychology 35: 4–28.
UNICEF (2013). Equity in Learning? A Comparative Analysis of the PISA 2009 Results in Central and Eastern Europe and The Commonwealth of Independent States. Geneva: United Nations Children’s Fund.
World Bank (2001). Engendering Development – Through Gender Equality in Rights, Resources and Voice. Washington, DC.
World Bank (2012A). World Development Report 2012: Gender Equality and Development. Washington, DC.
World Bank (2012B). On Norms and Agency Conversations about Gender Equality with Women and Men in 20 Countries. Washington, DC.
World Bank (2014). “Moldova: Gender Disparities in Endowments and Access to Economic Opportunities”. Report 76077-MD, Washington, DC.
[1] The exception was the seminal Boserup (1970).
[2] See for instance Baden (1993).
[3] See Kabeer (2003) for an overview of research in development economics and policy experience relevant to the achievement of the Millennium Development Goals from the perspective of gender equality.
[4] Research – see Bhattacharya, Gathmann and Miller (2013) – however suggests that it might have been changing alcohol policy rather than transition per se that caused the sudden increase in mortality.
[5] The IMF has published a number of reports recently, such as Elborgh-Woytek et al (2013) and Kazandjian, Kolovich, Kochhar and Newiak (2016).
[6] See for instance, Becker et al (2010) and OECD (2015).
[7] Stereotype threat is defined as when an individual perceives to be ”at risk of confirming, as a self-characteristic, a negative stereotype about one’s social group” in the seminal paper by Steele and Aronson (1995).
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.
[18] Zaiats, D. 2015. The authorities will strengthen the fight against the shadow economy [Electronic resource]. – Mode of access: https://news.tut.by/economics/465337.html.
[19] On public procurement and repealing Directive 2004/18/EC [Electronic resource]// Directive 2014/24/EU of the European Parliament and of the Council / 26 Februay 2014. – Mode of access: https://news.tut.by/economics/465337.html.
[20] On making amendments and alterations to Instruction on the procedure of conducting cash transactions and the procedure of the cash settlement in Belarusian rubles on the territory of the Republic of Belarus // Resolution of the National Bank of the Republic of Belarus / 31.03.2014. #199. Rus: – О внесении дополнений и изменений в Инструкцию о порядке ведения кассовых операций и порядке расчетов наличными денежными средствами в белорусских рублях на территории Республики Беларусь. Mode of access: http://pravo.by/document/?guid=12551&p0=B21428983&p1=1&p5=0.
[21] Prozorro [Electronic source]. – Mode of access: https: //prozorro.gov.ua/en.
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
Source: Total Economy Database and IMF staff calculations.
Figure 2. GDP level in Poland and Ukraine
Source: Total Economy Database and IMF staff calculations.
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
Source: Total Economy Database and IMF staff calculations.
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
Source: IFA Statistics and IMF staff calculations.
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
Source: Total Economy Database and IMF staff calculations.
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
Source: Total Economy Database and IMF staff calculations.
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
Source: Total Economy Database and IMF staff calculations.
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
Source: Total Economy Database and IMF staff calculations.
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
Source: EBRD and IMF staff calculations.
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
Source: EBRD, Total Economy Database and IMF staff calculations.
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
Source: Total Economy Database and IMF staff calculations.
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
Source: EBRD, Total Economy Database and IMF staff calculations.
Similarly, richer countries have a more vibrant private sector (Figure 14).
Figure 14. Market reforms and private sector share in the economy
Source: EBRD, Total Economy Database and IMF staff calculations.
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
Source: WEO database and IMF staff calculations.
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
Source: WEO database and IMF staff calculations.
Figure 17. Labor markets in EU new member states
Source: Eurostat.
Figure 18. Labor utilization and productivity
Source: Total Economy Database, UN population statistics and IMF staff calculations.
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.