Location: Eastern Europe
Revisiting Growth Patterns in Emerging Markets
Recent studies document that emerging markets are rather similar in their growth patterns despite profound differences in starting conditions and productivity fundamentals. This challenges the common view on productivity as the main growth engine. The crucial role of the external environment for emerging markets emphasized by numerous studies adds to this doubt. I argue that productivity fundamentals still matter and remain the core driver of sustainable growth. However, external factors are crucial for understanding deviations from the trajectory of sustainable growth, i.e. episodes of growth accelerations/decelerations.
Challenges for Understanding Growth in Emerging Markets
As we enter the 4th decade of economic transition in Central and Eastern Europe (CEE), the causes and directions of causality of long-term growth in emerging markets might need to be reconsidered. Some recent studies emphasize that growth trajectories in emerging markets are pretty similar, i.e. average growth rates do not differ too much, while jumps and drops in growth rates are synchronous for the bulk of emerging economies (e.g. Fayad and Perelli, 2014). For instance, a decade ago the level of GDP per capita (in 2011 international $) in Macedonia was roughly 45% of that in the Slovak Republic, which likely reflected the productivity (measured through the Global Competitiveness Index) gap between them. During the last decade, Macedonia has roughly closed this productivity gap. Growth theory would postulate that this should have transformed into faster output growth in Macedonia vs. Slovak Republic closing well-being gap. However, the two countries’ had throughout the decade roughly equal average output growth and the well-being gap today is still the same as it was ten years ago.
Such observations seem to conflict with existing theoretical views. First, this is a challenge to the well-being convergence concept that results from growth theory. Moreover, if we measure growth in terms of the speed of closing the well-being gap with respect to the frontier (the US economy), one may argue even for divergence. For instance, Figure 1 presents a scatter-plot for a sample of emerging markets relating the initial conditions – well-being level in 1995 (GDP per capita relative to one of the US economy) – and the average speed of well-being gap (vs. the US economy) closing throughout 1996-2017 (measured in p.p. of corresponding gap ).
Second, the evidence that productivity gains do not automatically trigger output growth challenges a common view that productivity is the major driver for sustainable growth.
Figure 1.Starting Conditions and Well-Being Gains
Source: Own computations based on data from World Development Indicators database (World Bank).
What are possible explanations for the observed similarity in growth rates of emerging markets?
A study by the IMF (2017) suggests a response: growth in emerging markets is similar and synchronous due to the external environment. This study emphasizes the crucial dependence of medium-term growth in developing countries on the following factors: growth of external demand in trade partners, financial conditions, and trade conditions. Moreover, it states that these factors are dominant in explaining the episodes of growth strengthening/weakening.
Does this explanation change the growth nexus for emerging markets? Can one state, that while external factors are crucial for growth and growth in developing countries is rather homogenous, the productivity gains are not so important anymore?
I would say no. First, for better understanding of growth patterns we must clearly compare the relative importance of productivity gains vs. external factors in affecting the growth schedule. Second, we must separate relatively short-term fluctuations in GDP growth from sustainable growth.
Detecting Relative Importance of Growth Drivers
To answer the question about the relative importance of productivity fundamentals and growth factors, I study a panel of 34 emerging market economies (EBRD sample netted from 3 countries for which the data is not available) for 11 years (2007-2017).
To evaluate the relative importance of productivity and external factors, I use a standard approach of running panel growth regressions with fixed effects. At the same time, I make a number of novelties in the research design.
First, for measures of productivity, I engage a unique database – Global Competitiveness Indicators by World Economic Forum (WEF). Although this database provides an insightful perspective on productivity fundamentals at the country level, it is rather seldom a ‘guest’ in economic research. From this database, I extract a number of individual indicators in order to detect which ones among them that have the strongest growth-enhancing effect. For an alternative specification, I use principal components of 9 individual indicators from this database as proxies for productivity gains.
Second, for external factors, I use an approach similar to the IMF (2017) and calculate variables representing external demand growth, trade conditions, and financial conditions (such as a measure of capital inflows) for each country. Moreover, in respect to external demand growth, I use different competing measures (based on either imports of GDP growth of trade partners) and choose the best one in each individual equation. By doing so, I allow this dimension of the external environment to be represented in each model to the largest possible extent.
Third, I depart from using output growth as the only measure of economic growth and response variable in growth regressions. I argue that for international comparison purposes it is worthwhile to consider also the speed of closing the gap towards the frontier (the US economy). On the one hand, this measure is strongly correlated with the traditional output growth rate. On the other hand, this measure, in a sense, nets out the growth rate of a country from global growth, thus capturing something more unique and peculiar just to individual countries’ gains in well-being. Furthermore, I argue that in the discussion about the factors behind growth, one should distinguish between relatively short and long term growth. Annual growth rates, especially at relatively short time horizon, are too dependent on fluctuations, which may be interpreted in terms of growth rate strengthening/weakening. However, to emphasize the property of growth sustainability, we should get rid of ‘unnecessary noise’. For this purpose, I also introduce a trend growth rate measured in a most simple way as the 5 year moving average (following the discussion in Coibion et al. (2017), show that the bulk of measures of ‘potential’ growth are not good enough to get rid of demand shocks and these measures are pretty close to simple moving average measures).
I apply this definition of trend growth both to ‘standard’ GDP growth rate and to the speed of closing the gap towards frontier. So, finally I have 4 response variables: ‘standard’ growth rate, the speed of closing the gap to frontier, and two corresponding measures of trend growth.
Sustainable Growth Mainly Depends on Productivity
Having short-term (annual) growth rate as response variable (either ‘standard’ or the one in terms of closing the gap) provides results close to those in IMF (2017). It may be interpreted in a way that the external environment is more important than productivity factors. If dividing all regressors into two broad groups of factors – external and productivity – the former is responsible for up to 70% of the growth effect, while the latter for about 30%. Among external environment factors, the most important one is financial conditions. Its relative importance is roughly 50% of the group of external factors’ total.
Among productivity fundamentals, an important contributor to short-term growth is the quality of the macroeconomic environment. According to the methodology of WEF (2017), this indicator encompasses the fiscal stance, savings-investment balance, the external position, inflation path, debt issues, etc.
When refocusing from short-term growth to the growth trend as a response variable, the relative importance of the factors behind growth changes. Productivity fundamentals in this case drive up to 80% of growth effect, while external factors are responsible for the remaining 20%. It is worth noting here that the proportion in favor of productivity factors is higher for the concept of closing the gap to frontier rather than for ‘standard’ trend growth rate. This evidence may be interpreted as additional justification for treating this measure of growth as ‘good’ at reflecting individual properties of a country in a global landscape.
Furthermore, the role of individual variables also changes. Among external factors, the most important role in driving sustainable growth belongs to trade conditions and external demand growth, while the role of financial conditions is either miserable or insignificant at most. Among productivity factors as drivers of trend growth, the quality of the macroeconomic environment seems to play a special role, as well as the efficiency of the goods market and the financial system.
Conclusions
The evidence showing rather similar and synchronous growth in emerging markets and recent evidence on the crucial importance of external factors for emerging markets should not lead us to incorrectly believe that productivity fundamentals do not matter anymore. Productivity fundamentals are still the core driver of sustainable growth. At the same time, we should keep in mind the important role of the external environment for emerging markets. However, changes in the external environment are more likely to generate relatively short-term growth rate fluctuations, while having a modest impact on the sustainable growth trajectory. Hence, a country aiming to secure sustainable growth should still first of all think about productivity fundamentals.
References
- Coibion, O., Gorodnichenko, Y, Ulate, M. (2017). The Cyclical Sensitivity in Estimates of Potential Output, National Bureau of Economic Research, Working Paper No. 23580.
- EBRD (2017). Transition Report 2017-2018, European Bank for Reconstruction and Development, London, UK.
- Fayad, G., and Perelli, R. (2014). Growth Surprises and Synchronized Slowdown in Emerging Markets—An Empirical Investigation, IMF Working Paper, WP/14/173.
- IMF (2017). Roads Less Traveled: Growth in Emerging Markets and Developing Economies in a Complicated External Environment, in IMF World Economic Outlook, April, 2017, pp. 65-120.
- World Economic Forum (2017). The Global Competitiveness Report 2017-2018, Geneva: World Economic Forum.
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.
Stylized Facts from 25 Years of Growth in Transition
This brief summarizes the growth experience of transition countries 25 years after the dissolution of the Soviet Union. We divide our sample into two main groups: the 10 transition countries in Eastern Europe and the Baltics that became EU members in 2004 and 2007 (EU10); and the 12 countries (ex Baltics) that emerge from the Soviet Union (FSU12). The growth experiences of these two groups have been distinctly different. The magnitude of the initial transition decline in output was much more severe in the FSU12 group. Despite growing almost 2 percentage points faster than the average EU10 for the following fifteen years, the FSU12 group is still further behind the EU10 group than they were at the beginning of transition. This illustrates how hard it is for countries to recover from large negative income shocks and thus the importance for countries to avoid such negative events. However, there are no signs of transition countries being stuck in a low or middle-income trap or that natural resource wealth leads to lower growth during this period.
2017 marked the 25-years anniversary after the dissolution of the Soviet Union and the beginning of the transition for the economies in the region. In a recent paper, we explore the growth experience of transition countries over these 25 years (Becker and Olofsgård, 2017). The paper has four main parts: an overview of the transition literature focusing on growth; a part that provides a detailed description of growth in transition; an analytical section that investigate if we can explain growth in transition countries with a standard growth model; and finally an exploration of whether institutional and other variables that have been highlighted in the transition literature (but are excluded from the basic growth model) are correlated with growth in transition countries. This brief summarizes the descriptive part of the paper, while the more analytical sections will be the topic of future briefs.
For most of the paper, we divide our sample into two main groups; the 10 transition countries in Eastern Europe and the Baltics that became EU members in 2004 and 2007 (EU10); and the 12 countries that emerged from the Soviet Union (FSU12). In addition, we include three transition countries that are not part of either group (Croatia, Albania and Macedonia – Other3) and we also divide the FSU12 group into the four countries that export significant amounts of fuel (FSUF) and the eight countries that do not (FSUNF). There are of course remaining differences within these groups, but this aggregate analysis allows us to see certain patterns in the transition process more clearly.
Initial output collapses
The focus in economics is often on how to generate higher growth and not about protecting against significant drops in output. There are some exceptions, including Becker and Mauro (2006) and Cerra and Saxena (2007), where the focus is on output losses and how countries recover after crises. For transition countries, a very important feature of the economic development process is exactly the initial drop in income and the time it has taken countries to recover from the initial phase of transition. Table 1 shows how much income fell in the different country groups and the time it took to get back to the pre-transition income level.
Table 1. Output drops and recoveries
Source: Becker and Olofsgård (2017)
The initial collapse in the FSU12 group was enormous, with income cut in half. The EU10 countries also had massive output losses, but “only” lost a quarter of their income on average. This took over a decade to recover from, while the path back to pre-transition income levels in the average FSU12 country was almost twice as long. There have been many papers written on the economic chaos that was part of the initial transition process, and explanations for this decline has been attributed to, e.g., misleading data, lack of functioning markets, shock therapy and poor economic and legal institutions in general. All of these factors have likely played important roles in the process, but regardless of the explanation, this was a very unfavorable time in terms of economic outcomes for hundreds of millions of people in these countries. Avoiding such costly drops in output should be a top priority for economic policy makers in any country at all times, not just in transition.
From collapse to growth
In most transition countries, the initial phase of decline in transition lasted several years, but eventually the negative growth rates turned positive (Figure 1). Again, we can see that the EU10 group had fewer years of declining incomes with growth resuming in 1993, while for the FSU12 group, growth in transition only started in 1996/7.
Figure 1. Bust-Boom countries
Source: Becker and Olofsgård (2017)
What is less visible in Figure 1 due to the wide scale needed to capture the initial output drops is that the FSU12 groups has shown significantly higher growth than the EU10 group in the last 15 years. Over the more recent period, the average FSU12 country has grown by close to 6 percent, while growth for the EU10 has been around 4 percent per annum (Table 2).
Table 2. Real GDP/cap growth
Source: Becker and Olofsgård (2017)
The faster growth in FSU12 countries is particularly pronounced among the fuel exporters, which were growing by one and a half percentage point faster than the non-fuel exporters between 2000 and 2015. But the table also shows that the very negative growth experience during the first ten years of transition is hard to erase and the EU10 countries have grown faster over the full 25-year period compared to the FSU12 countries. In terms of understanding the growth experience of the different country groups and time periods, it is clear that the sharp increase in international oil prices during the last 15 years of the period generated high growth in the fuel exporting countries in the FSU12 group. Interestingly though, also the non-fuel exporters grew faster than the EU10 in this time period. This is likely linked to spillovers from Russia to the other countries in the region, but could also be related to some recovering after the massive initial declines in output. Such macro and external factors are not always stressed in discussions of growth in transition countries, which more often focus on the pace of reforms or strength of institutions, but seem to be relevant at this aggregate level when comparing the initial and later phases of transition.
Relative incomes in transition countries
Growth or the lack thereof is of importance in determining income levels, which is what we generally think is what influences welfare. The question is then what the growth processes we have analyzed imply for income levels in transition countries, and in particular, how the income levels in these countries compare with other countries.
Figure 2. Income relative to 15 old EU countries
Source: Becker and Olofsgård (2017)
The short story here is that the relative ranking of the different groups is largely unchanged from the start of transition until the end of 2015. The group of countries that eventually joined the EU has the highest income level while the non-fuel exporting FSU countries have the lowest. However, the leading group still only has around 60 percent of the income of the average “old” EU country while the average FSU12 country has half of that or around 30 percent of the income of the old EU countries. This puts the relatively high growth rates of the FSU12 group over the last 15 years in perspective; the road to reach old EU level incomes is long indeed. Also, within the FSU group, it is clear that there is a sharp dividing line between the fuel exporters and the rest. This is in stark contrast to the notion of a “natural resource curse” that is often blamed for poor growth in oil and mineral rich countries.
Growth traps in transition?
One issue that comes up with regards to both low and middle-income countries is if they are stuck at a certain level in the relative income rankings of the world. This is referred to as the low or middle-income trap and the question is if there are signs of transition countries being stuck in such traps.
Figure 3. Moving up the income ladder
Source: Becker and Olofsgård (2017)
Figure 3 shows how transition countries are classified into the World Banks income groups low income (1 in the Figures scale), lower middle income (2), higher middle income (3) and high income (4) groups.
It is clear that the FUS 12 group of countries was sliding down the scale initially, but since the beginning of the 2000’s, all of the transition countries have been climbing up the World Bank income ranking scale without any apparent signs of a low or middle-income trap.
Policy conclusions
There are of course country differences along all the dimensions discussed in this brief but grouping the transition countries together provides some interesting general observations of growth in transition. First of all, it is clear that it is very hard to fully recover from large drops in income. Even with the help of some extra growth following a crisis, it seems to take a long time for most countries to make up for lost ground. This suggests that policy makers in transition as well as other countries need to take measures to hedge the really bad outcomes and not only focus on how to generate an extra one percent of growth.
The other observation is that at the aggregate level, external factors and more mechanical macro boom-bust-boom type of growth factors may dominate what we generally think of as the long-run determinants of growth (such as institutions, education, and micro level reforms to make markets work better) over very long time spans. This does not mean that the focus on the more fundamental growth drivers should diminish, but it is important that reforms in these areas are complemented with a macroeconomic framework that reduces the risks of costly output collapses.
Finally, it is clear that the incomes generated by natural resources can produce growth at the macro level and that there is little evidence that transition countries should be stuck at any particular level in the global income rankings. Go transition countries!
References
- Becker, T, and A. Olofsgård (2017), “From abnormal to normal—Two tales of growth from 25 years of transition”, SITE Working paper 43, September.
- Becker, T., and P. Mauro, (2006). “Output Drops and the Shocks That Matter”. IMF Working Papers 06/172.
- Cerra, V., and S.C. Saxena (2008). ”Growth Dynamics: The Myth of Economic Recovery”. American Economic Review, 98(1), 439–457.
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).
Traces of Transition: Unfinished Business 25 Years Down the Road?
This year marks the 25-year anniversary of the breakup of the Soviet Union and the beginning of a transition period, which for some countries remains far from completed. While several Central and Eastern European countries (CEEC) made substantial progress early on and have managed to maintain that momentum until today, the countries in the Commonwealth of Independent States (CIS) remain far from the ideal of a market economy, and also lag behind on most indicators of political, judicial and social progress. This policy brief reports on a discussion on the unfinished business of transition held during a full day conference at the Stockholm School of Economics on May 27, 2016. The event was organized jointly by the Stockholm Institute of Transition Economics (SITE) and the Swedish Ministry for Foreign Affairs, and was the sixth installment of SITE Development Day – a yearly development policy conference.
A region at a crossroads?
25 years have passed since the countries of the former Soviet Union embarked on a historic transition from communism to market economy and democracy. While all transition countries went through a turbulent initial period of high inflation and large output declines, the depth and length of these recessions varied widely across the region and have resulted in income differences that remain until today. Some explanations behind these varied results include initial conditions, external factors and geographic location, but also the speed and extent to which reforms were implemented early on were critical to outcomes. Countries that took on a rapid and bold reform process were rewarded with a faster recovery and income convergence, whereas countries that postponed reforms ended up with a much longer and deeper initial recession and have seen very little income convergence with Western Europe.
The prospect of EU membership is another factor that proved to be a powerful catalyst for reform and upgrading of institutional frameworks. The 10 countries that joined the EU are today, on average, performing better than the non-EU transition countries in basically any indicator of development including GDP per capita, life expectancy, political rights and civil liberties. Even if some of the non-EU countries initially had the political will to reform and started off on an ambitious transition path, the momentum was eventually lost. In Russia, the increasing oil prices of the 2000s brought enormous government revenues that enabled the country to grow without implementing further market reforms, and have effectively led to a situation of no political competition. Ukraine, on the other hand, has changed government 17 times in the past 25 years, and even if the parliament appears to be functioning, very few of the passed laws and suggested reforms have actually been implemented.
Evidently, economic transition takes time and was harder than many initially expected. In some areas of reform, such as liberalization of prices, trade and the exchange rate, progress could be achieved relatively fast. However, in other crucial areas of reform and institution building progress has been slower and more diverse. Private sector development is perhaps the area where the transition countries differ the most. Large-scale privatization remains to be completed in many countries in the CIS. In Belarus, even small-scale privatization has been slow. For the transition countries that were early with large-scale privatization, the current challenges of private sector development are different: As production moves closer to the world technology frontier, competition intensifies and innovation and human capital development become key to survival. These transformational pressures require strong institutions, and a business environment that rewards education and risk taking. It becomes even more important that financial sectors are functioning, that the education system delivers, property rights are protected, regulations are predictable and moderated, and that corruption and crime are under control. While the scale of these challenges differ widely across the region, the need for institutional reforms that reduce inefficiencies and increase returns on private investments and savings, are shared by many.
To increase economic growth and to converge towards Western Europe, the key challenges are to both increase productivity and factor input into production. This involves raising the employment rate, achieving higher labor productivity, and increasing the capital stock per capita. The region’s changing demography, due to lower fertility rates and rebounding life expectancy rates, will increase already high pressures on pension systems, healthcare spending and social assistance. Moreover, the capital stock per capita in a typical transition country is only about a third of that in Western Europe, with particularly wide gaps in terms of investment in infrastructure.
Unlocking human potential: gender in the region
Regardless of how well a country does on average, it also matters how these achievements are distributed among the population. A relatively underexplored aspect of transition is to which extent it has affected men and women differentially. Given the socialist system’s provision of universal access to education and healthcare, and great emphasis on labor market participation for both women and men, these countries rank fairly well in gender inequality indices compared to countries at similar levels of GDP outside the region when the transition process started. Nonetheless, these societies were and have remained predominantly patriarchal. During the last 25 years, most of these countries have only seen a small reduction in the gender wage gap, some even an increase. Several countries have seen increased gender segregation on the labor market, and have implemented “protective” laws that in reality are discriminatory as they for example prohibit women from working in certain occupations, or indirectly lock out mothers from the labor market.
Furthermore, many of the obstacles experienced by small and medium-sized enterprises (SMEs) are more severe for women than for men. Female entrepreneurs in the Eastern Partnership (EaP) countries have less access to external financing, business training and affordable and qualified business support than their male counterparts. While the free trade agreements, DCFTAs, between the EU and Ukraine, Georgia, and Moldova, respectively, have the potential to bring long-term benefits especially for women, these will only be realized if the DCFTAs are fully implemented and gender inequalities are simultaneously addressed. Women constitute a large percentage of the employees in the areas that are the most likely to benefit from the DCFTAs, but stand the risk of being held back by societal attitudes and gender stereotypes. In order to better evaluate and study how these issues develop, gendered-segregated data need to be made available to academics, professionals and the general public.
Conclusion
Looking back 25 years, given the stakes involved, things could have gotten much worse. Even so, for the CIS countries progress has been uneven and disappointing and many of the countries are still struggling with the same challenges they faced in the 1990’s: weak institutions, slow productivity growth, corruption and state capture. Meanwhile, the current migration situation in Europe has revealed that even the institutional development towards democracy, free press and judicial independence in several of the CEEC countries cannot be taken for granted. The transition process is thus far from complete, and the lessons from the economics of transition literature are still highly relevant.
Participants at the conference
- Irina Alkhovka, Gender Perspectives.
- Bas Bakker, IMF.
- Torbjörn Becker, SITE.
- Erik Berglöf, Institute of Global Affairs, LSE.
- Kateryna Bornukova, Belarusian Research and Outreach Center.
- Anne Boschini, Stockholm University.
- Irina Denisova, New Economic School.
- Stefan Gullgren, Ministry for Foreign Affairs.
- Elsa Håstad, Sida.
- Eric Livny, International School of Economics.
- Michal Myck, Centre for Economic Analysis.
- Tymofiy Mylovanov, Kyiv School of Economics.
- Olena Nizalova, University of Kent.
- Heinz Sjögren, Swedish Chamber of Commerce for Russia and CIS.
- Andrea Spear, Independent consultant.
- Oscar Stenström, Ministry for Foreign Affairs.
- Natalya Volchkova, Centre for Economic and Financial Research.
Is War Good for a Country’s Political Institutions?
Author: Tom Coupe, KSE.
Recent research suggests that experiencing war violence might make people more likely to turn out during elections. Using data from the conflict in Eastern Ukraine, we show, however, that people who were injured or had close friends or relatives killed or injured were less likely to turn out at the 2014 parliamentary elections. We also show that the impact of violence on turn out and political views depends on the type of violence one experienced.
Urban Land Misallocation and Markets in Russian Cities
Authors: Paul Castañeda Dower, CEFIR and William Pyle, Middlebury College.
Former socialist countries inherited factory-dominated cityscapes since planners made industrial location decisions in relative ignorance of land’s opportunity costs. Drawing on unique survey evidence and policy variation across territorial units within Russia, this brief discusses the relationship between land tenure reforms and land reallocation. The evidence points to land privatization as an important factor in the reallocation of land in Russian cities.
Macroeconomic Performance and Preferences for Democracy
This policy brief summarizes the results of our research on factors influencing preferences for democracy in transition countries. The aim of this work was to detect which macroeconomic and individual factors impact the choice of supporting democracy. The results showed that the performance of the country, described by level of GDP, unemployment, level of corruption and economic growth, has a serious impact on an individual’s perception of democracy. At the same time, individual factors like education and age also influence people’s choice of support of democratic authorities.
Individual perception of democracy is a question that attracts the attention of policymakers. The macroeconomic instability that has been observed worldwide lately is likely to impact individual attitude toward democratic values and political institutions. The recent economic crisis brought a deterioration of the economic situation around the world and provided new challenges to cope with. It is likely that macroeconomic indicators have an impact on how a person perceives democracy. Literature studying similar questions has shown that GDP growth, unemployment and inflation all affect personal attitude to democratic institutions (Clarke et. al., 1994; Barro, 1999; Papaioannou and Siourounis, 2008). As for individual characteristics, the level of education is revealed by the literature as a very important factor in the context of the individual’s propensity of democracy approval.
The literature on the determinants of political support and attitudes to democracy was mostly focusing on exploring stable world economies with long-formed and steady-functioning democracies. We tried to look at a similar question in the context of transition economies, where democratic institutions are still under development.
We intend to estimate individuals’ propensity to favor democratic values. The specification of our econometric model was based on the literature addressing the same topic. The estimation procedure used probit econometric techniques, which allows for the calculation of the propensities of interest while taking into account the influence of both macroeconomic factors and individual characteristics. The paper used two sources of data: macroeconomic information was collected from the World Development Indicators of the World Bank, and individual-level cross-sectional data was obtained from Life in Transition Survey (LITS) 2010, which initially covered 38864 individuals from 35 countries. However, as the paper focuses on countries in transition, the final set only included individuals from 30 countries, most from Eastern Europe, Baltics and CIS, and excluded representatives of Western Europe. This data allowed for substantial data variation in the context of economic development vs. perception of democratic values (Graph 1).
Figure 1. Support of Democracy and GDP Per Capita
Source: WDI and LITS 2010
Inclusion of different macroeconomic variables together with individual factors allowed for an evaluation of their importance and level of impact on the perception of democratic values (Table 1). The results show that GDP per capita has a positive and significant effect on individuals’ perception of democratic values, which is in line with the literature claiming that standard of living in countries with not so high level of GDP is positively correlated with satisfaction with their life and the political system (Easterlin, 1995; Clark et al., 2008; Stevenson and Wolfers, 2008). Inflation rates are not significant and do not influence individuals’ attitude to democracy. On the other hand, economic growth is strictly positive and significant, and an increase of the economic growth rate raises propensity of democratic support by around 1.6 percentage points. The possible explanation here is that the growth rate of GDP works as a proxy of expectations for improvements of the standard of living in the future.
Table 1. Influence of Macroeconomic and Individual Factors on Perception of Democracy
Unemployment works as an indicator of a country‘s economic performance and has an expected negative sign in terms of individuals’ satisfaction with life and political institutions, which is also in line with the results in the literature (Di Tella et al., 2001; Wagner and Schneider, 2006). Impact of unemployment was tested using a cross product of unemployment and the Freedom House Index (this latter indicator shows the level of political and civil rights from 1 (most free) to 7 (least free)). The sign on this cross product is positive, which captures their mutual positive impact on the support for democracy. Thus, the higher the unemployment in a country with a low level of democratization is, the larger the probability of democratic support by individuals in these countries is. The indicator for the level of corruption in a country was also taken into account, via the Corruption Perception Index. This index ranks countries on a scale from 0 (highly corrupt) to 10 (effectively, corruption-free). The results show that the less corrupt a country is, the higher the propensity that an individual in that country will support democracy is. In fact, one additional point in the index increases the propensity of support by almost 4 percentage points. Military expenditures negatively affect the support of democratic values, and so does the existence of oil in the country. Here, military expenditures may be seen as a proxy for a less democratic regime, so that the leaders there have higher incentives to rule using suppressive measures with a support of military force in the country (Mulligan, Gil and Sala-i-Martin, 2004).
As for the individual factors, both secondary and higher education appear to be very important factors with a positive impact on the satisfaction with democracy. This finding follows the literature (Barro, 1999; Przeworski et al., 2000; Glaeser et al., 2004). In our results, people with secondary or higher education degree showed 10 and 18 percentage points higher propensity of support, respectively. Age also seem to matter: positive perception of democracy is specific to those aged 18-54, compared to the older generation, which goes in line with the explanation that senior citizens are more conservative than younger citizens. We also observe a negative significant coefficient on female gender, which may, perhaps, be related to women being more conservative than men.
Subjective relative income measure (answer to the question “to which income quintile do you think you belong to?”) has a positive impact on the support for democracy. Surprisingly, individuals from middle-income group have a more positive attitude than those who regard themselves as rich. Employment status is positively correlated with the support for democracy. Moreover, self-employment and employment in the public sector have a larger effect on the propensity of positive attitude to democratic values than employment in the private sector.
Divorced and widowed people expressed less support for democracy than single individuals, which might signal some dissatisfaction that impacts on personal attitude. Urban residency is positively correlated with the support of democracy. The same relationship is present for the risk tolerance of an individual. Finally, inclusion of a subjective measure of life satisfaction brought some changes to the general picture. It appeared that those who are satisfied with life strongly support the democratic values and such mentality raises the propensity of support by 7 percentage points. Moreover, inclusion of this variable makes the effect of being rich insignificant.
To sum up, the results showed that economic performance of the country described by various macroeconomic indicators has a serious impact on individual’s perception of democracy and, most probably, of other forms of government. At the same time individual factors also influence people’s satisfaction with the authorities. Thus, individual support of a political system is based on the results of performance of both the individual and the country.
References
- Barro R. 1999. “Determinants of Democracy.”Journal of Political Economy 107, #S6.
- Clark A. and Oswald A.J. 1994.“Unhappiness and Unemployment.”EconomicJournal104.
- Clark A., FrijtersP. and Shields M. 2008. “Relative Income,Happiness and Utility: An Explanation for the Easterlin Paradox and Other Puzzles.” Journal of Economic Literature46,# 1.
- DiTellaR., MacCulloch R.J., Oswald A.J. 2001. “Preferences over inflation and unemployment: Evidence from surveys of happiness.”American Economic Review91.
- Easterlin R. 1995. “Will Raising the Incomes of All Increase the Happiness of All?”Journal of Economic Behavior and Organization27, # 1.
- Glaeser E., La PortaR., Lopez-de-SilanesF. and ShleiferA. 2004.“Do Institutions Cause Growth?” Journal of Economic Growth.9, #3.
- Mulligan C.B., Gil R. and Sala-i-Martin X. 2004. “Do Democracies HaveDifferent Public Policies than Nondemocracies?” Journal of Economic Perspectives18, #1.
- Papaioannou, E. and Siourounis G. 2008.“Economic and Social Factors Drivingthe Third Wave of Democratization.” Journal of Comparative Economics36, #3.
- Prezworski A., Alvarez M., Cheibub J. and LimongiF. 1996. “WhatMakes Democracy Endure?” Journal of Democracy 7, #1.
- Stevenson, B. and Wolfers, J. 2008. “Economic Growth and SubjectiveWell-Being: Reassessing the Easterlin Paradox.” Brookings Papers on Economic Activity 1.
- Wagner A.F. andSchneider F. 2006. “Satisfaction with Democracy and the Environment in Western Europe: A Panel Analysis.” IZA Discussion Papers 1929, Institute for the Study of Labor (IZA).
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.
Managed Competition in Health Insurance Systems in Central and Eastern Europe
This policy brief summarizes common trends in the development of health care systems in the Czech Republic, Slovakia, and Russia in late 1990s–early 2000s. These countries focused on regulated competition between multiple health insurance companies. However, excessive regulation led to various deficiencies of the model. In particular, improvements in such quality indicators of the three health care systems as infant and under-five mortality are unrelated to the presence of multiple insurers or insurer competition.
A number of transition countries in Central and Eastern Europe and the former Soviet Union introduced health care systems with compulsory enrollment, obligatory insurance contributions unrelated to need and coverage according to a specified package of medical services. This so-called social health insurance (SHI) model (Culyer, 2005) is regarded as a means for achieving universal coverage, stable financial revenues, and consumer equity (Balabanova et al. 2012; Gordeev et al., 2011; Zweifel and Breyer, 2006; Preker et al., 2002). While most transition countries chose to only have a single health insurance provider on the market, the Czech Republic, Slovakia, and Russia allowed competitive (and often private) insurers in the new system. However, the evidence from the three countries shows excessive regulation of health insurers and limited instruments for insurer competition within indebted post-reform health care systems (Naigovzina and Filatov, 2010; Besstremyannaya, 2009; Medved et al., 2005). Consequently, the three countries may have been over-enthusiastic in putting large emphasis on market forces in the reorganization of health care systems in economies with a legacy of central planning (Diamond, 2002).
This brief addresses the results of Besstremyannaya (2010), which assesses the impact of private health insurance companies on the quality of health care system. While various performance measures reflect different goals of national and regional health care systems (Joumard et al., 2010; Propper and Wilson, 2006; OECD, 2004; WHO, 2000), aggregate health outcomes directly related to the quality of health care are commonly infant and under-five mortality (Lawson et al., 2012; Gottret and Schieber, 2006; Wagstaff and Claeson, 2004; Filmer and Pritchett, 1999). Consequently, Besstremyannaya’s (2010) analysis regards mortality indicators as variables reflecting the overall quality of health care system.
The estimations employ data on Russian regions in 2000-2006. The results indicate that regions with only private health insurers have lower infant and under-five mortality. However, given the low degree of competition on the social health insurance market in Russia, we hypothesize that this effect is mostly driven by positive institutional reforms in those regions. Indeed, incorporating the effect of institutional financial environment, we find that the impact of private health insurers becomes insignificant.
Development of a Social Health Insurance Model in the Czech Republic, Slovakia, and Russia
At the beginning of their economic transition, the Czech Republic, Slovakia, and Russia established a model for universal coverage of citizens by mandatory health insurance (Balabanova et al., 2012; Medved et al., 2005; Sheiman, 1991). The revenues of the new SHI system came from a special payroll tax and from government payments for health care provision to the non-working population. The main reason for combining certain features of taxation-based and insurance-based systems was the desire to establish mandatory health insurance as a reliable source of financing in an environment with unstable budgetary revenues (Lawson and Nemec, 2003; Preker et al., 2002; Sheiman, 1994). The insurance systems instituted in the three transition countries correspond to the major SHI principles implemented in Western Europe: contributions by beneficiaries according to their ability to pay; transparency in the flow of funds; and free access to care based on clinical need (Jacobs and Goddard, 2002).
The Czech Republic, Slovakia, and Russia placed emphasis on regulated competition, decreeing that SHI should be offered by multiple private insurance companies with a free choice of the insurer by consumers. Managers of private insurance companies were assumed to perform better than government executives (Lawson and Nemec, 2003; Sinuraya, 2000; Curtis et al., 1995), so an intermediary role for private insurance companies was seen as a key instrument for introducing market incentives and improving the quality of the health care system (Sheiman, 1991).
However, the activity of health insurance companies in the three countries was heavily regulated, since the content of benefit packages, size of subscriber contributions, and the methods of provider reimbursement were decided by government, and tariffs for health care were frequently revised (Lawson et al., 2012; Rokosova et al., 2005; Zaborovskaya et al., 2005; Praznovcova et al., 2003; Hussey and Anderson, 2003). In particular, Russian health care authorities enforced rigid assignments of areas, whose residents were to be served by a particular health insurance company (Twigg, 1999) and imposed informal agreements with health insurance companies to finance providers regardless of the quality and quantity of the health care (Blam and Kovalev, 2006). As a result, the three countries experienced an initial emergence of a large number of health insurance companies, followed by mergers between them, resulting in high market concentration (Sergeeva, 2006; Zaborovskaya et al., 2005; Medved et al., 2005).
In Russia, the Health Insurance Law (1991) specified that until private insurers appeared in a region, the regional SHI fund or its branches could play the role of insurance companies. Therefore, several types of SHI systems emerged in Russian regions in the 1990s and early 2000s: the regional SHI fund might be the only agent on the SHI market; the regional SHI fund might have branches, acting as insurance companies; SHI might be offered exclusively by private insurance companies; or SHI might be offered by both private insurance companies and branches of the regional SHI fund (Figure 1). The variety of SHI systems reflects the fact that many regions opposed market entry by private insurance companies (Twigg, 1999). Indeed, the boards of directors of regional SHI funds usually included regional government officials (Tompson, 2007; Tragakes and Lessof, 2003) who were reluctant to reduce government control over SHI financing sources (Blam and Kovalev, 2006; Twigg, 2001). The controversy with health insurance legislation created a substantial confusion at the regional and the municipal level (Danishevski et al., 2006).
Figure 1. Health insurance agents in Russia in 2000-2006, (number of regions) 
This context suggests that Russian regions provide an interesting study field to address the impact of private health insurance companies on the quality of health care system. In particular, the wide variety of SHI systems across Russian regions, as well as the gradual introduction of the health insurance model in Russia provide a sufficient degree of variation in practices and outcomes to allow for a well-specified empirical analysis.
Data and Results
In our analysis we use data on Russian regional economies between 2000 and 2006 (as based on data availability). Our measures of health outcomes are given by the pooled regional data on infant and under-five mortality. Our key explanatory variable is the presence of only private health insurers in the region. Arguably, the coexistence of public and private health insurance companies does not enable effective functioning of private health insurers owing to their discrimination by the territorial health insurance fund. Therefore, in the empirical estimations we focus on the presence of only private health insurers in the region, regarding it as a measure of effective health insurance model. The analysis also employs a variety of important socio-economic and geographic variables influencing health outcomes (per capita gross regional product (GRP), share of private and public health care expenditure in gross regional product, share of urban population, average temperature in January).
The results of the first set of our empirical estimations demonstrate that the presence of only private health insurers in a region leads to lower infant and under-five mortality. Furthermore, an increase in the share of private health care expenditure in GRP leads to a decrease in both mortality indicators. The result is consistent with numerous findings about the association between personal income and health status in Russia (Balabanova et al., 2012; Sparling, 2008).
Prospective reimbursement of health care providers is associated with a decrease in infant and under-five mortality. The finding suggests the existence of a quasi-insurance mechanism in the Russian SHI market. Operating in an institutional environment where provider reimbursement is based on prospective payment, private insurance companies in effect shift a part of their risk to providers (Glied, 2000; Sheiman, 1997; Chernichovsky et al., 1996).
Table 1. Factors leading to decreased infant and under-five mortality in Russia
Although our analysis shows that the presence of only private health insurers is statistically associated with improvements in infant and under-five mortality, we believe that the influence is indirect. Namely, the overall positive institutional environment in the region may result in both a decrease of mortality indicators and a lower coercion of regional authorities towards the presence of private health insurance companies.
To test this hypothesis, we use financial risk in a region as a measure of institutional environment and incorporate it in the analysis through an instrumental variable approach. (We measure financial risk by an expertly determined rank ordered variable by RA expert rating agency; this variable reflects the balance of the budgets of enterprises and governments in the region, with lower ranks corresponding to smaller risk.)
In line with our hypothesis, the results suggest that the presence of private health insurance companies now becomes insignificant in explaining infant and under-five mortality.
Discussion
The existing literature suggests that the improvement in infant and under-five mortality in the Czech Republic, Slovakia, and Russia can be attributed primarily to an increase of health care spending (Gordeev et al. 2011; Besstremyannaya, 2009; Lawson and Nemec, 2003) rather than being an effect of the social health insurance model with multiple competing insurers. It should be noted that insufficient government payments for the non-working population and a decline of the gross domestic product in the early transition years left SHI systems in the three countries indebted (Naigovzina and Filatov, 2010; Sheiman, 2006; Medved et al., 2005), which undermined the development of the managed competition in the health care provision.
In Russia (and also in the Czech Republic and Slovakia) there is little competition between insurers, and surveys show that the main factors causing consumers to change their health insurance company are change of work or residence, and not dissatisfaction with the insurer (Baranov and Sklyar, 2009). The fact that law suits on defense of SHI patient rights are rarely submitted to courts through health insurers (Federal Mandatory Health Insurance Fund, 2005) may also be evidence of the failure of Russian health insurance companies to win customers on the basis of their competitive strengths.
Summary and Policy Implications
The above findings as well as the other mentioned literature suggest that improvements of infant and under-five mortality in the Czech Republic, Slovakia, and Russia are not associated with the positive role of managed competition in the social health insurance system. In particular, in Russia the decrease in infant and under-five mortality is likely to be related to financial environment, rather than the existence of insurance mechanisms or competition between health insurance companies. One possible explanation of this absence of effect may come from the excessive regulation of the private insurance markets, as well as the insufficient competition between insurers. Importantly, the health insurance reform, implemented in Russia in 2010, both addressed underfinancing (by raising payroll tax rates) and took a step towards fostering provider competition, by allowing private providers to enter the social health insurance market (Besstremyannaya 2013). However, insurance companies are still not endowed with effective instruments for encouraging quality by providers, which may greatly undermine their efficiency.
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References
- Balabanova D, Roberts B, Richardson E, Haerpfer C, McKee V. 2012. Health Care Reform in the Former Soviet Union: Beyond the Transition. Health Services Research 47(2): 840-864.
- Baranov IN, Sklyar TM. 2009. Problemy strakhovoi modeli zdravookhraneniya na primere Moskwy i Sankt-Peterburga (Problems of insurance model in health care: the example of Moscow and Saint Petersburg). In X International Conference on the Problems of Development of Economy and Society, Yasin E.G (ed), Moscow: Higher School of Economics, vol.2.
- Besstremyannaya GE. 2013. Razvitie systemy obyazatelnogo meditsinskogo strakhovaniya v Rossijskoi Federatsii (Development of the Mandatory Health Insurance system in the Russian Federation) Federalizm 3: 201-212
- Besstremyannaya GE. 2010. Essays in Empirical Health Economics. PhD thesis. Keio University (Tokyo).
- Besstremyannaya GE. 2009. Increased public financing and health care outcomes in Russia. Transition Studies Review 16: 723-734.
- Blam I, Kovalev S. 2006. Spontaneous commercialization, inequality and the contradictions of the mandatory medical insurance in transitional Russia. Journal of International Development 18: 407–423.
- Culyer AJ (2005) The Dictionary of Health Economics, Edward Elgar.
- Danishevski K, Balabanova D, McKee M, Atkinson S. 2006. The fragmentary federation: experiences with the decentralized health system in Russia. Health Policy and Planning 21: 183–194.
- Gordeev VS, Pavlova M, Groot W. 2011. Two decades of reforms. Appraisal of the financial reforms in the Russian public healthcare sector. Health Policy 102(2-3): 270-277.
- Hussey P, Anderson GF. 2003. A comparison of single- and multi-payer health insurance systems and options for reform. Health Policy 66: 215-228.
- Jacobs R, Goddard M. 2002. Trade-offs in social health insurance systems. International Jthenal of Social Economics 29(11): 861-875.
- Lawson C, Nemec J, Sagat V. 2012. Health care reforms in the Slovak and Czech Republics 1989-2011: the same or different tracks? Ekonomie a management 1, 19-33.
- Lawson C, Nemec J. 2003. The political economy of Slovak and Czech health policy: 1989-2000. International Political Science Review 24(2): 219-235.
- Medved J, Nemec J, Vitek L. 2005. Social health insurance and its failures in the Czech Republic and Slovakia: the role of the state. Prague Economic Papers 1:64-81.
- Praznovcova L, Suchopar J, Wertheimer AI. 2003. Drug policy in the Czech Republic. Jthenal of Pharmaceutical Finance, Economics and Policy 12(1): 55-75.
- Preker AS, Jakab M, Schneider M. 2002. Health financing reforms in Central and Eastern Europe and the former Soviet Union, in Funding Health Care: Options for Europe, Mossalos E., Dixon A., Figueras J., Kutzin J. (Eds.), European Observatory on Health Care Systems Series: Open University Press, 2002.
- Rokosova M, Hava P, Schreyogg J, Busse R. 2005. Health care systems in transition: Czech Republic. Copenhagen, WHO Regional Office for Europe on behalf of the European Observatory on Health Systems and Policies.
- Sheiman I. 1991. Health care reform in the Russian Federation. Health Policy 19: 45–54.
- Sheiman I. 2006. O tak nazyvaemoi konkurentnoi modeli obyazatelnogo meditsinskogo strahovaniya (On so-called competitive model of mandatory health insurance). Menedzher Zdravoohraneniya 1: 52-58.
- Sheiman I. 1997. From Beveridge to Bismarck: Health Financing in the Russian Federation’. In Innovations in Health Care Financing, Schieber G. (ed.), Discussion Paper 365, 1997, Washington DC: The World Bank.
- Sinuraya T. 2000. Decentralization of the health care system and territorial medical insurance coverage in Russia: friend or foe? European Jthenal of Health Law 7:15–27.
- Sparling AS. 2008. Income, drug, and health: evidence from Russian elderly women. PhD dissertation. University North Carolina at Chapel Hill, UMI Dissertations Publishing.
- Tompson W. 2007. Healthcare reform in Russia: problems and perspectives. Working Papers 538, OECD Economics Department
- Tragakes E, Lessof S. 2003.Russian Federation, Health Care Systems in Transition, The European Observatory, WHO, Europe.
- Twigg J. 1999. Obligatory medical insurance in Russia: the participants’ perspective. Social Science and Medicine 49: 371–382.
- Twigg, JL. 2001. Russian healthcare reform at the regional level: status and impact. Post-Soviet Geography and Economics 42: 202–219.
- Zaborovskaya AS, Chernets VA, Shishkin SV. 2005. Organizatsiya upravleniya i finansirovaniya zdravoohraneniyem v subjektah Rossijskoi Federatsii v 2004 godu (Organization of management and finance of healthcare in Russian regions in 2004)
- Zweifel P, Breyer F. The economics of social health insurance. In The Elgar Companion to Health Economics, Jones A. (ed.), Edward Elgar, 2006.
- Wagstaff A. 2010. Social health insurance reexamined. Health Economics 19: 503–517.
Old-Age Poverty and Health – How Much Does Income Matter?
The question concerning the material situation of older people and its consequences for their wellbeing seems to be more important than ever. This is especially true given rapid demographic changes in the Western World and economic pressures on governments to reduce public spending. We use data from the Survey of Health, Ageing and Retirement in Europe (SHARE) to examine different aspects of old-age poverty and its possible effects on deterioration in health. The data contains information on representative samples from 12 European countries including the Czech Republic and Poland. We use the longitudinal dimension of the data to go beyond cross sectional associations and analyze transitions in health status controlling for health in the initial period and material conditions. We find that poverty matters for health outcomes in later life. Wealth-defined and subjective poverty correlates much more strongly with health outcomes than income-defined measure. Importantly subjective poverty significantly increases mortality by 58.3% for those aged 50–64 (for details see Adena and Myck, 2013a and 2013b).
Measuring Poverty
When measuring poverty, the standard approach is to define the poverty threshold at 60% of median equalized income. This standardized measure offers some advantages, such as simplicity and comparability with already existing studies. However, there are valid arguments against its use when analyzing old-age poverty. The permanent-income theory provides arguments against current income as a major determinant of quality of life of older people. Moreover, poverty defined with respect to current income while taking account of household size through equalization, ignores other important aspects of living costs such as disability or health expenditures. Additionally, most analysis using income-poverty measures ignore such aspects as housing ownership and housing costs.
Our analysis examines different aspects of poor material conditions of the elderly. The first poverty definition refers to respondents’ wealth as an alternative to income-defined poverty. Poor households, defined with reference to wealth (“wealth poverty” – WEALTH), are those that belong to the bottom third of the wealth distribution of the sample in each country. For this purpose, household wealth is the sum of household real assets (net of any debts) and household gross financial assets. Secondly, we compare the above poverty measures to a subjective measure of material well-being. This measure is based on subjective declarations by respondents, in which case (“subjective poverty” – SUB) individuals are identified as poor on the basis of a question of how easily they can make ends meet. If the answer is “with some” or “with great” difficulty, individuals in the household are classified as “poor”.
One reflection of potential problems with the standard income poverty measure becomes visible when it is compared with the subjective measure. The graph below shows the differences in country rankings when using one or the other poverty measure. The country with the greatest disproportion is Czech Republic. While being ranked as second according to the income measure, it is ninth according to the subjective measure.
Figure 1. Country Ranks in Old-Age Poverty According to an Income versus a Subjective Measure
Even more striking is the fact that the differences between ranks are not because of over or under classification of individuals as poor, but rather because of misclassification. Figure 2 shows that there is little overlap between different poverty measures. The share of individuals classified as poor according to all three measures is only 7.95%, whereas it is 60% according to at least one of the measures.
Figure 2. Poverty Measure Overlap
Measuring Well-Being
We examine three binary outcomes measuring the well-being of the respondents – two reflecting physical health, and one measuring individuals’ subjective health. The two measures of physical health are generated with reference to the list of twelve symptoms of bad health and the list of twenty-three limitations in activities of daily living (ADLs). In both cases, we define someone to be in a bad state if they have three or more symptoms or limitations. The two definitions are labelled as: “3+SMT” (three or more symptoms) and “3+ADL” (three or more limitations in ADLs). Subjective health “SUBJ” is defined to be bad if the subjective health assessment is “fair” or “poor”. Finally, we also analyze mortality as an “objective” health outcome.
Poverty and Transitions in Well-Being and Health
There is some established evidence in the literature that poverty negatively affects health and other outcomes at different stages of life.[1] At the same time, there is little evidence on how the choice of the poverty measure might result in under- or over-estimation of the effects of poverty. We address this question by examining different poverty measures as potential determinants of transitions from good to bad states of health.
The results confirm that living in poverty increases an individual’s probability of deterioration of health. In a compact form, Figure 3 presents our results from 12 separate regressions (4 outcomes, three poverty measures). Here we report the odds ratios related to the respective estimated poverty dummies. Individuals classified as poor according to the income measure are 37.7% more likely to report bad subjective health in a later wave of the survey than their richer counterparts; they are 4.5% more likely to suffer from 3 or more symptoms; 18.7% more likely to suffer from 3 or more limitations; and 5% more likely to die. The last three effects, however, are not statistically significant.
In contrast, the effects of wealth-defined poverty and subjectively assessed poverty are 2-8 times stronger than those of income poverty, and they are also significant for all outcomes but death. Overall, wealth-defined poverty and subjective assessment of material well-being strongly correlate with deterioration in physical health (exactly the same goes for improvements in health, see Adena and Myck 2013b).
Figure 3. Poverty and Transitions from Good to Bad States Overlap
Poverty and Mortality in the Age Group 50-64
Our analysis reveals differences between age groups and confirms the decreasing importance of income (and thus income defined poverty) with age. As compared to the average effects presented in Figure 3, for the younger age group 50–64 income poverty proves more important as a determinant of bad outcomes, with transition probabilities between 20 and 40% for all outcomes (see Figure 4). The magnitudes are closer to those of other poverty measures, but still lower in all cases. Importantly, we find that wealth-defined and subjective poverty is an important determinant of death in the age group 50–64.
Figure 4. Poverty and Transitions from Good to Bad States 50-64
Notes: Data weighted using Wave 2 sample weights. Source: Authors’ calculations using SHARE data (Wave 2, release 2.5.0, Wave 3, release 1, Wave 4, release 1).
Conclusions
The role of financial conditions for the development of health of older people significantly depends on the measure of material well-being used. In this policy brief, we defined poverty with respect to income, subjective assessment, and relative wealth. Of these three, wealth-defined poverty and subjective assessment of material well-being strongly and consistently correlate with deterioration and improvements in physical and subjective health. We found little evidence that relative income poverty plays a role in changes in physical health of older people. This suggests that the traditional income measure of household material situation may not be appropriate as a proxy for the welfare of older populations, and may perform badly as a measure of improvements in their quality of life or as a target for old-age policies. To be valid, such measures should cover broader aspects of financial well-being than income poverty. They could incorporate aspects of wealth and the subjective assessment of material situations as well as indicators more specifically focused on the consumption baskets of the older population.
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References
- Adena, Maja and Michal Myck (2013a): “Poverty and transitions in key areas of quality of life”, in: Börsch-Supan, Axel, Brandt, Martina , Litwin, Howard and Guglielmo Weber (eds.) “Active Ageing and Solidarity between Generations in Europe – First Results from SHARE after the Economic Crisis.”
- Adena, Maja and Michal Myck (2013b) Poverty and Transitions in Health, IZA Discussion Paper 7532, IZA-Bonn.