Project: FREE policy brief
Is There a Dutch Disease in Russian Regions?
The low economic diversification in Russia is commonly blamed on the abundance of energy resources. This brief summarizes the results of our research that investigates the presence of Dutch disease effects across Russian regions. We compare manufacturing subsectors with different sensitivity to the availability of natural resources across Russian regions with varying natural resource endowments. We find no evidence of differential deindustrialization across subsectors, thereby offering no support for a Dutch disease. This finding suggests that the impact of energy resources on Russian manufacturing is more likely to go through the “institutional resource curse” channel. Thereby, we argue that more efficient policies to counteract the adverse effect of resources on the Russian economy should focus on improving the institutional environment.
Russian abundance in oil and gas, and the ways it could negatively affect long-term economic performance and institutional development is not a new debate. One of the key concerns is the influence of energy resources on Russian industrial structure. Energy resources are often blamed for the low diversification of the economy, with an extensive resource sector and the dominant oil and gas export share.
In a forthcoming chapter (Le Coq, Paltseva and Volchkova), we contribute to this debate by exploring the channels through which abundance in energy resources influences the industrial structure in Russia. Our main focus is on the deindustrialization due to the expansion of the natural resource sector, the so-called ‘Dutch disease’. Specifically, we explore the impact of energy resources on the growth of manufacturing subsectors in Russian regions. Adopting a regional perspective allows us to separate the Dutch disease mechanism from the main alternative channel of the institutional ‘resource curse’. This brief summarizes our findings.
Dutch disease vs. institutional resource curse
The Dutch disease and the institutional resource curse are, perhaps, the most discussed mechanisms proposed to explain the influence of natural resources on economic performance (see e.g., earlier FREE brief by Roine and Paltseva for a review). In an economy facing a Dutch disease, a resource boom and resulting high resource prices shift production factors from manufacturing industries towards resource and non-tradable sectors. As a result, a country experiencing a resource boom would end up with a slow-growing manufacturing and an under-diversified economic structure. Since the manufacturing sector is often the main driver of economic growth, the economic development may be delayed. If, instead, an economy is suffering from the institutional ‘resource curse’, it is the interplay of weak institutions and adverse incentives created by resource rents that leads to a slow growth of manufacturing and delayed development.
Importantly, offsetting the potential negative impact of these two channels requires different policy interventions. In the case of a Dutch disease, a state can rely on direct industrial policy mechanisms targeted towards increasing the competitiveness of the manufacturing sector and isolating it from the effect of booming resource prices. For example, it can use subsidies or targeted trade policy instruments, or channel money from increased resource prices out of the economy through reserve fund investments abroad.
In the case of an institutional resource curse, on the other hand, resource rents and weak institutions may undermine and disrupt the effect of such policies. In this case, state policies should be targeted, first and foremost, towards promoting good institutions such as securing accountability and the transparency of the state, and protecting property rights. This suggests that properly understanding the channels through which resource wealth impacts the economy is necessary for choosing appropriate remedial measures.
In our analysis, we address the differential impact of energy resources in Russian regions. This regional perspective allows us to single out the Dutch disease effect, and disregard the mechanisms of a political resource curse to the extent that the relevant institutions do not differ much across regions.
Resource reallocation effect vs. spending effect
The mechanism of a Dutch disease implies two channels through which a resource boom negatively affects the manufacturing sector. First, a resource boom implies the reallocation of production factors from other sectors of economy such as manufacturing or services to the resource sector, a so-called ‘resource reallocation effect’. Second, an additional income resulting from a boom in the resource sector leads to an increase in demand for all goods and services in the economy. This increase in demand will be accommodated differently by different sectors, depending on their openness to world markets. Namely, in non-tradable sectors, isolated from international competition, there will be an increase in prices and output. This, in turn, will increase the prices on domestic factor markets. For tradable manufacturing sectors the price is determined internationally and cannot be adjusted domestically. As a result, production factors will also reallocate away from manufacturing to non-tradable sectors, a so-called “spending effect”.
The strength of either effect is likely to be different across different subsectors of manufacturing depending on the sectoral specificities. In particular, subsectors with higher economies of scale are likely to be more affected by the outflow of factors towards the resource sector through the “resource reallocation effect”. Similarly, subsectors that are more open to international trade are likely to be affected by the “spending effect”.
These observations give raise to our empirical strategy: we access differences in growth of regional manufacturing subsectors with different sensitivity to the availability of energy resources, where sensitivity reflects economies of scale, for the first mechanism, and openness to the world market, for the second mechanism. In other words, we test whether manufacturing subsectors with higher economies of scale (or openness) grow slower than subsectors with lower economies of scale (or openness) in regions rich in energy resources, as compared to the regions poor in energy resources. Observing differential deindustrialization, depending on the industry’s exposure to the tested mechanism, would offer support to the presence of a Dutch disease.
Note that the validity of our empirical strategy relies on the fact that there is high variation in resource abundancy and structure of the manufacturing sectors across Russian regions (as illustrated by Figures 1 and 2).
Figure 1. Geographical distribution of fuel extractions relative to gross regional product; 2014, percent.
Source: Authors’ calculation based on Rosstat data. Note: Figures for regions exclude contribution of autonomous okrugs where applicable.
Figure 2. Regional diversity in manufacturing structure, 2014.
Source: Rosstat.
Data and results
Our empirical investigation covers the period 2006—2014. The data on manufacturing subsector growth and regional energy resource abundancy come from Rosstat, the sensitivity measures across different manufacturing sectors are approximated based on data from Diewert and Fox (2008) (economies of scale in US manufacturing), and OECD (sectoral openness to trade).
The results of our estimation show that the differences in growth rates of manufacturing subindustries across Russian regions with varying natural resource endowments cannot be explained by the sensitivity of these subindustries to the availability of energy resources. This can be seen from Table 1, where the coefficient of interest – the one of the interaction term between the measure of sectoral sensitivity if resource abundance and regional energy resource wealth – is not significantly different from zero, no matter how we measure the sensitivity: by the returns to scale or by openness to international trade.
Table 1. Estimation of Dutch disease effect with different sensitivity measures.
| Dependent variable: average annual growth index of sectoral output | ||
| Sensitivity measure: Economies of scale | Sensitivity measure: Openness | |
| Subsector sensitivity * Size of the fuel extraction sector in the region
|
-0.0353
(0.0873) |
0.0674
(0.0954) |
| Subsector fixed effect | YES | YES |
| Region fixed effect | YES | YES |
| Observations | 1,185 | 1,185 |
| R-squared | 0.1574 | 0.1577 |
Source: Authors’ calculations.
These results hold true if we control for differences in regional taxes, labor market conditions, and other region-specific characteristics by including regional and sectoral dummy variables, if we consider alternative measures of energy resource wealth, and if we use other, non-parametric estimation methods.
In other words, our data robustly offers no support for the presence of a Dutch disease in Russian regions.
Conclusion and policy implications
Diversification is often mentioned by the Russian government, as one of the top economic policy priorities, and the need for ‘diversification’ has been used in the political debate as an argument for an active industrial policy.
However, the policy measures that are necessary to counter the effect of abundant energy resources on diversification and, more generally, on economic development may be highly dependent on the prevailing channel through which resources affect the economy. In particular, while active industrial policy may be justified as a remedy in the case of a Dutch disease, industrial policy may well be ineffective, or even harmful, in the presence of an institutional resource curse mechanism.
In our study, we find no support for the Dutch disease effect when looking at the impact of energy resources on the growth of regional manufacturing sectors. Thereby, to counterbalance the resource curse effect on the Russian economy, we argue that it may be more efficient to improve the institutional environment than to use active government policies affecting industrial structures.
References
- Diewert, W. E and Fox, K. J. (2008) ‘On the estimation of returns to scale, technical progress and monopolistic markups’, Journal of Econometrics, 145(1-2): 174-93.
- Le Coq, C., Paltseva E., and Volchkova N., forthcoming. “Regional impacts of the Russian energy sector”, in Perspectives on the Russian economy under Putin, eds. Becker and Oxenstierna, London, Routledge.
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.
The Russian economy under Putin (so far)
Russians are heading to the polling booths on March 18, but where will the economy head after Putin has been elected president again? This brief provides an overview of the economic progress Russia has made since 2000 as well as an economic scorecard of Putin’s first three tenures in the Kremlin and uses this to discuss what can be expected for the coming six years. Although significant growth has been achieved since 2000, all of this came in the first two tenures of Putin in the Kremlin on the back of increasing oil prices. In order to generate growth in his upcoming presidential term, Putin and his team will need to address the significant needs for reforms in the institutions that form the basis for modern market economies. Otherwise, Russia will continue to be hostage to the whims of the international oil market and eventually lose most of its exports and government revenues as the world moves towards a carbon free future. Perhaps this is beyond the scope of Putin as president, but not beyond the horizon of young Russians that will be casting their votes on Sunday and in future elections.
Let’s assume that Putin will be elected president again on March 18 (for once a very realistic assumption made by an economist). What will this mean for the Russian economy in the coming six years given what happened during his previous and current tenures in the Kremlin? To assess the future as well as to understand Putin’s power and popularity, this brief starts by looking back at the economic developments in Russia since Putin first became president.
Although many different factors enter the power and popularity function of Putin, economic developments have a special role in providing the budget constrain within which the president can operate. A higher income level means more resources to devote to any particular sector, project, voting group or power base. This is not unique to Russia, but sometimes forgotten in discussions about Russia, that often instead only focus on military power or control of the security apparatus and media. These are of course highly relevant dimensions to understand power and popularity in Russia, but so is economic development, particularly in the longer run.
Russia’s economy in the world
The economic greatness and progress of a country is usually assessed in terms of the size of the economy, how much growth that has been generated, and how well off the citizens are relative to the citizens of other countries. So, by our common indicator gross domestic product (GDP), has Russia become a greater and more powerful country since Putin first became president? Table 1 shows two things, the absolute level of GDP measured in USD at market exchange rates and the rank this gives a country in a sample of 192 countries in the world that the IMF collects data on (this brief is too short for a long discussion of the most relevant GDP measure, but GDP at market exchange rates makes sense when comparing the economic strength of countries in a global context, Becker 2017 provides a discussion of alternative measures as well). When Putin become president for the first time in 2000, the value of domestic production was estimated at $279 billion, which implied a 19th place in the world rankings of countries’ GDP. In 2016, almost three presidential terms of Putin later, Russia’s GDP had increased by 4½ times to $1281 billion and its ranking improved to 12th place in the world. This clearly is an impressive record by most standards. However, the Russian economy is still the smallest economy of the BRIC countries and corresponds to only 7 percent of the US economy in 2016. In other words, impressive progress by Russia but the country is (still) not a global superpower in the economic arena.
Table 1. Russia in the world (GDP in USD bn)
Source: IMF (2017)
For the average Russian, income per capita is a measure more closely connected to consumption and investment opportunities or ‘welfare’. Progress in this area is also more likely to affect how individuals assess the performance of its political leaders. Of course, progress in terms of overall GDP and GDP per capita is closely linked unless something unusual is happening to population growth. Therefore, it is not surprising that GDP per capita also increased by around 4½ times between 2000 and 2016 (Table 2). This is the first order effect of the economic development in Russia, but in addition, citizens of Russia moved up from a world income rank of 92nd to 71st. This has implications when Russian’s compare themselves with other countries and can in itself provide a boost of national pride.
It also directly affects opportunities and status for Russians visiting other countries. Being at place 71 may not be fully satisfactory to many, but we should remember that due to the rather uneven income distribution in Russia, many of the people that travel abroad are far higher up on the global income ranking than what this table indicate. Nevertheless, Russia is far behind the Western and Asian high-income countries in terms of GDP per capita. And although the picture would look less severe if purchasing power parity measures are used, the basic message is the same; Russia has still a lot of catching up to do before its (average) citizens enjoy the economic standards of high-income countries.
Table 2. Russian’s in the world (GDP/capita)
Source: IMF (2017)
The macro scorecard of Putin
So what generated the impressive 4½ times increase in income in USD terms from 2000 to 2016 and can we expect high growth during Putin’s next six years in office? The short answer to the first question is the rise in international oil prices and to the second question, we don’t know. Table 3 provides a comparison of different economic indicators for Putin’s two first terms in office compared with his current term (where GDP data ends in 2016 so the sample is cut short by a year). It is evident that the impressive growth over the full period is entirely due to the strong growth performance in the first two presidential tenures. Rather than generating growth in the most recent period, the economy has shrunk. This is explained by the evolution of international oil prices, which quadrupled in the first eight years and instead halved in the more recent period. These swings in oil prices have also been accompanied by significant shifts in foreign exchange reserves, the exchange rate, and the value of the stock market.
In Becker (2017) I discuss in more detail the importance of international oil prices in understanding the macro economic development in Russia. In particular, it is important to note that it is changes in oil prices that correlate with GDP growth and other macro variables and that the problems with predicting oil prices makes it very hard to make good predictions of Russian growth.
Table 3. A macro scorecard of Putin in office
Source: Becker (forthcoming)
Policy conclusions
To break the oil dependence and take control of the economic future of Russia, the president will need to implement serious institutional reforms that constitute the basis for a modern, well-functioning market economy in his next term. Otherwise, Russia will continue to be hostage to unpredictable swing in international oil prices and nobody—including the president, the central bank, the IMF and financial markets—will be able to predict where the Russian economy is heading in the next couple of years.
Figure 1. Reforms (still) needed
Source: World Bank (2017)
In the longer run, the prediction is much easier. With the world moving towards a green economy, the price of oil will see a structural decline that will rob Russia (and other oil exporters) of most of its export and government revenues. The reforms which basically every economist agree are needed are related to market institutions and Figure 1 provides a clear illustration of key reform areas. The progress during Putin’s years in office has been modest at best. Swedish institutions in 2016 have been added to the figure as a comparison and it is clear that the institutional gap between Russia and Sweden is significant. Of course, all countries are different, but Russian policy makers that are interested in reforming its economy are most welcome to Sweden for a discussion of what we have done to build our institutions.
References
- Becker, T. (2017). ‘Macroeconomic Challenges’, in Rosefielde, S., Kuboniwa, M., Mizobata, S. and Haba K. (eds.) The Unwinding of the Globalist Dream: EU, Russia and China, Singapore: World Scientific Publishing.
- Becker, T. (forthcoming), ‘Russia’s economy under Putin and its impact on the CIS region’, Chapter 2 in T. Becker and S. Oxenstierna (eds.) Perspectives on the Russian Economy under Putin, London: Routledge.
- IMF (2017), World Economic Outlook database, April 2017 edition available at http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx
- World Bank (2017), Worldwide Governance Indicators (WGI), 2017 update available at http://info.worldbank.org/governance/wgi/index.aspx#home
Poland’s Road to “High Income Country” Status: Lessons Learnt – Not Only for Other Countries
In this brief we summarize and discuss results presented in a recent World Bank Report focused on Poland’s path from middle to high-income country status. In the period until 2015, Poland’s economic development distinguished itself by its stability and consistency of the implemented reform package, and its inclusive nature. Poland became classified as a high-income country after only 15 years from gaining a middle-income status. At the same time, income inequality remained stable and absolute poverty levels fell significantly. The World Bank Report offers lessons from and insights for Poland, which are discussed from the perspective of the policies implemented by the governments in the last two years.
Poland’s status in the World Bank nomenclature has recently been “upgraded” from being middle to high-income country. While this categorization is only a nominal change, it reflects the country’s economic development over the recent decades and is an important recognition of the success of a wide range of reforms implemented across a broad number of areas. Notably, Poland moved from the middle to high-income status in a period of less than 15 years.
In a book recently published by the World Bank, it is argued that the Polish experiences from the reform process can serve as valuable lessons for countries that are in the process of, or have just embarked upon major socio-economic reforms, as well as for those, who have fallen into the so-called middle-income trap and are looking for solutions to their stagnant economies. At the same time, in comparison to other established high-income countries, there are a number of insights that Poland’s policy makers ought to bear in mind in order to stay on course of the reform process and continued stable growth.
Looking at policies of the recent governments, however, one gets a strong impression that some important insights have been ignored. As rapid population aging looms over the horizon, the lack of necessary adjustments combined with the risks to stability of the political and economic environment might in the medium run have significant implications for Poland’s further development.
The big picture
The key feature of the Polish socio-economic policy approach, over the period covered by the World Bank analysis (i.e. up to 2015), was a unique consistency of a broad direction taken by subsequent administrations. This allowed the reform process to develop without major breaks or U-turns, which ensured the overall stability of the socio-economic environment and provided stable investment prospects. The World Bank highlights the key role of institutions, including rule of law, property rights, and democratic accountability of different levels of government. Basic market institutions, including the respect for rules on price and product regulations, corporate governance and market regulations, as well as foreign trade and investment, have played a crucial role. This framework allowed for continued improvement in the efficiency of resource allocation – including the allocation between sectors of the economy, as well as between and within enterprises.
Crucially, Poland prepared well and took full advantage of the integration with the European Union. The EU accession was first used as a common anchor for stability of the reform process, and after 2004, the European funds became an additional engine of growth. At the macro level, stability of the fiscal framework with limited deficits and public debt were combined with appropriate regulation and supervision of the financial sector, an independent central bank, and close links to global markets.
Shared prosperity
While the above points provided the basis for Poland’s economic development, the Report highlights another unique feature of Poland’s success, namely the degree to which the fruits of the process have been equally shared among different groups of society. The overall income inequality has remained relatively stable, with the Gini coefficient actually falling slightly between 2005 and 2014, from 0.351 to 0.343. Relative income poverty levels remained stable over this period (at about 20%), and the levels of absolute poverty fell significantly. For example, the proportion of the population living on less than $10 per day fell from 51.3% in 2005, to 29.6% in 2014. Growing incomes were primarily driven by increases in labor earnings, but employment growth – in particular among older age groups –also made a contribution. The government’s labor market policy also played a role with a rapid increase in the level of the national minimum wage (NMW), which grew by 65% in real terms between 2005 and 2015, i.e. almost twice as fast as the average wage. While there is evidence that the rapid growth in the NMW had negative effects on employment – in particular among temporary, young, and female workers, these have been relatively modest. Additionally, the tax and benefit policy has contributed to reduced inequality. It has been estimated that nearly half of the reduction in the Gini coefficient, over the period 2005–2014, resulted from reforms of the tax and benefit system (Myck and Najsztub, 2017).
It is clear that human capital was one of the cornerstones of Poland’s success in recent years. Developments on the labor market, such as a rapid productivity growth, were facilitated by a well-educated labor force, which could respond and adjust to the changing conditions and requirements. In this regard, Poland’s advantage in comparison to many other low and middle-income countries has been the relatively high level of spending on public education and healthcare, not only since the start of the economic transformation in the 1990s, but also before that. Indicators, such as the infant mortality rate, were low in Poland already in the 1980s, and have since further improved (see Figure 1). For a long time, public spending on education has been at levels comparable to those in established high-income countries (see Figure 2). Additionally, a series of reforms to the education system since 1990, have resulted in improvements in the quality and coverage of education. This, in turn, has lead to a rapid improvement of scores in language, mathematics, and science in the PISA study (Programme for International Student Assessment), in which Polish students recently outperformed those from many other OECD countries (OECD 2014). Importantly, the improvements in the education results have been found across the socio-economic spectrum, which further stresses the inclusive character of the changes that have taken place.
Figure 1. Infant mortality rate (per 1,000 live births), 1980 and 2014
Notes: Countries grouped in the following manner: red – middle-income countries; blue – new high-income countries; green – established high-income countries. Horizontal lines represent group averages. Source: World Bank (2017), Figure 5.16, based on World Development Indicators.
Figure 2. Government expenditure on education, percent of GDP, 1990
Source: World Bank (2017), Figure 5.11, see notes to Figure 1.
Insights for Poland
“As economies enter the high-income group, weakness in economic institutions such as the rule of law, property rights, and the quality of governance become increasingly important to sustain convergence.”
World Bank (2017)
While the Polish reform experience, over the period examined in the World Bank Report, offers important lessons for other countries aspiring to the high-income status, the authors point out that Poland’s continued development needs to rely on further improvements in a number of key areas. The following policy areas have been highlighted in the Report:
- Working on more inclusive political and economic institutions and enhancing the rule of law with the focus on the judiciary;
- Adjustments to fiscal policy in particular to deal with the consequences of population aging;
- Increasing the domestic level of savings to facilitate large investment needs;
- Supporting innovation through more intense competition and high quality research education;
- Improving social assistance programs and access to high quality health and education for low income groups;
- Increasing the progressivity of the tax system to support inclusive growth;
- Adjusting migration policies to bring in skills and innovative ideas and compensate for the country’s aging workforce.
“Sustaining Poland’s record of high, stable growth will require adjustments to fiscal policy (…). Government will need to create the fiscal space to deal with the increasing pressures coming from aging, the inevitable decline of EC structural funds for investment, and a more uncertain global context.”
World Bank (2017)
Lessons, insights and recent policies
While several of the Law and Justice majority governments’ policies since 2015 have been well in line with the World Bank recommendations, there have also been a number of questionable policy areas. One major concern seems to relate to the broad background of reforms of the judiciary, which have drawn significant criticism of the European Commission and other international institutions. Implications of such major changes for economic growth are uncertain but potentially very damaging.
Another long-term concern arises from the new pension age reform. From the socio-economic perspective, rapid ageing of the population is one of the main challenges facing the country. Between 2015 and 2030, the number of people aged 65+ will grow from 6.1 million to 8.6 million, i.e. by over 40%. This will put significant strains on the country’s public finances due to increasing public-pension expenditures and growing costs of health and long-term care. These pressures will only be exacerbated by the current government’s decision to lower the statutory retirement age to 60 for women and 65 for men, from the target uniform age of 67 legislated in the reform of 2012. Given the contributions-defined nature of the Polish pension system, this will result in significantly lower levels of pensions, especially among women, and a substantial drain on public finances resulting from lower levels of contributions and taxes.
The generous family benefits of the Family 500+ Program – implemented in 2016 and which cost about 1.3% of the GDP – have also been criticized on a number of grounds. They have undoubtedly changed the financial conditions of numerous families and limited the extent of child poverty. At the same time, they contribute to maintaining low levels of female labor-force participation and there is so far little indication that they have significantly changed Poland’s very low fertility rate. It seems that while the program may have positive long-term consequences resulting from reduced poverty, it is unlikely to shift the demographic dynamics.
Uncertainty also surrounds the consequences of a haphazard major education reform, which is another trademark policy of the Law and Justice party. The reform re-introduced the 8+4 system in place of the post-1999 three-level educational arrangement (6+3+3). The new system takes the number of years of general education back from 9 to 8 years, and instead extends by one year the length of secondary schooling. While the potential effects of such a change are difficult to foresee, the 8+4 system may be in particular disadvantageous to children from rural areas, who are most likely to continue their education in their rural primary schools for the two extra years.
A number of steps taken by the government since late 2015, and in particular those related to the redistributive policies implemented in the last two years, seem to be consistent with the World Bank insights. On the other hand, the approach towards the reforms of the judiciary, the general approach to the rule of law, and the reforms of education and pension regulations, quite clearly appear to ignore not only the insights, but also the lessons resulting from Poland’s own experience of the recent decades. Given the challenge of rapid aging in the Polish population, there seems to be much gained from taking them seriously if the current and future administrations want to ensure Poland’s continued inclusive growth and to secure its status as an established high-income country.
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This policy brief draws heavily on the World Bank (2017) Report: “Lessons from Poland, Insights for Poland: A sustainable and inclusive transition to high-income status” (co-authored by Michal Myck) and the accompanying Working Paper by Myck and Najsztub (2016). Views and opinions expressed in this brief are the sole responsibility of the author and are not endorsed by the World Bank or CenEA.
References
- Myck, M., and M. Najsztub (2016) “Distributional Consequences of Tax and Benefit Policies in Poland: 2005–2014.” CenEA Microsimulation Report 02/16, Centre for Economic Analysis, Szczecin.
- OECD (Organisation for Economic Co-operation and Development) (2014) PISA 2012 Results: What Students Know and Can Do—Student Performance in Mathematics, Reading and Science (Volume I: Revised edition, February 2014). Paris: OECD Publishing.
- World Bank (2017) “Lessons from Poland, Insights for Poland: A sustainable and inclusive transition to high-income status”, The World Bank, Washington.
School Financing, Teacher Wages and Educational Outcomes in Russia
The policy proposal to increase the share of budget spent on public education implies that higher financing leads to better quality of education. This, however, is far from certain. We test and compare the effects that different levels of financial resources available to schools and relative teacher wages have on educational outcomes. Russia provides a good opportunity for testing this relationship due to its high level of regional heterogeneity. We find that increasing school financing per se does not noticeably improve educational outcomes. Only when additional financing leads to an improvement of the position of teachers in the regional wage distribution, we observe higher educational outcomes for students. We provide some tentative evidence on the possible channels of this effect.
School education is a complex and multifaceted process, and measurable educational outcomes are affected by many different factors. These may include students’ innate abilities and family resources as well as various characteristics of the school environment and teaching practices. In the literature, one of the important factors is the level of school financing provided by the government. This is also one of the key issues in the debates about the public policy in education. However, there is no consensus in the academic literature about the degree of influence of financial resources available to schools on educational outcomes.
The effect of school financing should depend on how it is spent. Since education is a human capital-intensive sector, a major part of this money is spent on teacher remuneration. Whether the size and structure of teacher pay affect the effectiveness of their work and ultimately the student outcomes is still an open question. Some studies argue that it is not absolute but that relative teacher wages matter (Loeb and Page, 2000; Britton and Propper, 2016). Hanushek et al. (2017) use cross-country data and show that the relative position of teachers in the wage distribution affects self-selection into the teaching profession in terms of skills, and that teacher skills in turn affect student outcomes.
While there are studies looking at various determinants of the quality of school education in the transition-economy context (e.g. Amini and Commander, 2012), the effect of school financial resources has not yet been studied. In Lazareva and Zakharov (2018), we exploit spatial variation in educational resources in Russia to try to answer this question. We test and compare the effects of school budget financing and relative teacher wages on educational outcomes for the period 2006–2014. We estimate these effects for two different measures of educational outcomes at different levels of school education system.
Institutional Context and Data
In Russia the system of general education covers eleven years: the first nine years are compulsory for all children, after that one can continue to high school for two more years or move into vocational education system. The school system is predominantly financed by the government and the share of private schools is very low.
In the 1990s and early 2000s, the system of general education was heavily underfinanced. Teacher remuneration was quite low compared to the average wage in the economy, and a job as a schoolteacher was not very attractive. In the mid-2000s, with the fast economic growth, the Russian government made an effort to increase school financing and to raise teacher wages. Importantly, schools are financed at the regional level, through the budgets of the regions, which results in significant cross-regional variation.
There are 85 administrative regions currently in Russia and they differ a lot in terms of economic conditions, regional budget income and expenditures. We use data on regional-level budget expenditures on general education from the Russian Treasury statistics (http://www.roskazna.ru/). In order to account for inflation and cross-regional differences in prices, we normalize the per-student amount of school budget financing by the minimum regional cost of living (as estimated by the Russian statistical office) in a particular year.
As our data show, the amount of budget financing of the general education system has been growing in real terms during 2006–2013. The average regional budget financing per student (adjusted for the differences in the cost of living across regions and years) has increased by 40% during this period. A large part of this growth occurred in 2012. In that year a presidential decree was adopted which required that teachers’ wages should be raised to the level of the average regional wage. Regions had to allocate more money for teacher wages during the following years in order to meet this target. Even after adjusting for the regional cost of living, the level of school financing differs a lot across regions throughout the period.
The amount of school financing is also significantly correlated with the gross regional product per capita, i.e. with the level of economic development of the region. We observe the largest gap in school financial resources between the small group of the richest regions (Moscow, Sankt Petersburg and resource extracting regions) and the remaining regions. Such persistent inequality in school resources may lead to unequal access to high quality education across Russian regions. This inequality is exacerbated by the fact that in less economically developed regions families have fewer resources to compensate for the underfinancing of public schools.
The structure of school expenditures in the regional budgets shows that the major part of financing (about 80 percent) is spent on remuneration of teachers and school administration. Hence, the effect of regional school expenditures on student outcomes should go through teacher wages. We use data on average regional teacher wages from Rosstat (Russian Federal State Statistics Service) and the Russian Ministry of Education. As we argued previously, it is important to test the effect of relative teacher salary. Our data show that the average regional school wage relative to the average regional wage has grown during the observation period, in particular in 2008–2009 and, at a higher rate, in 2012–2013 (due to the presidential decree mentioned above). Again, there is a significant variation among regions, which is observed throughout the period.
Empirical Results
In order to test the effect of school resources and teacher wages on educational outcomes, we use two measures of educational outcomes. First, we use the average regional score on Unified State Examination (USE). It was introduced in all Russian regions starting from 2009 and students graduating from grade 11 take the test. This is a high stakes examination as the result of this exam is accepted as entrance exams at universities throughout the country. USE in mathematics and Russian language are compulsory for all graduates of grade 11. Therefore, we will use the scores in these subjects. Note that USE scores measure educational outcomes of those students that stayed in high school after grade 9 – this is about 60 percent of the age cohort.
An alternative measure of educational outcomes is the data from PISA international educational assessment (PISA – Programme for International Student Assessment run by OECD, http://www.oecd.org/pisa/). Russia participates in PISA since 2003. We use data from waves 2006, 2009, 2012, and 2015. Students take this test at the age of 15, which means that the majority of this age cohort is in grade 9.
In our regression analysis on regional data, we additionally control for a number of regional characteristics that may be correlated with school financing or teacher wages, such as population size, share of urban population, regional poverty (share of population below the poverty line), within-region income inequality (decile coefficient), and gross regional income per capita (also adjusted for the cost of living). Since we have panel data, we use a panel fixed effects estimation method, which accounts for all unobserved time-invariant regional heterogeneity.
Our results show that the level of per-student school financing does not significantly affect USE results. At the same time, we find a significant positive effect of relative teacher wages on USE results both in math and Russian language with the lag of one to two years. We find the same results on PISA data: individual student scores in math, reading and science are significantly positively affected by the level of the relative regional teacher wages. Our results hold in instrumental variable estimation, which we conduct in order to account for potential endogeneity problems.
What are the potential channels through which relative teacher wage may affect student results? One possible channel is self-selection of teachers. When teacher wages increase relative to other jobs, being a teacher become more attractive for higher skilled individuals. Higher skilled teachers help students to achieve better educational results. We cannot directly test this channel, as we do not have data on teacher turnover in Russian schools. Besides, we observe a positive effect of relative teacher wages on student scores with a lag of just one-two years. This seems to be a too short time period for teacher turnover to have a significant effect.
Another potential channel of the observed effect is an improvement in teacher motivation or teacher morale. We can only provide some suggestive evidence for this effect. In the early and mid-2000s, when teacher pay was quite low, a significant share of teachers were considering quitting their jobs or switching to another occupation. As teacher survey data show, after the significant increase in teacher pay in 2008–2012 this share declined and teacher motivation and job satisfaction improved. Additional evidence in support of this hypothesis comes from the school-level data in the PISA 2012 survey. We estimate the effect of relative regional school wage on teacher morale (as evaluated by a school head) and find a positive and statistically significant relationship.
Conclusion
We find that increasing school financing from the regional budgets per se does not noticeably improve educational results. Only when additional financing leads to an improvement of the position of teachers in the regional wage distribution, we observe higher educational outcomes for students. The potentially interesting future direction of research is to study how not just the relative size, but also the structure of teacher wages (i.e. elements of incentive pay introduced in Russian schools) affects educational outcomes.
References
- Amini, Chiara & Commander, Simon, 2012.”Educational Scores: How does Russia Fare?” Journal of Comparative Economics, Elsevier, vol. 40(3), pages 508-527.
- Britton, Jack and Carol Propper, 2016, Teacher pay and school productivity: Exploiting wage regulation, Journal of Public Economics 133 (2016) 75–89.
- Hanushek, Eric A., Marc Piopiunik, Simon Wiederhold, 2017, The Value of Smarter Teachers: International Evidence on Teacher Cognitive Skills and Student Performance, NBER Working Paper w20727.
- Lazareva, O. and A. Zakharov, 2018, School Financing, Teacher Wages and Educational Outcomes: Evidence from the Russian School System.
- Loeb, Susanna and Marianne E. Page, 2000, Examining the Link between Teacher Wages and Student Outcomes: The Importance of Alternative Labor Market Opportunities and Non-Pecuniary Variation, the Review of Economics and Statistics 2000 82:3, 393-408.
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.
Financial Stress and Economic Contraction in Belarus
This brief summarizes the results of an analysis of financial stress episodes in the Belarusian economy. Based on a principal component analysis, I construct a financial stress index for Belarus (BFSI) that incorporates distinctive indicators for the banking sector, exchange market and external debt risks covering the period January 2004 to September 2016. Next, I identify episodes of financial turmoil in Belarus using the BFSI and assess the consequences for the real economy. Finally, I investigate the long-run relationship between financial stress and economic activity in Belarus.
It has become conventional wisdom that a well developed and smoothly operating financial system is critically important for economic growth (see Levine, 2005). It helps in overcoming frictions in the real sector, influencing economic agents’ savings and investment behavior, and therefore enabling the real economy to prosper (Beck, 2014).
In contrast, financial stress to financial system can be defined as the force that influences economic agents through uncertainty and changing expectations of loss in financial markets and financial institutions. It arises from financial shocks such as banking or currency crises (Iling & Ying, 2006). Consequently, the current stress level in the financial system can be quantified by combining a number of key individual stress measures into a single composite indicator – the Financial Stress Index (FSI).
In practice, such indices are already widely used, and allow regulators to maintain financial stability and help investors to assess the overall riskiness of investments in financial instruments of the country. The FSI for Belarus (BFSI) has been estimated for the first time and can be used as an early warning signal of systematic risk in the Belarusian financial sector (Mazol, 2017). In the financial context, systematic risk captures the risk of a cascading failure in the financial sector, caused by inter-linkages within the financial system, resulting in a severe economic downturn.
Construction of the FSI for Belarus
Based on a principal component analysis, the calculated index incorporates distinctive indicators for banking-sector risk estimated by the Banking Sector Fragility Index (BSFI), currency risk assessed by the Exchange Market Pressure Index (EMPI), and the external debt risk proxied by the growth of total external debt.
The BFSI reflects the probability of a crisis (episode of financial stress) – the smaller is the indicator, the better. The stability regime ends, when the BFSI exceeds a predetermined threshold. In particular, episodes of financial stress are determined as the periods when the BFSI is more than one standard deviation above its trend, which is captured by the Hodrick–Prescott filter. The identified episodes of financial stress show that one or more of the BFSI’s subcomponents (banking, external debt or foreign exchange) has changed abruptly.
Episodes of financial stress
During 2004—2016, two episodes of financial stress were detected in the economy of Belarus (see Figure 1). In both cases, there were large devaluations of the Belarusian currency, caused by the need to adjust its real exchange rate.
Figure 1. Episodes of financial stress in Belarus 2004—2016
Source: Author’s own calculations.
The first episode began in December 2008 and ended in May 2009. This episode was mainly a consequence of the global economic and financial crisis that caused a deep recession in Russia, reducing Russia’s demand for import of products from Belarus, further loss of competitiveness due to the sharp depreciation of the Russian ruble and deterioration of the current account balance and the depletion of foreign exchange reserves.
The second episode of financial stress began in December 2011 and ended in May 2012. It was caused by the renewed unbalanced macroeconomic policy aimed primarily at boosting aggregate demand by increasing government spending and accelerating economic growth; and monetary policy aimed at targeting the exchange rate. All this has led to problems in the foreign exchange market that eventually encompassed issues in the banking sector and caused a sharp reduction in foreign exchange reserves.
Financial stress and recessions
Figure 2 shows the contribution of each of the sub-indices to the increase in the BFSI.
Figure 2. The dynamics of components of BFSI during 2004-2016
Source: Author’s own calculations.
The main feature of the graph is that the currency stress is the prevailing factor in the two identified stress episodes. However, while the origins of the second episode were in the currency market, by early 2012, the stress had become much more broad based – the banking stress and the external debt stress contributed significantly to BFSI growth at the same time.
In contrast, since the beginning of 2016 until the end of the observation period, an upward movement in the BSF sub-index was detected indicating that the National Bank of Belarus (NBB) had to be worried about instability in the banking sector, which was mostly related to a loans crisis of state-owned enterprises (SOEs). A loans crisis of SOEs in Belarus means the inability of these enterprises to repay their debts and the need for budget coverage of their obligations and investments in fixed capital (see Figure 3). This happened due to a significantly higher cost of capital for SOEs after the second episode of the financial stress had begun.
Figure 3. Sources of investment financing and overdue loans of Belarusian enterprises
Source: Belstat.
Correspondingly, in the late 2016, the above problems have amplified the external debt stress (lack of external financing) in the economy of Belarus (see Figure 2).
Next, the results showed that financial stress negatively influences economic activity proxied by the index of composite leading indicators (CLI). In particular, an increase by one standard deviation (s.d.) in the BFSI leads to the contraction in the CLI index by 0.5 s.d. (see Mazol, 2017).
Moreover, financial stress has caused significant real output losses. The first episode of financial stress has resulted in the contraction of GDP by 5.9%. Second one has pushed Belarusian economy into a severe recession, which lasted 52 months with cumulative output losses about 12.9% of GDP (see Table 1).
Table 1. Descriptive statistics on episodes of financial stress and recessions in Belarus
| Episodes of financial stress | Duration (months) | Output lossa
(% of GDP) |
Number of months after start of financial stress to recession | |
| Financial
stress |
Recessionb | |||
| December 2008 –
May 2009 |
6 | 12 | -5.85 | 0 |
| December 2011 –
May 2012 |
6 | 52 | -12.89 | 6 |
Note: a) output loss is measured as GDP below trend during recession; b) a recession is occurred if there was a serious contraction in the economic activity (CLI) during six month or more. Source: Author’s own calculations.
Finally, a great reliance of Belarusian economy on external financing is associated with longer and sharper downturn in the aftermath of second episode of financial stress (see Figure 2).
Conclusion
The study has three policy implications. First, the BFSI may be considered as a comprehensive indicator that successfully determines the main episodes of financial stress in Belarusian economy and can be used to study their macroeconomic consequences.
Second, the BFSI identifies the most salient stress factors for Belarus, thereby showing which financial sectors need to be monitored carefully by national regulator to avoid a critical buildup of risks in the financial system.
Third, efforts to confine financial stress will support the country’s economic activity in the long run, which may include intervention in the foreign exchange market and build up of investor confidence in the economy.
References
- Beck, Thorsten, 2014. “Finance, growth, and stability: lessons from the crisis”. Journal of Financial Stability, 10, 1-6.
- Illing, Mark; and Ying Liu, 2006. “Measuring financial stress in a developed country: an application to Canada”. Journal of Financial Stability, 2, 243-265.
- Levine, Ross, 2005. “Finance and growth: theory and evidence”. In: Aghion, P., Durlauf,S.N. (Eds.), Handbook of Economic Growth, vol. 1A. Elsevier, Amsterdam, 865-934.
- Mazol, Aleh, 2017. “The influence of financial stress on economic activity and monetary policy in Belarus”. BEROC Working Paper Series, WP no. 40, 33 p.
Individual Retirement Timing in Russia: Implications for Pension Age
This policy brief summarizes the findings in a paper where individual exit trajectories of Russians from the labor market to economic inactivity are examined using survival analysis methods based on the Russian Longitudinal Monitoring Survey for 1995-2015. Among other results, the analysis shows that the statutory retirement age has a significant impact on the time of exit from the labor market for both men and women, but the effect is very high for women. This is an interesting and unexpected result, given no penalty for working beyond the pension age of those already retired, the five-year difference in statutory retirement age between males and females, and the low pension age in Russia on an international scale. This questions the painlessness of rising the retirement age for women, should the decision finally be taken.
An ageing population, combined with a slowdown in economic growth, challenges the Russian public finances with an increased deficit of the Pension fund. In addition, the persistently negative natural population growth against the backdrop of ageing has predetermined a decline in the working-age population in the foreseeable future. Older cohorts are therefore becoming a potentially attractive source to increase the size of the labor force. All this has actualized the discussion about the need to increase the Russian retirement age (see, for instance, Maleva and Sinyavskaya, 2010). However, little is known about the labor market situation of older age groups and, in particular, about the process of their exit from the labor market
The Russian pension system, unlike the pension systems of many developed countries, hardly penalizes continuation of work after reaching retirement age and documenting a pension (working pensioners lose only pension indexation). The changes in pension law that have entered into effect since 2015 encourage continued work without recourse to retirement, but there have been few responses to the innovation so far. Coupled with the low pension replacement rate (i.e., the proportion of wages substituted by pension), this makes the process of leaving the labor market nontrivial, since a large number of people of retirement age remain on the labor market after reaching retirement age.
Denisova (2017) examines individual exit trajectories of Russians from the labor market to pension-age economic inactivity applying survival analysis to the Russian Longitudinal Monitoring Survey (RLMS-HSE). The major research questions are the following: What determines the length of stay of older age groups in the Russian labor market? What is the role of the statutory retirement age in this process?
Data and research methodology
The RLMS-HSE for the period of over 20 years, from 1995 to 2015, is the empirical basis of the research (http://www.cpc.unc.edu/rlms). I limit the sample to age 45-72 as there is practically no retirement by age before age 45, and 72 years is the upper boundary of the working age definition internationally accepted by statisticians. I exclude from the sample those who are on retirement and did not work or seek work for the entire period of observation, since their decision to end working activity remained outside the observation period.
An episode in the survival analysis of exit from the labor market into pension-age inactivity is an episode of working life. The analytical time in this case is the age of the respondent. The failure event (the moment of exit from the labor market to pension-age economic inactivity) is defined by the simultaneous fulfillment of three conditions: the respondent does not work, does not look for a job, and receives retirement pension. Only the final exits from the labor market into inactivity are considered, while temporary exits are disregarded.
I evaluate proportional hazard models, which suggest that exogenous economic factors shift the baseline hazard function (which reflects the average entire sample hazard rate at each age) proportionally. A semi-parametric Cox model specification with robust errors clustered at individual level is used.
The vector of explanatory characteristics includes education; marital status; experience in the labor market (work at an enterprise with a state share; entrepreneurship versus work for wages); health characteristics (subjective and objective); settlement type; and attainment of statutory retirement age. In all cases, I control for the year of the survey.
Given the differences in the behavior of men and women in the labor market, the regression analysis is run separately for the subsamples of men and women. The statistical significance of the differences in returns to factors between men and women is tested based on the results of the full sample regression with interaction terms.
Averaged process of exit from the labor market
The averaged process of leaving the labor market pending on age is conveniently described through so-called Kaplan-Mayer’s survival function (an estimate of the survival process). As seen from Figure 1, the process of exit prior to age 55 for women and 60 for men is very slow, while the rate of exit becomes almost permanent and slows down after 70 years. Men stay in the labor market longer: 25% of women leave the labor market at the age of 58 years, whereas for men this age is 60. The threshold of 75% of the sample that left the labor market is reached in the sample of women by the age of 70, and 71 for men.
Determinants of exit
The analysis of older cohorts’ exit from the labor market via survival methods confirms important determinants of the process, previously identified in literature. The impacts of health and of financial incentives are in this group of results.
Figure 1. Survival functions, men and women
Source: Author’s calculations based on RLMS-HSE 1995-2015 data
Health status is the key factor for men’s exit into inactivity: the exit to inactivity is accelerated by 71 percentage points for males with bad health, whereas for women this factor is statistically irrelevant.
A higher per capita household income is correlated with later exit from the labor market. A higher income from the main place of employment has no statistically significant effect when we control for household income and is at an extended boundary (15%) of statistical significance if we do not. Both variables indirectly reflect the pension replacement rate, and I interpret the results as an indirect confirmation that workers at the top part of the income distribution, being inadequately insured by the pension system, remain on the labor market longer.
The identified peculiarities of the exit to pension-age inactivity of the Russian elderly are of major interest. Unlike many developed countries, only highly skilled persons remain in the labor market longer than others, while the behavior of middle-skilled groups, and skilled and unskilled workers does not statistically differ between them.
Employment at state-owned enterprises slows down women’s exit to inactivity but is not significant for men. Self-employment and entrepreneurship prolong the presence in the labor force, by 41 percentage points for women.
The regression analysis demonstrates that the statutory retirement age has a significant impact on the time of exit from the labor market for both men and women, and the effect is significantly higher for women: the hazard rate of inactivity rises by 63 percentage points when a woman reaches 55 years, and by 25% when a man reaches 60. For men, an effect comparable in size is the self-assessment of health as poor.
Discussion
The results, on the one hand, confirm those for developed countries: health status is the key factor for men’s exit into inactivity, and financial motives have a significant impact. At the same time, the peculiarities of the Russian labor market are reflected in a differing labor market exit process of various professional groups, in the sense that self-employment and entrepreneurship and work at state enterprises postpone exit into inactivity. The high sensitivity of women to the statutory retirement age, which by 2.5 times exceeds the sensitivity of men, is one of the new and unexpected results, taking into account that the statutory retirement age for women in Russia is very low by international standards. This questions the painlessness of rising the retirement age for women, should the decision finally be taken. Indeed, given the very low pension age for females, an (gradual) increase in the retirement age for women would seem not to raise strong objections. However, our result testifies that the normative border of the retirement age has a decisive influence on women’s choice of time of exit from the labor market, even under control (as far as data permits) on differences in education, situation in the labor market and family circumstances. In this situation, the process of rising the retirement age, if such a decision is taken, can be rather painfully accepted by those who so strongly focus on its current meaning in their life plans.
References
- Denisova, Irina, 2017, “Exit of senior age cohorts from the labor market: survival analysis approach” – forthcoming in Population and Economics.
- Maleva T.M., Sinyavskaya O.V., 2010 “Raising the retirement age: pro et contra, Journal of the New Economic Association, No. 8, pp. 117-139.
Russian Financial Markets, Pension Funds and ETFs
In this brief, I consider problems arising from the virtual non-existence of index funds and/or Exchange Traded Funds (ETFs) in the Russian financial markets. While the Russian economy requires cheaper money for firms’ investments and better options for pensioners, there are almost no instruments that allow stocks for long-term value acquisition by the pension funds. I argue that more passive options and better representation of Russian stock indices may be beneficial for both the real economy and future pensioners.
Russian financial markets
In Russia, banks play a more important role in the economy than financial markets (see Danilov et al., 2017). Comparing the two, we observe bank assets to GDP ratio of about 100%, and financial markets to GDP of less than 45%. The current proportion of sources of corporate and household financing (2/3 of banks and 1/3 of financial markets), and the value of financial markets to GDP, is similar to Germany. However, the banking system in Russia is smaller and less stable. For example, it attracts passives that are very short-term, with average duration of less than 3 years.
One of the causes of the underdeveloped financial markets is the low amount of money in non-government pension funds, and the restrictive regulation that requires them to protect initial capital of future pensioners. This reduces the investment opportunity set of these pension funds, as volatile stocks are unattractive to them, and instead the funds mostly choose to invest in bonds. This is specific to the Russian market: for example, there are no such restrictions in the European approach (European Commission, 2017). However, both in developed countries and in emerging markets, stocks provide higher long-term returns than bonds. Thus, future pensioners in Russia lose on the upside, and the economy sticks to banks as the main source of investment.
The macro economy is also less effective due to the small financial markets. In the data (see Cournède et al., 2015), we see a positive correlation between the growth of outstanding stocks/bonds and the economic growth for low enough levels of total value of financial markets. While causality goes in both directions (higher GDP means need for more financial instruments), this is a compelling reason to develop financial markets.
Finally, people in Russia do not “believe” in stocks and bonds. If one compares the deposit rate in a bank with the yields of the same bank, the former is almost uniformly lower than the latter. Yet, even in the case of Sberbank, the largest bank in Russia, individuals prefer to keep their money in deposits or in foreign currency. This is a signal of low financial literacy, as well as of low income, or lack of trust; this is evident in many surveys (S&P, 2015).
Therefore, our research question is: what could be done to make the Russian market more attractive to domestic investors, and make them invest and save for pensions?
Indexing
There are many papers regarding diversification and investment opportunities of individual investors. As recent research shows (see Bessembinder, 2017), individual stocks are not good for investment even on US market. Namely, most stocks return less than Treasury bills at monthly horizons. Due to this property of financial markets, it is important that domestic investors have access to wide indices.
Moreover, Berk and Binsbergen (2015) demonstrate that active mutual funds generate as much of profits as they retain as fees. This means that individual investors are better off if they choose passive options, like index funds or Exchange Traded Funds (ETFs), as their main investment vehicle. Index funds and ETFs mostly invest in one index, say S&P500 of the 500 largest US stocks, and their explicit mandate is to stick to this index. Index funds can only be bought through a broker, while ETFs are traded on an exchange, like stocks. This makes them different in terms of possibility of active portfolio rebalancing. However, both are very passive by nature.
These arguments lead to the first conclusion: to improve investment opportunities of pension funds and individual investors, as well as the macroeconomic stability, the regulator might motivate institutional market participants to provide more passive, diversified, and stock-based portfolios.
ETFs and robo-advising in Russia
One way to increase the number of passive options is to allow more ETFs in Russian stock exchanges. As ETFs and their availability to investors have to be confirmed by the regulator (the Central Bank), one cannot immediately add new ETFs to the market. Index funds are another option. However, they have a long and sad history in the Russian market: most (about 95%) of the so-called “index funds” deviate from their benchmarks and do not follow indices. This has to do with the openness of the funds: while mutual funds and index funds have to report their stock/bond/cash holdings once a quarter, ETFs publish it daily. So one can check that ETFs follow their mandates with ease. Moreover, ETFs are usually cheaper and thus save returns for investors.
While existing ETFs on the Moscow Stock Exchange already cover a wide range of markets and even some sectors (including the Russian stock market, US S&P500, Europe and China), they are still too small in terms of assets under management (about $150 millions) and are issued by one company (FinEx). Currently, FinEx ETFs are almost the only option to invest passively, and to diversify, in the Russian market. At the same time, in most markets, index funds are marginally better saving/retirement/investment vehicle as they require less trading fees and thus save returns for low-income investors.
Regulators can facilitate the process of indexation in at least two following ways: (i) allow introduction of more index funds or ETFs in the market (requires regulator’s supervision and confirmation); and (ii) provide incentives to brokers and financial advisors to make them their first recommendation to individual investors and pension funds (as is done in the US, see BNY Mellon, 2016).
Another way to cater to low-income investors is robo-advising – an ongoing revolution in the financial markets. This tool allows investors to get wealth management advice for a small fee (about 0.15% in the best case), and it mostly invests in low-cost, passive ETFs that allow diversification of investments. While this is still new for Russia (and done by FinEx with partners from banks), it has become more widespread in developed markets. Assets under management with robo-advisors increase rapidly and now exceed $220 billions. This tool is useful for investors who are not financially literate, do not have economic or financial education, but still need good investment opportunities. In Russia, robo-advising may become a norm for so-called “non-qualified” investors – people with low enough savings and no educational certificates on financial markets. The regulator has not yet confirmed this, but we see many signs that it will go in this direction. One problem for this market is that it is still not official, and human financial advice is considered as a norm for non-qualified investors if they would like to expand their investment universe to say derivatives.
A big positive side of robo-advising is the reduction of human errors. As Richard Thaler, Nobel Prize winner of 2017, has persuasively shown in his research that humans make many judgement errors. These mistakes lead to lower returns on investment, too much trading that eats returns due to fees, and higher wealth inequality. Robo-advisers avoid all that and allow individual investors to save and invest more long-term.
The second conclusion is: regulators should help the financial industry to develop better robo-advising software that uses ETFs; use these robo-advisers as replacement for human advisers; and advertise this as the option for long-term investment, including pension funds.
Conclusion
Russian financial markets should provide more financial instruments to Russian firms and higher flexibility for investors. The Central Bank as the supervisor of financial markets, and the Ministry of Economic Development as the main government branch responsible for economic growth, may take additional steps to increase availability of passive investment options for Russian citizens. Reforms of incentives of brokerage firms might be needed, yet the ultimate goal is to improve well-being and pensions, and probably make good use of the money of long-term domestic investors. One possible option is to widen already existing ETFs market and allow individual investors to use robo-advising to invest in many instruments, even if these investors are not highly qualified or wealthy.
References
- Bessembinder, Hendrik, 2017. “Do Stocks Outperform Treasury Bills?”, Journal of Finance, Forthcoming. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2900447.
- Berk, Jonathan B. and Jules H. van Binsbergen, 2015. “Measuring skill in the mutual fund industry”, Journal of Financial Economics, vol. 118, issue 1, 1-20. https://econpapers.repec.org/article/eeejfinec/v_3a118_3ay_3a2015_3ai_3a1_3ap_3a1-20.htm.
- BNY Mellon, 2016. “Accelerating Growth: The Department of Labor Conflict of Interest Rule and its Impact on the ETF Industry”, memo. https://www.bnymellon.com/_global-assets/pdf/our-thinking/accelerating-growth-the-dol-conflict-of-interest-rule.pdf
- Cournède, Boris; Oliver Denk, and Peter Hoeller, 2015. “Finance and Inclusive Growth”, OECD economic policy papers. http://www.oecd-ilibrary.org/economics/finance-and-inclusive-growth_5js06pbhf28s-en?crawler=true
- Danilov, Y.A.; A.E. Abramov and O.V. Buklemishev, 2017. “Reform of financial markets and non-banking financial sector” (in Russian), Policy report. https://csr.ru/wp-content/uploads/2017/07/Report-Financial-markets-v2-web.pdf.
- European Commission, 2017. “Pan-European Personal Pension Product (PEPP)”, memo. http://europa.eu/rapid/press-release_MEMO-17-1798_en.htm
- S&P Global Finlit Survey, 2015. http://gflec.org///initiatives/sp-global-finlit-survey/
Highlights for Commemoration of the 1917 Russian Revolution – Hints for Further Study
Professional historians in general have an ambivalent attitude towards anniversaries and commemorations of historical events, be they epochal or not. On the one hand, centennials and similar memorials may alleviate the funding of one’s research projects as the authorities likewise wish to highlight certain events. On the other hand, jubilee years can tend to divert historians from their ordinary research directions. Not for nothing would even frank scholars from Oxford, England complain in 2014 of the “tyranny of celebrations” and wish that nothing comparative to the centennial of the Great War 1914-1918 would appear soon.
In Russia, similar attitudes seem not to have appeared with respect to the centennial of the 1917 revolutions, the February and October revolution as traditionally called. In my April 2017 policy brief, I noted how universities all over Russia organized conferences devoted to various aspects of 1917. Many more publications have appeared as well as translations or new editions of classical works. Here I only hint at some accomplishments that may deserve to be studied for anyone who is genuinely interested in the historical debates in Russia.
This autumn, the leading institutes of the Academy of Sciences, the Institute for General History (IVI RAN) and the Institute for Russian History (IRI RAN) held their grand events with participation of leading scholars from the West, inter alia Hélène Carrère-d’Encausse and Alexander Rabinovich, to mention only a few. The IRI RAN presented its two-volume “The Russian revolution in 1917: The Power, Society, Culture” with the same emphasis as the main theme of the conference, i.e. how the historiography of the February and October revolution changed over time (see http://iriran.ru/?q=node/1699).
Western mass media and Russia observers in particular have during 2017, in my view, one-sidedly focused on how Kremlin would, or not, ‘celebrate’, ‘commemorate’, or even ‘want to forget’ the epochal events in Russia one hundred years ago. In contrast to other anniversaries, the 200th of Napoleon’s war on Russia or the 100th of the First World War, the highest political spheres have, as it seems for good reasons, left the information sphere quite free for the professional historians, film and TV producers, and others to commemorate at their own behest the 1917 revolution.
One important source of information about the commemoration of the 1917 Russian Revolution is the book published by AIRO-XXI, Association for the Study of Russian History in the 21th Century, led by the renowned historiographer Gennadyi Bordiugov. Just as for the anniversaries of the Victory in World War Two (in 2005 and 2015), Bordiugov and his colleagues in AIRO-XXI started a huge monitoring project in late 2016 in order to follow how various groups and centres all over Russia, as well as in major Western countries, were to commemorate the 1917 Russian revolution. The monitoring is by now complete and the result is the mighty book “Revolution-100. A Reconstruction of the Jubilee” (http://www.airo-xxi.ru/-2017-/2395–100-). This will for a long time serve as the best introduction to how Russia – in the broadest terms – comes to grips with the jubilee. The first articles give the background – how the October revolution was celebrated in the Soviet era and the major changes in the post-1991 Russia. Several contributions give the present-day context – how parallels are drawn between contemporary events in Russia and abroad, on the one hand, and the Russian revolution, on the other hand. The virtual sphere today, the Internet and blogosphere take up a much more important space for the younger generation than books and encyclopaedias; therefore the monitoring project also includes surveys of which aspects of the revolution are treated therein.
In contrast to what originally was set as leitmotiv for the commemoration – a reconciliation among groups and personalities with divided approaches to the Bolshevik takeover in particular and the Soviet experiment in general, most publications, exhibitions and meetings that the AIRO-XXI have monitored show that the epochal historical cataclysms one hundred years ago still are as divisive as before. The great contrast is that disputes are formalized and fact-based, that arguments from any side are given due consideration, and that most accept the device that “there is no final truth in history, merely arguments without end”.
The AIRO-XXI monitoring also treats the cinema, television and Internet series that were shown in connection with the jubilee. Much media interest was connected with the protests from the Orthodox Church against the film “Matilda” as it allegedly defamed the last tsar Nikolai II for showing his love affair in the 1890s with a prima ballerina. The artistic freedom finally triumphed and the debates only slightly influenced the mass of cinemagoers. We can also note that Russian television channels have sent pedagogical and dramatic series on some of the major figures of the revolution. One on the mythical Aleksandr Parvus (Helphand) with his views on revolutionizing Russia during the war, even with the help of the German General Staff; the other on Leo Trotskii as people’s commissar of war from 1918. These series and many others are vividly described in the AIRO-XXI volume by the philologist Boris Sokolov, who clearly presents where historical facts might have been twisted for the sake of art.
Mention should finally be made, for those who wish to follow how Russia’s leading professional historians analyse the revolution, that many lectures given at universities during 2017 are available at YouTube. Suffice it here to mention Vladimir Buldakov (for his books, see my previous policy brief), who since the 1980s researched the Russian revolutions and presented his main theses in “Krasnaya Smuta” (Red Troubled times). In 2017, he has lectured on this theme for various audiences (compare https://www.youtube.com/watch?v=SG9T3H55Hrk;https://www.youtube.com/watch?v=JnRXgCqGBrg; https://www.youtube.com/watch?v=9UPYYBnYow8)
To appreciate how an academic discussion on the ‘Great Russian Revolution ‘ – as many scholars today prefer to treat the events in 1917 – at its best can deepen our understanding, it is well worth pondering the arguments by renowned historians Aleksandr Shubin, Aleksandr Vatlin, Tatiana Nekrasova, Gennadii Bordiugov and Vladimir Pantin in the Kultura Channel program series “Chto delat?” (What is to be done) (https://www.youtube.com/watch?v=KQF0o8adIDw). Although each of the specialists had their own interpretations and various approaches, the mentor Vitalii Tretiakov, well-known journalist and formerly chief-editor of “Nezavisimaya Gazeta, managed to step-by-step highlight the issues that have divided historians in the past, as well as such matters that will call for renewed research.
In early 2017, some hoped that commemorative arrangements on the 1917 revolution would lead towards reconciliation between those opposing groups who still reason and argue as one or the other political parties of that era, between those who sympathized with the socialists in general and/or the Bolsheviks in particular, on the one hand, and those who ideologically has more affinity with the Liberal, Conservative or Monarchist groups, on the other hand. While such reconciliation is not yet in sight, the many articles in mass media, museum exhibitions and TV series have definitely heightened the older generations’ understanding of the very complex, intricate nature of the political, social and military forces that first led to the dissolution of tsarism, their fact-based knowledge of the tentative to establish a full democratic country even in the framework of the world war, and finally to a better grasp – than the standard Soviet orthodox narratives – of why and how the seemingly minuscular Bolshevik party could successfully grasp power in November 1917 and in the end also triumph in the devastating civil war.
It goes without saying that for school teachers all over Russia, the commemorative arrangements have provided a golden opportunity to engage their pupils and students in various forms of so-called living history, i.e. combining the state’s grand story with the localities’ and the families’ own histories.
Paid Work after Retirement – Does Quality of Your Main Job in the Past Matter?
In this brief, we summarize the results of a recent analysis focused on identifying the key determinants of engagement in paid work after retirement based on life histories data from the Survey of Health, Ageing and Retirement in Europe (SHARE). We find a strong link between the probability of work after retirement and indicators of quality of work prior to labor market exit, such as high physical and psychosocial demands, lack of control or receiving adequate social support. These results suggest a potentially important role of job-quality regulations. We find no significant association with past experience of adequate rewards with respect to efforts in the main job, which suggests that involvement in paid work after retirement may to a lesser extent be driven by financial concerns. This might mean that policy initiatives targeted at higher level of labor market activity among retirees should stress non-material aspects of employment in later life.
The collection of data in the 7th wave of the Survey of Health, Ageing and Retirement in Europe (SHARE) proceeded in 2017, and the Centre for Economic Analysis (CenEA) has recently published a report based on information collected in previous waves of the survey. The report entitled “The Polish 50+ generation in the European context: activity, health and wellbeing” examined among other issues the determinants of labor market activity of people aged 50+ with a special focus on Poland (Myck and Oczkowska, 2017).
SHARE is a panel survey conducted every two years and focuses on health conditions, material situation and social relations of the population aged 50 years and older. In 2017, in the 7th Wave, interviews were conducted with over 80,000 participants in 26 European countries and Israel. While the survey usually focuses on contemporary conditions of respondents, the interviews in Wave 3 (the SHARE-Life conducted in 2008-2009) is concerned with respondents’ life histories and topics such as family history, mobility and work histories.
In this brief, we draw on one of the chapters from the report and present results of a analysis that combines information on the quality of the main job of the respondents’ working careers, with information on engagement in paid work among retired individuals to examine key determinants of undertaking paid work after labor market exit.
Work histories in SHARE
The life-history interview includes a series of 12 questions evaluating effort-reward imbalance in the main job of individuals’ working careers (Siegrist and Wahrendorf, 2011; Siegrist et al., 2004; 2014). Based on these questions, five dimensions of the quality of the workplace were identified: physical and psychosocial demands, control, social support and reward (see Table 1). Figure 1 presents an example of the distribution of answers to one of the questions used to define these dimensions, which asked about the extent to which the respondents’ main jobs was physically demanding. Generally, men’s past main job is more often described as physically demanding than women’s. While less than half of respondents in France and Sweden claimed physically strenuous main job, the respective measure in Poland and Greece was as high as 75%.
Table 1. Dimensions of job quality
| Dimension | SHARE Questionnaire Items |
| Physical demands |
– „My job was physically demanding.” – „My immediate work environment was uncomfortable (for example, because of noise, heat, crowding).” |
| Psychosocial demands | – „My work was emotionally demanding.”
– „I was exposed to recurrent conflicts and disturbances.” |
| Control | – „I was under constant time pressure due to a heavy workload.”
– „I had very little freedom to decide how to do my work.” |
| Social support at work | – „I received adequate support in difficult situations.”
– „There was a good atmosphere between me and my colleagues.” – „In general, employees were treated fairly.” |
| Reward |
– „I had an opportunity to develop new skills.” – „I received the recognition I deserved for my work.” – „Considering all my efforts and achievements, my salary was adequate.” |
Notes: answer categories: “strongly agree, agree, disagree, strongly disagree”. Source: adapted from Siegrist and Wahrendorf (2011).
Figure 1. “My job was physically demanding”
Notes: includes wave 3 respondents with at least 10 years of seniority who retired by the time of wave 6; weighted. Source: own calculation based on SHARE data waves 3 (2008-2009) and 6 (2015).
Following Wahrendorf and Siegrist (2011), for the purpose of further analysis, we construct five measures of workplace quality based on the questions listed in Table 1. For each dimension of job quality, we calculate a sum-score of answers (from 1 “strongly agree” through 2 “agree”, 3 “disagree” to 4 “strongly disagree”) to selected questions, and identify the upper (lower) tertile of observations. We create five binary indicators (with 1 meaning “yes”) describing the quality of work in the sense of high physical or psychosocial demands, lack of control, and adequate social support or adequate reward. The results are presented in Figure 2 in association with the frequency of paid work after retirement.
Figure 2. Associations between quality of work in the past and frequency of paid work after retirement
Notes: includes wave 3 respondents with at least 10 years of seniority who retired by the time of wave 6 from selected countries (CZ, FR, DE, GR, PL, ES, SE); weighted. Source: own calculation based on SHARE data waves 3 (2008-2009) and 6 (2015).
In most cases the percentage of retirees engaged in paid work was significantly higher among those positively evaluating the quality of their past workplace. The only dimension where no significant difference was found in the level of involvement in paid work was between the retirees who estimated rewards at work as adequate to their efforts and those who assessed them otherwise.
What determines paid work after retirement?
The role of the five measures of job quality was further examined using models of probability of paid work after retirement. Apart from quality indicators regarding the main job, controls included total labor market experience, unemployment incidence, as well as detailed demographics and information concerning current health status and material conditions. Odds ratios were estimated separately for men and women from a group of selected countries: Czech Republic, France, Germany, Greece, Poland, Spain and Sweden.
Higher education is positively associated with the odds of employment after retirement, but have the opposite effect for age, poor health and living in rural areas. Each additional year of labor market experience increases the odds of working after retirement, but we find no significant effect of unemployment episodes.
Both men and women without experience of high physical demands and lack of control in their main job have higher odds of working after retirement than those who declared such experiences. For example, men who did not experience highly, physically demanding main jobs have 1.4 times higher odds of work after retirement compared to those who did. The respective odds for those who did not experience lack of control are 1.9. On the other hand, high psychosocial demands and adequate social support have significant influence only among retired women. Women who did not report high psychosocial demands had 1.25 times higher odds of work after retirement, while those who received adequate support in their past job had 1.5 times higher odds. We find no significant effect of the experience of adequate rewards with respect to efforts in the main job, and similarly no significant association between material conditions and employment of retirees. Both of these may imply that involvement in paid work after retirement is to a lesser extent driven by financial concerns.
Further discussion and policy implications
Differences in the degree of engagement in paid work after retirement with respect to the assessment of past job quality suggest a potentially important role of job quality regulations. At the same time, lack of significant association between the material situation and paid work after retirement implies that policy initiatives targeted at higher levels of labor market activity among retirees may benefit from stressing the non-material aspects of employment in later life.
Results point to a strong link between quality of work in the past and probability of work after retirement, which is in line with what other studies have showed: e.g. that low quality of work in the past strongly correlates with the desire to retire as soon as possible (e.g. Dal Bianco et al., 2014). Given the demographic pressure on public finances observed or expected in many developed countries, and foreseen reductions in the generosity of pension benefits, increasing the level of engagement in paid work after labor market exit may become an important policy challenge. The results summarized in this brief suggest that governments should, on the one hand, pay attention to the labor market conditions faced by those currently employed, and on the other hand focus on a broad set of incentives to encourage employment among older generations, going beyond financial remuneration.
References
- Dal Bianco, C., Trevisan, E., Weber, G., 2014. „I want to break free. The role of working conditions on retirement expectations and decisions”, European Journal of Ageing, 12(1), 17-28.
- Myck, M., Oczkowska, M. (eds.), 2017. „The Polish 50+ generation in the European context: activity, health and well-being. Results from the SHARE survey” („Pokolenie 50+ w Polsce na tle Europy: aktywność, zdrowie i jakość życia. Wyniki na podstawie badania SHARE”), CenEA (in Polish).
- Siegrist, J., Li, J., Montano, D., 2014. “Psychometric properties of the effort-reward imbalance questionnaire”. Düsseldorf University.
- Siegrist, J., Starke, D., Chandolab, T., Godinc, I., Marmot, M., Niedhammer, I., Peter, R., 2004. “The measurement of effort-reward imbalance at work: European comparisons”, Social Science & Medicine, 58, 1483-99.
- Siegrist, J., Wahrendorf, M., 2011. “Quality of Work, Health and Early Retirement: European Comparisons”, in: Börsch-Supan, A., Brandt, M., Hank, K., Schröder, M. (eds.). “The Individual and the Welfare State: Life Histories in Europe”. Springer Berlin Heidelberg.
- Wahrendorf, M., Siegrist, J., 2011. “Working conditions in midlife and participation in voluntary work after labour market exit”, in: Börsch-Supan, A., Brandt, M., Hank, K., Schröder, M. (eds.). “The Individual and the Welfare State: Life Histories in Europe”. Springer Berlin Heidelberg.