Location: Russia
The State of Russia Ahead of the Election
The Stockholm Institute of Transition Economics (SITE) and the Embassy of Finland have the pleasure to invite you to a seminar “The State of Russia Ahead of the Election”.
Russia is an important political and economic player in the Baltic Sea Region. The Embassy of Finland and the Stockholm Institute of Transition Economics (SITE) aim to gather Finnish and Swedish experts on Russia to discuss how the upcoming presidential election will impact economic and political development in Russia.
The seminar will take place at the Embassy of Finland (Gärdesgatan 11) on Thursday March 15, 13.00–16.00, with registration at 12.30. The format is short presentations and panel discussions that will allow time for questions and comments. The seminar will be moderated by Torbjörn Becker, Director of SITE.
Date: Thursday, March 15, 13.00–16.00 starting with registration at 12.30.
Place: Embassy of Finland, Banquet Hall, Gärdesgatan 11, Stockholm
RSVP: The number of seats for this event is limited, therefore we invite you to register for the event using the Eventbrite registration form as soon as possible, but no later than March 8.
Event Program
| 12.30 | Registration |
| 13.00-13.05 | Welcome Mikael Antell, Chargé d’affaires, Embassy of Finland |
| 13.05–13.50 | Setting the scene—political developments Martin Kragh, PhD, Associate Professor, Head of Russia and Eurasia Programme, Swedish Institute of International Affairs. Carolina Vendil Pallin, Deputy Research Director, Swedish Defence Research Agency. |
| 13.50–14.55 | Russian economic outlook—from stagnation to reforms? Economic situation and proposed reforms; banking sector and prospects for growth. Iikka Korhonen, Head of Research, The Bank of Finland Institute for Economies in Transition (BOFIT), Laura Solanko, Senior Advisor, BOFIT |
| 14.55-15.00 | Final word Mikael Antell |
| 15.00-16.00 | Reception |
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.
The Determinants of Renewables Investment
On the 24th of October, SITE held the first of its series of Energy Talks, replacing what for one decade had been known as SITE Energy Day. For this first edition, SITE invited Thomas Sterner, Professor of Environmental Economics at the University of Gothenburg to give a presentation under the headline of “Technological Development, Geopolitical and Environmental Issues in our Energy Future”. To comment on the presentation, Leonid Neganov, Minister of Energy of Moscow Region, and Karl Hallding, Senior Research Fellow at the Stockholm Environment Institute (SEI), had been invited. This policy brief reports on the important subjects presented by our guests as well as the discussion that took place during the event.
From climate change concerns to climate change targets
Thomas Sterner began his presentation by addressing the well-known issue of climate change, a constantly current topic.
Different versions of Figure 1 (below) have been used extensively by those discussing climate change over the last decades, most notably by the previous US President Al Gore in his 2006 documentary “An Inconvenient Truth”. It shows the concentration of CO2 (carbon-dioxide) in the atmosphere over the past 400,000 years. There is wide agreement within the scientific community that the emissions of greenhouse gases (GHG), such as CO2, methane and nitrous oxides, have led to the shifting weather patterns and increased temperature over the past century (NASA, 2017).
Figure 1. Level of CO2 in the Atmosphere
Notes: The vertical red line is the Keeling curve, showing how the concentration has changed since 1958. Source: Allmendinger, 2007.
Predicting the impact of these emissions is far from an exact science: the temperature increases are likely to be unevenly spread across the world as shown in Figure 2. Some areas are likely to be particularly afflicted, especially coastal lowlands susceptible to flooding and semi-arid areas where droughts can become more likely. Unless current emission levels start to decrease, we are likely to observe severe results of climate change within 20 years, such as displacement and increased migration in the wake of extreme weather (NIC, 2016). For instance, adverse health effects in China, or decreasing productivity in South-East Asia, have already become apparent due to current increased temperatures (Kan, 2011; Kjellstrom, 2016).
Figure 2. Predicted Temperature Increase
Source: IPCC, 2013.
To tackle this issue and its negative economic impacts, many policy makers have agreed to replace fossil fuels with renewables. Renewables is the collective term of energy sources that have a neutral or negative net-effect of GHG emissions and are extracted through resources that are continuously replenished, e.g. solar, wind and hydro power, and biomass energy.
As the issue of climate change is a global one, the transition to renewables needs to be global too. International climate agreements have hence long been the accepted norm to approach climate change issues. The Paris Agreement is currently the guiding principle, in spite of the announcement of the Trump administration to withdraw the United States. Though instrumental in creating a momentum in the transition to lower levels of GHG emissions, it comes with many flaws. Its goal of a maximum average temperature increase of 2°C might be considered radical given current levels. However, the policy instruments that the target depends on – the Intended Nationally Determined Commitments (INDCs) – shift the responsibility to individual nations and remove the global responsibility. As Thomas Sterner pointed out, the first three words of this acronym remove indeed any binding force, and elementary game theory tells us that it will be hard, not to say unlikely, for all signatories to remain cooperative in achieving the target of 2°C.
Investing in renewables: from political choice to competitive choice
As stated above, investing in renewables is a necessary condition to achieve climate change targets. Indeed, there are some countries that have pushed the development of renewables with the aim to reduce the fossil fuel dependency to a minimum level in a very near future (see Figure 3). However, most of these investments are currently driven by political will. A natural question is whether renewables technologies can be competitive.
It is a fact that costs of renewables have been severely decreased in the last decade (Timmons et al., 2014). However, as Thomas Sterner mentioned, the cost of renewables and of fossil fuels are still very place and time specific and depends on the scale. Investments in renewables are growing and solar and wind power have both seen production capacities increasing markedly yearly over the last years (GWEC, 2016; IEA, 2017a). However, coming from an initial low level, it will take some time before we will be able to rely on them.
Even with massive investments and decreasing generation costs, the intermittent nature of most renewable energies will still impede the competitiveness of renewables. Solar and wind power are the technologies where most of the development has been centred (Frankfurt School-UNEP Centre/BNEF, 2017). They are highly weather dependent and electricity production from these sources cannot be secured all of the time. This makes countries dependent on backup technologies. In some countries, the obvious answers to these challenges have been hydro and nuclear power. Both technologies have their respective drawbacks though.
Figure 3. World’s Top 10 Investors in Renewable Energy in 2016
Notes: New Investments $BN, Growth on 2015. Source: Frankfurt School-UNEP Centre/BNEF, 2017.
Hydro power requires a geography that allows for dams, which in turn change the nature markedly around them and may not be available during drought periods. Nuclear energy has surrounding safety aspects that most recently came to light with the 2011 Fukushima Daaiichi nuclear disaster, leading Germany to decide to shut down all of its 17 reactors by 2022 (25 % of the country’s electricity production). Moreover, it may also be technically difficult to have nuclear as a backup technology given the associated ramping and start-up constraints.
Two further remarks on the intermittency problem can be made. First, this problem is likely to become more severe when policymakers push for large-scale electrification (c.f. EU Energy Roadmap established in 2011). For example, the full electrification of transport or heating sector will drive up the demand for and consumption of electricity. As this happens, the need for something to secure constant energy access will increase.
Second, only the development of technologies that allow electricity storage could solve this issue permanently. However, the current technological progress regarding batteries’ capacity cannot yet offer the solution (J. Dizard, 2017).
Oil price, a reference price
Another important aspect stressed by Thomas Sterner was to take into account the significant role of fossil fuel prices. Although identifying an optimal oil price for a fossil-free future is not a straightforward procedure, as discussed during the event.
The high price of oil during the late 00s and early 10s stimulated the development of alternative technologies. As awareness of climate change and its effects increased among policy makers and the general public, there was a momentum to push for the development of renewables.
As investments in renewables went up, so did investments in another less green technology: hydraulic fracturing, or fracking. In the 10 years between 2005 and 2015, the United States alone saw the extraction of shale gas and oil to increase six-fold. (EIA, 2016) In part to maintain a market share, OPEC countries exceeded their own set production limits and oil prices tumbled from around $100 per barrel to around $50 (Economist, 2014).
With roughly three years behind us of somewhat stable and low oil prices, the question is what the implications of this are. It makes it more difficult to phase out fossil fuels as demand for them goes up, depressing efforts put into the research and deployment of renewables. Energy efficiency also becomes less important, driving up waste and stopping investments in energy conservation.
On the other hand, with low oil prices, investments in the fossil-fuels industry are also less likely to take place. Keeping resources in the ground becomes more palatable as profit margins are pushed down. This, in turn, is likely to have a positive effect on environment by decreasing the level of GHG emissions.
The invited guests, Leonid Neganov and Karl Hallding spoke more in depth about two central countries that contribute in shaping global environmental policy.
The local conditions, Russia and China examples
As the world’s fourth largest supplier of primary energy and the largest supplier of natural gas to the EU (IEA, 2017b), Russia presents an interesting case to observe as a country supplying fossil fuels. Leonid Neganov, Minister of Energy of Moscow Region, commented on the current policy direction of the country. He explained that non-renewable, GHG emitting energy sources make up a majority, roughly 60% of the Russian energy balance. The rest is provided by more or less equal shares of nuclear and hydro power. New renewable technologies make up a miniscule share of an estimate 0.2% of the current total.
According to Neganov, in the coming 20 years, we should not expect to see too much of a change. Though total output is expected to increase, the share of GHG-neutral energy will remain more or less constant, though the share of renewables are set to increase to 3% according to the current drafts of Russian energy policy. A more pronounced transition to other energy sources are more likely in a longer perspective towards 2050, even though circumstances may naturally change over the coming decades.
Other available information also points to that Russia has decided to tackle the shift in consumption of its major market in Europe by widening its geographic reach. Massive infrastructure investments, such as the Altai and TurkStream gas pipelines, will enable Russia to more easily reach markets that are currently beyond any practical reach.
With the Altai pipeline, Russia will be able to provide China with natural gas at a much greater level than before. China being by far the largest producer of coal sees an opportunity to shift away from the consumption of a resource that during winters causes its major cities to periodically become enveloped in clouds of smog and at the same time also decrease its GHG emissions. The environmental benefits of natural gas as opposed to coal should not be exaggerated though. Thomas Sterner pointed out that methane, the main compound of natural gas, is a considerably more potent GHG than CO2. A total leakage of an estimated 1% negates the environmental benefits, he said.
Karl Hallding, Senior Research Fellow at SEI, particularly stressed the need to look at China. It is the supplier of half of the world’s coal, extraction levels remain high. (BP, 2017) Domestic consumption is decreasing but consumption of Chinese coal is, however, more likely to shift geographic location rather than to be left in the ground, said Hallding. Through massive infrastructure investments, such as the New Silk Road, and in energy production in Sub-Saharan Africa, China spreads its influence (IEA, 2016). By exporting emissions, the impact at the global level will not change.
References
- Allmendinger, Waldron, 2007. “Global Climate Change” http://www.geo.cornell.edu/eas/energy/the_challenges/global_climate_change.html (2017-10-27)
- BP, 2017. “BP Statistical Review of World Energy June 2017”, http://www.bp.com/statisticalreview, (2017-10-26).
- Dizard John, 2017. “Batteries are not atom bombs, integerated circuits or penicillin”, July.
- Economist, 2014. “Sheiks v shale”, Leader in the Economist, 2014-12-04. https://www.economist.com/news/leaders/21635472-economics-oil-have-changed-some-businesses-will-go-bust-market-will-be (2017-10-27).
- Energy Information Administration. 2016. “Shale gas and tight oil plays production in the U.S. from 1999 to 2015”. Statista. https://www.statista.com/statistics/183740/shale-gas-production-in-the-united-states-since-1999/, (2017-10-27).
- EU Commission, “Supplier countries” https://ec.europa.eu/energy/en/topics/imports-and-secure-supplies/supplier-countries, (2017-10-27)
- EU Commission, 2011. Energy Roadmap 2050,
- Frankfurt School-UNEP Centre/BNEF, 2017. “Global Trends in Renewable Energy Investment 2017” https://europa.eu/capacity4dev/unep/documents/global-trends-renewable-energy-investment-2017, (2017-10-27).
- GWEC, 2016. “Global Wind Report”, http://gwec.net/global-figures/graphs/, (2017-10-27).
- IEA, 2017a. “2016 Snapshot of Global Photovoltaic Markets”, Report IEA PVPS T1-31:2017, http://www.iea-pvps.org/fileadmin/dam/public/report/statistics/IEA-PVPS_-_A_Snapshot_of_Global_PV_-_1992-2016__1_.pdf, (2017-20-27)
- IEA, 2017b. “Key World Energy Statistics” http://www.iea.org/publications/freepublications/publication/KeyWorld2017.pdf, (2017-10-26)
- IEA, 2016. “Boosting the Power Sector in Sub-Saharan Africa –China’sinvolvement”, http://www.iea.org/publications/freepublications/publication/partner-country-series—boosting-the-power-sector-in-sub-saharan-africa—chinas-involvement.html, (2017-10-26).
- IPCC, 2013. “Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change” (Technical Summary) https://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_TS_FINAL.pdf (2017-10-27)
- Kan, Haidong, 2011. “Climate Change and Human Health in China”, Environmental Health Perspectives, 119(2), A60-A61.
- Kjellström, Tord, 2016. “Impact of Climate Conditions on Occupational Health and Related Economic Losses: A New Feature of Global and Urban Health in the Context of Climate Change”, Asia Pacific Journal of Public Health, 28(2S), 28S-37S.
- NASA, 2017. “Scientific consensus: Earth’s climate is warming”, https://climate.nasa.gov/scientific-consensus/, (2017-10-27).
- NIC, 2016. “Implications for US National Security of Anticipated Climate Change”, NIC WP 2016-01 https://www.dni.gov/files/documents/Newsroom/Reports%20and%20Pubs/Implications_for_US_National_Security_of_Anticipated_Climate_Change.pdf, (2017-10-27).
- Timmons, David; Harris, Jonathan M.; and Broch, Brian, 2014 “The Economics of Renewable Energy”, Global Development and Environment Institute, Tufts University, http://www.ase.tufts.edu/gdae/education_materials/modules/RenewableEnergyEcon.pdf, (2017-10-27).
Ethnic Networks in Ex-USSR
Do ethnic networks facilitate international trade when formal institutions are weak? Using data collected by ethnologists on the share of ethnic groups across countries, this study assesses the effect of ethnic networks on bilateral trade across the sphere of the former Soviet Union. This region provides a perfect setting to test for this effect as both forced re-settlement of entire ethnic groups during the Stalin era and artificially drawn borders in Central Asia led to an exogenous ethnic composition within countries. While ethnic networks do not seem to have played a role in inter-republic trade during the Soviet Union, they did facilitate trade in the years following the collapse of the Soviet Union, a transitional period when formal institutions were weak. This effect, however, eroded steadily from the early 2000s.
Economists and historians alike study the role of ethnic networks in international trade. Some prominent examples are the Greek commercial diaspora of the Black Sea in the 19th century (Loannides and Minoglou, 2005), the Maghribi traders in 11th-century North Africa (Greif, 1993), or the overseas Chinese all around the world in the last decades (Rauch and Trindade, 2002). Such networks facilitate trade by building trust relationships, enforcing contractual agreements in weak legal environments, matching buyers with faraway sellers that speak different languages, and by exchanging information on arbitrage opportunities.
In “Ethnic Minorities and Trade: The Soviet Union as a Natural Experiment”, forthcoming in The World Economy, we study the Soviet Union (USSR) to assess the role of ethnic networks in international trade. We argue that ex-USSR countries are particularly well suited for such a study. Indeed, the ethnic diversity of ex-USSR countries is exogenous, partly due to the creation of artificial borders cutting through ethnic homelands, and partly due to forced relocations (deportations) during the Stalin era, which brought ethnic groups to various remote regions of the USSR. This exogeneity adds power to our empirical strategy.
Ethnic Networks in the USSR
We first build a measure of ethnic networks based on the size of common ethnic groups using ethnologists’ data from the Ethnic Power Relations Dataset on the resulting ethnic groups across ex-USSR countries (Vogt et al., 2015; Bormann et al., Forthcoming). It covers all ethnic groups in every country of the world from 1946 to 2013. While there is some yearly variation in the data, we focus on the cross-section average for the pre-1991 period as per our identification strategy based on exogenous distributions.
Figure 1 gives an overview of the spatial distribution of ethnic groups, such as Russian, Kazakh, or Uzbek.
Figure 1. Ethnic Groups in the USSR
Source: Authors’ own ArcGIS mapping based on the EPR-ED dataset.
Russians are ubiquitous across the Soviet sphere. Countries with the largest ethnic Russian populations are Kazakhstan, Estonia, Latvia and Moldova. At the same time, Russia is very diverse. Almost all of the 60 ex-USSR ethnic groups are present in Russia, and ethnic Russians account for only 62% of the population. Most countries are ethnically diverse. Kazakhstan for example is home to Russians as well as Germans, Tatars, Ukrainians, Uzbeks and Uighurs.
From the information on ethnic populations within each country, we create an ethnic network index as the sum of products of common ethnic groups as a share of the country’s population. Figure 2 presents a matrix overview of the ethnic network index among country pairs with darker shades corresponding to higher scores. Some high scoring country pairs are Russia—Kazakhstan, Ukraine—Russia, Uzbekistan—Tajikistan, Kyrgyzstan—Uzbekistan, Latvia—Kazakhstan, and Ukraine—Kazakhstan.
Figure 2. Ethnic Networks Index
Source: Authors’ estimates. The index is the sum of products of common ethnicities as a share of the country’s population.
Effect of Ethnic Networks on Bilateral Trade in the USSR
Next, we evaluate the impact of ethnic networks on aggregate trade between the countries of the former Soviet sphere. We use trade data from two sources. First, the data on internal trade between Soviet republics from 1987 to 1991 are from the input-output tables of each Soviet Union republic as compiled by the World Bank mission to the Commonwealth of Independent States (Belkindas and Ivanova, 1995). Second, the Post-1991 to 2009 trade data are from the Correlates of War Project (Barbieri et al., 2009, 2016), which offers the best coverage of the trade in the region.
We follow the migrant network and trade literature and estimate a standard log-linear gravity equation controlling for importer-year and exporter-year fixed effects (Anderson and van Wincoop, 2003).
Figure 3 presents the results on the effect of ethnic networks on trade over time. We observe that there is no effect in the period before the end of the USSR, a positive effect after the breakup of the Soviet Union, and an erosion of this effect from 2000s on (omitting Russia from the sample does not alter the results).
These results can be explained with the fact that in the Soviet Union ethnic ties did not matter as official production and trade were centrally planned by the State Planning Committee, Gosplan, and by State Supplies of the USSR, or Gossnab, which was in charge of allocating producer goods to enterprises. Free trade was forbidden. However, once the Soviet system collapsed and before countries could establish more formal trade ties, the first reaction and fallback option for many people was to reach out to their co-ethnics (in the 1990s) to substitute for the broken chains of the centrally planned trade (Gokmen, 2017). The other reason is that the institutional framework was at its weakest in this transitional period, and hence, reliance on informal institutions such as ethnic networks may have been especially strong (Greif, 1993). Once systematic and formal trade ties could be established, more and more traders no longer had to rely on their ethnic networks and this could explain the decline in the effect in the 2000s.
Figure 3. The Effect of Ethnic Networks on Trade over Time
Source: Authors’ estimates. Estimate of the effect of ethnic networks on bilateral trade in a gravity model controlling for distance, contiguity, and importer and exporter fixed effects.
Conclusion
This study shows that ethnic minorities played a role in shaping trade patterns across ex-USSR countries, but only in the early years following the collapse of the Soviet Union. Thus, we argue that reliance on informal institutions, such as ethnic networks, in forming trade relations is especially strong when the institutional framework is at its weakest in the transition period. This message may hold, not only for transition countries, but also for other developing countries with poor institutions.
References
- Anderson, J. E. and E. van Wincoop, 2003. “Gravity with Gravitas: A Solution to the Border Puzzle,” American Economic Review, 93, 170-192.
- Barbieri, K., M. G. Omar, and O. Keshk, 2016. “Correlates of War Project Trade Data Set Codebook, Version 4.0.”
- Barbieri, K., M. G. Omar, O. Keshk, and B. Pollins, 2009. “TRADING DATA: Evaluating our Assumptions and Coding Rules,” Conflict Management and Peace Science, 26, 471-491.
- Belkindas, M. and O. Ivanova, 1995. “Foreign Trade Statistics in the USSR and Successor States,” Tech. rep., The World Bank, Washington, DC.
- Bormann, N. C., L. E. Cederman, and M. Vogt, Forthcoming. “Language, Religion, and Ethnic Civil War,” Journal of Conflict Resolution.
- Gokmen, G., 2017. “Clash of civilizations and the impact of cultural differences on trade,” Journal of Development Economics, 127, 449-458.
- Gokmen, Gunes; Elena Nickishina; and Pierre-Louis Vezina, forthcoming. “Ethnic Minorities and Trade: The Soviet Union as a Natural Experiment”, The World Economy.
- Greif, A., 1993. “Contract enforceability and economic institutions in early trade: The Maghribi traders’ coalition”, The American Economic Review, 525-548.
- Loannides, S.; and I. P. Minoglou, 2005. “Diaspora Entrepreneurship between History and Theory”, London: Palgrave Macmillan UK, 163-189.
- Rauch, J. E. and V. Trindade, 2002. “Ethnic Chinese networks in international trade”, Review of Economics and Statistics, 84, 116-130.
- Vogt, M., N. C. Bormann, S. Regger, L. E. Cederman, P. Hunziker, and L. Girardin, 2015. “Integrating Data on Ethnicity, Geography, and Conflict: The Ethnic Power Relations Dataset Family,” Journal of Conflict Resolution, 1327-1342.
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.
“New Goods” Trade in the Baltics
We analyze the role of the new goods margin—those goods that initially account for very small volumes of trade—in the Baltic states’ trade growth during the 1995-2008 period. We find that, on average, the basket of goods that in 1995 accounted for 10% of total Baltic exports and imports to their main trade partners, represented nearly 50% and 25% of total exports and imports in 2008, respectively. Moreover, we find that the share of Baltic new-goods exports outpaced that of other transition economies of Central and Eastern Europe. As the International Trade literature has recently shown, these increases in newly-traded goods could in turn have significant implications in terms of welfare and productivity gains within the Baltic economies.
New EU members, new trade opportunities
The Eastern enlargements of the European Union (EU) that have taken place since 2004 included the liberalization of trade as one of their main pillars and consequently provided new opportunities for the expansion of trade among the new and old members. Growth in trade following trade liberalization episodes such as the ones contemplated in the recent EU expansions could occur because of two reasons. First, because countries export and import more of the goods that they had already been trading. Alternatively, trade liberalization could promote the exchange of goods that had previously not been traded. The latter alternative is usually referred to as increases in the extensive margin of trade, or the new goods margin.
The new goods margin has been receiving a considerable amount of attention in the International Trade literature. For example, Broda and Weinstein (2006) estimate the value to American consumers derived from the growth in the variety of import products between 1972 and 2001 to be as large as 2.6% of GDP, while Chen and Hong (2012) find a figure of 4.9% of GDP for the Chinese case between 1997 and 2008. Similarly, Feenstra and Kee (2008) find that, in a sample of 44 countries, the total increase in export variety is associated with an average 3.3% productivity gain per year for exporters over the 1980–2000 period. This suggests that the new goods margin has significant implications in terms of both welfare and productivity.
In a forthcoming article (Cho and Díaz, in press) we study the patterns of the new goods margin for the three Baltic states: Estonia, Latvia and Lithuania. We investigate whether the period of rapid trade expansion experienced by these countries after gaining independence in 1991—average exports grew by more than 700% between 1995 and 2008 in nominal terms, and average imports by more than 800%—also coincided with increases in newly-traded goods by quantifying the relative importance of the new goods margin between 1995 and 2008. This policy brief summarizes our results.
Why focus on the Baltics?
The Baltic economies present an interesting case for a series of reasons. First, along a number of dimensions, the Baltic countries stood out as leaders among the formerly centrally-planned economies in implementing market- and trade-liberalization reforms. Indeed, those are the kind of structural changes that Kehoe and Ruhl (2013) identify as the main drivers of extensive margin increases. Second, unlike other transition economies, as part of the Soviet Union the Baltics lacked any degree of autonomy. Thus, upon independence, they faced a vast array of challenges, among them the difficult task of establishing trade relationships with the rest of the world, which prior to 1991 were determined solely from Moscow. Lastly, as former Soviet republics, the Baltic states had sizable portions of ethnic Russian-speaking population, most of which remained in the Baltics even after their independence. At least in principle, this gave the Baltic economies a unique potential to better tap into the Russian market.
Defining “new goods”
We use bilateral merchandise trade data for Estonia, Latvia and Lithuania starting in 1995 and ending in 2008, the year before the Global Financial Crisis (GFC). The data are taken from the World Bank’s World Integrated Trade Solution database. The trade data are disaggregated at the 5-digit level of the SITC Revision 2 code, which implies that our analysis deals with 1,836 different goods.
To construct a measure of the new goods margin, we follow the methodology laid out in Kehoe and Ruhl (2013). First, for each good we compute the average export and import value during the first three years in the sample (in our case, 1995 to 1997), to avoid any distortions that could arise from our choice of the initial year. Next, goods are sorted in ascending order according to the three-year average. Finally, the cumulative value of the ranked goods is grouped into 10 brackets, each containing 10% of total trade. The basket of goods in the bottom decile is labeled as the “new” goods or “least-traded” goods, since it contains goods that initially recorded zero trade, as well as goods that were traded in positive—but low—volumes. We then trace the evolution of the trade value of the goods in the bottom decile, which represents the growth of trade in least-traded goods.
Findings
For ease of exposition, we present the results for the average Baltic exports and imports of least-traded goods, rather than the trade flows for each country. Results for each individual country can be found in Cho and Díaz (in press). We report the least-traded exports and imports to and from the Baltics’ main trade partners: the EU15, composed of the 15-country bloc that constituted the EU prior to the 2004 expansion; Germany, which within the EU15 stands out as the main trade partner of Latvia and Lithuania; the “Nordics”, a group that combines Finland and Sweden, Estonia’s largest trade partners; and Russia, because of its historical ties with the Baltic states and its relative importance in their total trade.
Least-traded exports
Figure 1 shows the evolution over time of the share in total exports of the goods that were initially labeled as “new goods”, i.e., those products that accounted for 10% of total trade in 1995. We find that the Baltic states were able to increase their least-traded exports significantly, and by 2008 such exports accounted for nearly 40% of total exports to the EU15, and close to 53%, 49% and 49% of total exports to Germany, the Nordic countries, and Russia, respectively. Moreover, we find that the fastest growth in least-traded exports to the EU15 and its individual members coincided with the periods when the Association Agreements and accession to the EU took place. Finally, we discover that the rapid increase in least-traded exports to the EU15 during the late 1990s and early 2000s is accompanied by a stagnation of least-traded exports to Russia. This suggest that, as the Baltics received preferential treatment from the EU, they expanded their export variety mix in that market at the expense of the Russian. Growth in least-traded exports to Russia only resumed in the mid 2000s, when the Baltics became EU members and were granted the same preferential treatment in the Russian market that the other EU members enjoyed.
Figure 1. Baltic least-traded exports
Source: Cho and Díaz (in press).
Least-traded imports
Figure 2 plots the evolution of Baltic least-traded imports between 1995 and 2008. We find that new goods imports also grew at robust rates, but their growth is about half the magnitude of the growth in the least-traded exports—the least-traded imports nearly doubled their share, whereas the least-traded exports quadrupled it. The least-traded imports from the EU15 and its individual members exhibited consistent growth throughout. On the other hand, imports of new goods from Russia—which had also been growing since 1995—started a continuous decline starting in 2003. This change in patterns can be attributed to the Baltics joining the EU customs union. Prior to their EU accession, the average Baltic tariff was in general low. Upon EU accession, the Baltics adopted the EU’s Commercial Common Policy, which removed trade restrictions for EU goods flowing into the Baltics, but—from the perspective of the Baltic countries—raised tariffs on non-EU imports, in turn discouraging the imports of Russian new goods.
Figure 2. Baltic least-traded imports
Source: Cho and Díaz (in press).
Are the Baltics different?
Figure 1 shows that the Baltic states were able to increase their least-traded exports by a significant margin. A natural question follows: Is this a feature that is unique of the Baltic economies, or is it instead a generalized trend among the transition countries?
Table 1: Growth of the share of least-traded exports (percent, annual average)
Source: Cho and Díaz (in press).
Table 1 reveals that the new goods margin played a much larger role for the Baltic states than for other transition economies such as the Czech Republic, Hungary and Poland (which we label as “Non-Baltics”), for all the export destinations we consider. Moreover, we find that while until 2004—the year of the EU accession—both Baltic and Non-Baltic countries displayed high and comparable growth rates of least-traded exports, this trend changed after 2004. Indeed, while there is no noticeable slowdown in the Baltic growth rate, after 2004 the Non-Baltic growth of least-traded exports to the world and to the EU15 all but stops, with the only exception being the Nordic destinations.
Conclusion
The Baltic states, and in particular Estonia, are usually portrayed as exemplary models of trade liberalization among the transition economies. Our results indicate that the Baltics substantially increased both their imports and exports of least-traded goods between 1995 and 2008. Since increases in the import variety mix have been shown to entail non-negligible welfare effects, we expect large welfare gains for the Baltic consumers experienced due to the increases in the imports of previously least-traded goods. Moreover, the literature has documented that increases in export variety are associated with increases in labor productivity. Our findings reveal that the Baltics’ increases in their exports of least-traded goods were even larger than their imports of new goods, thus underscoring the importance of the new goods margin because of their contribution to labor productivity gains.
References
- Broda, Christian; and David E. Weinstein, 2006. “Globalization and the gains from variety,” Quarterly Journal of Economics, Vol. 121 (2), pp. 541–585.
- Chen, Bo; and Ma Hong, 2012. “Import variety and welfare gain in China,” Review of International Economics, Vol. 20 (4), pp. 807–820.
- Cho, Sang-Wook (Stanley); and Julián P. Díaz. “The new goods margin in new markets,” Journal of Comparative Economics, in press.
- Feenstra, Robert C.; and Hiau Looi Kee, 2008. “Export variety and country productivity: estimating the monopolistic competition model with endogenous productivity,” Journal of International Economics, Vol. 74 (2), pp. 500–518.
- Kehoe, Timothy J.; and Kim J. Ruhl, 2013. “How important is the new goods margin in international trade?” Journal of Political Economy, Vol. 121 (2), pp. 358–392.