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Individual Retirement Timing in Russia: Implications for Pension Age

Posted on January 15, 2018 | Policy Brief

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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

Posted on December 18, 2017 | Policy Brief

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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

Highlights for Commemoration of the 1917 Russian Revolution – Hints for Further Study

Posted on December 11, 2017 | Policy Brief

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Professional historians in general have an ambivalent attitude towards anniversaries and commemorations of historical events, be they epochal or not. On the one hand, centennials and similar memorials may alleviate the funding of one’s research projects as the authorities likewise wish to highlight certain events. On the other hand, jubilee years can tend to divert historians from their ordinary research directions. Not for nothing would even frank scholars from Oxford, England complain in 2014 of the “tyranny of celebrations” and wish that nothing comparative to the centennial of the Great War 1914-1918 would appear soon.

In Russia, similar attitudes seem not to have appeared with respect to the centennial of the 1917 revolutions, the February and October revolution as traditionally called. In my April 2017 policy brief, I noted how universities all over Russia organized conferences devoted to various aspects of 1917. Many more publications have appeared as well as translations or new editions of classical works. Here I only hint at some accomplishments that may deserve to be studied for anyone who is genuinely interested in the historical debates in Russia.

This autumn, the leading institutes of the Academy of Sciences, the Institute for General History (IVI RAN) and the Institute for Russian History (IRI RAN) held their grand events with participation of leading scholars from the West, inter alia Hélène Carrère-d’Encausse and Alexander Rabinovich, to mention only a few. The IRI RAN presented its two-volume “The Russian revolution in 1917: The Power, Society, Culture” with the same emphasis as the main theme of the conference, i.e. how the historiography of the February and October revolution changed over time (see http://iriran.ru/?q=node/1699).

Western mass media and Russia observers in particular have during 2017, in my view, one-sidedly focused on how Kremlin would, or not, ‘celebrate’, ‘commemorate’, or even ‘want to forget’ the epochal events in Russia one hundred years ago. In contrast to other anniversaries, the 200th of Napoleon’s war on Russia or the 100th of the First World War, the highest political spheres have, as it seems for good reasons, left the information sphere quite free for the professional historians, film and TV producers, and others to commemorate at their own behest the 1917 revolution.

One important source of information about the commemoration of the 1917 Russian Revolution is the book published by AIRO-XXI, Association for the Study of Russian History in the 21th Century, led by the renowned historiographer Gennadyi Bordiugov. Just as for the anniversaries of the Victory in World War Two (in 2005 and 2015), Bordiugov and his colleagues in AIRO-XXI started a huge monitoring project in late 2016 in order to follow how various groups and centres all over Russia, as well as in major Western countries, were to commemorate the 1917 Russian revolution. The monitoring is by now complete and the result is the mighty book “Revolution-100. A Reconstruction of the Jubilee” (http://www.airo-xxi.ru/-2017-/2395–100-). This will for a long time serve as the best introduction to how Russia – in the broadest terms – comes to grips with the jubilee. The first articles give the background – how the October revolution was celebrated in the Soviet era and the major changes in the post-1991 Russia. Several contributions give the present-day context – how parallels are drawn between contemporary events in Russia and abroad, on the one hand, and the Russian revolution, on the other hand. The virtual sphere today, the Internet and blogosphere take up a much more important space for the younger generation than books and encyclopaedias; therefore the monitoring project also includes surveys of which aspects of the revolution are treated therein.

In contrast to what originally was set as leitmotiv for the commemoration – a reconciliation among groups and personalities with divided approaches to the Bolshevik takeover in particular and the Soviet experiment in general, most publications, exhibitions and meetings that the AIRO-XXI have monitored show that the epochal historical cataclysms one hundred years ago still are as divisive as before. The great contrast is that disputes are formalized and fact-based, that arguments from any side are given due consideration, and that most accept the device that “there is no final truth in history, merely arguments without end”.

The AIRO-XXI monitoring also treats the cinema, television and Internet series that were shown in connection with the jubilee. Much media interest was connected with the protests from the Orthodox Church against the film “Matilda” as it allegedly defamed the last tsar Nikolai II for showing his love affair in the 1890s with a prima ballerina. The artistic freedom finally triumphed and the debates only slightly influenced the mass of cinemagoers. We can also note that Russian television channels have sent pedagogical and dramatic series on some of the major figures of the revolution. One on the mythical Aleksandr Parvus (Helphand) with his views on revolutionizing Russia during the war, even with the help of the German General Staff; the other on Leo Trotskii as people’s commissar of war from 1918. These series and many others are vividly described in the AIRO-XXI volume by the philologist Boris Sokolov, who clearly presents where historical facts might have been twisted for the sake of art.

Mention should finally be made, for those who wish to follow how Russia’s leading professional historians analyse the revolution, that many lectures given at universities during 2017 are available at YouTube. Suffice it here to mention Vladimir Buldakov (for his books, see my previous policy brief), who since the 1980s researched the Russian revolutions and presented his main theses in “Krasnaya Smuta” (Red Troubled times). In 2017, he has lectured on this theme for various audiences (compare https://www.youtube.com/watch?v=SG9T3H55Hrk;https://www.youtube.com/watch?v=JnRXgCqGBrg; https://www.youtube.com/watch?v=9UPYYBnYow8)

To appreciate how an academic discussion on the ‘Great Russian Revolution ‘ – as many scholars today prefer to treat the events in 1917 – at its best can deepen our understanding, it is well worth pondering the arguments by renowned historians Aleksandr Shubin, Aleksandr Vatlin, Tatiana Nekrasova, Gennadii Bordiugov and Vladimir Pantin in the Kultura Channel program series “Chto delat?” (What is to be done) (https://www.youtube.com/watch?v=KQF0o8adIDw). Although each of the specialists had their own interpretations and various approaches, the mentor Vitalii Tretiakov, well-known journalist and formerly chief-editor of “Nezavisimaya Gazeta, managed to step-by-step highlight the issues that have divided historians in the past, as well as such matters that will call for renewed research.

In early 2017, some hoped that commemorative arrangements on the 1917 revolution would lead towards reconciliation between those opposing groups who still reason and argue as one or the other political parties of that era, between those who sympathized with the socialists in general and/or the Bolsheviks in particular, on the one hand, and those who ideologically has more affinity with the Liberal, Conservative or Monarchist groups, on the other hand. While such reconciliation is not yet in sight, the many articles in mass media, museum exhibitions and TV series have definitely heightened the older generations’ understanding of the very complex, intricate nature of the political, social and military forces that first led to the dissolution of tsarism, their fact-based knowledge of the tentative to establish a full democratic country even in the framework of the world war, and finally to a better grasp – than the standard Soviet orthodox narratives – of why and how the seemingly minuscular Bolshevik party could successfully grasp power in November 1917 and in the end also triumph in the devastating civil war.

It goes without saying that for school teachers all over Russia, the commemorative arrangements have provided a golden opportunity to engage their pupils and students in various forms of so-called living history, i.e. combining the state’s grand story with the localities’ and the families’ own histories.

Paid Work after Retirement – Does Quality of Your Main Job in the Past Matter?

Posted on December 4, 2017 | Policy Brief

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In this brief, we summarize the results of a recent analysis focused on identifying the key determinants of engagement in paid work after retirement based on life histories data from the Survey of Health, Ageing and Retirement in Europe (SHARE). We find a strong link between the probability of work after retirement and indicators of quality of work prior to labor market exit, such as high physical and psychosocial demands, lack of control or receiving adequate social support. These results suggest a potentially important role of job-quality regulations. We find no significant association with past experience of adequate rewards with respect to efforts in the main job, which suggests that involvement in paid work after retirement may to a lesser extent be driven by financial concerns. This might mean that policy initiatives targeted at higher level of labor market activity among retirees should stress non-material aspects of employment in later life.

The collection of data in the 7th wave of the Survey of Health, Ageing and Retirement in Europe (SHARE) proceeded in 2017, and the Centre for Economic Analysis (CenEA) has recently published a report based on information collected in previous waves of the survey. The report entitled “The Polish 50+ generation in the European context: activity, health and wellbeing” examined among other issues the determinants of labor market activity of people aged 50+ with a special focus on Poland (Myck and Oczkowska, 2017).

SHARE is a panel survey conducted every two years and focuses on health conditions, material situation and social relations of the population aged 50 years and older. In 2017, in the 7th Wave, interviews were conducted with over 80,000 participants in 26 European countries and Israel. While the survey usually focuses on contemporary conditions of respondents, the interviews in Wave 3 (the SHARE-Life conducted in 2008-2009) is concerned with respondents’ life histories and topics such as family history, mobility and work histories.

In this brief, we draw on one of the chapters from the report and present results of a analysis that combines information on the quality of the main job of the respondents’ working careers, with information on engagement in paid work among retired individuals to examine key determinants of undertaking paid work after labor market exit.

Work histories in SHARE

The life-history interview includes a series of 12 questions evaluating effort-reward imbalance in the main job of individuals’ working careers (Siegrist and Wahrendorf, 2011; Siegrist et al., 2004; 2014). Based on these questions, five dimensions of the quality of the workplace were identified: physical and psychosocial demands, control, social support and reward (see Table 1). Figure 1 presents an example of the distribution of answers to one of the questions used to define these dimensions, which asked about the extent to which the respondents’ main jobs was physically demanding. Generally, men’s past main job is more often described as physically demanding than women’s. While less than half of respondents in France and Sweden claimed physically strenuous main job, the respective measure in Poland and Greece was as high as 75%.

Table 1. Dimensions of job quality

Dimension SHARE Questionnaire Items
Physical demands

– „My job was physically demanding.”

– „My immediate work environment was uncomfortable (for example, because of noise, heat, crowding).”
Psychosocial demands – „My work was emotionally demanding.”

– „I was exposed to recurrent conflicts and disturbances.”
Control – „I was under constant time pressure due to a heavy workload.”

– „I had very little freedom to decide how to do my work.”
Social support at work – „I received adequate support in difficult situations.”

– „There was a good atmosphere between me and my colleagues.”

– „In general, employees were treated fairly.”
Reward

– „I had an opportunity to develop new skills.”

– „I received the recognition I deserved for my work.”

– „Considering all my efforts and achievements, my salary was adequate.”

Notes: answer categories: “strongly agree, agree, disagree, strongly disagree”. Source: adapted from Siegrist and Wahrendorf (2011).

Figure 1. “My job was physically demanding”

Notes: includes wave 3 respondents with at least 10 years of seniority who retired by the time of wave 6; weighted. Source: own calculation based on SHARE data waves 3 (2008-2009) and 6 (2015).

Following Wahrendorf and Siegrist (2011), for the purpose of further analysis, we construct five measures of workplace quality based on the questions listed in Table 1. For each dimension of job quality, we calculate a sum-score of answers (from 1 “strongly agree” through 2 “agree”, 3 “disagree” to 4 “strongly disagree”) to selected questions, and identify the upper (lower) tertile of observations. We create five binary indicators (with 1 meaning “yes”) describing the quality of work in the sense of high physical or psychosocial demands, lack of control, and adequate social support or adequate reward. The results are presented in Figure 2 in association with the frequency of paid work after retirement.

Figure 2. Associations between quality of work in the past and frequency of paid work after retirement

Notes: includes wave 3 respondents with at least 10 years of seniority who retired by the time of wave 6 from selected countries (CZ, FR, DE, GR, PL, ES, SE); weighted. Source: own calculation based on SHARE data waves 3 (2008-2009) and 6 (2015).

In most cases the percentage of retirees engaged in paid work was significantly higher among those positively evaluating the quality of their past workplace. The only dimension where no significant difference was found in the level of involvement in paid work was between the retirees who estimated rewards at work as adequate to their efforts and those who assessed them otherwise.

What determines paid work after retirement?

The role of the five measures of job quality was further examined using models of probability of paid work after retirement. Apart from quality indicators regarding the main job, controls included total labor market experience, unemployment incidence, as well as detailed demographics and information concerning current health status and material conditions. Odds ratios were estimated separately for men and women from a group of selected countries: Czech Republic, France, Germany, Greece, Poland, Spain and Sweden.

Higher education is positively associated with the odds of employment after retirement, but have the opposite effect for age, poor health and living in rural areas. Each additional year of labor market experience increases the odds of working after retirement, but we find no significant effect of unemployment episodes.

Both men and women without experience of high physical demands and lack of control in their main job have higher odds of working after retirement than those who declared such experiences. For example, men who did not experience highly, physically demanding main jobs have 1.4 times higher odds of work after retirement compared to those who did. The respective odds for those who did not experience lack of control are 1.9. On the other hand, high psychosocial demands and adequate social support have significant influence only among retired women. Women who did not report high psychosocial demands had 1.25 times higher odds of work after retirement, while those who received adequate support in their past job had 1.5 times higher odds. We find no significant effect of the experience of adequate rewards with respect to efforts in the main job, and similarly no significant association between material conditions and employment of retirees. Both of these may imply that involvement in paid work after retirement is to a lesser extent driven by financial concerns.

Further discussion and policy implications

Differences in the degree of engagement in paid work after retirement with respect to the assessment of past job quality suggest a potentially important role of job quality regulations. At the same time, lack of significant association between the material situation and paid work after retirement implies that policy initiatives targeted at higher levels of labor market activity among retirees may benefit from stressing the non-material aspects of employment in later life.

Results point to a strong link between quality of work in the past and probability of work after retirement, which is in line with what other studies have showed: e.g. that low quality of work in the past strongly correlates with the desire to retire as soon as possible (e.g. Dal Bianco et al., 2014). Given the demographic pressure on public finances observed or expected in many developed countries, and foreseen reductions in the generosity of pension benefits, increasing the level of engagement in paid work after labor market exit may become an important policy challenge. The results summarized in this brief suggest that governments should, on the one hand, pay attention to the labor market conditions faced by those currently employed, and on the other hand focus on a broad set of incentives to encourage employment among older generations, going beyond financial remuneration.

References

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The Determinants of Renewables Investment

Posted on November 13, 2017 | Policy Brief

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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

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Ethnic Networks in Ex-USSR

Posted on November 6, 2017 | Policy Brief

20171106 Ethnic Networks in Ex-USSR Image 01

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.

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Rewarding Whistleblowers to Fight Corruption?

Posted on October 23, 2017 | Policy Brief

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Whistleblower reward programs, or “bounty regimes”, provide financial incentives to witnesses that report information on infringements, helping law enforcement agencies to detect/convict culprits. These programs have been successfully used in the US against procurement fraud and tax evasion for quite some time, and were extended to fight financial fraud after the recent crisis. In Europe there is currently a debate on their possible introduction, but authorities appear much less enthusiastic than their US counterparts. In this brief, we discuss recent research on two commonly voiced concerns on whistleblower rewards – the risk of increasing false accusations, and that of crowding out other motivations to blow the whistle – and the adaptations these programs may need to fight more general forms of corruption. Research suggests that the mentioned concerns can be handled by an appropriate design and management of the programs, as apparently done in the US, and that these programs can indeed be a cost effective instrument to fight corruption, but only in countries with a sufficient quality of the judicial system and administrative capacity. They may instead be problematic for weak institutions environments.

Corruption and fraud seem to remain highly widespread in almost all countries. For example, a recent survey of over 6,000 organizations across 115 countries shows that one in three organizations, both worldwide and in the US, experienced fraud in the past 24 months, prevalently in the form of asset misappropriation, cybercrime, corruption, and procurement and accounting fraud (Global Crime Survey, 2016).

Whistleblower (protection and) reward programs are a possibly effective tool to combat fraud and corruption, at least in the light of the US successful experience, where for a long time whistleblowers reporting large federal fraud have been entitled to up to 30% of recovered funds and sanctions under the False Claims Act. The US Internal Revenue Service (IRS) also allows whistleblower rewards in the tax area, and the Dodd-Frank Act introduced them for financial and securities fraud, apparently also with success (c.f. Call et al., 2017, and Wilde, 2017).

In Europe and the rest of the world, instead, rewards are absent and whistleblowers are still poorly protected from retaliation from employers. Some countries have taken encouraging legal steps to at least improve protection, and a discussion is ongoing at the G20 level on how to further improve the situation (G20 report, 2011).

Although many praise whistleblowers, there has been a large range of objections raised against introducing rewards (and even against improving whistleblower protection); mostly by corporate lawyers and lobbyists, but also by regulatory and law enforcement agencies (see Nyreröd and Spagnolo, 2017, for an overview).

In the rest of this brief, we focus on two often voiced concerns, the risks of eliciting false/fraudulent reporting and of crowding out of non-financial motivation, on which recent research has shed light that should be taken into account in the current policy debate. We then discuss some problems linked to the use of whistleblower rewards programs in a more general corruption context.

Fraudulent reports

One concern commonly raised in the discussion of whistleblower rewards is that they may create incentives to fraudulently report false or fabricated information in the hope of receiving a reward. Although clearly an important concern to take into account, we only know of very few anecdotal cases of malicious or false reporting, and fraudulent reporting does not appear to have been a major problem in the US (see again Nyreröd and Spagnolo, 2017 for an overview of the empirical evidence).

A recent paper by Buccirossi, Immordino and Spagnolo (2017) analyzes this concern within a formal economic model and shows that it is not a ground (or an excuse) for not introducing appropriately designed and managed protection and reward programs in countries with sufficiently effective court systems. In these countries, stronger sanctions against lying to the court can (and should) be introduced to balance the incentives for manipulation that may be generated by large bounties. Most legal systems already have defamation and perjury laws, which means that a whistleblower is already committing a crime by fraudulently reporting false information, that can easily be strengthened where necessary without giving up whistleblower rewards. According to this study, the balancing of incentives is what allows the US to effectively use large financial incentives for whistleblowers, besides a very strong protection from retaliation, with little problems in terms of fraudulent reports.

However, the study also shows that this is only possible if the precision (effectiveness, independence) of the court system is sufficiently high. Where court systems are imprecise, the interaction between courts’ mistakes in the legal case based on the information reported by the whistleblower and in the following case for perjury/defamation against the whistleblower if the first case is dismissed, incentives for fraudulent reports, and courts’ adaptation of the standard of proof to account for these incentives, make it impossible to appropriately balance the two incentives. Therefore, whistleblower reward programs should not be introduced in environments where the law enforcement system is ineffective, independently from why it is so (bureaucratic slack, incompetence, political interference, corruption, etc.).

Crowding-out non-financial motivation

Another concern is that whistleblower rewards may have a “crowding out” effect on intrinsic motivation. The problem is that “the commodification of whistleblowing via the provision of bounties may render would-be whistleblowers less likely to come forward by reducing the moral valance of the wrongdoing” (Engstrom, 2016:11). Recent experimental evidence suggests that this concern is overstated. In particular, Schmolke and Utikal (2016) investigate the effects of whistleblower rewards in an environment where one subject may increase his payoff at the cost of harming the group, and find rewards to be highly effective in increasing the number of crimes reported. Data from that experiment suggests a little role for crowding out of non-monetary motivation, if any. Another recent study by Butler, Serra and Spagnolo (2017) investigates if and how monetary incentives, expectations of social approval or disapproval, and the salience of the harm caused by the reported illegal activity interact and affect the decision to blow the whistle. Experimental results show that financial rewards significantly increase the likelihood of whistleblowing and do not substantially crowd out non-monetary motivations activated by expectations of social judgment. The study also finds that public scrutiny and social judgment decrease (increase) whistleblowing when the public is less (more) aware (aware) of the negative externalities generated by the reported crime. All in all, most the recent studies we are aware of suggest that crowding-out of non- financial concerns is not a first-order problem for whistleblower reward schemes as long as there is a clear perception of the public harm linked to the illegal behavior reported by the whistleblower.

Whistleblower rewards and corruption

Although whistleblowing can occur in any sector, firm, or government, an area of particular interest is corruption. Corruption in public procurement is estimated to cost the EU 5.3 billion Euros annually. Hence, corruption deterrence through increased whistleblowing could save the EU significant resources annually (EC Report, 2017).

Contrary to fraud, corruption always takes at least two parties, a bribe taker, typically a government official or politician, and a bribe giver, which may be a firm or an individual. The fact that at least one additional party is involved than in the standard case of fraud, should make whistleblower rewards programs even more powerful since they may deter corruption by increasing the fear that a (potential or real) partner in crime may blow the whistle, even when no third party witness observes the illegal act (Spagnolo, 2004).

When the reported wrongdoer is an individual, as is often the case with corruption, there may be an issue in the use of rewards for whistleblowers linked to the funding of the rewards (c.f Nyreröd & Spagnolo, 2017b for an overview).

In the current US schemes, rewards for whistleblowers are ‘self-financing’, as they constitute a fraction of the funds recovered thanks to the whistleblower or/and of the fines paid by the culprits. An individual and a government official involved in a corrupt deal may, however, not be wealthy enough for the fines and the recovered funds to amount to a sufficiently strong incentive to blow the whistle, given the loss of future gains from the corrupt relationships and the various forms of retaliation whistleblowing may lead to. This problem is of course also relevant for fraud when an individual with few or well-hidden assets is the culprit, rather than a corporation, but it seems particularly relevant for corruption.

Whistleblower reward programs are also malleable to the concerns at hand. If the priority is to combat higher-level corruption, then setting a monetary threshold for when a claim is to be considered is appropriate to limit administrative costs for the program. Indeed, a concern with utilizing whistleblower rewards programs for combating lower-level corruption is that the administrative burden required looking through the whistleblower claims and the costs of limiting abuses may outweigh the benefits gained in detection and deterrence. This concern is also valid for small fraud and tax evasion, which is why all the US programs have a minimum size for cases eligible to whistleblower rewards, but the problem is likely to be more relevant to the case of ‘petty’ corruption. These programs are more suited for ‘large cases’ in which the amount of funds recovered is large enough to pay for rewards and administrative costs, making these programs self-financing even without calculating the benefits for the deterrence/prevention of future infringements. However, when focusing on large corruption cases, other issues become relevant.

An issue particularly important for the case of ‘grand’ corruption is how independent the judicial system is from political pressure, and how able it is to protect whistleblowers against politically mandated retaliation. If corrupt politicians can importantly influence courts, the police or other relevant administrative agencies, then protection can hardly be guaranteed and inducing witnesses to blow the whistle through financial incentives may put their life at risk, although sufficiently large rewards can partly compensate for this risk and help escaping part of the retaliation.

Conclusion

On the whole, whistleblower rewards, in general and in the corruption context specifically, remain a promising tool to detect and deter crime. Careful design and implementation are necessary, because as for any powerful tool, these programs can be well used to do great thing, but also misused to do great damage. As the US experience has shown, along with sufficiently independent and precise courts and an effective administration of law enforcement, well designed and administered whistleblower reward programs hold the promise of greatly improving fraud and corruption detection and of being self-financing through recovered funds and fines.

Of course, even in a very good institutional environment, a poor design and/or implementation can lead to poor performance and do more harm than good (c.f. the case of leniency policies in China discussed in Perrotta et al., 2017). Moreover, in poor institutional environments, where the court system is not sufficiently precise and independent and other law enforcement institutions are not effective, even well-designed and implemented whistleblower reward schemes may bring more problems than benefits. Whistleblower rewards, as any other high-powered incentives, need good governance to ensure that the potentially very high benefits they can generate will be realized. Third parties like international courts and organizations could potentially provide for some low institution environments, the independent safe harbor necessary to protect whistleblowers and a check on court effectiveness for the award of financial incentives.

References

  • Global Economic Crime Survey, 2016. Available at: https://www.pwc.com/gx/en/economic-crime-survey/pdf/GlobalEconomicCrimeSurvey2016.pdf
  • Buccirossi, P., Immordino, G., and Spagnolo, G., 2017. “Whistleblower Rewards, False Reports, and Corporate Fraud”. SITE Working Paper No. 42, available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2993776
  • European Commission Report, 2017. Estimating the Economic Benefits of Whistleblower Protection in Public Procurement, Milieu Ltd.
  • Engstrom, D., 2016. “Bounty Regimes”, in Research Handbook on Corporate Criminal Enforcement and Financial Misleading (Jennifer Arlen ed., Edward Elgar Press, forthcoming 2016)
  • Butler, J., Serra, D., and Spagnolo G., 2017. “Motivating Whistleblowers.” Unpublished manuscript.   Available at: https://www.aeaweb.org/conference/2017/preliminary/1658
  • Schmolke, K.U., Utikal, V., 2016. “Whistleblowing: Incentives and Situational Determinants.” FAU – Discussion Papers in Economics, No. 09/2016. 2016. Available at: https://ssrn.com/abstract=2820475
  • Call, A.C., Martin, G.S, Sharp, N.Y., Wilde, J.H., 2017. “Whistleblowers and Outcomes of Financial Misrepresentation Enforcement Actions.” Journal of Accounting Research, forthcoming.
  • Wilde, J.H., (2017). “The Deterrent Effect of Employee Whistleblowing on Firms’ Financial Misreporting and Tax Aggressiveness”, The Accounting Review, forthcoming.
  • Nyreröd, T. Spagnolo, G., 2017a “Myths and evidence on whistleblower rewards”, SITE Working Paper No.
  • Spagnolo, G., 2004. “Divide et Impera: Optimal Leniency Programs.” CEPR Discussion Papers 4840, 2004.
  • Nyreröd, T. Spagnolo, G. 2017b. “Whistleblower Rewards in the Fight against Corruption?” (in Portuguese), forthcoming in the book  Corrupção e seus múltiplos enfoques jurídi
  • Berlin-Perrotta, M., Qin, B. and Spagnolo, G., 2017. “Leniency, Asymmetric Punishment and Corruption: Evidence from China,” SITE Working Paper. Available at:https://ssrn.com/abstract=2718181 or http://dx.doi.org/10.2139/ssrn.2718181
  • G20 Anti-Corruption Action Plan, Protection OF Whistleblowers Study on Whistleblower Protection Frameworks, Compendium of Best Practices and Guiding Principles for Legislation, 2011. Available at: https://www.oecd.org/g20/topics/anti-corruption/48972967.pdf
  • Wolfe S., Worth M., Dreyfus S., Brown A.J., 2015. Breaking the Silence, Strengths and Weaknesses in G20 Whistleblower Protection Laws, 2015. Available at: https://blueprintforfreespeech.net/wp-content/uploads/2015/10/Breaking-the-Silence-Strengths-and-Weaknesses-in-G20-Whistleblower-Protection-Laws1.pdf

Latvia Stumbling Towards Progressive Income Taxation: Episode II

Posted on October 16, 2017 | Policy Brief

20171015 Latvia Stumbling Towards Progressive Income Taxation Image 01

In August 2017, the Latvian parliament adopted a major tax reform package that will come into force in January 2018. This reform was a long-awaited step from the Latvian authorities to make the personal income tax more progressive. Some of the elements of the adopted reform, e.g. the changes in the basic tax allowance are estimated to help reducing the tax wedge on low wages and help addressing the problem of high income inequality. At the same time, the way the newly introduced progressive tax rate is designed will effectively lead to a reduction in the tax burden on labor and will hardly introduce any progressivity to the system.

In recent years, reducing income inequality has become one of the top priorities of the Latvian government. Income inequality in Latvia is higher than in most other EU and OECD countries, and the need to address this issue has been repeatedly emphasized by the Latvian officials, the European Commission, the World Bank and OECD.

The main reason for high income-inequality is a low degree of income redistribution ensured by the tax-benefit system. The personal income tax (PIT) has been flat since the mid-nineties. While the non-taxable income allowance introduces some progressivity to the system, the Latvian tax system is characterized by a very high tax burden on low wages, compared to other EU and OECD countries.

Since the beginning of 2017, the government has worked on an extensive tax reform package that was passed in the parliament in August and will become effective as of January 2018.

Two years ago, we wrote about the tax reform of 2016. In this brief, we estimate the effect of the 2018 reform on the tax burden on labour and income inequality. We will only consider changes in direct taxes on personal income – the changes in enterprise income tax and excise tax are outside the scope of our analysis. Parts of our estimations are done using the tax-benefit microsimulation model EUROMOD (for more details about the EUROMOD modelling approach, see Sutherland and Figari, 2013) and EU-SILC 2015 data.

Tax reform 2018

We focus our analysis on four elements of the reform that are expected to affect income inequality and that are described below. In our simulations, however, we take into account all changes in the PIT rules.

First, the flat PIT rate of 23% will be replaced by a progressive rate with three brackets: 20% (applied to annual income not exceeding 20,000 EUR), 23% (for annual income above 20,000 EUR and below 55,000 EUR) and 31.4% (applied to income exceeding 55,000 EUR per year).

Second, the maximum possible PIT allowance will be increased and the structure of the PIT allowance will be made more progressive. Latvia has a differentiated allowance since 2016, which means that individuals with lower incomes are eligible for a higher tax allowance. Figure 1 shows the changes in the non-taxable allowance that will be introduced by the reform. Another important change is that the differentiated allowance will be applied to the taxable income in the course of the year. The current system foresees that, during a calendar year, all wages are taxed applying the lowest possible allowance (60 EUR per month in 2017), but workers eligible for a higher allowance have to claim the overpaid tax in the beginning of the next year.

Figure 1. Basic PIT allowance before (2017) and after (2018-2020) the reform, EUR

Source: compiled by the authors.

Third, the rate of social insurance contributions will be increased by 1 percentage point. Social insurance contributions are capped and the cap will be increased from 48,600 EUR per year to 55,000 EUR per year, i.e. to the same income threshold that divides the top PIT bracket.

Finally, the reform will modify the solidarity tax – a tax, which was introduced in Latvia in 2016 and which is paid by top income earners. When this tax was initially introduced, one of its objectives was to eliminate the regressivity from the tax system caused by the cap on social insurance contributions. Hence, the rate of the solidarity tax was set at the same level as the rate of social insurance contributions and was effectively replacing social insurance contributions above the cap. The reform foresees that part of the revenues from the solidarity tax (10.5 percentage points) will be used to finance the top PIT rate. This element of the reform implies that after January 2018 those falling into the top PIT bracket will, in fact, not face a higher PIT rate than those falling into the second income bracket – the introduction of the top rate will be offset by the restructuring of the solidarity tax.

Results

There are four main findings. First, the reform will reduce the tax wedge on labor income, whereas the tax wedge on low wages will remain high by international standards. Second, most of the PIT taxable income earners (93.5%) will fall into the bottom income bracket. Hence the reform will effectively reduce the tax burden, while the effect on progressivity is very limited. Third, the (small) increase in tax progressivity is ensured mainly by changes in the tax allowance, while the effect of changes in the tax rate on progressivity is negligible: Even those few PIT payers that fall into the top tax bracket will not experience any increase in the tax burden due to a compensating change in the solidarity tax. Finally, it is mainly the households in the middle of the income distribution that will gain from the reform.

Effect on tax wedge

We start with a simple comparison of the average labor tax wedge in Latvia and other OECD countries for different wage levels before and after the reform. The tax wedge measures the share of total labor costs that is taxed away in the form of taxes or social contributions payable on employees’ income.

Table 1. Average tax wedge for single wage earners without dependents in Latvia and other OECD countries, before and after the reform

 

67% of average worker’s wage

  

100% of average worker’s wage

  

167% of average worker’s wage
OECD average in 2016, % (a) 32.3 36.0 40.4
Latvia 2016, % (a) 41.8 42.6 43.3
Latvia’s rank in 2016* (a) 6 11 16
Latvia 2018, % (b) 39.4 42.3 42.6
Latvia 2019, % (b) 39.1 42.1 42.6
Latvia 2020, %(b) 39.0 41.9 42.8

Source: (a) OECD and (b) authors’ calculations. Note: * Ranking across 35 OECD countries. Higher ranking implies higher tax wedge relative to other countries.

Table 1 shows that the tax wedge on low wages (67% of an average worker’s wage) in Latvia is pretty high. In 2016, it was the 6th highest across OECD countries, while the tax wedge on high incomes (167% of the wage) is much closer to the OECD average.

While the reform will slightly reduce the tax wedge for low wage earners (from 41.8% to 39.0% in 2020), it will still remain high by OECD standards. Despite an increase in PIT rate for high-income earners, the reform will also lower the tax wedge for those who earn 167% of the average wage. Why? The explanation comes from the income thresholds for the tax brackets. The income of those earning 167% of the average wage is estimated to fully fall into the first tax bracket in 2018–2019 and only slightly exceed the income bracket for the second PIT rate by 2020. This means that most of the incomes of people earning 167% of the average wage will be taxed at the rate of 20%, which is lower than the current flat rate of 23%. Moreover, in 2020, only a small share of their income will be taxed at 23% – the same rate that these individuals would have had faced in the absence of the reform. Hence, we observe a reduction in the tax wedge for high-income earners.

Generally, only a very small share of taxpayers will fall into the middle and the top income brackets. According to our estimations, as many as 93.5% of all PIT taxable income earners will fall into the lowest income bracket, and only about 6.5% will fall into the second income bracket and about 0.5% will face the top PIT rate.

Apart from the progressive PIT schedule, the reform envisages important changes in the solidarity tax. As explained above, part of the revenues from the solidarity tax will be used to finance the top PIT rate. Therefore, even those (very few) taxpayers whose income will exceed the threshold for the top PIT rate, will not experience any increase in the tax burden because of the compensating change in the solidarity tax. Therefore, the reform will effectively reduce the tax burden on labour with very little effect on progressivity.

While lowering the tax burden is generally welcome, the motivation for applying the top rate to such a small group of taxpayers is not clear. For example, in their recent in-depth analysis of the Latvian tax system, the World Bank (World Bank, 2016) came up with a tax reform proposal that envisaged a considerably lower threshold for the top PIT rate, which, according to our estimations, would cover about 12% of the taxpayers. Given the limited budget resources and an especially high tax wedge on low wages, a more targeted reduction in the tax burden would be preferable. Similar concerns about insufficient reduction in the tax burden on low-income earners are expressed in the latest OECD economic survey of Latvia (OECD, 2017).

Effect on income distribution

Below we present the results from the tax-benefit microsimulation model EUROMOD. Figure 2 shows the simulated change in equivalized disposable income by income deciles compared to the baseline “no-reform” scenario in 2018-2020.

Figure 2. Change in equivalized disposable income by income deciles caused by the reform compared to “no-reform” scenario, %

Source: authors’ calculations using EUROMOD-LV model

The first thing to note is that these are mainly households in the middle of the income distribution who will gain from the reform – their income will increase due to both the increase in non-taxable allowance and the introduction of the progressive rate.

The gain in the bottom of the income distribution is smaller for several reasons. First, the proportion of non-employed individuals (unemployed and non-active) is larger in the bottom deciles. Second, individuals with low wages are less likely to gain from the reduction in the tax rate and the increase in the basic allowance, since they might already have most of their income untaxed due to the currently effective basic allowance. The same applies to pensioners who have a higher basic allowance than the employed individuals and who are mainly concentrated in the bottom of income distribution.

Our results suggest that the wealthiest households will also see their incomes grow as a result of the reform (by about 1% in 10th decile). The growth is ensured by the fact that annual income below 20,000 EUR will be taxed at a reduced rate of 20%, and, taking into account that even in the top decile only about half of the individuals get income from employment that exceeds 20,000 EUR per year, the gain from the tax reduction is considerable even in the top decile. A reduction in the tax allowance for high-income earners will have a negative effect on wealthy individuals’ income, but this will be more than compensated by the above positive effect of the change in the tax rate. Hence, the net effect on the incomes in the top deciles is estimated to be positive.

Finally, Table 2 summarizes the effect of the reform on the income distribution, measured by the Gini coefficient on equivalized disposable income. On the whole, the reform is estimated to slightly reduce income inequality – in 2020, the Gini coefficient is expected to be 0.6 points lower than it would have been in the absence of the reform. This reduction is mainly driven by the changes in the non-taxable allowance, while the three PIT rates are estimated to have an increasing impact on income inequality.

Table 2. Gini coefficient on equivalized disposable income in the reform and “no-reform” scenario

2018 2019 2020
“No-reform” scenario 35.2 35.4 35.7
Reform scenario 35.0 35.0 35.1

Source: authors’ calculations using EUROMOD-LV model

Conclusion

The 2018 tax reform was a long-awaited step from the Latvian authorities on the way to a more progressive tax system. The planned changes in the basic tax allowance are estimated to help reducing the tax wedge on low wages and help addressing the problem of high income-inequality.

At the same time, the second major aspect of the reform, the introduction of a progressive PIT rate, raises more questions than answers. The progressive rate, the way it is designed, will effectively lead to an across-the-board reduction of the tax burden on labor and will hardly help to reach the proclaimed objective of taxing incomes progressively. Given the limited budgetary resources and given that taxes on low wages will remain high compared to other countries even after the reform, a more targeted reduction of the taxes on low-income earners would have been a more preferred option.

References

  • OECD, 2017. “OECD Economic Surveys: Latvia 2017”, OECD Publishing, Paris. http://dx.doi.org/10.1787/eco_surveys-lva-2017-en
  • Sutherland, H. and Figari, F., 2013. “EUROMOD: the European Union tax-benefit microsimulation model”, International Journal of Microsimulation, 1(6), 4-26.
  • World Bank, 2016. “Latvia Tax Review”, available at http://fm.gov.lv/files/nodoklupolitika/Latvia%20Tax%20Review%20Draft%20231216%20D.pdf

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On Economics of Innovation Subsidies in Russia

Posted on October 9, 2017 | Policy Brief

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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.

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Fiscal Redistribution in Belarus: What Works and What Doesn’t?

Posted on September 30, 2017 | Policy Brief

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Belarus proudly calls itself a social state. Indeed, Belarus boasts one of the lowest poverty and inequality levels in the region. Fiscal policy in Belarus is equalizing and pro-poor, effectively redistributing income from rich to poor. As in Russia and many other Post-Soviet states, the equalizing effect of the fiscal policy in Belarus is mostly attributable to the pension system. Some of the other social policies are highly inefficient, failing to redistribute income. The prominent examples are utility subsidies and student stipends, which mainly benefit the upper part of the income distribution. The lack of adequate unemployment benefits is an opportunity to improve the efficiency of the social support system in Belarus.

The Constitution of Belarus characterizes Belarus as a social state, and Belarus takes its social state status seriously. The economic growth in the beginning of the 2000’s was strongly pro-poor (Chubrik, 2007). Poverty according to the national definition (calorie-based poverty line, which in 2015 corresponded to $10.67 PPP per day) declined from 42% in 2000 to 5.7% in 2016, while the poverty according to the international threshold of $3.1 per day in PPP terms is fully eradicated. Belarus also has one of the lowest levels of income inequality in the region with a Gini coefficient of only 0.27 (UNDP, 2016).

How much of the pro-poor and equalizing effects could be attributed to the government policy? Probably it is impossible to give a complete answer to the question. Many non-formalized and not easily quantifiable government policies lead to the decrease in poverty and inequality. For example, the policy of support to state-owned enterprises might have redistributive effects through job creation. However, the absence of access to relevant data makes it impossible to estimate the effects of the policy.

Some of the government policies, on the other hand, are easily quantifiable with available data. Bornukova, Chubrik and Shymanovich (2017) analyze the redistributive effects of fiscal policies in Belarus using the Commitment to Equity methodology (Lustig, 2016). The authors find that the direct taxes and transfers in Belarus (taxes, transfers, and subsidies) are equalizing and pro-poor, lowering the national poverty headcount by 17 percentage points and the income Gini coefficient from 0.41 to 0.27. The high equalizing effect of the fiscal policies in Belarus surpasses those in other developing countries, including Russia where the direct taxes and subsidies reduced the income Gini coefficient by 0.13 (Lopez-Calva et al., 2017). The remaining discussion in this brief is based on the results from Bornukova, Chubrik and Shymanovich (2017), if not otherwise stated.

Fiscal policies and their redistributive effects

Taxation

The two types of direct personal taxes – the personal income tax and the social contributions tax – are both almost flat in Belarus. To fight tax evasion, the Belarusian authorities introduced flat tax rates in 2009, following a successful experiment in Russia. The personal income tax has some small exemptions for families with children, while the social contributions tax has a lower rate for agriculture employees. However, the effect of these deductions is relatively small: the direct taxes decrease the Gini coefficient by only 0.015.

The indirect taxes – the value-added tax, the import duties, and the excises – are weakly regressive, putting the burden of taxation on the poor. This is particularly true for the alcohol and tobacco excises. Again, the main purpose of these taxes is to penalize unwelcome behavior, and not to redistribute income, hence the result is not unexpected, and common for many countries. Overall the indirect taxes in Belarus increase the Gini coefficient by 0.05.

Direct transfers

Direct transfers are responsible for most of the equalizing effects of the fiscal policies. This is not surprising, given that the main purpose of the direct transfers is to fight poverty and provide support for those in need. However, most of the transfers are not need-based or targeted to the poor. Instead they are assigned to households based on their socio-economic characteristics aside income, such as age and maternity status.

Pensions are the main factor of reducing poverty and inequality. They reduced the Gini coefficient by 0.11 and decreased poverty (according to national definition) by 19 percentage points. The incredible effectiveness of the pensions is largely explained by the absence of other sources of income of the retirees. The majority of them does not work, and have no other pension savings or passive income. Pensions in Belarus are also redistributive in nature since they only weakly depend on one’s income during the working life.

Different benefits and privileges also decrease poverty and inequality, but at a much smaller scale. The childcare benefits (for families with children aged 0-3 years) contribute most to the effects, decreasing the Gini coefficient by 0.013 and poverty by 3 percentage points. The variety of privileges does not contribute much due to their relatively small size.

Subsidies

Utilities and transport subsidies are also important elements of the social support system, and their existence is usually justified by the necessity to support those in need. Since the utilities subsidies are incorporated into tariffs and available for everyone independent of need, they are in fact benefitting the rich (i.e. people with big apartments and houses).

Figure 1. Incidence of utilities subsidies by income deciles

Source: Bornukova, Chubrik and Shymanovich, 2017

As seen on Figure 1, upper deciles receive more support through utilities subsidies, and this support is quite substantial, often surpassing $1 per day in PPP. However, as a share of income the utilities subsidies are still progressive, and they in fact decrease the Gini coefficient by the tiny amount of 0.006, and decrease poverty (as any handout). The same is true for transport subsidies.

What could be improved?

Due to the flat nature of direct taxation and an absence of well-targeted needs-based transfers, some of the people in need still fall through the cracks. 1.9% of the population actually becomes poor after we account for the direct taxes and transfers. This headcount increases to 3.3% if we account for indirect taxes.

Another important issue is the efficiency of government transfers and subsidies in fighting poverty and inequality. It is not surprising that pensions have the largest equalizing contribution, as the government spends almost 11% of GDP on pensions. If we account for this fact and look at the efficiency (effect on poverty and inequality per dollar spent), pensions are not the leading program. It is in fact surpassed by different kinds of child support. Given that mothers in Belarus are allowed to take 3 years of unpaid maternity leave, which decreases household income, childcare benefits are relatively efficient.

The unexpected leader in efficiency is unemployment benefits, despite (or maybe due to) their negligible size. Shymanovich (2017) shows that unemployed face high risks of poverty, suggesting that an increase in the size of unemployment benefits and an easier access may bring huge benefits. The current minuscule size of the benefits (around $10-15 per month) is still enough to lift some people out of poverty, and has important equalizing effects, generating the biggest “bang for the buck” out of all benefits.

The student grants (stipends), the utilities subsidy and the transport subsidy have very low efficiency. These programs relocate a lot of funds to the upper deciles of the income distribution. Our calculations show that if all benefits, privileges and subsidies were not available to those in the top two income deciles, the Belarusian budget could save 1.4% of GDP.

Conclusion

Fiscal policies in Belarus are quite effective in redistributing income. Bornukova, Chubrik and Shymanovich (2017) show that the direct taxes and transfers in Belarus result in a decrease of poverty by 17 percentage points, and decrease the Gini coefficient of inequality from 0.41 to 0.27. The pension system has the most important contribution, decreasing poverty by 19 percentage points, and the Gini coefficient by 0.11.

However, the absence of a needs-based, well-targeted social support system leads to many inefficiencies. Direct and indirect taxes lead to impoverishment of 3.3% of population, which is not compensated by direct transfers.

The absence of targeting also leads to 1.4% of GDP redistributed towards the two upper income deciles through benefits, privileges and subsidies. This is, of course, highly inefficient. Better targeting could allow saving these funds or redirecting them to unemployment benefits – the most efficient but a very small benefits program so far.

References

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