Tag: Russia
Conflict, Minorities and Well-Being
We assess the effect of the Russo-Georgian conflict of 2008 and the Ukrainian-Russian conflict of 2014 on the well-being of minorities in Russia. Using the Russian Longitudinal Monitoring Survey (RLMS), we find that the well-being of Georgians in Russia suffered negatively from the 2008 Russo-Georgian conflict. In comparison, we find no general effect of the Ukrainian-Russian conflict of 2014 on the Ukrainian nationals’ happiness. However, the life satisfaction of Ukrainians who reside in the southern regions of Russia in close proximity to Ukraine is negatively affected. We also show that the negative effect of conflict is short-lived with no long-term legacy. Additionally, we analyze the spillover effect of conflict on other minorities in Russia. We find that while the well-being of non-Slavic and migrant minorities who have recently moved to Russia is negatively affected, there is no effect on local minorities who have been living in Russia for at least ten years.
Militarized conflict affects a myriad of socioeconomic outcomes, such as the level of GDP (Bove et al. 2016), household welfare (Justino 2011), generalized trust and trust in central institutions (Grosjean 2014), social capital (Guriev and Melnikov 2016), and election turnout (Coupe and Obrizan 2016). Importantly, conflict has also been found to directly affect individual well-being (Frey 2012, Welsch 2008).
However, previous research studying individual well-being in transition countries largely abstracts from heightened political instability and conflict proneness, while this has been particularly pertinent in transition countries. Examples of transition countries facing various types of conflicts are abound, such as Yugoslavia, Ukraine, Tajikistan, Russia, Armenia, Azerbaijan, Moldova, and so on. Therefore, it is imperative to explore how conflict shapes well-being in transition countries.
In a new paper (Gokmen and Yakovlev, forthcoming), we add to our understanding of well-being in transition in relation to conflict. We focus on the effect of Russo-Georgian conflict of 2008 and the Ukrainian-Russian conflict of 2014 on the well-being of minorities in Russia. The results suggest that the well-being of Georgians in Russia suffered negatively from the 2008 Russo-Georgian conflict. However, we find no general effect of the Ukrainian-Russian conflict of 2014 on the Ukrainian nationals’ happiness, while the life satisfaction of Ukrainians who reside in the southern regions of Russia in close proximity to Ukraine is negatively affected. Additionally, we analyze the spillover effect of conflict on other minorities in Russia. We find that while the well-being of non-slavic and migrant minorities who have recently moved to Russia is negatively affected, there is no effect on local minorities who have been living in Russia for at least ten years.
Data and Results
We employ the Russian Longitudinal Monitoring Survey (RLMS) which contains data on small neighborhoods where respondents live. Starting from 1992, the RLMS provides nationally-representative annual surveys that cover more than 4000 households with 10000 to 22000 individual respondents. The RLMS surveys comprise a broad set of questions, including a variety of individual demographic characteristics, health status, and well-being. Our study utilizes rounds 9 through 24 of the RLMS from 2000 to 2015.
In this survey, we identify minorities with the question of “What nationality do you consider yourself?” Accordingly, anybody who answers this question with a non-Russian nationality is assigned to that minority group.
We employ three measures of well-being. Our main outcome variable is “life satisfaction.” The life satisfaction question is as follows: “To what extent are you satisfied with your life in general at the present time?”, and evaluated on a 1-5 scale from not at all satisfied to fully satisfied. Additionally, we use “job satisfaction” and “health evaluation” as outcomes of well-being.
Our results suggest that our primary indicator of well-being, life satisfaction, for Georgian nationals has gone down in the Russo-Georgian conflict year of 2008 compared to the Russian majority (see Figure 1). The magnitude of the drop in life satisfaction is about 39 percent of the mean life satisfaction. Our estimates for the other two well-being indicators, job satisfaction and health evaluation, also indicate a dip in the conflict year of 2008. Lastly, our estimates show that the negative impact of the conflict does not last long. Although there is a reduction in the well-being of Georgians both on impact in 2008 and in the immediate aftermath in 2009, the rest of the period until 2015 is no different from the pre-2008 period.
Figure 1. Life Satisfaction of Georgian Nationals in Russia
Source: Authors’ own construction based on RLMS data and diff-in-diff estimates.
Furthermore, when we investigate the effect of the Ukrainian-Russian conflict of 2014, we find no negative effect on the life satisfaction of Ukrainians. One explanation for why the happiness of Ukrainians in Russia does not seem to be negatively affected in 2014 is that the degree of integration of Ukrainians into the Russian society is much stronger than the degree of integration of Georgians. On the other hand, our heterogeneity analysis reveals that in the southern parts of Russia closer to the Ukrainian border, where there are more Ukrainians who have ties to Ukraine, Ukrainian nationals are differentially more negatively affected by the 2014 conflict. The differential reduction in the happiness of Ukrainians is about 19 percent of the mean life satisfaction.
Moreover, we also look into whether there is any spillover effects of the Russo-Georgian and the Ukrainian-Russian conflicts on the well-being of other minorities. We first carry out a simple exercise on non-Slavic minorities of Russia. We pick the sample of non-Slavic ex-USSR nationals that are similar to Georgians in their somatic characteristics, such as hair color and complexion. This group of people include the nationals of Azerbaijan, Kazakhstan, Uzbekistan, Kyrgyzstan, Turkmenistan and Tajikistan. We treat this group as “the countries with predominantly non-Slavic population” as their predominant populations are somatically different from the majority Russians, and thus, might either have been subject to discrimination or might have feared a minority backlash to themselves during the times of conflict. This conjecture finds some support below in Figure 2 in terms of violence against minorities. We observe in Figure 2 that hate crimes and murders based on nationality and race peak in 2008.
Our estimates also support the above hypothesis and propose that there is some negative effect of the 2008 conflict on non-slavic minorities’ happiness as well as their job satisfaction, whereas 2014 conflict has no effect.
Figure 2. Hate Murders in Russia over Time
Source: Sova Center
Next, we investigate the spillover effects of conflict on Migrant Minorities. Migrant minorities are minorities who have been living in their residents in Russia for less than 10 years. We conjecture that these minorities, as opposed to the minorities who have been in place for a long time, could be more susceptible to any internal or external conflict between Russia and some other minority group for fear that they themselves could also be affected. Whereas other types of longer-term resident minorities, which we call Local Minorities, are probably less vulnerable since they have had more time to establish their networks, job security, and most likely also have Russian citizenship. Our estimates back up the above conjecture and demonstrate that migrant minorities suffer negatively from the spillover effects of the 2008 conflict onto their well-being captured by any of the three measures, and not from the 2014 conflict, whereas there is no negative impact on local minorities.
Conclusion
In this paper, instead of focusing on the direct impact of conflict on happiness in war-torn areas, we contribute to the discussion on conflict and well-being by scrutinizing the well-being of people whose country of origin experiences conflict, but they themselves are not in the war zone. Additionally, we show that some other minority groups also suffer from such negative spillovers of conflict. Being aware of such negative indirect effects of conflict on well-being is essential for policy makers, politicians and researchers. Most policy analyses ignore such indirect costs of conflict, and this study highlights the bleak fact that the cost of conflict on well-being is probably larger than it has been previously estimated.
References
- Bove, V.; L. Elia; and R. P. Smith, 2016. “On the heterogeneous consequences of civil war,” Oxford Economic Papers.
- Coupe, T.; and M. Obrizan, 2016. “Violence and political outcomes in Ukraine: Evidence from Sloviansk and Kramatorsk”, Journal of Comparative Economics, 44, 201-212.
- Frey, B. S., 2012. “Well-being and war”, International Review of Economics, 59, 363-375.
- Gokmen, Gunes; and Evgeny Yakovlev, forthcoming. “War and Well-Being in Transition: Evidence from Two Natural Experiments”, Journal of Comparative Economics.
- Grosjean, P., 2014. “Conflict and social and political preferences: Evidence from World War II and civil conflict in 35 European countries” Comparative Economic Studies, 56, 424-451.
- Guriev, S.; and N. Melnikov, 2016. “War, inflation, and social capital,” American Economic Review: Papers & Proceedings, 106, 230-35.
- Justino, P., 2011. “The impact of armed civil conflict on household welfare and policy,” IDS Working Papers.
- Welsch, H., 2008. “The social costs of civil conflict: Evidence from surveys of happiness” Kyklos, 61, 320-340.
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.
Understanding Currents in the Contesting Information Spheres
Computers and internet merely added new forms to age-old forms of propaganda. Its general purpose is, as it always has been, dualistic: to shape citizens’ image of their own country, and to streamline their views of foreign partners, competitors or enemies. Studies on information wars are often one-dimensional, i.e. presenting only actions directed against one’s own state. New Russian textbooks on information wars have a more complex approach and present long historical retrospective overviews.
Reports on disinformation campaigns are nowadays regular in the information sphere in Sweden, as in the West in general. The changes of today’s propaganda compared to classic stereotypes of the Cold War confrontations seem obvious. However, many debates on how to counter a feared information war or fake news campaigns apparently lack a long-term historical perspective. Therefore, they appear unnecessarily alarmist and might even miss their claimed purpose – to promote a sound political debate on domestic and international affairs.
Trends in Swedish information spheres – a retrospective overview
From time to time, a dominant political climate and consensus is challenged. During the prosperous 1950s, Sweden formed a self-image of the “golden middle way” between capitalism and socialism. Many aspects of this self-image were indeed partly myths. A Swedish author, Göran Palm, happened to be one of the succinct observers to challenge our prejudiced visions. His books “An unjust reflection” and “Indoctrination in Sweden” reached a wide audience and forced many to reconsider our achievements as a welfare state. Gunnar Fredriksson, editor of a Social-Democratic newspaper, alerted readers to the intricacies of “the politicians’ language” as a means to distort realities or evoke positive or negative emotions.
These books from the late 1960s were milestones for heightening the public awareness of mass media manipulation. A similar trend and radical change of Sweden’s self-image is taking place today. Until recently, the predominant view has been that Sweden represents a successful experience in forming a multicultural society, despite a few obvious crisis phenomena.
However, an awareness concerning the stress on the social fabric has spread from outsiders in the political scene towards mainstream parties. One example can highlight how changes have occurred. In January 2017, the Swedish journalist Katerina Janouch was scolded for an interview on Czech television, in which she inter alia stated her own personal view of the many problems that Sweden definitely is confronted with. After a vivid debate with harsh arguments involving even high-ranking politicians over her apparently controversial statements, she wrote a diary-like book “The Image of Sweden”. On a micro level, this fascinating personal experience succinctly shows how the image of Sweden changed over the last year, what has been accepted and what is still hotly debated concerning economics, migration and social problems.
Picture 1. “Bilden av Sverige” Book Cover
Over a short period, new political trends appeared. The political agenda has changed; serious debates treat formerly taboo topics. This is essentially because objective challenges to the economic stability, social fabric and cohesion cannot be ignored.
Even more noteworthy is, that given the outcome of the US presidential election campaign and the Brexit plebiscite of 2016, in particular the alleged role of outsiders’, supposedly decisive, involvement in these political events, Sweden has revitalized its organs on countering foreign political propaganda, which had been inactive after the Cold War era. Leading newspapers jointly with radio and TV intend to cooperate in order to thwart any attempts in 2018 to covertly interfere or overtly influence the upcoming parliamentary elections in September. Alerts against supposed disinformation campaigns by Russian mass media were at the center-stage of an annual defense policy conference in Sälen. The previous attempts to describe and analyze the supposed Russian information war efforts towards Sweden as presented hitherto seem, in my view, to lack in source collection from Russian mass media and blogospheres. They merely illustrate rather than form a structured picture of the Russian information spheres as a multiform complex.
Contests between the information spheres in Russia and the West
Therefore, as the Swedish proverb goes, “let’s turn the keg” and try to see things in a new perspective, by turning our usual modes of thought and preconceptions upside-down. A broad awareness on state propaganda in Russia, in the past as well as at present, can deepen our understanding of ongoing information wars. How does a Russian student in political sciences become aware of the formations of their nation’s self-image, as well as of foreign propaganda against their country? How do Russian scholars analyze their recent conflicts with neighboring states? What can they tell us of the general awareness concerning information warfare in the Russian public?
Three Russian historians, Viktor Barabash, Gennadii Bordiugov and Elena Kotelenets, all active in AIRO-XXI about which you can read more of here, give a broader perspective on how state propaganda has changed since the early 20th century till our times. They illustrate how countries at war, starting during World War I, directed propaganda to mass armies with, in general, literate soldiers and by that tried to influence the enemy’s morale. They evaluate how effective various forms of propaganda were, given the new technologies radio and TV during the Second World War and the Cold War eras.
After several in-depth chapters on the technological changes in the information era, on the cyber technological advances that have radically transformed traditional espionage, they finally describe how the information wars were carried out in Russia’s conflicts since 2000 (South Ossetia in 2008, Ukraine during the “Orange Revolution” and “Euro-Maidan”). Particular emphasis is devoted to how the conflicting parties formed their propaganda to their own population, on the one hand, and versus the opposing state, on the other hand.
Picture 2. ”Gosudarstvennaia propaganda i informatsionnye voiny” Book Cover
It is striking that in contrast to the Russian textbook by Barabash, Bordiugov and Kotelenets, very few analysts in Sweden have managed to present the contemporary information wars as a two-sided conflict; with two sides mutually intertwined in their mass media and social media strivings. Instead, information warfare is described as originating solely from more or less sophisticated “troll factories” in various locations in Russia. A couple of obviously forged “documents” ascribed to Swedish political leaders are sometimes referred to, although their actual effects have been nil.
In Sweden, as well as in the West in general, much has been stated on the real or imagined disinformation campaigns launched by Russia. Sometimes, they are said to direct public opinion in other states or even to influence the electorate (USA, United Kingdom). The role of relatively peripheral news agencies like RT (Russia Today) or Sputnik have seen their role amplified beyond reasonable belief. A further simplification is to reduce any Russian interpretation of events as a piece of falsification (fake news). Warnings of “Putin’s narrative” or “Russian Television fake stories” are common in mass media. In comparison, students of the Barabash textbook must undertake textual analyses of conflicting Russian and foreign opinions.
If one does not know history, you are likely to repeat its mistakes – so goes the proverb. Just as likely is the case where one repeat past generations’ mistakes because you are leaning on the mythology surrounding many events in your country’s past.
Minister of Culture Vladimir Medinskii has carried out a broad research project on the shifting images of Russia in the West, from eldest time when written sources by travelers are available. Although other historians criticized his original thesis on this subject for certain methodological flaws, there is no doubt that Medinskii accomplished a great feat as a popularizer of intricate phases in Russia’s history.
One book concerns the new historiography of the 1939–45 war on the Eastern Front. Since the late 1980s, many formerly taboo topics concerning the war were studied based on formerly secret archives as well as on interviews with veterans. In his book on the Great Patriotic War, Medinskii carefully unravels old myths and rejects new simplifications or distortions of battle histories.
Picture 3. “Mify o Rossii” Book Cover
Every historical nation tends to develop its own historiographical paradigm, which might be more or less objective and in conformity with general interpretations in other nations. However, just as often one nation’s image of their neighbors, former enemies or partners may differ substantially; thus are created the stereotypes of “the others”. In his grand comparative survey of Russia from the 12th century to the present, Medinskii provides the engaged reader with a plethora of examples of distortions of Russia’s history, created not only by foreign observers but also by ideologically motivated compatriots. Many legends on “eternal traits” in Russia are challenged. A Western reader of Medinskii’s book is bound to reflect on the various measures by which his or her country is evaluated in comparison with Russia.
In conclusion, the information contests or wars are only one element in the wider concept of cyber and hybrid wars. Observing our Swedish debate on the nefarious effects of alleged Russian disinformation, the absence of self-awareness is remarkable on how our own image of Russia (in our mass media and in the public opinion) is in itself the unconscious product of a pre-war attitude (sometimes alluded to as our age-long Russia-fear /Rysskräck/).
On the contrary, the legacy of the Soviet epoch has apparently raised the cultural curiosity among the Russian public. Mass media and publishing companies created a multidimensional panorama of their country’s past. The concerned Russian readers seem fairly well aware of politicization of historical issues and international affairs. Not for nothing do they often get substantial “food for thought” from the foreign news media translations, provided online by the InoSmi.ru site; a translation bureau, which took over the task of the Soviet-era magazine “Za Rubezhom”, and which lends its commentary fields open for anyone to comment. Even a cursory survey of commentary fields reveals their spontaneous character, rather than something created by Kremlin’s purported “troll armies”.
It goes without saying that a general and highly sophisticated awareness of overt or covert forms of meddling by a foreign state in the political process of any country must be welcomed and promoted. However, it is an open question how successful certain organized counter-disinformation strategies will be, e.g. EU’s site EUvsDisinfo.eu, NATO’s East StratCom Task Force or the Swedish joint public radio and TV with leading newspapers to “combat fake news”. Leaving much broader fields in the information sphere for freer opinion making in mainstream media as well as in the blog sphere might prove to be a sounder path towards dialogues, debates and mutual understanding.
References
- Barabash, V. & G. Bordiugov & E, Kotelenets, Gosudarstvennaia propaganda i informatsionnye voiny (2015), AIRO-XXI
- Fredriksson, G., Det politiska språket (1966 and later editions), Tiden.
- Janouch, K., Bilden av Sverige (2017), Palm Publishing.
- Palm, G., En orättvis betraktelse, (1966) and Indoktrineringen i Sverige (1968), PAN/Norstedts
- Medinskii, V., Voina: Mify SSSR, 1939 – 1945 (2011) and Mify o Rossii (2015), Abris/OLMA
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.
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
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.
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.
On Economics of Innovation Subsidies in Russia
Following the general agreement that innovation is a source of economic growth, the Russian government has provided various stimuli to foster domestic innovation. One of the mechanisms of innovation policy is research subsidies. This policy brief starts off with a discussion of the theoretical predictions and empirical evidence, which relates the economic incentives of research subsides to innovation and growth. We then address the potential adverse effects of focusing innovation subsidies mainly on large public companies in Russia. Finally, we attempt to establish a link between the innovation rate and market competition within Russian industries.
Overview
According to data from the Russian Statistical Agency, the R&D intensity – measured by R&D expenditure as percent of sales – increases with company size. Companies with 50 to 500 employees spend 1% of their sales on R&D, while the R&D intensity varies from 2 to 5% of sales for larger businesses (see Figure 1). The size non-neutrality of R&D in Russia contradicts the findings in the theoretical and empirical literature, which hold for companies in the developed countries (Cohen, 2010). An explanation may be the excessive government support to public companies in Russia, and in particular, to larger public corporations. A positive consequence of such policies is that public corporations come ahead of private companies, not only in R&D intensity, but also in innovation rates (see Figures 2–3).
However, government support towards innovation does not necessarily have a positive impact on overall economic activity. The purpose of this brief is to discuss the unwanted effects of the government policy in the form of research subsidies, both in theory and in an application to public companies and corporations in Russia. We base our analysis on the outcomes of the 2014–2017 micro surveys by the Analytical Center under the Government of the Russian Federation.
The role of government
Fighting under-provision of innovation
According to the seminal paradigm of the endogenous growth models with technological change, companies are engaged in quality competition, and their innovations are explained by a rational decision to raise profits through expanding the markets for existing products or entering markets for new products (Schumpeter, 1942; Romer, 1990; Grossman and Helpman, 1991; Kletter and Kortum, 2004). The innovation becomes one of the causes of economic growth, which is proved in empirical applications for developed countries, such as the U.S., Japan and the Netherlands (Akcigit and Kerr, 2010; Lentz and Mortensen, 2008; Grossman, 1990).
Figure 1. Innovation rate and R&D intensity by company size (number of employees)
Source: Indicators of Innovation in the Russian Federation: 2017. Tables 2.4, 2.16, Data for 2015. Innovative rate is % of companies involved in innovative activity.
However, the technological change is closely linked to knowledge disclosure, which means that new products become vulnerable to imitation, and that the non-rival character of knowledge causes an under-provision of innovation on the market (Arrow, 1962). The argument supports the cause for government policies through the system of intellectual property rights on the legal side, and research subsidies as an economic mechanism (Rockett, 2010; Hall and Lerner, 2010). Research subsidies are expected to have a positive effect on innovation rate, as is empirically shown for the U.S. in Acemoglu et al. (2016) and Wilson (2009). However, the impact on economic growth is ambiguous (Acemoglu et al., 2013; Grossman, 1990).
Figure 2. Innovation rate and R&D intensity by ownership
Source: Indicators of Innovation in the Russian Federation: 2017. Tables 2.6, 2.17, Data for 2015, public corporations are different from organizations by regional/federal government.
Figure 3. Share of public funds in R&D financing, % of company budget
Notes: Indicators of Innovation in the Russian Federation: 2017. Table 1.13; Innovation Development Programmes of Russian State-Owned Companies, Fig.4.
Unwanted effects of subsidies
Two concerns are associated with subsidization of innovation. First, while research subsidies may stimulate innovation among the targeted companies, the growth effect is likely to be heterogeneous across companies in the industry or economy, leading to a neutral or even negative overall effect. For instance, the increased innovation rate in subsidized large incumbents may curb entry of new (and more productive) firms, so the net outcome is deceleration of growth in the economy (Acemoglu et al., 2013). Research subsidies may even cause a shrinking of the high-tech sectors: if skilled labor moves from manufacturing to research labs, manufacturing may experience a shortage of labor, resulting in the net effect being a decrease in production (Grossman, 1990).
Another extreme of subsidizing entrants, in view of antitrust policies, occurs when former entrants change their market status to incumbents: now they face lower profits relative to newer entrants and hence, become less incentivized in their economic activity (Segal and Whinston, 2007).
Second, innovation policy (for instance, in the form of subsidies) may sometimes not even increase the innovation rate. Indeed, incumbents have no incentives to innovate in order to keep their market power or to prevent entry of higher quality firms in industries with non-perfect competition (Rockett, 2010; Qian, 2007).
Both mechanisms are likely to hold for Russian industries, where the protection of large public corporations has led to low competition, various forms of distortions on the market and hence, weak incentives to innovate.
Potential adverse effects in Russia
Large companies are likely to attract public attention owing to their obvious advantages in spreading fixed costs of innovations (Cohen,
2010). Russia is no exception to the phenomenon, so public corporations, which are commonly of a large size, received government subsidies. However, the subsidy is primarily used for acquiring new technologies and perfecting design, rather than conducting R&D (See Figure 4 with comparison available for communications and IT industry). The fact points to a possibility of a small effect of innovations on growth of public companies. Only if the research subsidy is spent on delegating the R&D research to specialized firms, with a subsequent acquiring of the resulting technology, the existing policy of supporting public corporations may induce their growth and/or growth of the corresponding industry.
Figure 4. Structure of spending the research subsidy in communications and IT in 2013, %
Notes: Indicators of Innovation in the Russian Federation: 2017. Table 1.134 Innovation Development Programmes of Russian State-Owned Companies, Fig.3.
In an attempt to formally assess the effect of innovation subsidies on company growth, we focus on the time profiles of the common proxies for company size: sales, profits and employment (Akcigit et al., 2017; Akcigit and Kerr, 2010; Acemoglu et al., 2013). The macroeconomic literature predicts that innovation becomes one of the channels for an increase of each of the three variables through a rise in quality. Motivated by this literature, the micro-data analysis “On the Interaction of the Elements of the Innovation Infrastructure”, conducted by the Analytical Center under the Government of the Russian Federation (2014), asked companies to assess their changes in sales, profits and employment in response to the innovation subsidy. As a result, the outcomes of the above analysis allow for a comparative assessment of the impact of the government’s innovation subsidy for public and private companies.
In particular, the results point to higher growth across private companies owing to research subsidies: the percent of private companies with new employees is higher than that of public companies. Similarly, the percentage of private companies that increased market share or raised profits/export due to subsidies exceed those of the public companies (see Figure 5). Here, we interpret new hires as employment growth and increase of market share as a potential indicator of sales growth.
Figure 5. Economic activity owing to research subsidies, % of companies
Source: Analytical Center under the Government of the Russian Federation, 2014. Fig.22
The innovation activity in private Russian companies lead to a higher prevalence of new products in comparison with public companies. The fact goes in line with a more important role of research and development in the innovative activity of private Russian companies (see Figure 4).
Finally, we attempt to establish a link between the innovation rate and market competition at the level of Russian industries. For this purpose, we use the results of the annual surveys “An assessment of the competitiveness in Russia”, conducted in 2015–2017 by the Analytical Center across 650–1500 companies from 84 Russian regions. The respondents were asked if they implemented R&D as a strategy for raising their competitiveness. We use the percentage of firms doing R&D as a proxy for the innovation rate. Competition in the industry was evaluated by respondents on a five-point scale (no competition, weak, median, high and very high), and we combine the prevalence of the two top categories as a proxy for competition in the industry.
Figure 6. Competition and R&D in Russian industries, % of firms
Source: Analytical Center under the Government of the Russian Federation, 2017, pp.8, 18.
The results show that innovative activity in the form of R&D or product modification is observed in industries with relatively high competition in Russia – for instance, in machinery and electric/electronic equipment (Figure 6). At the same time, industries where competition is not as high (e.g. woodworking, construction) show absence of either type of innovation. The findings go in line with the economic theory about market competition being a prerequisite for the rational choice of companies about innovation. Moreover, if the purpose of government subsidies is to foster innovation, the effective allocation of subsidies would imply the focus on Russian industries with high competition – here various forms of innovation do play a role in the company strategy on the market.
Conclusion
Our analysis outlines the theoretical foundations for the potential adverse effects of innovation policies in the form of research subsidies. The unwanted outcomes may relate to heterogeneity of companies and absence of the association between innovation activity and growth on non-competitive markets.
We offer the empirical evidence, which points to the undesired effects of subsidizing public companies in Russia. For instance, compared to the overall Russian sector of communications and IT, the innovative activity in public corporations has a weaker association with research and development. Additionally, compared to private companies, the innovations may result in smaller prevalence of increased exports, profits or new hires, as well as in a less frequent development of new products by public companies in Russia.
References
- Acemoglu, D., Akcigit, U., Bloom, N., Kerr, W. R., 2013. “Innovation, reallocation and growth”, National Bureau of Economic Research Working paper, No. 18993.
- Acemoglu, D., Akcigit, U., Hanley, D., Kerr, W. (2016). Transition to clean technology. Journal of Political Economy, Volume 124(1), pages 52-104.
- Akcigit, U., Kerr, W. R., 2010. “Growth through heterogeneous innovations” National Bureau of Economic Research Working Paper, No. 16443.
- Analytical Center under the Government of the Russian Federation, 2014. “On the Interaction of the Elements of the Innovation Infrastructure”, Analytical report, in Russian.
- Analytical Center under the Government of the Russian Federation, 2015-2017. “An Assessment of the Competitiveness in Russia”, Analytical reports, in Russian.
- Arrow, K., 1962. “Economic welfare and the allocation of resources for invention”, In The Rate and Direction of Inventive Activity: Economic and Ssocial Factors, Princeton University Press, pages 609-626.
- Cohen, W. M., 2010. “Fifty years of empirical studies of innovative activity and performance”, Handbook of the Economics of Innovation, Volume 1, pages 129-213.
- Grossman, G. M., Helpman, E., 1991. “Quality ladders in the theory of growth”, The Review of Economic Studies, Volume 58(1), pages 43-61.
- Grossman, G.M., 1990. ”Explaining Japan’s innovation and trade”, BOJ Monetary and Economic Studies, Volume 8(2), pages 75-100.
- Hall, B. H., Lerner, J., 2010. “The financing of R&D and innovation”, Handbook of the Economics of Innovation, Volume 1, pages 609-639.
- Indicators of Innovation in the Russian Federation: 2017. N. Gorodnikova, L. Gokhberg, K. Ditkovskiy et al.; National Research University Higher School of Economics, in Russian.
- Innovation Development Programmes of Russian State-Owned Companies: Interim Results and Priorities, 2015. M. Gershman, T. Zinina, M. Romanov et al.; L. Gokhberg, A. Klepach, P. Rudnik et al. (eds.), National Research University Higher School of Economics, in Russian.
- Klette, T. J., Kortum, S., 2004. “Innovating firms and aggregate innovation”, Journal of Political Economy, Volume 112(5), pages 986-1018.
- Lentz, R., Mortensen, D.T., 2008. “An empirical model of growth through product innovation”, Econometrica, Volume 76(6), pages 1317–1373.
- Qian, Y., 2007. “Do national patent laws stimulate domestic innovation in a global patenting environment? A cross-country analysis of pharmaceutical patent protection, 1978–2002”, The Review of Economics and Statistics, Volume 89(3), pages 436-453.
- Rockett, K., 2010. “Property rights and invention”, Handbook of the Economics of Innovation, Volume 1, pages 315-380.
- Romer, P. M. (1990). Endogenous technological change. Journal of political Economy, 98(5, Part 2), S71-S102.
- Segal, I., Whinston, M.D., 2007. “Antitrust in innovative industries”, American Economic Review, Volume 97(5), pages 1703-1730.
- Schumpeter, J., 1942. “Creative destruction”, Capitalism, Socialism and Democracy, pages 82-83.
- Wilson, D. J., 2009. Beggar thy neighbor? The in-state, out-of-state, and aggregate effects of R&D tax credits. The Review of Economics and Statistics, Volume 91(2), pages 431-436.
Intergenerational Mobility of Russian Households
To understand the nature of income inequality one needs to know how persistent the inequality is across generations. The same inequality levels could conceal different intergenerational mobility. We utilize the Russian Longitudinal Monitoring Survey (RLMS-HSE) to find out how large intergenerational mobility in Russia is as measured by income, educational and occupational mobility. We find that although a sizeable upward intergenerational educational mobility, there is a pronounced occupational immobility and a low level of intergenerational income mobility. Indeed, the position of children in the income distribution is highly correlated with the income position of their parents, especially their mothers.
Sizeable and non-decreasing inequality in Russia poses a threat to social stability and long-term sustainability. Inequality in Russia has remained high throughout the transition period, and even slightly increased in the 2000s; the Gini inequality index rose from 0.397 in 2001 to 0.416 in 2014. The ratio of average incomes of the highest decile to those of the lowest decile also increased from 13.9 to 16 during this same period. This income gap is driven primarily by the gap between incomes of the top decile and all of the others: the top decile is estimated to have thirty percent of total monetary income in the economy. Furthermore, income inequality originates in earnings inequality: the top decile of wage earners gets thirty five percent of total wage earnings in the economy.
A key question is how persistent the inequality is, given that the same inequality levels could conceal different intergenerational mobility. In particular, social stability is challenged when income inequality is stable across generations, or put differently; there is little intergenerational mobility. Economic developments of the last 25 years seem to increase the risks of getting this problem in Russia.
Data and research methodology
We employ Russian Longitudinal Monitoring Survey (RLMS-HSE) to find out how large intergenerational mobility in Russia is as measured by income, educational and occupational mobility (Denisova and Kartseva, 2016). The RLMS-HSE questionnaires in 2006 and 2011 contain questions on dates of birth, education and occupation of the father and mother of the respondent when the respondent was 15 years old.
To study occupational and educational mobility, we use the subsample of respondents of 25-55 years old and utilize the information on education and occupation of the respondent and his/her parents. We then estimate whether the parental education level predicts the probability that children have a university degree, a secondary or a junior professional degree.
To study intergenerational occupational mobility, we estimate influence of parental occupation on the probability that the child works as a manager, a professional, a technician or professional associate, a clerk, a qualified worker or an unskilled worker.
To study the child-parent income correlation based on RLMS is trickier. There is a panel component in RLMS but it is not long enough to study intergenerational mobility directly since we for most cases are not able to observe both parents and children during their working ages. To overcome the problem we impute wages for parents. In particular, we choose respondents aged 25-35 (children) in 2006 (and 2011). We then identify respondents born in the period 1945-1961 (1945-1966 for children in 2001) (‘parents’) and use the labor market information for this group as of 1995 (2001 as robustness check) to impute parental wages. We estimate a wage equation (separately for males and females) on the sample of ‘parents’ and then use the estimated returns (coefficients) and the reported age and education of respondent’s mother and father to impute wages of respondent’s parents.
We follow Björklund and Jantti (1997) to estimate the child-parent correlation of earnings based on the equation:
delta= β0 + β1X+ β2 delta_father + β3 delta_mother + ε
where delta=log(wage/average wage in respective sample), X – age, education, settlement type, region. Standard errors are clustered on primary sampling unit.
Intergenerational educational mobility
Our analysis shows that the education of parents, high professional (university) and secondary professional in particular, is a major determinant of children’s education. Moreover, there are clear signs of upward educational mobility across generations for both males and females: the coefficients in the transition parent-child matrix are significantly higher above the diagonal (Table 1).
Table 1. Father-child education matrix
Source: Authors’ calculations based on RLMS
The probability to have a university degree is 2.4 percentage points higher if the mother’s education is at university level (as compared to secondary school), and 2.1 percentage points higher if the father’s degree is at university level (as compared to secondary school). A secondary professional degree of parents also increases the probability of a child getting a university degree by about 1 percentage point. The probability of having secondary professional degree decreases if the father or mother has a university degree.
Intergenerational correlation of occupations
There are signs of sizeable occupational rigidity between generations, especially for the top two occupational groups (managers and professionals). The probability that a child works in the same occupational group is the highest for parents-professionals: it is 40% for fathers-professionals and 35% for mothers-professionals. Surprisingly, it is also rather high for parents employed as skilled workers – about 20%. These patterns survive controlling for other variables.
Income mobility
The correlation of parent-child wages measured for 2006 data are presented in Table 2. The results point to the sizeable average intergenerational rigidity of relative wages: the wage elasticity of children’s wages with respect to parental wages is about 0.4. This is at the level of the intergenerational wage rigidity in the US (Solon 1999).
There is sizeable gender asymmetry in the rigidity: we observe a high and significant correlation of son-mother wages, but an insignificant correlation of son-father wages. There is no significant correlation of daughter-parents wages.
Table 2. Parent-child income correlations, 2006
Source: Authors’ calculations based on RLMS
Conclusion
Generational poverty stemming from low intergenerational income mobility is a threat for sustainable development in any country. The economic and social development in transition seems to increase the risks of having this problem in Russia. Our estimates show that although there is sizeable upward intergenerational educational mobility in Russia, there is a pronounced occupational immobility, and low level of intergenerational income mobility. Indeed, the position of children in the income distribution is highly correlated with the income position of their parents, especially mothers. These findings are worrisome signals important for the design of policies of sustainable development.
References
- Björklund, Anders; and Markus Jantti, 1997. “Intergenerational Income Mobility in Sweden Compared to the United States,” American Economic Review, 87(5), 1009–18.
- Denisova, Irina; and Marina Kartseva, 2016, “Intergenerational Mobility of Russian Households”, mimeo
- Solon, Gary, 1999. “Intergenerational Mobility on the Labor Market,” Chapter 29 in Handbook of Labor Economics, Vol.3 edited by O.Ashenfelter and D.Card , 1761-1800.