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Whither Russia’s History Thought? Trends in Historical Research, Teaching and Policy-Making

Posted on May 12, 2014 | Policy Brief

The next Russian generation’s understanding of their country’s past may turn out to be more refined and complex than at present whether or not the current project of a single history-textbook and accompanying pedagogical materials are successful. Rather than imposing a new version of Stalin’s infamous ‘Short course’, as certain Western mass media predicts, the new history books will probably reflect even the most debated parts of Russia’s history from the 800s to the present, and in particular the turbulent 20th century.

Western mass media have a tendency to focus on Russian historical debates only when ‘spectacular’ and/or ‘scandalous’ events appear. For example, few news agencies paid any attention as to how the school textbooks on Russia’s contemporary history had changed through the 1990s. A whole year history classes were cancelled in the late glasnost period! This was because the Soviet-era teaching was recognized as totally outmoded in light of all the revelations on Stalinism. Starting in the mid-1990s, several groups of renowned historians produced new textbooks, history maps, and CD-ROM-materials for Russian general schools. In these pedagogical devices for children up to the final 11^th class, few if any of the formerly ‘taboo questions’ remained unmentioned. By the early 2000s, a new historical landscape of Russia’s past – especially from the 1860s to the present – had appeared. Every history teacher had a number of handbooks to choose among. However, with time, it was obvious that not only did the basic ideological and political attitudes of the textbook writers influence how they presented a historical narrative. There was also a wide divergence in how even the basic facts on historical events were described.

History teaching in Russian schools has thus been highlighted in Western mass media only when a certain author has been criticized or a specific textbook lost its recommendation from the Russian Ministry of Education. Therefore, the understanding in the West, even in academic circles, of how the Russians in general have changed their perception of their country’s past is likely superficial. The obvious language barrier is only a first hindrance that explains this ignorance. The lack of knowledge of, and even an interest in, i) Russian professional historians, ii) popularizes and publicists in mass media, and iii) the general public as shown in social media describing epochs and events in the past, may also be related to a certain degree of Russophobia, traditionally present in the West.

Instead, the Western average reader tends to get his views on Russia’s Vergangenheitsbewältigung, that is its ‘coming to terms with the past’, from highly restricted analyses like Sherlock’s book (Sherlock 2007) or polemical surveys like Satter’s (Satter 2011). Sherlock investigates the glasnost debates, but ignores the changes in the 1990s and draws farfetched conclusions on the present Putin-period, based on statements by politicians. Satter concentrates on how certain leftist, pro-Stalinist opinions remain in the public sphere concerning history writing or history-memorialization with respect to the victims of state terror and repression. These two authors emphasize how politicians, rather than professional historians, have made statements, or sometimes suppressed commemorative actions on Russian history, thus creating a skewed image of how the past is analyzed in the historians’ community. In reality, there are few subjects, especially concerning the Stalinist period, that have not been investigated because of lack of sources and of non-access to archives. The remaining ‘white spots’ on the historical map concern matters that are likewise often state secrets in other states, such as military intelligence. Given how much was until 1991 classified in the archives, it is worthwhile pondering how much historians and archivists in Russia have already achieved.

The Russian professional historians’ achievements in the post-Soviet period can now be grasped easily in the solid 1,500 pages long volume, edited by one of Russia’s foremost historiographers Gennadii Bordiugov (Bordiugov 2013). Bordiugov and his colleagues have held numerous conferences since the mid-1990s where practically every new research project on all aspects of Russia’s 20^th century history has been analyzed. These have been updated and collected into a massive volume. Another conference was devoted to the changing character of the historical community in general, to the research and teaching conditions in Russian universities, as well as to the interaction between historians and politicians (Bordiugov 2012). To a large extent, the economic history of Russia was until the late 1980s hampered by its rigid attachment to the Marxist and Leninist schemes of ’historical materialism’. Thus, starting during the glasnost era, Russian economic historians have made serious revisions, widespread re-interpretations and new research on practically all important stages of the evolution of the Tsarist economy, in particular concerning the early industrialization, the banking system and the entrepreneurial efforts in the 19^th century. These achievements are well reflected in the two-volume encyclopedia on Russia’s economic history from oldest times till 1917, under the scientific guidance of academician and head of the Institute of Russian History of the Academy of Sciences, Iurii Petrov (Petrov 2008).

A new trend in the field is the outright proclaimed and implemented ‘history policy’ (in line with a state’s economic, social and foreign policy). Politicians strive to use their country’s past, its military feats or civilian achievements for their present purposes. This has been apparent in Russia as well as in Eastern and Western Europe, first in the wake of the collapse of the communist regimes, and then as a matter of geopolitical and socio-economic confrontation. The resolutions on 20^th century history by the PACE, OSCE and other forums are examples of such history policy. Without doubt Russian publicists have also been involved in dreadful ‘wars of memory’ in particular vis-à-vis the Baltic states and Ukraine (see Borgiugov 2011b). However, among both Russian historians and certain politicians there exists a better grasp of the risks involved in history policy campaigns than seems to be the case in some East European countries. This is easily explicable, given the Russian state’s complicated thousand-year legacy of multi-cultural encounters, complex forms of conquest and expansion, social conflicts and revolutions, as well as religious and ideological controversies.

Thus, a striving towards a unified version of Russian history was reflected in the proposals by a commission set up in 2013 to formulate the ‘concept for a new, single textbook for schools on Russian history’. The initiative to substitute a multitude of textbook by a single one was set out in early 2013 in a directive from president Vladimir Putin. The original idea in Putin’s directive was to eliminate internal contradictions concerning historical events, and create a solid handbook in history with presumably straightforward, undisputable ‘facts’, just like the natural sciences can be said to have ‘a single knowledge framework’. Academicians Aleksandr Chubarian, Iurii Petrov, other historians as well as scholars from other disciplines plus politicians, led the commission. This initiative from Putin has been widely interpreted as a new stage in ‘history policy’ of the Russian government with the purpose of enforcing a new kind of patriotism or even legitimizing the allegedly ever more authoritarian present regime. However, when the concept for a single textbook was published in late autumn 2013, it became apparent that the commission had formulated a new academic, rather than a politicized framework for presenting Russia’s whole history, from the 800s to the present, with merely sketched outlines for each epoch, century of crucial decade. In over thirty appendices to the concept, leading experts describe major historical controversial questions, such as Ivan IV (‘The Terrible’), Vladimir Lenin and the 1917 Revolutions. Suffice it to mention that the appendix on the Great Terror 1937-1938 is written by Russia’s leading expert on Stalinism, professor Oleg Khlevniuk (see e.g. Khlevniuk 2008).

In early summer 2014, we can expect that the official announcement on the conditions for participation in the writing of the new textbook on Russia’s history will be announced. Just as for architectural contests, the mere presentation of a master-copy of the ‘pedagogical package’, i.e. not only the textbook but also guidelines for teachers, historical atlases, working notebooks with tasks for pupils, as well as audio and video materials will demand substantial investments from the participants’ side. Although the remuneration, in case of winning the contest, may be great, it is not expected that more than a few institutions or groups of historians will find the financial resources at hand. These proposed new textbooks will then be circulated and judged in a manner that remains to be determined.

The initial reactions in 2013 by Russian politicians and Western journalists at the appearance of the concept were skeptical. Concerns, however, were often somewhat biased. For example, in an article in ‘The Moscow Times’ the opposition politician Vladimir Ryzhkov had no objections on the first one thousand years of Russia’s history outlined in the concept. Instead, Ryzhkov lamented that the last paragraphs in the concept on Putin’s presidency had not mentioned certain oligarchs and recent dissenters. (Ryzhkov 2013). The American historian and specialist on Ukrainian history Mark van Hagen expressed his fears that Putin’s textbook would try to indoctrinate the Russian masses in a manner similar to how Stalin’s infamous ‘Short Course of the Bolshevik Party’s history’, but, of course, with a presumably new authoritarian, Orthodox Christian and multicultural Russian idea (quoted in Reuters. 2013).

It remains to be seen how much of such fears turn out to be prescient, or on the contrary, wide of the mark. Already at the official presentation in January 2014 of the commission’s result to president Putin, a number of changes in the original proposal for a single textbook were apparent. A careful reading of Putin’s speeches as well as those of Sergei Naryshkin, chairman of the Russian Historical Society and speaker of the Duma, and Academician Chubarian, scientific leader of the commission, indicate that the pedagogical package (i.e. the teacher’s handbook, textbook, map and task booklets, as well as CD-ROM and video) are likely to be much more pluralistic, as to interpreting history, than what either the initiators intended originally or what their critics presumed eventually.

Although the original idea formulated by the president himself included a phrase on giving the school children just ‘one single textbook’ (Russian: edinyi uchebnik) with new narrative, free of contradictions and contested interpretations, we can already see that even the announced concept for such a ‘single history textbook’ may well turn out to be as dynamic and thought-provoking as the real historical events were. Another alternative outcome that cannot be excluded, will be that not one single, but a few new textbooks – with different pedagogical and other highlights – will be declared as winners, provided that they reflect the new, more nuanced version of Russia’s history from oldest times to the present. In either case, these new pedagogical instruments are bound to reflect, given dozens of special surveys by experts on the debates among historians added to the concept, the achievements of archivists, professional historians and teachers in the past quarter-century. Thus, in conclusion, while substantial arguments may be raised against the political request of a single textbook on Russia’s history, the presentation of this new concept and the forthcoming contest may turn out to produce a number of excellent history teaching materials that in a wider sense will reflect both the professional historians’ achievements in recent decades, the publicists’ opinions and the expectations of the broad public.

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References

Bordiugov, Gennadii, editor (2011a), Nauchnoe soobshchestvo istorikov Rossii: 20 let peremen, (Russia’s scientific community of historians: 20 years of changes), Moscow: AIRO-XXI.
Bordiugov, Gennadii (2011b), ‘Voiny pamjati’ na postsovetskom prostranstve (‘Memory wars’ in the post-Soviet spheres), Moscow: AIRO-XXI.
Bordiugov, Gennadii, editor (2013) Mezhdu kanunami: Isotricheskie issledovaniia v Rossii za poslednie 25 let (Between tomorrows: Historical research in Russia in the last 25 years), Moscow: AIRO-XXI.
Khlevniuk, Oleg (2008), Master of the House, Stalin and His Inner Circle, New Haven, CT: Yale University Press.
President of Russia, Meeting with designers of a new concept for a school textbook on Russian history http://eng.news.kremlin.ru/news/6536accessed 2014-05-07
Petrov, Iurii, chief editor (2008), Ekonomicheskaia istoriia Rossii s drevneishikh vremen to 1917. Entsiklopediia, Moscow: Rosspen).
Reuters. US edition Gaabriela Baczynska ‘Putin accused of Soviet tactics in drafting new history book’ 18 November 2013, http://www.reuters.com/article/2013/11/18/us-russia-history-idUSBRE9AH0JK20131118, accessed 20140507Ryzhkov, Vladimir (2013), ‘Putin’s Distorted History’, The Moscow Times, 18 November 2013.
Satter, David (2011) It Was a Long Time Ago, and It Never Happened Anyway: Russia and the Communist Past, New Haven. CT: Yale University Press.
Sherlock, Thomas (2007) Historical Narratives in the Soviet Union and Post-Soviet Russia: Destroying the Settled Past, Creating an Uncertain Future, London: Palgrave Macmillan.

Skill Structure of Demand for Migrants in Russia: Evidence from Administrative Data

Posted on May 5, 2014 | Policy Brief

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Authors: Simon Commander (IE Business School, EBRD and Altura Partners) and Irina Denisova (CEFIR, NES).

Using Russian Ministry of Labor administrative data for all legal migrant applications in 2010 and matching the migrant to the sponsoring firm, we find that there is some – albeit limited – evidence of firms using migrants to address high skill shortages. However, the overwhelming majority of migrants are skilled or unskilled workers rather than qualified professionals; a reflection of the low underlying rates of innovation and associated demand for high skill jobs.

Migration policy continues to be a priority in Russian economic policy. This is driven both by a demand for labor – given the unfavorable demographic trends of the last decades – and the easily available supply from the CIS countries. It is still not clear, however, what is the skills structure of the demand for migrants. Relatively new administrative data on demanded permissions to employ migrants sheds however some light on the issue.

In particular, we use the 2010 nationwide dataset ‘Job positions filled by migrants’ published by the Russia Federal Employment Service. The dataset gives detailed information on the applications for permits for migrants, including the 4-digit occupation, firm ID and the offered wage. The Federal Employment Service’s role is to approve or reject an application. In almost all cases documented in this dataset, approval was granted. Moreover, in 99% of the cases, the duration of the permitted contract was one year.

The data allow us to study the skill composition of demand for migrants from the legal sector, with the sizeable illegal labor migration staying beyond the scope of the study. The total number of applications for all of Russia in 2010 was just over 890,000, of which nearly 250,000 or 28% originated from firms in Moscow. The analysis below uses the permission data for the 21 most developed Russian regions (a full version of the paper is available as Commander and Denisova, 2012).

A breakdown of the number of requests in 2010 by skill type using the one-digit ISCO-88 classification (Managers, High-level professionals, Mid-level professionals, Service worker, Skilled agricultural workers, Craft and trades workers, Plant and machine operators, Unskilled workers) shows that over 70% of the requests were for skilled and unskilled workers. At the same time, about 17% of the total migration requests were for higher-level professionals (7%) and managers (10%). Among managers, nearly nine out of ten requests were for production or department managers with no more than 12% of managerial migration requests being for top-level executives. Among the category of high-level professionals, architects and engineers accounted for over two-fifths of requests.

Is the situation any different in the main urban labor markets? In Moscow a lower proportion – around two thirds of the migrant applications – were for skilled and unskilled workers. The starkest difference was that professionals working in IT accounted for a minute share of total high-level skill applications in Russia, but nearly 9% in Moscow. Thus, while there are some differences in the migration profile between Moscow and the rest of the country, the broad picture that emerges is one where migration policy and practice seem to be responding mainly to the apparent bottlenecks at the lower-skill end of the labor market.

Legal requests for migrants are massively dominated by requests concerning low-skill groups; and illegal migrants, as shown by anecdotal evidence, are mainly low skilled. At the same time, there is a sizeable demand for qualified migrants, managers and professionals. There are two potential motives to issuing a request for a qualified migrant: to economize on the costs of labor by substituting a local laborer with a migrant; or to fill in the gap of the scarce qualification/skills hardly available domestically. The two motives could be distinguished by looking at the wage offers associated with the posted positions and comparing them with wages paid in comparable occupations in the same region. The aim of the exercise is to see – particularly within the categories of higher-skilled applicants – whether they command any wage premium that might reflect their scarcity value.

Figures 1-2 plot the reported (relative) wage offers for two migrant skill categories: Department Managers (ISCO code=122) and Computing Professionals (ISCO code=213). The figures depict distributions of relative (to the region average) wage in logs, thus implying that the points around 0 are the wage offers at the level of regional average, above 0 means positive wage premium, and below 0 means negative wage premiums (economizing on the costs). Each figure also gives the mean search wage from the EBRD survey of recruiting agencies in 2010 (relative to the regional average).

Figure 1. Relative Wage Distribution, Production and Operation Department Managers (ISCO-88 Code: 122)

Source: Authors’ calculations based on Rostrud 2010

It is clear from Figure 1 that the wage offers for migrants do not identify any clear positive selection effect, in that migrants’ wages mostly fall below the survey search mean comparators. In the majority of cases, the offered wages also fall below the regional average wage thus implying that the motive is to substitute for cheaper labor.

The demand for migrants with skills of IT professionals is more complicated: there are those who offer wages below regional average, but there is also a large group of those ready to pay a wage premium to attract migrants (with log wage above zero). The search through recruiting agencies (the survey wage) would still require offering higher wages.

Figure 2. Relative Wage Distribution, IT Professionals (ISCO-88 Code: 213)

Source: Authors’ calculations based on Rostrud 2010

For further analysis, the migration dataset was mapped to the ORBIS (a dataset assembled by Bureau van Dijk) firm observations using the unique national tax identification code (so called INN). The ORBIS data includes information on firms’ balance sheets and simple performance data such as output per employee.

When looking only at demand from firms that lie in the top 10-20% of the productivity distribution (productivity is calculated as output per worker in the narrowly defined industry), the picture looks somewhat different: wage offers tend to lie above the average (Figure 3). It is likely that the most productive firms tend to offer wages higher than both regional average for the occupation and the survey-based search wages. This implies that the scarcity of skills on the domestic labor market is one of the more important motives behind the demand for migrants from high-productivity firms.

Figure 3. Relative Wage Distribution, Production and Operation Department Managers (ISCO-88 Code: 122), 10% Most Productive Firms

Source: Authors’ calculations based on Rostrud 2010 and Orbis-Roslana

To control for other firm characteristics, we run regressions relating the relative wage of a migrant to a set of firm and region characteristics, including measures of size and ownership, a measure of recent growth in the region, as well as the level and change in foreign direct investment in a given region since 2007. We also control for the tightness of the local labor market, using a measure of search wages raised in the EBRD survey compared to average wages in a region. The estimates are run with and without region, industry and occupation controls. The results show that relatively high wages tend to be associated with large and/or foreign-owned firms. Growth in a region or the level of FDI per capita are not systematically associated with the relative wage once controls enter the regression, suggesting that the relative wage is largely determined by firm-level features. The measure of labor market tightness enters positively but is insignificant whencontrolling for industry, region and occupation.

Overall, the data from the Russian Ministry of Labor that documents all applications for migrants to Russia in 2010 and allows matching the migrant to the sponsoring firm, show that there is very limited evidence of firms using migrants to fill high-skill jobs. In fact, the overwhelming majority of migrants, skilled or unskilled workers, were mostly originating from other states of the CIS. Furthermore, most were hired at relatively low wages in comparison to the occupation/region averages or the wages reported in the EBRD survey of recruiting firms. At the same time, there is a sizeable portion of demand for skilled migrants, which are offered wage premiums. The demand originates mostly from highly productive firms. Migration policy should acknowledge these different motives behind the demand for migrants.

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References

Simon Commander and Irina Denisova “Are Skills a Constraint on Firms? New Evidence from Russia”, IZA Discussion Paper No. 7041, November 2012

Financial Support for Families with Children and Its Trade-Offs: Balancing Redistribution and Parental Work Incentives

Posted on April 28, 2014 | Policy Brief

Authors: Michal Myck, Anna Kurowska and Michal Kundera, CenEA.

Reforms of tax-benefit system of financial support for families with children have a broad range of consequences. In particular, they often imply trade-offs between effects on income redistribution and work incentives for first and second earners in the family. Understanding the complexity of the consequences involved in reforming family policy is crucial if the aim is to “kill two birds with one stone” namely to reduce poverty and improve incentives to work. In this brief, we illustrate these complex trade-offs by analyzing several scenarios of reforming financial support for families with children in Poland. We show that it is possible to create incentives for second earners in the family to join the labor force without destroying the work incentives of the first earners. Moreover, the same reform would allocate resources to families with lower incomes, which could result in a direct reduction of child poverty.

Financial support for families with children is an important and integral part of the broad family policy package, the goals of which fall into two basic categories of reducing child poverty and increasing labour market activity of parents (Whiteford and Adema, 2007; Björklund, 2006; Immervoll, et al., 2001). However, the particular policy aimed at one of these objectives may be detrimental to the achievement of other goals. For example, family/child benefits may directly increase family income and thus reduce child poverty. These same benefits could have a negative effect on parental incentives to work, particularly for so-called second earners, usually mothers (see e.g. Kornstad and Thoresen, 2007). However, employment of both parents often turns out to be crucial for a long-term poverty reduction (Whiteford and Adema, 2007).

The trade-offs implied by the different family policy instruments are often poorly understood or treated superficially in the policy debate. The effect of this lack of understanding may result in badly designed policy reactions to identified problems, which in turn may imply that one of the objectives is achieved at the cost of the other, or even that policies work against all of them in a longer perspective.

Using the Polish microsimulation model SIMPL, we simulate modifications of several elements of the Polish tax and benefit system to demonstrate the complex nature of trade-offs between income and employment policy, and within employment policy itself. The underlying assumption of the analysis is that any effective policy that aims at lowering child poverty in the long run ought to realize and address issues of parental labour market activities. Governments should therefore aim at a design of financial support for families to provide assistance to poor households and at the same time strong work incentives for parents.

The Polish system of support for low-income families, Family Benefits, consists primarily of Family Allowance (FA) with supplements. These are means-tested and are available to families with net incomes below 504 PLN (€121) per month and per person. The value of the FA depends on the age of the child and ranges from 68 PLN to 98 PLN (€16.40 to €23.60) per month. For eligible parents this is supplemented by additional means-tested payments to such groups as lone parents, families with more than two children, and those with school-aged children. Eligibility for Family Benefits is assessed with reference to a threshold, which once exceeded makes the family ineligible to claim the benefits. This point withdrawal of benefits implies very high effective marginal tax rates and has significant implications for average effective rates of taxes (see Myck et al., 2013). In addition to Family Benefits, financial support for families is also channelled through the tax system. Tax-splitting (joint taxation) is available to married couples and lone parents, and since 2007 parents can set their tax liabilities against the Child Tax Credit, which is a non-refundable tax credit, the maximum value of which is 1,112.04 PLN (€268) per year for every dependent child.

The starting point for our analysis, and a reference in terms of potential costs of the reform, is the move to tapered withdrawal of Family Benefits (System 1). For this purpose we use the rate of withdrawal at 55%, which is the rate used in a broadly studied in-work support programme in the UK, the Working Families’ Tax Credit (WFTC) in the late 1990s and early 2000s (see, e.g.: Blundell et al., 2000; Brewer et al., 2006; Clark et al., 2002). Application of the taper implies that with an increase of net income of 1 PLN beyond the withdrawal threshold, the total value of benefits is reduced by 0.55 PLN. Such a change would imply greater certainty and predictability of benefit receipt, compared to the current point withdrawal system. However, as it extends the availability of benefits to families who currently no longer qualify for them, it would carry additional costs. We estimate this cost to be in the range of about 1.04 billion PLN (€250mln) per year, an increase in the total value of family benefits by about 14%.

Changes in Family Benefits under System 2 involve simple increases in the values of Family Allowance, which is raised by 20% given the above cost benchmark of 1.04 billion PLN. The final reform to Family Benefits (System 3) combines introduction of the withdrawal taper (at 55%) with a bonus system for two-earner families with the specific aim of providing stronger work incentives for second earners. The bonus consists of an increase in the level of the withdrawal threshold by 50% for families where both parents work compared to the baseline threshold value.

The first reform of Child Tax Credit (System 4) assumes an increase in the value of the CTC by 19.8% (calibrated to cost same 1.04 billion PLN), while the second uses this tax credit instrument to reward two-earner status. In the latter case, double-earner couples are granted an additional value of the credit (92.70 PLN per month). The cost of this reform is again calibrated to the level of other reforms by adjusting the earnings requirement set for both parents to qualify as double-earner couples. This calibrated requirement is 2,324.50 PLN per month and per person, which is equivalent to 176.5% of the minimum wage.

The assumptions underlying the modelled scenarios are very clearly reflected in the (static) distributional effects of the simulated changes. The proportional changes in incomes among families with children by population decile groups resulting from the simulated reforms are demonstrated in Figure 1A for Systems 1-3 and Figure1B for Systems 4-5.

Figure 1. Distributional consequences of modelled reforms: Proportional changes in incomes of families with children by income deciles.

Source: Authors’ calculations using the SIMPL microsimulation model on PHBS 2010 data.

Figures 2 and 3 show how the modelled reforms would affect incentives to work for first and second earners measured as average changes in replacement rates^{^[1]} (RRs) by centiles of the baseline distribution of replacement rates for modelled families. The RR for the first earner is the ratio of the family income when neither partners work and the family income when the first earners works full time. The RR for the second earner is the ratio of the family income when only first earners work and the family income when both partners work full time. Lowest values of RRs imply the strongest incentives and highest values reflect the weakest incentives to work. When the difference in RR between the Baseline and a particular System is greater than zero it implies that this System increases incentives to work for a particular earner compared to the Baseline. This approach provides evidence on the trade-off between improving work incentives for those facing strong and weak incentives in the baseline system. The pattern that emerges from Figures 2 and 3 reflects to some extent the distributional effects of the chosen reforms (Figure 1). This is because richer families are usually those with high labour market incomes and thus low RRs (high labour market incentives), while poorer families face weaker incentives given their low actual (or potential) earnings, and thus face higher replacement ratios.

Figure 2. Changes in RRs by baseline work incentives – first earners

Source: Authors’ calculations using the SIMPL microsimulation model on PHBS 2010 data.

Notes: Based on a sample of couples with children. System 5 does not change first earner incentives.

Figure 3. Changes in RRs by baseline work incentives – second earners

Source: Authors’ calculations using the SIMPL microsimulation model on PHBS 2010 data.

Notes: Based on a sample of couples with children.

Apart from the well-established trade-off between equity and labour market concerns, our paper draws attention to the need to balance out first and second earner work incentives as well as incentives by the degree of existing financial motivation to work.

Reforms at the two extremes of the distributional spectrum, namely an increase in the level of Family Benefits (System 2) and a Child Tax Credit bonus for two-earner couples (System 5), result in very different incentive effects. The former significantly weakens incentives of both first and second earners in couples, while the second, which specifically directs resources at second earners, produces important improvements in incentives to work for second earners. However, these gains focus on the part of the spectrum of the baseline distribution of work incentives where these are already strong. This contrasts with a reform in which a two-earner “bonus” is created as part of Family Benefits (System 3). This system increases the generosity of in-work support for first earners in couples in a similar way to the benchmark reform. At the same time, however, it improves the attractiveness of work for second earners by raising the level of income from which benefits are withdrawn for couples in which both partners are working.

This arrangement balances out the negative influence on second earner incentives of the income effect of making work more financially attractive for first earners, which does not happen under our benchmark scenario (System 1). Moreover, we demonstrate that trying to increase work incentives through higher levels of Child Tax Credit available to families would have a positive effect on the work incentives of a large number of families, in particular on first earners in couples. The flip side of this effect would be some negative incentive effects on second earners, but generally both types of effect would be very low given the assumed cost restriction of the modelled reforms.

Naturally, there is an endless number of ways in which a billion PLN can be spent on families with children. As we argued above, each type of reform will have a complex set of consequences on household incomes and incentives to work for parents. The breakdown of employment pattern in Poland suggests that to increase labour market activity, the family support policy should focus on trying to make work pay for second earners in couples, most of whom are women. As we demonstrated this can be done in such a way as to balance out incentives for first earners and provide strong incentives to those second earners who currently face the weakest incentives to work. At the same time, resources would be directed to families in the lower half of income distribution that could result in direct reduction of child poverty.

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References

Blundell R., A. Duncan, J. McCrae and C. Meghir (2000) The Labour Market Impact of the Working Families’ Tax Credit, Fiscal Studies, vol. 21(1), pp. 75-104.
Brewer M., A. Duncan, A. Shephard and M.-J. Suarez (2006) “Did Working Families’ Tax Credit Work? The Impact of In-Work Support on Labour Supply in Great Britain”, Labour Economics, vol. 13, pp. 699-720.
Björklund A. (2006) Does family policy affect fertility? Journal of Population Economics, vol. 19 (1), pp. 3-24.
Clark T., A. Dilnot, A. Goodman, and M. Myck (2002) Taxes and Transfers, Oxford Review of Economic Policy, vol.18 (2), pp. 187-201.
Immervoll H., H. Sutherland, K. de Vos (2001) Reducing child poverty in the European Union: the role of child benefits, in: Vleminckx K. and Smeeding T.M. (eds) Child well-being, Child poverty and Child Policy in Modern Nations. What do we know? Revised Edition; The Policy Press: Bristol.
Kornstad T. and T. O. Thoresen (2007) A Discrete Choice Model for Labor Supply and Child Care, Journal of Population Economics, vol. 20 (4), pp. 781-803.
Myck, M., A. Kurowska, and M. Kundera (2013) “Financial Support for Families with Children and its Trade-offs: Balancing Redistribution and Parental Work Incentives”, Baltic Journal of Economics, 13(2), 59-84.
Whiteford P. and W. Adema (2007) What Works Best in Reducing Child Poverty: A Benefit of Work strategy? OECD Social, Employment and Migration Woking Papers, nr 51, OECD, Paris.

[1]For the couples in the subsample we compute three sets of family-level incomes, conditional on employment either of the first earner (who is the person with higher expected earnings in a couple) or of both partners; Y(1,1) for the scenario where both partners are employed (full-time); Y(1,0) for the scenario where the first earner is employed (full-time); Y(0,0) for the scenario where both partners are not employed. This allows us to compute replacement ratios for the first earner (RR1) and the second earner (RR2) for each of the analysed tax and benefit systems (S): RR1(s,j)=Y(s,j)(0,0)/Y(s,j)(1,0) and RR2(s,j)=Y(s,j)(1,0)/Y(s,j)(1,1).

What Expansion of Mandatory Schooling Can and Cannot Do in Conservative Muslim Societies

Posted on April 7, 2014 | Policy Brief

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New research shows expanding mandatory schooling in conservative Muslim societies have broad positive effects on female empowerment but is not enough to overcome the significant barriers to female entry in the labor force.

Does expansion of public education empower women? A large literature documents the positive effects of education on women’s economic and social outcomes in developed countries, but we know less about its causal effects on women’s empowerment in Muslim societies where women’s participation in the labor market is limited and they often do not have control over their earnings or their own bodies (Doepke et al 2012). In fact, even though female education has been successfully expanding in many majority-Muslim countries, the number of legal rights enjoyed by women is few relative to men, and female labor-force participation remains low (UNDP 2005). The lack of a corresponding labor-force participation effect raises concerns over the efficacy of expanding education as a means of improving women’s rights in Muslim societies. On the other hand, education has been shown to have many important non-pecuniary effects outside the labor market, such as in health, marriage, and parenting style (Oreopolous and Salvanes 2011) and to the extent that these effects help empower women, they may constitute alternative mechanisms through which education may lead to women’s empowerment (even in the absence of large labor market returns). However, most of this research comes from countries and societies that are not majority-Muslim and where women do work to a larger degree. As such, disentangling non-pecuniary returns to education from its labor market (and thus pecuniary) returns is particularly challenging in most settings and whether education may empower women in the Muslim world remains an open question.

Even though scholars debate the fundamental causes for the severe degrees of gender inequality in Muslim societies, most posit a nexus of patriarchal culture, strong religious values, and restricting social norms as proximate explanatory factors. Historically, Lewis (1961) claims women’s status was “probably the most profound single difference” between Muslim and Christian civilizations. In more contemporary cross-country studies, Fish (2002) documents a negative cross-country correlation between having an “Islamic religious tradition” and female empowerment, while Barro and McCleary (2006) also show that Muslim countries tend to exhibit higher degrees of religious participation and beliefs. Comparing the effects of a business training program on female entrepreneurship among Hindu and Muslim women in India, Field et al (2010) find evidence in line with significantly stricter constraints to female labor-force participation among Muslim women. To the extent that barriers to entry due to religious values restrain women’s rights, an integral outcome of empowerment is therefore a woman’s ability to independently assert her own beliefs.

In a recent paper, Selim Gulesci and I exploit an extension of compulsory schooling in Turkey to estimate the causal effect of schooling on female empowerment (Gulesci and Meyersson 2014). Compulsory schooling laws have been extensively used to estimate returns to education in Western countries on labor market outcomes (Angrist and Krueger, 1991, Oreopoulos 2006), health and fertility (McCrary and Royer 2011, Lleras-Muney 2005, Black et al 2008) among others. We follow a similar strategy to provide meaningful causal parameters for the effect of a year of schooling on outcomes related to social status of women in Turkey, a majority-Muslim country.

In 1997, Turkey’s parliament passed a new law to increase compulsory schooling from 5 to 8 years. By this law, individuals born on or after September 1986 were bound to complete 8 years of schooling, whereas those born earlier could drop out after 5 years. Using the sample of ever-married women from the 2008 Turkish Demographic Health Survey (TDHS) we are able to observe outcomes 10 years after the law change was implemented.

We adopt a regression discontinuity (RD) design assigning treatment based on whether an individual’s month-and-year of birth was before or after the September 1986 threshold. As such, our identification strategy entails comparing cohorts born one month apart and relies on the assumption that these two groups should exhibit no systematic differences other than being subject to different compulsory schooling laws. We can thus calculate an RD treatment effect, illustrative of the causal effect of education for individuals born around the threshold.

Analysis of the sample of ever-married women focuses the RD treatment effects on a subset of the population that tends to be demonstratively poorer and more socially conservative, i.e. the very subpopulation that the reform was aimed at. In a comparison of ever- and never-married women, the reform only affected education among the former, and as a result, the exclusion of non-married women effectively means exclusion of non-compliers with the reform. This is a likely consequence of ex post single women being more likely to have attended school longer regardless of expanding reforms. We also show that the probability of selection into the married sample is not affected by the law.

Our results are as follow. First, we show the effect of the reform on women’s years of schooling. As a result of the reform, women’s average years of schooling increased by one year, and completion rates for junior-high (secondary) and high school completion increased by 24 and 8 percentage points (ppt) respectively. There is no significant impact of the reform on men’s schooling on average (mainly because the average man’s schooling in Turkey around the age threshold was already at a relatively high level). Thus, the reform effectively served to reduce the education gender gap by half.

Second, our RD estimates reveal that this additional year of schooling had significant secularizing effects. Ten years after the reform was implemented, and relative to sample means, women were 10 percent (8 ppt) less likely to wear a headscarf, 22 percent (10 ppt) less likely to have attended a Qur’anic study center and 18 percent (7 ppt) less likely to pray regularly.

Third, we find no evidence of schooling on the timing of either marriage or birth, nor on the number of children. We do however find significant effects on women’s decision rights with regards to both marriage and fertility decisions; a reform-induced year of schooling results in a 10 ppt (20 percent relative to the sample mean) increase in the likelihood of having a say in the marriage decision, and a 10 ppt (12 percent) increase in the likelihood of having a say in the type of contraceptive method adopted. We further find a reducing effect of schooling on the likelihood that a bride price was received by the women’s parents from their husband’s family upon their wedding.

Fourth, we document less pronounced and largely imprecise impacts on women’s labor market outcomes. Although our estimates indicate positive effects on non-agricultural employment in general, and self-employment in particular, these estimates are sensitive to the specification used. At the same time, we show significant positive effects of schooling on household wealth, largely driven by appliances related to women’s role as housewives. We are unable to explain this by observable increases in spousal quality, measured as husband’s years of schooling.

Altogether, our results indicate significant empowering effects of education, but whereas we document precise effects on decision rights, household wealth, and measures of social and religious conservatism, we fail to find equally concise effects on spousal and labor force outcomes. This prevents an interpretation relying exclusively on either labor market or assortative matching in the marriage market as the main channel of empowerment. In fact, an examination of heterogeneous effects reveal diverging effects depending on how socially conservative women’s backgrounds are; in rural areas, education pre-dominantly allows increased freedom to be more secular, greater decision rights over marriage, and less traditional marriages. In urban areas, education has similar effects, but also leads to increased labor force participation. We interpret this as increased education, and its associated bargaining power in the household, leading to different allocations depending on the preexisting level of women’s rights. Education may thus have only a partial effect on employment, as religious or cultural barriers to entry prevent women from realizing larger gains of education through the labor market.

Our paper adds to the research literature by providing meaningful causal parameters for the effect of a year of schooling on both social and religious outcomes for women in a majority-Muslim country. The findings point to a set of returns to schooling that take into context the socially conservative nature of the Turkish society where policies to increase schooling ultimately seem to improve women’s status (as captured by higher decision-making power and household wealth) but are unable to meaningfully break down the barriers that women face in entering the labor market, particularly in more conservative rural communities. While still having important empowerment consequences for women’s empowerment in Muslim societies, education may not be a magic bullet toward full emancipation. Policies hoping to achieve female empowerment will thus require complementary reforms in health and the labor market to address barriers to entry more directly.

References

Denisova, I., and S.Commander, S.Commander and I. Denisova (2012), ‘Are skills a constraint on firms? New evidence from Russia’, EBRD and CEFIR/NES, mimeo
Hausmann, R., and Klinger, B., (2007), “The Structure of the Product Space and the Evolution of Comparative Advantage”, CID Working Paper No. 146
Volchkova, N., Output and Export Diversification: evidence from Russia, CEFIR Working Paper, 2011
Angrist, Joshua D. and Alan. B. Krueger, 1991, “Does Compulsory Schooling Attendance Affect Schooling and Earnings?” Quarterly Journal of Economics, 106(1): 979-1014.
Barro, Robert and Rachel McCleary, 2006, “Religion and Economy”, Journal of Economic Per- spectives, 20(2): 49-74.
Black, Sandra, Paul Devereux, and Kjell G. Salvanes, 2008, “Staying in the Classroom and out of the Maternity Ward? The Effect of Compulsory Schooling Laws on Teenage Births”. Economic Journal, 118(530): 1025-54.
Doepke, Matthias, and Michelle Tertilt, 2009, “Women’s Liberation: What’s in it for Men?”, Quarterly Journal of Economics, 124: 1541-91.
Field, Erika, Seema Jayachandran and Rohini Pande, 2010, “Do Traditional Institutions Constrain Female Entrepreneurial Investment? A Field Experiment on Business Training in India”, American Economic Review Papers and Proceedings, 100: 125-29.
Gulesci, Selim, and Erik Meyersson, 2014, “For the Love of the Republic – Education, Secularism, and Empowerment”, working paper.
Lewis, Bernard, 1961, “The Emergence of Modern Turkey”, Oxford University Press: London.
McCrary, Justin, 2008, “Manipulation of the Running Variable in the Regression Discontinuity
Design: A Density Test,” Journal of Econometrics, 142(2): 698-714.
Lleras-Muney, Adriana, 2005, “The Relationship between Education and Adult Mortality in the United States,” Review of Economic Studies, 21(1): 189-221.
Oreopolous, Phillip, 2006, “Estimating Average and Local Average Treatment Effects of Education when Compulsory Schooling Laws Really Matter ”, American Economic Review, 96(1): 152-175.
Oreopolous, Philip and K. G. Salvanes, 2011, “Priceless: The Nonpecuniary Benefits of Schooling”, Journal of Economic Perspectives, 25(1): 159-184.
UNDP, 2005, “Arab Human Development Report 2005 – Towards the Rise of Women in the Arab World”.

Macroeconomic Performance and Preferences for Democracy

Posted on February 16, 2014 | Policy Brief

This policy brief summarizes the results of our research on factors influencing preferences for democracy in transition countries. The aim of this work was to detect which macroeconomic and individual factors impact the choice of supporting democracy. The results showed that the performance of the country, described by level of GDP, unemployment, level of corruption and economic growth, has a serious impact on an individual’s perception of democracy. At the same time, individual factors like education and age also influence people’s choice of support of democratic authorities.

Individual perception of democracy is a question that attracts the attention of policymakers. The macroeconomic instability that has been observed worldwide lately is likely to impact individual attitude toward democratic values and political institutions. The recent economic crisis brought a deterioration of the economic situation around the world and provided new challenges to cope with. It is likely that macroeconomic indicators have an impact on how a person perceives democracy. Literature studying similar questions has shown that GDP growth, unemployment and inflation all affect personal attitude to democratic institutions (Clarke et. al., 1994; Barro, 1999; Papaioannou and Siourounis, 2008). As for individual characteristics, the level of education is revealed by the literature as a very important factor in the context of the individual’s propensity of democracy approval.

The literature on the determinants of political support and attitudes to democracy was mostly focusing on exploring stable world economies with long-formed and steady-functioning democracies. We tried to look at a similar question in the context of transition economies, where democratic institutions are still under development.

We intend to estimate individuals’ propensity to favor democratic values. The specification of our econometric model was based on the literature addressing the same topic. The estimation procedure used probit econometric techniques, which allows for the calculation of the propensities of interest while taking into account the influence of both macroeconomic factors and individual characteristics. The paper used two sources of data: macroeconomic information was collected from the World Development Indicators of the World Bank, and individual-level cross-sectional data was obtained from Life in Transition Survey (LITS) 2010, which initially covered 38864 individuals from 35 countries. However, as the paper focuses on countries in transition, the final set only included individuals from 30 countries, most from Eastern Europe, Baltics and CIS, and excluded representatives of Western Europe. This data allowed for substantial data variation in the context of economic development vs. perception of democratic values (Graph 1).

Figure 1. Support of Democracy and GDP Per Capita

Source: WDI and LITS 2010

Inclusion of different macroeconomic variables together with individual factors allowed for an evaluation of their importance and level of impact on the perception of democratic values (Table 1). The results show that GDP per capita has a positive and significant effect on individuals’ perception of democratic values, which is in line with the literature claiming that standard of living in countries with not so high level of GDP is positively correlated with satisfaction with their life and the political system (Easterlin, 1995; Clark et al., 2008; Stevenson and Wolfers, 2008). Inflation rates are not significant and do not influence individuals’ attitude to democracy. On the other hand, economic growth is strictly positive and significant, and an increase of the economic growth rate raises propensity of democratic support by around 1.6 percentage points. The possible explanation here is that the growth rate of GDP works as a proxy of expectations for improvements of the standard of living in the future.

Table 1. Influence of Macroeconomic and Individual Factors on Perception of Democracy

Unemployment works as an indicator of a country‘s economic performance and has an expected negative sign in terms of individuals’ satisfaction with life and political institutions, which is also in line with the results in the literature (Di Tella et al., 2001; Wagner and Schneider, 2006). Impact of unemployment was tested using a cross product of unemployment and the Freedom House Index (this latter indicator shows the level of political and civil rights from 1 (most free) to 7 (least free)). The sign on this cross product is positive, which captures their mutual positive impact on the support for democracy. Thus, the higher the unemployment in a country with a low level of democratization is, the larger the probability of democratic support by individuals in these countries is. The indicator for the level of corruption in a country was also taken into account, via the Corruption Perception Index. This index ranks countries on a scale from 0 (highly corrupt) to 10 (effectively, corruption-free). The results show that the less corrupt a country is, the higher the propensity that an individual in that country will support democracy is. In fact, one additional point in the index increases the propensity of support by almost 4 percentage points. Military expenditures negatively affect the support of democratic values, and so does the existence of oil in the country. Here, military expenditures may be seen as a proxy for a less democratic regime, so that the leaders there have higher incentives to rule using suppressive measures with a support of military force in the country (Mulligan, Gil and Sala-i-Martin, 2004).

As for the individual factors, both secondary and higher education appear to be very important factors with a positive impact on the satisfaction with democracy. This finding follows the literature (Barro, 1999; Przeworski et al., 2000; Glaeser et al., 2004). In our results, people with secondary or higher education degree showed 10 and 18 percentage points higher propensity of support, respectively. Age also seem to matter: positive perception of democracy is specific to those aged 18-54, compared to the older generation, which goes in line with the explanation that senior citizens are more conservative than younger citizens. We also observe a negative significant coefficient on female gender, which may, perhaps, be related to women being more conservative than men.

Subjective relative income measure (answer to the question “to which income quintile do you think you belong to?”) has a positive impact on the support for democracy. Surprisingly, individuals from middle-income group have a more positive attitude than those who regard themselves as rich. Employment status is positively correlated with the support for democracy. Moreover, self-employment and employment in the public sector have a larger effect on the propensity of positive attitude to democratic values than employment in the private sector.

Divorced and widowed people expressed less support for democracy than single individuals, which might signal some dissatisfaction that impacts on personal attitude. Urban residency is positively correlated with the support of democracy. The same relationship is present for the risk tolerance of an individual. Finally, inclusion of a subjective measure of life satisfaction brought some changes to the general picture. It appeared that those who are satisfied with life strongly support the democratic values and such mentality raises the propensity of support by 7 percentage points. Moreover, inclusion of this variable makes the effect of being rich insignificant.

To sum up, the results showed that economic performance of the country described by various macroeconomic indicators has a serious impact on individual’s perception of democracy and, most probably, of other forms of government. At the same time individual factors also influence people’s satisfaction with the authorities. Thus, individual support of a political system is based on the results of performance of both the individual and the country.

References

Barro R. 1999. “Determinants of Democracy.”Journal of Political Economy 107, #S6.
Clark A. and Oswald A.J. 1994.“Unhappiness and Unemployment.”EconomicJournal104.
Clark A., FrijtersP. and Shields M. 2008. “Relative Income,Happiness and Utility: An Explanation for the Easterlin Paradox and Other Puzzles.” Journal of Economic Literature46,# 1.
DiTellaR., MacCulloch R.J., Oswald A.J. 2001. “Preferences over inflation and unemployment: Evidence from surveys of happiness.”American Economic Review91.
Easterlin R. 1995. “Will Raising the Incomes of All Increase the Happiness of All?”Journal of Economic Behavior and Organization27, # 1.
Glaeser E., La PortaR., Lopez-de-SilanesF. and ShleiferA. 2004.“Do Institutions Cause Growth?” Journal of Economic Growth.9, #3.
Mulligan C.B., Gil R. and Sala-i-Martin X. 2004. “Do Democracies HaveDifferent Public Policies than Nondemocracies?” Journal of Economic Perspectives18, #1.
Papaioannou, E. and Siourounis G. 2008.“Economic and Social Factors Drivingthe Third Wave of Democratization.” Journal of Comparative Economics36, #3.
Prezworski A., Alvarez M., Cheibub J. and LimongiF. 1996. “WhatMakes Democracy Endure?” Journal of Democracy 7, #1.
Stevenson, B. and Wolfers, J. 2008. “Economic Growth and SubjectiveWell-Being: Reassessing the Easterlin Paradox.” Brookings Papers on Economic Activity 1.
Wagner A.F. andSchneider F. 2006. “Satisfaction with Democracy and the Environment in Western Europe: A Panel Analysis.” IZA Discussion Papers 1929, Institute for the Study of Labor (IZA).

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

The Application of Composite Leading Indicators on the Single Economic Space Economies

Posted on February 10, 2014 | Policy Brief

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This brief is based on a CEFIR research project aimed at the short-term forecasting of socio-economic development of the member-countries of the Single Economic Space (SES), conducted for the Eurasian Economic Commission in 2013. This project focused on compiling composite leading indicators that could allow policymakers to identify phases of a business cycle and to forecast its turning points. We suggest a methodology for the selection of components of the Composite Leading Indicators (CLIs) for industrial production, and apply this methodology to predict industrial production in SES member states. Our methodology performs well for Russia and Kazakhstan, and slightly less so for Belarus.

The Charity of the Extremely Wealthy

Posted on January 27, 2014 | Policy Brief

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Analyzing data from the Giving Pledge (a public pledge to give away at least half of one’s fortune during one’s lifetime, launched by Bill Gates and Warren Buffett in 2010) and the Forbes billionaires’ list, I find that self-made billionaires are substantially more likely to give away large amounts of money, than do billionaires who inherited their money. Policy makers in many emerging markets with ‘new’ billionaires thus better quickly modernize their charity laws.

In 2010, two billionaires Bill Gates and Warren Buffett launched the Giving Pledge, a public pledge to give away at least half of one’s fortune during one’s lifetime (http://givingpledge.org/), which by now has been signed by 114 people. 114 are not much, you might think, and you might want to add your own name to the list. But, unfortunately, not everybody is invited to make this pledge. Gates and Buffet focus only on the extremely wealthy people: 85 of the signatories of the pledge are among the 1426 billionaires identified by Forbes in 2013, and most of the others were on Forbes’ billionaire list in earlier years. Of these 1426, 135 billionaires come from Central and Eastern Europe or the Former Soviet Union (see table I)

Worldwide, about 6% of billionaires (85/1426) have made this pledge. Among the signatories is one Russian billionaire, Vladimir Putanin, and one Ukrainian billionaire, Victor Pinchuk, which makes Ukraine score above average, with one out of ten, or 10% of Ukrainian billionaires signing.

Table 1. Number of 2013 Forbes Billionaires from the Former Soviet Union

	# 2013 Forbes Billionaires	# of Selfmade	Giving Pledge	Name of Signatory
Russia	110	110	1	Vladimir Potanin
Ukraine	10	10	1	Victor Pinchuk
Kazakhstan	5	4	0
Czech Republic	4	4	0
Poland	4	4	0
Romania	1	1	0
Georgia	1	1	0

In my most recent working paper, Claire Monteiro of Georgetown University and myself investigate whether it is possible to explain why these 6 % have signed, and the other 94% have not (yet) signed the Pledge. Or to put it in a more interesting way, why Putanin and Pinchuk signed but the other CEE/FSU oligarchs have not.

We investigate this question by analyzing whether generous billionaires have specific characteristics in common, characteristics that not so generous billionaires do not have. Doing this is possible because Forbes publishes not only a ranking of billionaires, it also provides background information about each billionaire like the billionaire’s education, age, how many children (s)he has and so on.

My analysis shows that three factors have a significant effect on the chance that a billionaire will be generous. First, a billionaire who is self-made is about three to four times more likely to sign than a billionaire who inherited his/her billion(s). This finding that how one earned one’s money affect how one spends this money is consistent with University of Chicago professor Richard Thaler’s ‘mental accounting’ theory and with earlier research showing that the propensity to consume is bigger if income received is framed as a bonus rather than if it is framed as a rebate, and the research showing that windfall gains (money won in a lottery) is more readily consumed than non-windfall gains (money for which one had to work). Note that all but one billionaire from the CEE/FSU are categorized by Forbes as self-made.

Second, billionaires with more money are more likely to sign the Giving Pledge and promise to give away half their fortune – for example, compared to an average billionaire who has about 4 billion dollar in estimated net worth (like Victor Pinchuk), a billionaire with an estimated net worth of about 15 billion dollars (like Vladimir Potanin) is roughly 50% more likely to promise to give away half of her/his fortune. Third, billionaires whose fortune comes from the technology/telecommunications industry are about twice as likely to announce that they will give away at least half of their fortune, compared to billionaires from other sectors.

The influence of other factors is small and less precisely estimated: older billionaires tend to be more likely to sign (possibly because being closer to the end of one’s life makes one think more about what one wants to leave behind), as do those who have more children (maybe because having more children makes it more likely that the inheritance will lead to fights among family members) or those having a Ph.D. Moreover, billionaires from the food and retail industry tend to be less likely to sign than those from the metallurgy industry.

Taken together my model predicts for Ukraine that Victor Pinchuk is the Ukrainian billionaire who is most likely to sign (4% probability), being 10 times more likely to sign than Yuriy Kosiuk (the Ukrainian billionaire who is least likely to sign with 0.4% probability). The difference in estimated net worth (3.8 billion versus 1.6 billion), age (52 versus 44), the number of children (4 versus 1) and education (Ph.D versus bachelor), and the sector in which they are active (metals and mining versus food and retail) explain this difference in probability. Victor Pinchuk is also about 30% more likely to sign than Rinat Akhmetov – while the latter has a higher estimated net worth (15.4 billion versus 3.8 billion), the effect of education (bachelor versus Ph.D), age (46 versus 52) and children (2 versus 4) play in favor of Victor Pinchuk, outweighing the wealth effect.

While it is definitely fun to do these kinds of computations, my research also has serious implications. The fact that inherited billionaires are much less charitable than the self-made billionaires means that academics should not assume that ‘all money is equal’ as they typically do – how you acquire money affects what you will do with it. It also implies that the countries from CEE/FSU with lots of ‘new’ wealth should modernize their charity laws quickly – once the self-made billionaires pass their wealth on to their children, it will become much more difficult to turn this massive wealth into charity.

▪

References

Tom Coupé and Claire Monteiro, The Charity of the Extremely Wealthy, Kyiv School of Economics, Discussion Papers 51.

* A version of this policy brief has been published in Russian at Forbes.ua.

Putting the “I” Back in Team: The Rise of International Teams in Science

Posted on January 20, 2014 | Policy Brief

In this policy brief, I discuss the increasing prevalence of international teams in the production of scientific knowledge. I outline several potential factors that may explain these trends and discuss recent evidence from an original survey of coauthors on scientific papers regarding their collaboration behavior. Finally, as a notable example of increased international collaboration, I discuss the increase in scientific collaboration between Russia and the US after the end of the Cold War.

The Increase in Collaboration and Internationalization of Teams

Teams are becoming more prevalent in science. Both the share of papers produced by teams and the number of scientists working on scientific papers has increased in recent decades (Wuchty, Jones and Uzzi, 2007). Economic theory suggests that scientific research is becoming increasingly collaborative since the frontier of scientific knowledge has become more complex and specialized so that more researchers are needed to combine their expertise to make advances (Jones, 2009). Team members are also becoming more geographically dispersed: the share of papers resulting from international collaborations has increased, and within the US, scientists today are more likely to have coauthors located in a different city than before (Freeman, Ganguli and Murciano-Goroff, 2014).

These trends can be seen clearly in the graph below from the National Science Board’s Science and Engineering Indicators 2012. It shows the share of both world papers and US papers from 1990-2010 that are coauthored, coauthored with domestic coauthors only, and coauthored with at least one international coauthor. Collaboration in general and international collaboration have been increasing steadily since 1990 both in the world and in the US. However, for the US, the share of domestic-only collaborations has plateaued, while it is increasing in the rest of the world. In a recent Nature article, Adams (2013) shows that this trend similarly holds for other Western countries (United Kingdom, Germany, France, the Netherlands, Switzerland), while for emerging economies (China, India, South Korea, Brazil, Poland), domestic collaborations are also increasing.

Figure 1. World and US Trends in Scientific Collaboration, 1990-2010

Source: From National Science Board (2012)

Why has Science Become More International?

There are many potential reasons for the recent increases in international collaboration. An important factor has likely been the spread of the scientific workforce and R&D activities throughout the world (Freeman, 2010). The growing number of science and engineering PhDs in developing countries, some of whom are international students and post-docs returning to their home countries has expanded the supply of potential collaborators around the world (Scellato, Franzoni, and Stephan, 2012). Another factor is funding that has shifted scientific production towards international teams, as increased government and industry R&D spending in developing countries and grant policies by the European Union and other countries have supported international cooperation.

The lower cost of travel and communication in recent decades has also reduced the cost of collaborating with people in different locations. For example, Agrawal and Goldfarb (2008) show how the expansion of Bitnet, the precursor to the Internet, led to increased collaboration between institutions within the US. Finally, the location of scientific equipment and materials, such as the CERN Large Hadron Collider, telescopes, or climatological data available only in certain parts of the world, have increased international collaboration, and in some fields, has made international collaboration a necessity.

Survey Evidence on Scientific Collaborations

In a recent paper, my coauthors and I present the results of an original survey we conducted of scientists regarding collaboration (Freeman, Ganguli and Murciano-Goroff, 2014). In August 2012 we conducted a web-based survey of the corresponding authors of scientific papers with at least one US coauthor published in 2004, 2007, and 2010 in the fields of Nanotechnology, Biotechnology, and Particle Physics.

We customized each survey to ask the corresponding author about the collaboration and individual team members. The survey questions asked about how the team formed, how it communicated and interacted during the collaboration, the contribution of each coauthor, types of research funding, and the advantages and disadvantages of working with the team. We received 3,925 responses, so that our response rate was approximately 20%.

The survey also asked the respondent which country each coauthor was “primarily based in during the research and writing” of the article. This gives us a more accurate measure of whether teams are international than can be typically gleaned from publication data, which are based on author affiliations at the time of publication. Defining international teams from author affiliations alone can produce errors if affiliations change between the time the research was undertaken and the time of publication, or because some people have affiliations from more than one country.

Our analysis of the survey data uses the respondents’ information to define US collocated, US non-collocated and international teams. One of our key results is that face-to-face meetings continue to play an indispensible role in collaborations: most collaborators first met while working in the same institution. Teams also reported that while carrying out the research, they communicated often through face-to-face meetings, even with coauthors from distant locations.

Figure 2 below displays how the corresponding author responded about how they first met their team members. It shows that former colleagues play a very important role in the formation of international teams, followed by former students, conferences and institution visits, which equally contribute. The graph also shows the similarity between international teams and US non-collocated teams in how coauthors met. For other survey questions, our analysis also shows similarities between international teams and US non-collocated teams, suggesting that the salient issues are more about geography in general rather than necessarily about national borders.

Figure 2. How Coauthors First Met

Source: From Freeman, Ganguli and Murciano-Goroff (2014)

Another key finding from our survey is that the main reason for most collaborations, whether domestic or international, is to combine the specialized knowledge and skills of coauthors. We also asked the corresponding authors their views of the advantages and challenges of their collaboration. The most often cited advantage for all types of collaborations was “Complementing our knowledge, expertise and capabilities” and “learning from each other”. For the challenges, US non-collocated and international teams tended to agree more that there was “Insufficient time for communication”, “Problems coordinating with team members’ schedules”, and “Insufficient time to use a critical instrument, facility or infrastructure”, but international teams did not report these problems more often than US non-collocated teams. Where international teams differed is that these teams were the most likely to agree that their “research reached a wider audience”.

International Collaboration After the End of the USSR

A small but significant part of the increase in international collaboration since the 1990s can be attributed to the end of the Cold War. In “Russian-American Scientific Collaboration” (Ganguli, 2012), I examine trends in international collaboration by Russian and US scientists since the end of the USSR. Given the nature of the Cold War and restrictions on travel and communication with the West, I show that there was a dramatic increase in the number of publications with at least one Russian and a US coauthor from 1985 to 2005.

In addition to the lifting of travel and communication restrictions, there are several factors that contributed to the surge in collaborations between American and Russian scientists after the end of the USSR. First, at the level of the Russian government, there was a switch to a more open and collaborative approach to science. Part of this effort included establishing international centers for research in Russia aimed at integrating Russia into the global science community. Another important factor facilitating collaborations with Western researchers were foreign grant programs. The large increase in the emigration of Russian scientists in the 1990s to the West also contributed to international collaboration. After emigrating, many Russian scientists maintained close links to their colleagues in Russia, and coauthored papers with their former colleagues, which are counted as internationally coauthored publications.

While many of these factors have aided international cooperation after the end of the USSR, there have also been significant challenges that made cooperation difficult. Some of these challenges in the early 1990s included the political instability, organizational turnover making long-term funding agreements difficult to implement, difficulty transferring funds due to the underdeveloped banking system, high taxation and customs duties, lack of effective intellectual property rights, poor infrastructure, lack of a shared language (both linguistic and cultural), and external regulations (see further discussion in OECD, 1994). However, many of these challenges have now been overcome, leading to the continued increase in international collaboration between Russian and US scientists.

My analysis in Ganguli (2012) shows that the increase in Russian-American collaboration was more pronounced in some fields of science versus others, particularly in Physics. Figure 3 shows that the bulk of the articles published with Russian and American coauthors were Physics articles, with a sharp increase occurring immediately after 1991.

Figure 3. Russia-United States Publications By Field, 1985-2005

Source: From Ganguli (2012)

While some of the differences across the fields can be attributed to the number of scientists active in these fields, there are also other potential contributing factors. For example, it may be that there was greater emigration of scientists from certain fields abroad, and links between emigrants and those who remained in Russia persisted. Graham and Dezhina (2008: 24) suggest that over 50 percent of emigrants were physicists and mathematicians. Another reason may be that international collaboration was more important in some fields due to the knowledge or resources needed to conduct research during the economic crisis of the 1990s. As Wagner Brahmakulam, Peterson, Staheli, and Wong (2002) point out, physics research received significant amounts of US government funding for international collaboration, partly because expensive equipment that is needed and through collaboration, countries could share costs. Also, physicists from many countries often meet and work together at international research centers like CERN. Moreover, in some fields, the US and Russian governments shared priorities in funding international cooperation, like biomedical and health sciences, energy, physics, while there were gaps in some areas where Russia devoted resources and the US did not, like chemistry (Wagner et al. 2002: 24). Graham and Dezhina (2008: 141) also discuss how Western colleagues benefited from working with Russians especially in fields like zoology, botany and the earth sciences, since the Russian colleagues provided access to data from unique regions not available previously.

Support for International Teams?

This policy brief has discussed some reasons for the increase in international scientific collaboration and related empirical evidence, including insights from collaboration after the end of the USSR. The growth in collaboration and the geographic dispersion of teams is likely to continue; the frontier of scientific knowledge will become more complex and specialized, so that an even greater numbers of researchers will be needed to combine their expertise, and they are likely to be spread across increasingly distant locations.

These trends raise many complex issues for policymakers. For some countries, international collaboration may be the only way to sustain the science sector as the frontier of knowledge becomes more complex and resource-intensive. For some, international collaborations may increase the emigration of home-grown talent to wealthier countries. To what extent international collaboration should be supported, and how, will be important policy questions going forward. Typically, funding for international projects has been the main policy lever, and the Russian experience suggests that grant programs did play a critical role in that case. As our survey evidence in Freeman, Ganguli and Murciano-Goroff (2014) suggests, face-to-face meetings are especially important in forming and sustaining international collaborations. Thus, funding mechanisms that include provisions for research stays and face-to-face meetings may be the most effective means for fostering international collaborations.

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References

Adams, J. (2013). “Collaborations: The Fourth Age of Research.” Nature, 497(7451), 557-560.
Agrawal A, Goldfarb A (2008). “Restructuring Research: Communication Costs and the
Democratization of University Innovation,” American Economic Review, 98(4):1578-1590.
Freeman, Richard B. (2010). “Globalization of Scientific And Engineering Talent: International Mobility of Students, Workers, and Ideas and The World Economy.” Economics Of Innovation And New Technology, Volume 19, issue 5, 201 pp. 393-406.
Freeman, Richard B., Ina Ganguli and Raviv Murciano-Goroff (2014). “Why and Wherefore of Increased Scientific Collaboration,” NBER Working Paper No. 19819, Issued in January 2014.
Ganguli, Ina (2012). “Russian-American Scientific Collaboration” in Y.P. Tretyakov (ed), Russian-Аmerican Links: Leaps Forward and Backward in Academic Cooperation. St. Petersburg, Russia: Nestor-Historia, pp. 120-135.
Graham, Loren and Irina Dezhina (2008). Science in the New Russia: Crisis, Aid, Reform. Bloomington and Indianapolis: Indiana University Press, 2008.
Jones, Ben (2009). “The Burden of Knowledge and the ‘Death of the Renaissance Man’: Is
Innovation Getting Harder?” Review of Economic Studies, 76:283-317.
National Science Board (2012). Science and Engineering Indicators 2012. Arlington VA: National Science Foundation (NSB 12-01).
National Science Board (2006). Science and Engineering Indicators 2006. Arlington VA: National Science Foundation (NSB 06-01).
OECD (1994). Science, Technology, and Innovation Policies. Federation of Russia. Paris: Organisation for Economic Co-operation and Development, 1994.
Scellato, G., Franzoni, C., & Stephan, P. (2012). “Mobile Scientists and International Networks,” NBER Working Paper 18613.
Wagner, Caroline, Irene Brahmakulam, D.J. Peterson, Linda Staheli, and Anny
Wong (2002). U.S. Government Funding for Science and Technology Cooperation with Russia.
Santa Monica, CA: RAND Corporation, 2002.
Wuchty, S., Jones, B. F., & Uzzi, B. (2007). “The Increasing Dominance Of Teams In Production Of Knowledge.” Science, 316(5827), 1036-1039.

Tajikistan Joining the Customs Union of Russia, Belarus and Kazakhstan: Pros and Cons

Posted on December 23, 2013 | Policy Brief

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Authors: I.A. Densiova, A.M. Malokostov, and N.A. Turdyeva, CEFIR

In this brief we summarize the results obtained in a CEFIR research project on the economic impact of Tajikistan joining the Customs Union of Russia, Belarus and Kazakhstan conducted for the Eurasian Development Bank in 2013 (EBD, 2013). We argue that integration has to be comprehensive to be mutually beneficial: indeed, trade effects are marginal, and the highest stakes are at migration regulation in the CU member-countries and the investment opportunities in Tajikistan.

Academic Inbreeding in Ukraine

Posted on December 9, 2013 | Policy Brief

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In Ukraine, having a university degree only provides a noisy signal of one’s productivity, which means social ties and personal relations play a relatively more important role in the Ukrainian economy in general. Therefore it should not come as a surprise that inbreeding is very common in Ukrainian academia; for example, about 50% of faculty obtained their university degree from the university that employs them. Given the absence of clear “quality signs” for fresh university graduates, inbreeding can be viewed as a second-best option for hiring decisions. Our econometric analysis shows that inbred faculty does not differ in its (observable) quality from non-inbred faculty. At the same time, ceteris paribus, inbred faculty has somewhat lower salaries. We also find that the extent of inbreeding is slightly higher in universities with a “national” status and lower in very small universities (of less than 1000 students).

Academic inbreeding is the practice of universities hiring their own graduates to academic positions. Inbred faculty is thus faculty employed at the same university from which they graduated. Inbreeding implies a low level of competition for faculty vacancies possibly resulting in low quality hires. However, inbred faculty can be cheaper, reduce the chance of a mismatch between university and faculty member, and can be better “tailored” to the needs of a certain university or discipline. For some specific narrow disciplines inbreeding can be the only way to hire faculty (for example, if only one university in a region provides courses in a certain discipline, teachers of that discipline most probably will be inbred). In research, inbreeding can help to pass on tacit knowledge but it can also prevent “fresh blood” and new ideas from entering into the university. In developed countries, universities usually try to limit inbreeding in order to first, “disseminate” their graduates and earn a good reputation, and second, hire the best graduates on the market through an open competition. In less developed countries, inbreeding is more common because of the higher role of personal relations in hiring decisions in general.

Although very widespread, academic inbreeding in Ukraine has received little or no attention from researchers or policy makers. Data on inbred faculty is similarly scarce. There is only one recent exception – in the summer of 2013, the Centre for Social Research surveyed about 400 university professors. The survey contains information on a wide range of aspects of faculty employment, such as working hours, publications, participation in conferences, income size etc., including the question on whether a person works at the same university from which (s)he graduated. We used this data to do an econometric analysis of the factors that determine inbreeding and the impact of inbreeding. We complemented the survey data by data from an online questionnaire we distributed among KSE graduates whom we know work in academia, their acquaintances and among the network of KSE partners who work in academia (a total of 59 responses).

Causes of Inbreeding

Besides providing a person with knowledge and skills necessary for a white-collar job, education has several other functions. One of them is signaling, i.e. people who successfully graduate from an educational institution should have higher abilities (ceteris paribus) than those with lower grades or dropouts. This function of education is almost entirely lost in Ukraine because of widespread corruption. In Ukraine, good students can obtain good skills and knowledge together with good grades. However, “bad” students can obtain the same grades for money: besides paying professors for exam grades, students can buy a course paper, a diploma thesis and even a doctoral dissertation. Cheating and plagiarism are also very widespread; not only in students’ work, but also in academic research. Hence, based on the diploma alone, a potential employer will have difficulties telling apart a “good” student from a “bad” one. Therefore, other screening mechanisms are relatively important in Ukraine.

Many private-sector employers, for example, will pay more attention to previous work experience and personal recommendations than formal education. For example, the ULMS-2007 survey shows that from 48% to 68% of people found a job through relatives or friends, which is comparable to the extent of inbreeding found by this study in academics (48.6% in the CSR-2013 survey, 68% in our online survey). This situation pushes students, who do not expect to be hired by relatives or friends, to find a full-time job already in the first or second year of studies, providing them with both incentives and funds to “buy” a diploma. This creates a “vicious circle” – the low value of a diploma makes employers looking at previous work experience, and the need to gain that experience further devalues diplomas.

For universities, “previous work experience” is the student’s performance during their studies. Hence, by inbreeding their own students, universities reduce uncertainty, which they would be facing if they looked for needed candidates on an open market. As the academic career of a person develops, (s)he can develop additional signals of his/her “quality”; first of all, scientific degrees (Candidate of Sciences, Doctor of Sciences) and/or ranks (Docent or Professor) and connected to them publications in Ukrainian and foreign journals (with the last ones being much more valuable). Therefore, as we show, younger and less distinguished faculty (with shorter teaching experience and without a Doctor degree or Professor rank) is more likely to work at a university from which they graduated.

Estimation Results

Our econometric estimation showed that the extent of inbreeding does not depend on the quality of a university as measured by its rank in Ukraine. Inbreeding is less common in very small universities (of less than 1000 students), and is independent of the university size after this threshold. Universities with a “national” status have slightly higher level of inbreeding.

We also show that inbred faculty does not differ in “quality” (measured as the number of publications in Ukrainian and foreign journals and the probability to get a foreign fellowship) from other faculty, although, ceteris paribus, inbred faculty do get lower salaries.

Results from both the CSR-2013 survey and our online questionnaire indicate that personal connections are very important both for entering a university and for further promotion. Usually an academic career starts when a person begins his/her Ph.D. studies; at the same time, (s)he starts working as an assistant or a lecturer (when admitting students to Ph.D. studies, universities prefer their own MA graduates). To move up the career ladder, a person should earn scientific degrees or ranks, have certain duration of teaching experience and a minimal required number of publications (all the formal requirements for certain academic positions are stipulated in a Decree of the Cabinet of Ministers). According to the law, currently there is no tenure system, and faculty is hired with one- three- or five-year contracts (the longest contracts can last up to seven years, but only in the universities with a “national” status).

Hiring Procedures at Universities

When a vacancy is open (e.g. a contract expires), a university should make an announcement in a pedagogical journal and/or on its website; then candidates should be interviewed at a chair meeting, and a selected candidate should be approved by the faculty dean. A candidate should have a required teaching experience and publications. There are about 1500 journals on the list of Higher Attestation Commission (the body that organizes the dissertations defense), which means that practically all universities issue at least one journal, and very few of them are refereed. This means that publishing in the home university’s journal is the cheapest and easiest way for a faculty member to get the needed number of publications. Therefore, publications are very often of very poor quality and do not contain any real research, especially in social sciences. To mitigate this problem, the Ministry of Education and Science introduced a new requirement for scientific degrees – since 2013, 20% of publications should be in foreign-refereed journals.

When hiring, all formal requirements and procedures are typically observed – a competition is announced, the chair meeting held, the candidate has the required duration of work experience and the number of publications (their quality is discussed above). However, in reality there is very often just one candidate “for” whom the vacancy is opened, and outside people, even if they apply for a vacancy, are ignored. Usually a chair meeting supports the opinion of a chair head, but either way, a dean could overturn a chair meeting decision, so despite seemingly open procedures, in reality a person’s employment depends on his/her relations with a chair head and/or a faculty dean. Studying at a university is the most common but not the only way to establish these relations. A person can get acquainted with a chair head or a faculty dean at a conference, be his/her relative or friend, or be recommended by his/her relative or friend.

Such a widespread reliance on personal connections is a legacy from the Soviet times when personal ties replaced market mechanisms, and students were allocated to their first workplaces rather than hired on a competitive basis. Since universities were situated in cities, staying at a university implied a better living environment, and salaries were also good. Therefore many students tried to stay at their alma mater by establishing good relations with a chair head or a faculty dean. Nowadays, university salaries are not competitive so students staying at universities are not necessarily the best ones. However, they are not the worst ones either because otherwise they would not be offered a position.

Concluding Remarks

In Ukraine, academic inbreeding provides universities with a relatively cheap and well-prepared workforce. On the other hand, it also fosters isolation of universities and conservation of existing “traditions” – whether good or bad. Given low academic mobility of both students and professors, this situation prevents dissemination of knowledge and lowers competition, which necessarily leads to degradation.

Currently, inbreeding is not on the agenda of either researchers or policy makers. In fact, no one seems to have considered it as a problem. Perhaps, it will not be discussed as a problem any time soon because there are many other “bigger” problems in Ukrainian higher education. To name a few, these are:

high centralization and insufficient level of university autonomy;
low salaries and high teaching workload of professors;
low extent of university research and very low quality of the existing research, especially in humanities and social sciences;
high corruption and low standards of studying and research work (ubiquitous cheating and plagiarism);
low sensitivity of educational programs to the needs of modern economy.

Perhaps, introduction of formal limits on inbreeding (setting a quota for both MA graduates admitted to Ph.D. programs and for Ph.D. graduates hired to teaching positions at the same university) could bring some “fresh air” into the system. This measure would extend the pool of candidates available to a university and introduce an element of competition between them. It would also create incentives both for universities to improve their Ph.D. programs and for students to put greater effort into studies.

References

Bilyk, Olga and Iuliia Sheron (2012) Do Informal Networks Matter in the Ukrainian Labor Market? EERC Working paper No 12/11E.
Coupe, Tom and Hanna Vakhitova (2010). Recent Dynamics of Returns to Education in Transition Countries, KSE/KEI Working paper.
Osipian, Ararat (2009). Corruption and Reform in Higher Education in Ukraine, Canadian and International Education, vol. 38, pp. 104-122.
Shaw, Marta, Chapman, David and Nataliya Rumyantseva (2011). The Impact of the Bologna Process on Academic Staff in Ukraine, Higher Education Management, vol. 23, pp. 71–91.
Stephens, Jason, Romakin, Volodymyr and Mariya Yukhymenko (2010). Academic Motivation and Misconduct in Two Cultures: A Comparative Analysis of US and Ukrainian Undergraduates, International Journal for Educational Integrity, vol. 6, pp. 47–60.