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The Tragedies in the Soviet Countryside of the Early 1930s: Research Frontiers and Rival Interpretations of the Famines
In November 2018, Viktor Kondrashin, expert historian on the Soviet famine in the early 1930s, organized a workshop at the Institute for Russian History of the Academy of Sciences (IRI RAN). Contributions by Russian and Ukrainian as well as British, Irish and Swedish historians summed up their research projects concerning the famines in Russia, Kazakhstan and Ukraine in 1929–1933. They highlighted the opposing interpretations of the causes of these famine-stricken regions. They also scrutinized the recent debates in the West of Anne Applebaum’s book Red Famine. Motivated by this enlightening discussion, this brief offers a short overview of the history, and contemporary state, of the Soviet famine debate.
In this brief, my purpose is to describe research frontiers concerning the Soviet famine in the early 1930s, based on my participation in the workshop at the Institute of Russian History of the Academy of Sciences in November 2018. Starting with a short historiographical background, I give examples of important archival contributions. Then I present contributions by individual scholars and their interpretations, concerning the causes of the 1929–33 famines in Soviet Russia and Ukraine. The separate famine in Kazakhstan 1929–30 was caused by forced sedentarisation and disbanding of the Kazakh people’s nomadic life; it claimed a proportionally higher number of deaths but would require quite a different analysis.
The collectivization of the peasantry was enforced in 1930–31. An initial abundant harvest 1930 seemed as a success for the kolkhoz system. It appeared to supply enough food for city dwellers and industrial workers as well as Red army soldiers. It also seemed to permit a large export of grain. This, and raw material exports in general, was crucial for the Soviet Union as hard currency generators for the import of machinery from the West. The five-year plan 1928–32 had overestimated how much these export commodities would generate. During the Great Depression, terms of trade turned dramatically against the Soviet export commodities. Likewise, the Soviet leadership had not foreseen how intensively collectivization would be resisted by peasants. Not only were many farming processes neglected in the new kolkhozes. Many peasants chose to slaughter horses, rather than giving them to the kolkhozy. The production of tractors could not yet substitute the loss of draught animals by ca. 15 per cent in 1930–31.
Weather conditions worsened and resulted in lower harvests in 1931 and 1932. A severe famine was imminent. Grain exports were cut. Rationing was severed. Although grain collection quotas were lowered in 1932, the greater famine severely hit the grain-producing regions in Ukraine, but also Kuban and Lower Volga regions and Northern Caucasus. The overall Soviet population losses by 1933 are estimated as 6–7 million, with approximately 3.5 million famine-related deaths in Ukraine.
This famine was a taboo topic in the Soviet era. The authorities managed to divert attention from the catastrophic consequences of collectivization and rapid industrialization. After World War Two numerous oral witnesses’ collections were gathered in the Ukrainian diaspora in Canada. In the late 1980s, the British historian Robert Conquest wrote his pioneering study Harvest of Sorrow. An accompanying TV documentary film made the general public in the West aware of the 1930s famine in the USSR.
Before that, during the “Thaw” in the early 1960s, established Russian historians had got Nikita Khrushchev’s directive to study primary sources concerning Stalin’s forced collectivization. However, their dramatic findings and frank book manuscript on the real costs of the collectivization was prohibited in 1965 by Khrushchev’s successors. Only during glasnost could these specialists, with Viktor Danilov (1925 – 2004) as one of the most visionary researchers, again analyze the agrarian history of the Soviet Union in the late 1920s and early 1930s.
Danilov’s primary concern was to make as many archival documents as possible available. He guided archivists and researchers to examine all relevant, central as well as regional, archives. Numerous documentary volumes, articles and monographs were produced, notably the 5-volume project The Tragedy of the Soviet Countryside, which showed both the excesses of the forced collectivization in 1930-33, and the famine conditions all over the USSR. Danilov also cooperated with other archivists to compile a documentary of how the secret police’s local officers in the countryside – often more accurately and frankly the communist party organs – did indeed describe the real situation in the villages. This project The Soviet Countryside as seen by VChK-OGPU-NKVD covers the whole interwar period 1918–39, and added unexpected perspectives on the dramatic period. In particular, it proves – contrary to what is sometimes believed – that Stalin and the leadership were very well informed of the dire situation that resulted from their policy decisions (see Samuelson 2007).
Today, we have not only oral history – eye-witnesses and relatives of the famine victims – but also a sufficiently reliable source base to describe all aspects of the transformation in the countryside. What remains however, is to set all this new empirical material into its context and to explain what caused the famine years 1929–1933? Which were its specific traits in different parts of the Soviet Union?
A most authoritative Russian expert on these topics is Viktor Kondrashin. He has continued the projects started by Danilov and published several archival documentary collections. The first is Famine in the USSR 1930 – 1934 with almost 200 facsimile archival documents. A larger archival publication by Kondrashin in four volumes (2011–13) expands the empirical basis for researchers. Of particular interest are those on the famine in various parts of the USSR. Kondrashin’s recent monograph The 1932-1933 Famine: The Tragedy of the Russian Countryside (2018) outlines his interpretation that the grand famine was the unexpected result of the collectivization. It struck in many regions of the Russian republic. It was not directed specifically against any ethnic group. Grain collection from the kolkhozes in 1931 and 1932 was brutally enforced. The Soviet leadership lacked information in 1932 concerning the real harvest. Only when the famine grew catastrophic in the winter of 1932/33, did the authorities change their policies: lowered grain requisition quotas, sent seed grain back to many regions, tried to evacuate suffering children from famine-struck regions. In short, that millions of people in Soviet Ukraine as well as in Russia died during the famine years was an unforeseen effect of a policy. In other words, it was not an intentional, genocidal policy directed towards the Ukrainian or any other people but a tragedy for all the peoples of the USSR.
In the West, major research on Soviet agriculture was done by Robert Davies and Stephen Wheatcroft. Their monograph The Years of Hunger (2004) is translated into Russian. It provides empirical data on all agricultural branches. Their conclusion is that “the Soviet leadership was struggling with a famine crisis which had been caused by their wrongheaded policies, but was unexpected and undesirable”. Davies and Wheatcroft emphasize that the changing policies in 1932/33 (lowering of grain collection, redistribution back to the peasant and shelter for famine-stricken youngsters) indicate that there was not any intention to “apply famine as a terror-weapon” as Conquest and many Ukrainian historians have stated. Stalin and other leaders made concessions to Ukraine in procurements, and were clearly trying to balance the subsistence needs of Ukraine and other regions. They cut down grain exports in 1932 to a minimum. But they did not acknowledge the famine to the West, asking for relief as Lenin had done in 1921–22, for fear of losing further in credibility worth. Also important to consider is that the Soviet leadership was particularly worried over a possible further Japanese expansion towards the Soviet Far East, after the takeover of Manchuria in 1931-32. This factor precluded any more use of the state reserves of grain (for the armed forces in case of war), to alleviate the situation in the starving areas.
Since the late 1990s, the Ukrainian historians have made different interpretations. The general famine all over the USSR is acknowledged as a consequence of Stalin’s policy. The climate as well as crop diseases led to shrinking harvests in 1931 and 1932. However, the famine that struck Ukraine in 1932/33 was essentially different. It is called Holodomor from holod – famine and morit’ – to kill. This interpretation presumes a genocidal intention of the Soviet leadership against the Ukrainian people, and its peasantry in particular. Since 2006, this interpretation is state law in the Ukraine and stresses that Holodomor was deliberately planned and executed by the Soviet regime in order to systematically destroy the Ukrainian people’s aspirations for a free and independent Ukraine, and subsequently caused the death of millions of Ukrainians in 1932 and 1933. The Ukrainian Rada adopted the law Pro Golodomor 1932 – 1933 rokiv v Ukraïni (Закон України: Про Голодомор 1932–1933 років в Україні) on 28 November 2006, which consequently set out the exact juridical terms that give the established framework for historiography in the Ukraine.
It is testimony of the high standards in the Russian academic tradition that Kondrashin invited the prominent Ukrainian historian Stanislav Kulchitskii and the Canadian-based Roman Serbyn, and others from Ukraine, to contribute to the anthology The Contemporary Russian-Ukrainian Historiography on the Famine 1932 – 1933 in the USSR. Here the reader himself can study and compare their argumentation for the Holodomor-interpretation. They present a different set of empirical data from each theme in this ongoing debate, concerning both agricultural and demographic figures, as well as the Soviet Communist party’s decisions versus Ukraine in late 1932 – early 1933.
The decisive question accordingly remains which of the rival interpretations is most solidly confirmed by traditional methods on history as science. In other words, whether there was an intention from Stalin, from central and/or regional leaders, to cause or to aggravate – as a terror-instrument – the famine in the Ukraine. In addition, it remains to be decided whether or not the concept of genocide, as defined in the 1948 United Nations Convention, is applicable to the famine in the Ukraine and other parts of the Soviet Union. The genocide interpretation is rooted in an academic tradition that stretches from Conquest’s above-mentioned Harvest of Sorrow to more recent works, such as by Timothy Snyder Bloodlands: Europe between Hitler and Stalin, Norman Naimark Stalin’s Genocides and numerous articles by Andrea Graziosi among other historians in the West.
Mention should finally be done of Anne Applebaum’s Red Famine: Stalin’s War on Ukraine (2017) as a most detailed and vivid description of the sufferings of the Ukraine people in the early 1930s. Her book was very positively reviewed not only in the mass media, but also by academic scholars like Sheila Fitzpatrick. However, Fitzpatrick had obviously misread the book and praised it for its refutation of the genocide interpretation. This forced Applebaum to clarify that precisely the opposite was her case: The famine in the Ukraine was intentional and foreseeable by the Soviet leadership, whose intention it was to subdue nationalist aspirations. In turn, this rejoinder forced Fitzpatrick in a commentary to withdraw all her praise for the book!
Given this hot debate, it is not surprising that, in the academic community, it was felt that matters could not be put to rest without thorough arguments. The editors of Contemporary European History organized a solid roundtable on Soviet famines, with written essays by leading historians and specialists (Volume 27, Issue 3, August 2018, pp. 432-434). These concise essays, by N. Naimark, N. Pianciola, T. Penter, J.A. Getty, A. Graziosi, S. Wheatcroft and others may serve as the best introduction to a thorny historical theme that can otherwise be difficult to grasp, not least because of the often politicized nature of the debates.
The autumn 2018 seminar at IRI RAN in Moscow was one in a long row of similar events – conferences and workshops on the history of the collectivization of the peasantry, the dekulakization and repressions against peasant protests, and the famines in various Soviet republics in 1929 – 1934. Already in spring 2004, a landmark conference took place at IRI RAN, where Viktor Danilov and Stanislav Kulchitskii, as representatives of the Russian vs. the Ukrainian perspective, debated for a whole day (!), albeit without converging viewpoints. At that stage, they could sum up a decade of archival research and chisel out divergent points for further research. Over the last fifteen years, scholars in both countries have made great strides to deepen the empirical foundation, notably by detailed mapping of the harvests, demographic changes and other indicators even at the local level. This new level of knowledge was well reflected in the various contributions at the seminar and in the above-mentioned anthology Contemporary Russian-Ukrainian Historiography.
References
- Applebaum, Anne, Red Famine: Stalin’s War on Ukraine, New York: Doubleday, 2017.
- Applebaum, Anne, Reply to Sheila Fitzpatrick’s review of Red Famine, Facebook: https://www.facebook.com/anneapplebaumwp/posts/as-an-author-who-also-writes-reviews-i-generally-try-to-avoid-responding-to-revi/704110623118513/
- Conquest, R., The Harvest of Sorrow: Soviet Collectivization and the Terror-Famine, Oxford University Press, 1986.
- Danilov, V.P. et altere, eds., Tragediia Sovetskoi Derevni: Kollektivizatsiia i raskulachivanie, 1927 – 1939, (The Tragedy of the Soviet countryside: Collectivization and dekulakization), five volumes, Moscow: Rosspen, 1999–2004.
- Danilov, V.P. et altere, eds. Sovetskaia derevnia glazami VChK-OGPU-NKVD, 1918 –1939, (The Soviet countryside as seen by VChK-OGPU-NKVD, 1918–1939), four volumes, Moscow: Rosspen, 1998–2005.
- Davies, R.W. & Wheatcroft, S.G., The Years of Hunger: Soviet Agriculture, 1931–1933, Palgrave Macmillan, 2004; also as translation: Gody goloda: Sovetskoe selskoe khoziastvo, 1931–1933, Moscow: Rosspen, 2011.
- Fitzpatrick, Sheila, “Red Famine by Anne Applebaum review – did Stalin deliberately let Ukraine starve?”, The Guardian, 25 August 2017, see 2019-03-26: https://www.theguardian.com/books/2017/aug/25/red-famine-stalins-war-on-ukraine-anne-applebaum-review
- Golod v SSSR 1929 – 1934, (The Famine in the USSR, 1929–1934), Moscow: Mezhdunarodnyi Fond Demokratiia, 2011–2013.
- Kondrashin, V.V. ed., Sovremennaia rossiisko-ukrainskaia istoriografiia goloda 1932–1933 gg. v. SSSR, (The Contemporary Russian-Ukrainian historiography of the famine 1932–1933 in the USSR), Moscow: Rosspen, 2011.
- Kondrashin, V.V., Golod 1932–1933 godov: Tragediia rossiiskoi derevni, (The Famine in 1932–1933: The Tragedy of the Russian countryside), Moscow: Rosspen, 2018.
- Kondrasjin, V.V., “Hungersnöden i Ryssland och Ukraina 1932–33, in Samuelson, L. (ed.), Bönder och bolsjeviker: Den ryska landsbygdens historia 1902–1939, EFI/HHS 2007, p. 140 – 173.
- Kozlov, V.P., Golod v SSSR 1930–1934//Famine in the USSR 1930–1934, Moscow: Federalnoe Arkhivnoe Agentstvo, 2009.
- Kulchitskii, S.V., “Obshchii i regionalnyi podkody k istorii velikoi tragedii narodov Rossii i Ukrainy”, (The General and regional approach to the great tragedy of the peoples of Russia and Ukraine), in Sovremennaia…istoriografiia, (above), pp. 107 – 206.
- ”Roundtable on Soviet Famines”, Contemporary European History, vol. 27: 3, August 2018, see: https://doi.org/10.1017/S0960777318000279
- Samuelson, L., “Gammal och ny historieskrivning om den sovjetiska landsbygden – “Arkivrevolutionens betydelse sedan 1990-talet”, in Bönder och bolsjeviker: Den ryska landsbygdens historia 1902–1939, EFI/HHS, 2007, p. 26–41.
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 Polish 1999 Administrative Reform and Its Implications for Inclusive Regional Development
On 1 January 1999, four major reforms took effect in Poland in the areas of health, education, pensions and local administration. After 20 years, only in the last case does the original structural design remain essentially unchanged. We examine the implications of this reform from the perspective of the distance of municipalities from their regional administrative capitals. We show that despite fears of negative consequences for municipalities which ended up on the periphery with respect to their post-reform administrative centres, the reform did not result in slower socio-economic development in these regions. We argue that regional inclusiveness in the process of development is likely to be an important factor behind the stability of Poland’s administrative design.
Introduction
Four major reforms took effect on 1 January 1999 in Poland, substantially changing the structure of healthcare, education, the pension system and local government administration. The extent of the changes and the fact that all four reforms were implemented on the same day could in fact be considered as representing a symbolic final step of the Polish socio-economic transition which had started nearly ten years earlier. However, in 2019, twenty years after the reforms took effect, the originally introduced structural design remains unchanged in only one of the four areas – local government.
In a recent paper (Myck and Najsztub, 2019) we take a close look at the implications of the 1999 administrative reform treating it as a form of a “natural experiment” and analysing its consequences for socio-economic development dynamics in municipalities, which ended up on the periphery with respect to their post-reform administrative capitals. Using a broad set of indicators we find that the reform did not have significant negative consequences for these municipalities and ensured inclusive development at the regional level. This might be an important factor which has determined the longevity of the administrative design implemented in 1999.
The local administrative design in Poland before and after 1999
Major administrative reforms are relatively infrequent, which makes the scope and scale of the one implemented in Poland on 1 January 1999 a rather unique point of reference for analysis of potential implications of administrative restructuring. The reform went far beyond the administrative rearrangement of local government, as it was the culmination of a process that reintroduced local autonomy to the Polish political system.
The goal of the reform was to further decentralise political power and increase public finance transparency. The middle tier of local government – the counties (powiats) – was reintroduced as a body responsible for the administration of institutions beyond the scope of a single municipality (e.g. hospitals, secondary schools, public roads, unemployment). At the same time the number of top tier administrative regions – the voivodeships – was reduced from 49 to 16, and their responsibilities were focused on overall regional development, higher education, regional infrastructure and the prospective management of EU funds. In the end, the reform resulted in the formation of 16 voivodeships, 308 counties, 66 towns with county status and 2478 municipalities. This administrative division of Poland has been in place, with minor modifications, since 1 January 1999 (for details and comments, see Blazyca et al. (2002), Regulski (2003) and Swianiewicz (2010)).
The reform implied the loss of regional administrative capital status for 31 cities (administration in two voivodeships, Lubuskie and Kujawsko-Pomorskie, is split between two capitals), and for nearly 60% of municipalities it resulted in an increase in the distance to their regional administrative centre compared with the pre-reform arrangement. These features of the reform are illustrated in Figure 1. Cities marked in blue used to be administrative capitals before 1999, while those marked in red maintained their status after the reform. The blue rays show the distance of municipalities from their respective administrative capitals before 1999, with the post-1999 distances marked in red. In the case of the two new voivodeships where two cities received capital status (Lubuskie and Kujawsko-Pomorskie), we measure the distance to the city that became the site of the regional government (sejmik wojewódzki), which is the key institution responsible for regional development.
Figure 1. Administrative arrangements in Poland before and after the 1999 administrative reform: voivodeships, capitals and distance from municipalities to regional administrative centres.
Notes: Blue rays show the distance of municipalities to their respective administrative capitals before 1999; the post-1999 distances to regional administrative centres is marked in red. Distances (in straight lines) between centroids of municipalities.
Source: BDL, own calculations.
Identifying implications of the reform for regional capitals and peripheral municipalities
An important concern related to the introduction of the reform was first, its consequences for the voivodeship capitals which lost this status due to the reduced number of top-tier regions. Secondly, at the level of municipalities, the question was whether the redesign of the administrative network would result in any negative changes of development dynamics in municipalities, which as a result of the reform landed on the periphery with respect to the new voivodeship capitals. In Myck and Najsztub (2019) we consider both of these concerns looking at a number of indicators of socio-economic developments, including population dynamics, local government finances as well as the intensity of nighttime lights measured by satellites, which has recently been treated in the literature as an overall proxy for economic development (Henderson et al., 2012; Pinkovskiy and Sala-i-Martin, 2016). We look at each of these problems using the difference-in-differences approach. In the first instance we compare the developments before and after the reform for voivodeship capitals, which maintained the status and those which did not, and in the latter we look at municipalities for which the distance to their administrative capital increased relative to those for which it remained unchanged or fell.
In the case of voivodeship capitals, due to the obvious differences between the two groups of pre-1999 capitals which in the end determined their post-reform status, our estimates can only be treated as descriptive. In the second case though, since municipalities had little choice with regard to their assignment to the new voivodeships, the results can safely be interpreted as causal. To address the differences between the two groups of municipalities, we apply the entropy balancing method of matching to ensure pre-reform uniformity in the distribution of the analysed municipality characteristics (Hainmueller, 2012; Adda et al., 2014). A summary of the results of both sets of estimations is presented in Table 1 where we show the difference-in-differences coefficients for six socio-demographic outcomes. The estimation period covers the years 1995-2012.
As we can see in Table 1 the only consistently negative and significant coefficient which we find in the two main specifications concerns net migration. Other than that, the results seem to go against the initial concerns with positive coefficients on own revenues, which are statistically significant in the case of the voivodeship capitals, though not in the case of peripheral municipalities. Results for the intensity of nighttime lights are negative in both cases but are not statistically significant. Particularly in the case of peripheral municipalities – where as we argued we can treat the results as causal – we find no evidence of major negative implications of the reform for socio-economic dynamics. This result, as we show in Myck and Najsztub (2019) is confirmed in a number of robustness tests.
Table 1. Diff-in-diff regression estimates for voivodeship capitals and municipalities
| Outcome | Voivodeship capitals: effect of loss of regional capital status | Municipalities: increased distance to administrative capitals | ||||
| Coeff. | t-stat. | Signif. | Coeff. | t-stat. | Signif. | |
| Population | ||||||
| Births, log | -0.139 | (-5.718) | *** | -0.000 | (-0.027) | |
| Deaths, log | 0.020 | (1.339) | 0.002 | (0.160) | ||
| Net migration, pers. | -1.902 | (-2.906) | ** | -12.579 | (-2.372) | * |
| Finances | ||||||
| Own revenues, p.c. log | 0.076 | (1.872) | + | 0.024 | (1.028) | |
| Own non-capital revenues, p.c. log | 0.136 | (2.307) | * | 0.033 | (1.246) | |
| Economic indicators | ||||||
| Total lights, p.c. log | -0.028 | (-1.396) | -0.002 | (-0.049) | ||
| Number of observations: | 882 | 43218 | ||||
Note: + p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001; standard errors clustered at the municipality level. Monetary values in real 2005 PLN terms. Values in log in cases where the dependent variable is log-normally distributed. Per capita estimations (p.c.) weighted by population size. All estimations include capital/municipality and time fixed effects.
Source: Authors’ calculations using data from the Local Data Bank (Bank Danych Lokalnych, BDL; data on population and finances) provided by the Polish Central Statistical Office (GUS) and nighttime lights data provided by the National Oceanic and Atmospheric Administration (NOAA) (Elvidge et al., 2009; National Geophysical Data Center (NGDC), 2010). Data for years 1995-2012.
The socio-economic development in central and peripheral municipalities with respect to the new voivodeship capitals seems therefore to be unaffected by the reform. Importantly also, despite concerns about the marginalization of the cities which lost the voivodeship capital status in 1999, their socio-economic performance has not been much worse compared to those which remained capitals and received greater administrative responsibilities and budgets to manage. From this point of view, the stability of the structure of Poland’s local government and the longevity of the administrative design implemented in 1999 should not be surprising. The claims of the need to change the Polish administrative design and promises of changes resurface at each parliamentary election. These promises have so far been left unmet and inclusivity of socio-economic development at the regional level that followed the reform is likely to be an important factor behind this.
Acknowledgements
The authors gratefully acknowledge the support of the Polish National Science Centre through project no. 2016/21/B/HS4/01574. For the full list of acknowledgments see Myck and Najsztub (2019).
References
- Adda, Jérôme, McConnell, Brendon, Rasul, Imran, 2014. Crime and the depenalization of cannabis possession: evidence from a policing experiment. Journal of Political Economy 122, 1130-1202. doi:10.1086/676932
- Blazyca, G., Heffner, K., & Helińska-Hughes, E. (2002). Poland – Can Regional Policy Meet the Challenge of Regional Problems? European Urban and Regional Studies, 9(3), 263–276. doi:10.1177/096977640200900305
- Elvidge, Christopher D., Ziskin, Daniel, Baugh, Kimberley E., Tuttle, Benjamin T., Ghosh, Tilottama, Pack, Dee W., Erwin, Edward H., Zhizhin, Mikhail, 2009. A fifteen year record of global natural gas flaring derived from satellite data. Energies 2, 595-622. doi:10.3390/en20300595
- Hainmueller, Jens, 2012. Entropy balancing for causal effects: a multivariate reweighting method to produce balanced samples in observational studies. Political Analysis 20, 25-46. doi:10.1093/pan/mpr025
- Henderson, J. Vernon, Storeygard, Adam, Weil, David N., 2012. Measuring economic growth from outer space. American Economic Review 102, 994-1028. doi:10.1257/aer.102.2.994
- Myck, M. and Najsztub, M., 2019. Implications of the Polish 1999 administrative reform for regional socio-economic development. CenEA Working Paper 1/2019.
- National Geophysical Data Center (NGDC), 2010. Version 4 DMSP-OLS night-time lights time series. https://ngdc.noaa.gov/eog/dmsp/downloadV4composites.html. Accessed 15 June 2015.
- Pinkovskiy, Maxim, Sala-i-Martin, Xavier, 2016. Lights, camera … income! Illuminating the national accounts–household surveys debate. The Quarterly Journal of Economics 131, 579-631. doi:10.1093/qje/qjw003
- Regulski, Jerzy, 2003. Local Government Reform in Poland: An Insider’s Story. Local Government and Public Service Reform Initiative, Budapest.
- Swianiewicz, Paweł, 2010. If territorial fragmentation is a problem, is amalgamation a solution? An East European perspective. Local Government Studies 36, 183-203. doi:10.1080/03003930903560547
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.
Ownership Structure, Acquisitions and Managerial Incentives
Both the theoretical and empirical literature assume that takeovers are less likely to occur when firms have large concentrated shareholders, e.g. family firms. Hence the disciplinary role of takeovers becomes irrelevant in incentivizing the management. We argue that this conjecture is false. Using a contracting model, we show that the existence of takeovers can work in favour of firms with controlling shareholders, amplifying the disciplinary effects relative to firms with dispersed shareholders. We further show how takeover threats interact with alternative governance structures, specifically, with monitoring and performance pay. While carrots (performance pay) and sticks (takeover threat) play substitute roles in incentive provision, the internal monitoring available to large shareholders is a substitute mechanism irrespective of the disciplinary effect of the market for corporate control.
Introduction
The nature of optimal corporate ownership has been a longstanding question in corporate governance literature. While large controlling shareholders can address managerial agency problems by monitoring management and alleviating the free-riding problem in takeovers (see e.g., Grossman and Hart, 1980; Demsetz and Lehn, 1985 and Burkart, Gromb and Panunzi, 1997), they may also expropriate other stakeholders by influencing management or deterring efficient takeovers to maintain their private control benefits (Stulz,1988). Empirical evidence about the effect of controlling shareholders, for example a founding family, on firm performance is also inconclusive (see Bertrand and Schoar (2006) who review the empirical studies on family ownership).
Amid the ongoing debate, we provide a new perspective on the role of controlling shareholders in the market disciplinary mechanism, and how it interacts with the firm’s potential synergy characteristics and internal governance mechanisms. While the use of performance pay and internal monitoring are easily justified by the extant literature, the disciplinary effects of the market for corporate control are less obvious. In many countries, there are debates about the social cost of concentrated ownership structures, and some regulators (e.g., the European Commission) have been advocating in favour of breaking up concentrated ownership structures to facilitate the market for corporate control and its managerial disciplinary function.
In contrast to this standard view, our analysis shows that the managerial disciplinary mechanism of synergistic takeover can be strengthened by the presence of controlling shareholders. Furthermore, while the control premium required by controlling shareholders reduces the incidence of synergistic takeovers, the internal monitoring performed by these shareholders can complement the market disciplinary mechanism in high synergy potential firms. Overall, it is ambiguous whether dismantling a concentrated ownership structure would increase firm value and, in particular, in firms which provide high synergy potential to acquirers.
Our analysis suggests that more sophisticated policies for the market for corporate control may improve the social welfare more effectively.
Controlling Ownership and Managerial Agency Problem
The managerial agency problem is relevant even when considering takeovers of family firms. Founders hold 15% of the CEO positions, 30% are held by descendants while the absolute majority of approximately 55% are held by professional managers (Villalonga and Amit, 2006). Bidders that operate in the same industry, for example, will be able to observe the state of demand to assess the synergistic improvements. In contrast, family owners are likely to be less actively involved in firm operations, and less informed about the industry/market situation, which suggests their lack of operational expertise vis-a-vis managers.
In the presence of potential conflicts of interest between the management and shareholders, the market for corporate control serves a disciplining role. Then why does the private benefit of controlling shareholders, which increases the takeover premium, strengthen this market disciplinary mechanism?
We argue that, notwithstanding their negative effect on the incidence of synergistic takeovers, the controlling shareholders can strengthen the managerial disciplinary effect of a takeover in firms that offer acquirers large business synergies.
To answer the question intuitively, suppose that the manager has no anti-takeover defense. In this case, the manager can secure herself from takeover threats only by increasing the market value of the firm, and, therefore, the takeover threat can discipline the manager. In firms which offer high synergy potential to the acquirers, however, the manager may find it too costly to increase the market value enough to deter a synergistic takeover. The control premium required by controlling shareholders can complement the market disciplinary mechanism in this circumstance, and, specifically, reduce the profitability of synergistic takeovers and make the acquirers’ bidding choice more sensitive to current market value. That is, it allows the managers of firms that offer high business synergies to reduce the takeover threat significantly by increasing the market value.
Technically, our model shows that the necessary and sufficient condition for the complementarity of ownership concentration and the market disciplinary mechanism is the log-convexity of the distribution function of potential business synergy. The market value increase from truthfully reporting the favorable state may, in itself, not significantly deter the takeover attempts for these firms since acquirers still find the business synergy more than offsets a high stock price. The control premium required by controlling shareholders makes truthful managerial reporting (and the corresponding market value enhancement) more effective in reducing the likelihood of a takeover. Specifically, the control premium increases the manager’s opportunity cost of misreporting and, in turn, it reduces the information rent that shareholders forgo to the manager.
Interaction with Other Governance Mechanisms
The analysis also provides implications for the relationship between ownership structure and other governance mechanisms, such as managerial compensation and the monitoring function of controlling shareholders.
Given that the managerial agency problem cannot be fully eliminated by the takeover threat and managerial compensation, the monitoring function of controlling shareholders can complement the other two governance mechanisms in our setting.
We show that the disciplinary effect of synergistic takeovers reduces the information rent paid to the manager and, thus, it diminishes managerial incentive pay. This implies that managerial pay-performance sensitivity is negatively associated with ownership concentration in firms which offer high business synergies. Furthermore, our analysis also shows that, in high synergy potential firms in which controlling shareholders strengthen the market disciplinary mechanism, monitoring function of controlling shareholders can complement the market disciplinary mechanism, and, thus, ownership concentration increases the operating efficiency relative to firms with dispersed ownership.
Conclusion
Contrary to the common prior, the disciplinary effect of synergistic takeovers can be stronger in high synergy potential firms with controlling shareholders due to improvements in incentives for managerial self-selection. Specifically, the control premium encourages the manager to deter the takeover threat by increasing the current value of the firm. In this case, managerial entrenchment is consistent with improvements in shareholder value.
The disciplinary effect acts as a complement to the internal monitoring efforts of controlling shareholders in reducing the amount of incentive pay required to induce managerial truthfulness. In contrast, the control premium in firms with few synergies isolates the manager from the takeover threat, making incentive provision reliant on internal monitoring.
However, the disciplining effect of synergistic takeovers is not without its costs, making the overall value implications ambiguous. Incentive provision requires that shareholders accept relatively low bidding prices, by allowing takeovers with negative synergies. Furthermore, tailoring correct incentive pay requires a relatively high distortion to effort levels in times of economic downturns. While controlling ownership is able to mitigate these concerns, the existence of a control premium also reduces the incidence of socially desirable synergistic improvements in firm value.
Overall, policy makers should take care when considering implementation of constraints on the controlling states in order to facilitate the market for corporate control.
References
- Anderson, Ronald C., and David M. Reeb, 2003. “Founding-family ownership and firm performance: Evidence from the S&P 500”, The Journal of Finance, 58, 1301-1327.
- Bertrand, Marianne, and Antoinette Schoar, 2006. “The role of family in family firms”, Journal of Economic Perspectives, 20, 73-96.
- Burkart, Mike, Denis Gromb, and Fausto Panunzi, 1997. “Large shareholders, monitoring and the value of the firm”, The Quarterly Journal of Economics,112, 693.
- Demsetz, Harold, and Kenneth Lehn, 1985. “The structure of corporate ownership: Causes and consequences”, Journal of Political Economy, 93, 1155-1177.
- Grossman, Sanford J., and Oliver D. Hart, 1980. “Takeover bids, the free-rider problem, and the theory of the corporation”, The Bell Journal of Economics,11, 42-64.
- Villalonga, Belen, and Raphael Amit, 2006. “How do family ownership, control and management affect firm value?”, Journal of Financial Economics, 80, 385-417.
- Stulz, Renee, 1988. “Managerial control of voting rights: Financing policies and the market for corporate control”, Journal of Financial Economics, 20, 25-54.
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.
Decentralization, E-Procurement and Efficiency of Public Procurement in Ukraine
This brief is based on a research that investigates if there’s a synergy effect of procurement and decentralization reforms in Ukraine on procurement efficiency. The analysis shows the similarity between new and old administrative units procurement performance. Although the analysis does not provide evidence of a significant synergy effect, such a similarity could be considered as something positive (due to the lower market power and capacity of the newly created administrative units) that should be analyzed further.
Decentralization in Ukraine
In April 2014, the Ukrainian government launched a systemic decentralization reform – a delegation of a significant part of resources and responsibilities from oblast and raion-level executive branches of the government to the local self-government level. The key issue of the reform was the creation of a strong basic level of local self-government in line with the European Charter of Local Self-Government. This is done through the creation of amalgamated hromadas (AH), the merger of several settlements with a single administrative centre.
An AH is governed by a council of the amalgamated hromada (CAH), a representative body of a local self-government. It is elected by residents of territorial communities and is responsible to independently resolve local issues, develop and approve AH budgets. Particularly, the government redistributed tax revenues and expanded the system of state subsidies (medical and educational subvention, subvention on development of amalgamated hromadas etc.) that could be used according to AH decisions.
In 2015, 159 AH were established. As of September 2018, 831 AH made up by 3,796 hromadas with 7 million residents (decentralization.gov.ua).
Public E-Procurement
Contemporaneously, a reform of public procurement has been implemented. According to the Law on Public Procurement of Ukraine, since August 2016, public procurement must be announced and executed through ProZorro, a public procurement web portal administered by the state enterprise. The e-procurement system consists of a central database, an auction module and commercial marketplaces (Figure 1).
In order to participate in public tenders, bidders can choose one of 22 commercial marketplaces (7 companies that provided initial investment for the project became the first marketplaces). The commercial marketplaces are web resources managed by private companies that provide access to the electronic procurement system.
Figure 1. ProZorro Architecture
The electronic procurement system does not completely cover the procurement cycle. Actually, it only covers the tendering process while planning and contract execution are mostly out of the system (plans are published online). Moreover, the existing legislation provides opportunities to manipulate tendering process by switching between different procedures. Within the ProZorro system there are 6 main procurement procedures that can be used by procuring entities depending on the volume and specifications of their needs.
Selection of procedures is based on a Threshold principle. There are three thresholds (Figure 2):
- Lower Threshold (LT). Contracting authorities are not obliged to report procurements in the electronic system if the total value of procurement is lower than UAH 50,000.
- Higher Threshold (HT). Contracting authorities are not obliged to use open competitive procedures if the total value of tender is lower than a defined level. This level is equal to UAH 200,000 for goods and services and UAH 1.5 million for construction.
- Euro Threshold (ET). The value of tender that requires applying the strictest competitive auction procedure. The euro threshold corresponds to thresholds used in EU public procurement legislation and is different for goods and services and construction works.
Transparency and efficiency indicators
Typically, a procurement process is divided into three stages: pre-tender stage, tender stage and post-tender stage. To measure efficiency and transparency of AH procurement, we constructed a system of eleven indicators that evaluate each stage of the procurement process (Table 1).
Table 1. Transparency and efficiency indicators used in the report
- Avoiding ProZorro. Both this and the following indicator would be associated with a decreased transparency, and, while not necessarily evidential, raise suspicions about procurement done in a less efficient and more collusive/corrupt way. AH are not inclined to avoid the ProZorro system. The share of procurements outside of ProZorro per AH is smaller than the corresponding indicators for other administrative units (Raion State Administrations, RSA, and unamalgamated hromadas, UH).
- Avoiding higher and euro thresholds. An analysis of ProZorro data shows that for AH, 84% and 11% of AH have at least one “suspicious” case for each corresponding threshold. For, RSA the indicators are 73% and 31% respectively.
- Unanswered questions. Having a productive dialogue with suppliers is of crucial importance for the success of the procurement. It helps to adjust the tender documentation so that it does not include discriminatory demands. Analysis shows that this practice is not dominant: relatively small proportion of AH and UH uses it.
- Level of competition. Higher competition is normally assumed to imply more efficient procurement deals. There is no difference in competition across administrative units and products (measured by the number of bidders per tender).
- High disqualification rates can be a consequence of ill prepared tender documentation with unclear technical specification or it can be a consequence of suppliers’ inexperience. It can also be a sign of corruption, when a tender committee is trying to find any reason to disqualify ‘unwanted’ suppliers. The analysis shows that disqualification is not a significant problem and, in fact, there are no significant differences across administrative units and products.
- Success rates. To successfully complete competitive procurement, the contracting authority has to determine the technical description of a good and its expected value based on their budget and market analysis. It also has to prepare and publish tender documentation and answer questions of potential suppliers. Finally, after the auction, the contracting authority has to evaluate documents of the auction winner and sign a contract. Failure in each of these steps will lead to unsuccessful or cancelled procurement. There is no significant difference across administrative unit groups in terms of procurement success rate
- Abnormal saving rate. Generally, a high saving rate (the difference between tender expected and contracted values) is regarded as a positive indicator, however, a too high rate is suspicious. It can be a sign of an inadequate expected value or an abnormally low price (suspicious behavior on behalf of the supplier). For the purpose of this study, we consider a saving rate abnormal if it is greater or equal to 30%. The analysis shows that AH had a significantly lower share of tenders with abnormally high saving rate than RSA. On average, 0.6% (in terms of value) of AH tenders are suspicious, for RSA this indicator equals 6.1%
- Contract termination. Frequent contract termination is a sign of significant inefficiencies in the procurement function of contracting authorities. The share of terminated contracts (as a percentage of the total contract value) is approximately similar for AH and RSA. On average, one AH has 5% of contract value terminated, while RSA indicator equals to 6%.
- Fixing the price with additional agreements. Although the Ukrainian Law on Public Procurement gives the right to amend the price per unit indicated, this right can be misused. It could lead to significantly higher costs. RSA are strikingly different from the other two groups – on average 20% of the RSA contract value stems from contracts with amended prices. This difference is the consequence of the different structure of goods and services procured by AH and UH on the one hand and RSA on the other.
- Share of largest supplier. Generally, it is considered to be a good practice, when contracting authorities are not overly dependent on one supplier. Approximately 30% of contract value of average AH and RSA belongs to one supplier. For UH this indicator is even higher (on average 48%) but it could be the consequence of the smaller number of contracts signed by UH.
Effect on prices
If contracts are successfully executed, the price of a good usually summarizes the efficiency of the procurement process.
There are many factors that affect the prices of goods in public procurements. On the one hand, AH (a) “realized” that they spent their own money and thus, they have more incentives to save and (b) have more power to choose where to spend. On the other hand, there are some factors that have the opposite effect: (a) because of low quantity demanded, the tenders announced are not interesting for large companies that could potentially provide lower price, and (b) the procurement officers could have insufficient capacity to negotiate lower price. Although, it is impossible to evaluate all these factors, we can assess their outcome – the contract price of a good.
For this analysis we looked at the prices on homogeneous goods such as food (potato, butter, eggs) and fuel (petrol A95, petrol A-92, diesel.
Table 2 summarizes the prices on the goods received by hromadas and compares it to the prices received by other types of entities (UHs and RSAs).
The data shows that for food products, AH average prices are lower or not different from UH, and slightly higher or not different from prices received by RSAs.
Even though there are some differences in prices of Petrol A-95 (partially due to inefficient planning and contracting at periods of higher prices), in general, the price level is very similar between all the entities.
In most cases, despite some warnings, there were no significant gaps between AH’s prices and UH or RSA. Moreover, the more competitive is the market of goods procured, the closer are prices received by different administrative units.
Table 2. Prices of goods by administrative units in 2017
Conclusion
The analysis shows the similarity between AH and RSA in terms of number of procurements, success and disqualification rates as well as competition level and share of terminated contracts. However, in cases when it is allowed by the Procurement Law, AH are more likely than RSA to choose direct selection of a supplier than a competitive procedure. Such behavior can be caused by a lack of professionalism (or even corruption), a desire to select a local trustworthy company or just because it is easier and faster to conduct uncompetitive procedure below the threshold.
On the other hand, AH are less inclined (in comparison to RSA) to avoid the ProZorro system (by using procurements below UAH 50 K) and to sign additional agreements that increase the price. Such behavior is potentially punishable by law. It can be suggested that procurement officers of AH only recently started to work with tenders above HT and are therefore more conscious of possible negative consequences of such actions.
The price per unit is the key indicator that summarizes information on procurement efficiency. Although AH show varying price efficiency, their prices of procured goods, in general, are not worse than in other administrative units’ groups. The more competitive the market, the closer are prices (especially in the case of fuels). Even if some gaps were observed, these differences are decreasing over time. Better planning can help to receive lower prices (better estimation of needs and choosing appropriate periods for procurement).
Currently, the analysis does not provide an evidence on a significant synergy effect of decentralization and procurement reforms. There are no significant differences between old and new administrative units. However, usually new communities have lower market power and capacity, and “no difference” could be considered as a positive sign that should be analyzed further.
References
- Shapoval, Natalia; Iavorskyi, Pavlo; Stepaniuk, Oleksa; Kovalchuk, Arthur. 2018. “An evaluation of decentralization impact on transparency and efficiency of public expenditures”. SKL International AB.
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.
Poverty Dynamics in Belarus from 2009 to 2016
This brief is based on research that studies the incidence and determinants of poverty in Belarus using data from the yearly Household Budget Surveys for 2009-2016. Poverty is evaluated from a consumption perspective applying the cost of basic needs approach. According to the results, in 2015-2016, absolute poverty in Belarus increased twofold and reached 29% of the population. Large household size, high number of children, single mothers and unemployment negatively affect household welfare and increase poverty risk. Moreover, living in rural areas increases the likelihood of being poor and correlates negatively with welfare.
Introduction
Sizeable and increasing poverty poses a threat to social stability and long-term sustainability for every country. Before 2009, Belarus registered over a decade of high and sustainable economic growth that enhanced the average standard of living and raised a substantial number of Belarusians out of poverty. According to the National Statistical Committee of the Republic of Belarus (Belstat), the poverty rate in Belarus (by official definition) has decreased from 41.9% of the population in 2000 down to 6.1% in 2008. The largest reported decline in poverty was in 2001 – from 41.9% to 28.9%.
Since then, Belarus experienced several episodes of economic crises – in 2009, 2011 and 2015-2016 (Kruk and Bornukova, 2014; Mazol, 2017a). Such economic downturns typically introduce considerable survival problems for many households. For example, according to the World Bank, in some countries the poverty rate may reach 50% (World Bank, 2000). In light of this, the small increase (0.3%) in the official poverty measure during these periods casts doubt on the official methodology used for poverty calculations. This brief describes an alternative measure of absolute poverty based on the widely recognized cost of basic needs approach; and summarizes the results of the study of how economic downturns in Belarus influenced welfare and poverty at the household level.
Data and methodology
The data used in this research are pooled cross-sections from 2009 to 2016 of the yearly Belarusian Household Budget Surveys with on average 5000 households in each sample obtained from Belstat. These surveys consist of household and individual questionnaires that contain important data about households including decomposition of expenditures and income by categories, detailed data on consumption of food items, the size, age and gender composition of households, living conditions, etc.
The analysis applies the cost of basic needs approach (Kakwani, 2003). It first estimates the cost of acquiring enough food for adequate nutrition (nutrition requirements for households of different size and demographic composition) per person (food poverty line) and then adds the cost of non-food essentials (absolute poverty line). The calculated poverty lines for each sampled household are compared with the household consumption per person. All measures are preliminary deflated to take into account differences in purchasing power over time and regions of residence.
In contrast, the official poverty measurement compares per capita disposable income of a household with national (official) poverty line, which is the average per capita subsistence minimum budget of a family with two adults and two children (see Table 1).
Table 1. Consumer budgets and absolute poverty line by year in Belarus, in constant BYN
| Year | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 |
| Subsistence minimum budget1 | 247 | 258 | 293 | 317 | 332 | 362 | 369 | 373 |
| Minimum consumer budget2 | 372 | 396 | 367 | 448 | 491 | 517 | 554 | 620 |
| Absolute poverty line3 | 383 | 395 | 437 | 448 | 468 | 475 | 499 | 520 |
Source: 1 Belstat; 2 Ministry of Labour and Social Protection Republic of Belarus; 3 author’s own calculations.
The empirical strategy of the analysis assumes setting the food, non-food and absolute poverty lines using the cost of basic needs approach, estimating poverty measures at the level of entire Belarus and its regions based on Foster-Greer-Thorbecke’s poverty indices (Foster et al., 1984), and analyzing the determinants of welfare and poverty using OLS and probit regressions.
Poverty incidence
The timeline of poverty analysis for Belarus can be subdivided into three periods: crisis of 2009-2011, recovery of 2012-2014, and a crisis of 2015-2016 (see Figure 1).
The results show that during the first period (from 2009 to 2011), absolute poverty at the national level increased from 30.9% to 32.6%. Incidence of absolute poverty for rural and urban areas in 2011 reached 45% and 28% of the population, correspondingly.
Figure 1. Incidence of absolute poverty and GDP per capita growth in Belarus
Source: Author’s own calculations.
Note: Estimates reflect weighted household data.
The second period (from 2012 to 2014) was characterized by a sharp poverty reduction. For example, the absolute national poverty headcount ratio has plummeted from 32.6% in 2011 to 14.9% in 2014, rural poverty dropped by 22.1 percentage points or almost by half and urban poverty decreased by 16.2 percentage points.
In turn, the third period saw a sharp rise in the incidence of poverty. From 2015 to 2016, the headcount ratio for absolute poverty increased by 14.4 percentage points. As a result, in 2016 absolute poverty in Belarus reached 29.3% or almost the same as in 2009 and 2011 (Mazol, 2017b).
Causes and determinants of poverty
The significant increase in poverty in 2015-2016 was due to a combination of several factors, including the household income decline in comparison with its growth in previous years, the increasing need to spend more on food necessities and the growth in food and especially non-food price levels.
As the Figure 2 shows, starting from 2015 there has been a rapid increase in the real cost of non-food budget for Belarusian households, while the food budget has remained almost the same in real terms. Correspondingly, in 2016 the non-food poverty line increased by 14.6%, while the food poverty line went up only by 2.9%.
Figure 2. Real monthly average per capita household expenditure on food and non-food items and real monthly standardized food and non-food poverty lines, 2009-2016, in BYN
Source: Author’s own calculations.
Note: Estimates reflect weighted household data.
Furthermore, as income fell (by 7.2% in 2015-2016), the share of food items in total expenditure increased and real non-food expenditure decreased. This is because household income was not enough to cover both expenditures on food and non-food items. Due to the 2015-2016 economic crisis the cost of meeting the food essentials increased so fast that it has squeezed the non-food budget, leaving insufficient purchasing power for non-food items.
The study also shows that among factors that substantially influence household welfare and poverty at the household level in Belarus are family size, the number of children in a household, presence in the household of economically inactive members. Moreover, single mothers in Belarus appear to be noticeably more vulnerable to macroeconomic shocks than full families both from welfare and poverty perspectives.
Additionally, one of the most important determinants of welfare and poverty in Belarus is spatial location of a household. In particular, poverty highly discriminates against living in rural areas. The poverty incidence for rural areas over 2009-2016 is approximately 10.5 percentage points (or 44%) higher than the national average, while that of the urban areas is nearly 4 percentage points (or 16%) below national average. Moreover, in 2015-2016 urban and rural disparity for poverty widened even more and reached 25.3% for urban vs 40.6% for rural areas.
Finally, two more factors, savings and access to a plot of land, have on average a large positive influence on consumption expenditure and aa negative one on the chance of getting poor.
Conclusion
Poverty alleviation and development reflect economic and social progress in any country. While Belarus initially achieved noticeable progress in this dimension, the economic and social development in recent years seems to increase problem of poverty in Belarus. The estimates show that in 2015-2016, absolute poverty in Belarus increased almost twofold. Household size, large numbers of children in a household, the presence in the household of economically inactive members are all factors that decrease household welfare and increase poverty. Single mothers also appear to be substantially more vulnerable to macroeconomic shocks. Finally, one of the most important determinants of welfare and poverty in Belarus is if a household is rural. These findings are important warning signals for the design of pro-poor policies in Belarus.
References
- Foster, J., J. Greer, and E. Thorbecke. (1984). A Class of Decomposable Poverty Measures. Econometrica, 52: 761-766.
- Kakwani, N. (2003). Issues in Setting Absolute Poverty Lines, Poverty and Social Development Papers No. 3, June 2003. Asian Development Bank.
- Kruk, D., Bornukova, K. (2014). Belarusian Economic Growth Decomposition, BEROC Working Paper Series, WP no. 24.
- Mazol, A. 2017a. The Influence of Financial Stress on Economic Activity and Monetary Policy in Belarus, BEROC Working Paper Series, WP no. 40.
- Mazol, A. 2017b. Determinants of Poverty With and Without Economic Growth. Explaining Belarus’s Poverty Dynamics during 2009-2016, BEROC Working Paper Series, WP no. 47.
- World Bank (2000). Making Transition Work for Everyone: Poverty and Inequality in Europe and Central Asia. Washington DC, The World Bank.
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.
Economic Growth and Putin’s Approval Ratings —The Return of the Fridge
This brief discusses how the approval ratings of president Putin covaries with economic growth. In most years the relationship between approval ratings for Putin and growth looks like approval ratings for politicians in most countries so that when growth is higher, the president is more popular. Or to use an American expression “it’s the economy stupid”. The caveat in Russia is that external events at times overshadow the importance of growth to the extent that the president’s ratings stay high and can even go up despite a faltering economy. In a time of low Russian growth, this is not good news for geopolitics unless Putin can be convinced to focus on policies that generate high, sustainable growth instead of international turbulence. That said, it is clear that poor economic growth carries a political cost also in Russia. The only sustainable way of maintaining high approval ratings for the president is by fostering economic growth since in the contest between “the TV and the fridge”, the fridge will eventually win.
Russia is a complex country and culture. Instead of the simple American saying “it’s the economy stupid”, Russians talk about “the TV vs the fridge”. This translates into that concerns about the economic situation can be made irrelevant by propaganda so that voters turn their eyes away from the half-empty fridge to follow how Russia’s armed forces fight the enemy in foreign countries.
The propaganda messages have of course varied over the years, but it seems that external enemies that threaten the nation are at the heart of many of the messages. This theme in propaganda is of course not unique to Russia, but it seems to carry more weight in Russia than in other countries.
The observation that propaganda is used and that it seems to work to a relatively large extent at times can lead to the conclusion that “it’s not the economy stupid” when it comes to approval ratings of the Russian leadership.
This observation is tempting as another piece of evidence on how Russia is different and unique, but this brief will show that in most times, it is indeed “the economy stupid” also in Russia.
Putin’s ratings and growth
The idea that Russia is different in that growth would not be important for the president’s approval rating can be justified empirically when we look at the full series of approval ratings of Putin as measured by the Levada center and corresponding quarterly growth rates going back to 1999 (Figure 1).
Instead of showing a strong positive correlation as we would expect, the correlation is negative 0.3. However, a more careful look at the observations in the scatter plot suggests that there are a few clusters of observations that create this negative correlation. In the figure, three distinct clusters are marked; first there is the period when Russia rebounded strongly from the 1998 crisis in 1999-2000, with growth rates that have not been seen before or after that time in Russia. The growth was an artefact of the previous massive decline in income in combination with a large devaluation, and later followed by oil price increases. This happened in Putin’s initial time in the highest offices when he was prime minister, interim president and then elected president. Although Putin enjoyed high ratings as a consequence, it was not in line with the extreme growth rates that were the result of events preceding his tenure and can thus be regarded as outliers.
The second cluster is related to the global financial crisis in 2008/09 when Russian growth took a major hit as oil prices collapsed and the exchange rate was not allowed to appreciate correspondingly. However, this crisis was blamed (as in many other countries) on the US and the West and did not cost Putin in terms of approval ratings.
The final cluster is related to the annexation of Crimea and ongoing involvement in the conflict in Eastern Ukraine. This period also coincides with a sharp drop in oil prices that taken together led to negative growth that then remained low for a prolonged period. We should note that before the annexation of Crimea, growth rates in 2013 were very low at 1-2 percent with approval ratings going down to 63 percent, which was an all-time low since Putin’s first year in office.
Figure 1. Ratings and growth
Source: Becker (2019)
If we purge the data from the three exceptional episodes that we have identified above, we get Figure 2. Note that the scale has not been changed from Figure 1. Now there are no observations of negative growth rates, but the distribution of growth rates is still rather spread out, going from around 1 to 9 percent growth. The spread of the growth distribution is important since it allows us to identify the relationship between growth and approval ratings more clearly.
The relationship between approval ratings and growth in Figure 2 is strongly positive with a correlation coefficient of 0.7, and in line with what we would expect in other countries. This is a quite remarkable shift from the negative correlation in Figure 1. Note that if approval ratings in 2014 had been behaving as in “normal” years, the regression line would have put them around 60 percent instead of the actual approval rating that peaked at 86 percent after the annexation of Crimea. Such is the strength of the TV.
Figure 2. Ratings and growth
Source: Becker (2019)
This is very clear evidence that Russia is a “normal” country in “normal” times, but that there are also times when other forces overshadow this normalcy.
Policy conclusions
Are there any policy conclusions that can be drawn from the stark contrast between figures 1 and 2? The answer is a very clear “yes”, both for the Russian leadership but also for the rest of the world that has economic interests and security concerns with Russia.
For the Russian president, the message is that it pays in terms of high approval ratings to generate growth and “keeping the fridge well stocked”. It is also clear that the high popularity rating that was seen after the annexation of Crimea has been followed by several years of poor growth. A forthcoming brief discusses how the increased uncertainty created by this event has led to lower capital inflows, lower domestic investments and lower growth.
Not surprisingly, the sustained low growth has started to show in terms of falling approval ratings. The polls at the end of 2018 and early 2019 (for when there is not yet data on growth rates) indicate a significant decline in approval ratings, down to 64 percent from over 80 percent at the end of 2017. This is linked to protests over pension reforms, but they in turn are a result of lower government revenues in an economy that lacks growth.
In other words, if growth does not return before the propaganda loses its appeal, this will eventually result in falling approval ratings for the president, which is what we are seeing now.
There are potentially also some policy conclusions for Russia’s foreign investors, trading partners and neighbors. When growth in Russia is low and no credible reform programs are on the horizon, expect external actions that take the attention away from poor economic performance while increasing the level of uncertainty both in Russia and abroad.
For the more pro-active external actors, finding ways to support Russia’s return to growth through dialogue on real economic reforms could perhaps be both politically feasible and of mutual interest to Russia and the West. There are clearly some geopolitical issues that may interfere with this process, but it should still remain high on the wish list of regular people in Russia and elsewhere. Let the fridge rule!
References
- Becker, T., 2019. “Russia’s macroeconomy—a closer look at growth, investment, and uncertainty”, forthcoming SITE Working Paper.
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.
Agricultural Exports and the DCFTA: A Perspective from Georgia
On June 27, 2014, Georgia and the EU signed an Association Agreement (AA) and its integral part – the Deep and Comprehensive Free Trade Area (DCFTA). In this policy brief, we discuss the changes and analyze the agricultural exports statistics of Georgia since 2014. Furthermore, we will provide the recommendations to capitalize on the opportunities that the DCFTA offers to Georgia.
Georgia is a traditional agrarian country, where agriculture constitutes an important part of the economy. 36.6% of the country’s territory are agricultural lands and 48.2% of the Georgian population live in villages. Although 55% of population are employed in agriculture, Georgia’s agriculture accounts for only 15.8% of its GDP (Geostat, 2019). Agricultural exports constitute an important part of Georgia’s economy, accounting for about 25-30% of total exports.
On June 27, 2014, Georgia and the EU signed an Association Agreement (AA) and its integral part, the Deep and Comprehensive Free Trade Area (DCFTA). On July 1st, 2016, the DCFTA fully entered into force. The DCFTA aims to create a stable and growth-oriented policy framework that will enhance competitiveness and facilitate new opportunities for trade. The DCFTA widens the list of products covered by the Generalized System of Preferences+ (GSP+) and sets zero tariffs on all food categories (only garlic is under quota), including potentially interesting products for Georgian exports – wine, cheese, berries, hazelnuts, etc. (Economic Policy Research Center, 2014).
As July 2018 marked only two years since the implementation of the DCFTA between Georgia and EU, valuable conclusions on its impact cannot be formulated yet. In this policy brief, we will give an overview of Georgia’s agricultural trade statistics, particularly, we will focus on agricultural exports and provide recommendations for capitalizing on opportunities offered by the DCFTA.
Georgia’s agricultural trade
Despite its potential and natural resources, Georgia is a net importer of agricultural products. In 2018, Georgia’s agricultural exports increased by 23.2% (181 million USD), while the respective imports grew by only 15.5% (179 million USD) compared to 2017. Therefore, the trade balance (the difference between exports and imports) remained almost unchanged at (-394) million USD (Figure 1).
Figure 1: Georgia’s Agricultural Trade (2014-2018)
Source: Geostat, 2019
Out of the sharp increase in agricultural exports, 100 million USD are attributed to tobacco and cigars. Since Georgia cultivates very little tobacco, the growth was instigated mostly from the import, slight processing and re-export of tobacco products. Consequently, the export of tobacco and cigars increased by 240% in 2018, and it currently holds second place (after wine) in Georgia’s total food and agricultural exports. It should be mentioned that wine exports contributed to 26 million USD in export growth.
Over the last five-year period, the top export countries for Georgia were mainly neighboring counties (Azerbaijan, Russia, Armenia, Turkey); for imports, we see the same neighboring countries as well as China and Ukraine. Observing the trade statistics over the years, 45% of Georgia’s agricultural exports were destined for markets in countries of the former Soviet Union, so-called Commonwealth of Independent States (CIS), while the EU’s share in Georgia’s total agricultural exports was 24%.
Trade relationships between Georgia and the EU
The EU is one of Georgia’s largest trade partners. The EU’s share of total Georgian imports was 28% in 2018, and for exports, 24%. Total exports have been more or less stable since 2014, except for 2016, when an 11% decrease was observed (Figure 2). Specifically, for agriculture, in 2017, the EU’s share of Georgian imports was 22%, and its share of exports was 19%. During the same period, the top export products were hazelnuts (shelled), spirits obtained by distilling grape wine or grape marc, wine, mineral and aerated waters and jams, jellies, marmalades, purées or pastes of fruit.
Figure 2: Total and Agricultural Exports to the EU (2014-2018)
Source: Geostat, MoF, 2019
In 2015 (before the full enforcement of the DCFTA), Georgia’s agricultural exports to EU countries (including the United Kingdom) increased by 20% compared to the previous year. This positive trend remained in 2016, when the same indicator increased by 5%. In 2017, which was quite a bad year in terms of harvest in Georgia, we observed a 38% decrease in the country’s agricultural export to the EU (Figure 2). This decrease was mainly caused by a significant decrease (64%) in hazelnut exports during the same period. The reason for such a large decrease is that hazelnut production suffered from various fungal diseases due to unfavorable weather conditions in 2017. The Asian Stink Bug invasion worsened the situation, and in the end, hazelnut exports dropped dramatically in both value and quantity. In 2018, Georgia’s agricultural export in EU slightly increased by 6% compared to 2017.
Trade relationships between Georgia and CIS countries
It is interesting to observe agricultural trade within the same time period with CIS countries. In 2018, the CIS’ share of Georgian imports was 51%, and its share of exports was 60%. The top export products to CIS countries were wine, mineral and aerated waters, spirits obtained by distilling grape wine or grape marc, hazelnuts (shelled), and waters, including mineral and aerated, with added sugar, sweetener or flavor, for direct consumption as a beverage. As we can see in both EU and CIS countries, the top export products are more or less the same. However, the main export destination market for Georgian hazelnuts are EU countries, but wine is mostly exported to the CIS countries.
Figure 3: Agricultural Exports to CIS Countries (2014-2018)
Source: Geostat, MoF, 2019
Due to the worsened economic situation in CIS countries, Georgia’s agricultural exports to these countries decreased by 37% in 2015. Such a sharp decrease was mainly driven by a significant decrease in the export of alcoholic and non-alcoholic beverages, hazelnut, and live cattle. However, since 2015, Georgia’s agricultural exports to CIS countries have been increasing; we observed a slight 2% increase in the value of agricultural exports in 2016, while the same indicator was 37% in 2017 (Figure 3). That was mainly caused by the increased exports of alcoholic and non-alcoholic beverages (wine by 61%, spirits by 28%, mineral and aerated waters by 22%). In 2018, Georgia’s agricultural export in CIS countries increased by 12% compared to 2017.
Conclusion
Despite its potential and comparative advantage in agriculture, Georgia is still a net importer of agricultural products and has negative trade balance (-394 mn USD). Two years after the DCFTA came into force, it is challenging to know its impact on Georgia’s agricultural trade due to the insufficient passage of time since. Notwithstanding, we can formulate some conclusions from trade statistics. The diversity of the destinations for Georgia’s agricultural exports has not changed through the years. Georgia’s agricultural exports has increased to the EU, but at a quicker pace to CIS too. Furthermore, Georgia’s share of agricultural exports to CIS countries is still significant (60%).
While it is obvious that Georgia needs to diversify its agricultural export destination markets, there are several challenges facing small and medium size farmers and agricultural cooperatives in Georgia that are not specific to implementation of the DCFTA. As the previous regime (GSP+) with the EU already covered most products, the DCFTA did not represent a significant breakthrough. On the path to European integration, the biggest challenge for Georgia is to comply to non-tariff requirements such as food safety standards and SPS measures. The attention should be paid on providing consultations to farmers regarding certification processes and standards and better information sharing (e.g. developing online platforms).
In Georgia, agri-food value chains are not well-developed and lack coordination among different actors. In order to capitalize on opportunities offered by the DCFTA, government and private sector should work together to improve logistics infrastructure. There is a need for upgrading at every stage of export logistics: warehousing, processing, labeling, regional consolidation, final customer services. In this regard, there are high approximation costs for business that should be considered as long-term investment to modernize agriculture and improve food the safety system in the country. This would boost the export potential not only to the EU, but to other countries with similar requirements as well.
References
- ISET Policy Institute, 2016. “DCFTA Risks and Opportunities for Georgia”
- Economic Policy Research Center, 2014. “Agreement on the Deep and Comprehensive Free Trade Area and Georgia”. Available only in Georgian
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.
Intergenerational Mobility in Africa
Recent economic research suggests that childhood environments in part determine success in life. So far, most of this evidence comes from rich countries. In a new paper, we use education data to measure intergenerational mobility across 26 African countries and find large differences across space. Results using data on migrants suggest that regions have causal effects on social mobility of Africans.
Why do people “make it” in life? Few of us can claim, as Robert Strauss, former U.S. ambassador to the Soviet Union and Russia, once quipped, that we were born in a log cabin we built ourselves. One chunk of individual success in climbing the social ladder is determined by our parents – be it through their genes (Sacerdote 2002, 2004), their parenting style (Doepke and Zilibotti 2017), or their income and connections. Another chunk is individual effort. Companies like Apple or Google were started in garages. That leaves our surroundings. Can the places we grow up in raise us up or pull us down? A growing body of research suggests that they can.
Growing evidence that “places matter” for individual mobility
At the forefront of these efforts, Chetty and Hendren (2018a, 2018b) have compared the incomes of American children to those of their parents. They link parents to kids through social security numbers in tax returns. Among families that moved, they find that children exposed to places with higher average social mobility for longer during childhood do better than children exposed to places with lower average mobility. Importantly, this holds when comparing the kids of parents with the same income and other observable characteristics, i.e. holding the “starting line” constant for everyone. Their findings have been reproduced for the U.S. (Chetty, Hendren, and Katz 2016), (Chyn 2018), Canada (Laliberte 2018), Australia (Deutscher 2018), and Denmark (Eriksen 2018). By contrast, studies identifying the causal effects of places on individual mobility in developing countries are still rare (a recent contribution by Asher, Novosad, and Rafkin (2018) on India is a notable exception).
New evidence from Africa
In a new paper (Alesina et al. 2018) we fill part of this gap by examining intergenerational mobility in Africa. After decades of stagnation, there is optimism about Africa’s future. Growth has returned (Young 2012), and some now see Africa as a continent of “1.2 billion opportunities” (Economist 2016). At the same time, anecdotal evidence suggests large inequalities, indicating that the recent aggregate gains may not be broadly shared, and that social mobility remains limited.
Measuring intergenerational mobility using education data
Measuring intergenerational mobility in Africa is difficult because of patchy data. Economists typically think of mobility in terms of income or wealth. In Africa, we lack tax records as well as administrative information linking children to parents. Instead we rely on censuses from 26 African countries and measure mobility using education data on children that share a household with their parents. [Card, Domnisoru, and Taylor 2018; Azam and Bhatt 2015; Narayan et al. 2018; Black and Devereux 2011 also study intergenerational mobility using education data.]
We measure upward mobility as the likelihood that kids of parents with less than primary education complete at least primary school. Similarly, we call an individual downwardly mobile if her parents have completed at least primary education and she has failed to do so. We compute these measures among children aged 14-18. This gives them enough time to complete primary school if they were ever going to do so. At the same time, most children at that age still live with their parents, which limits potential bias from co-residence selection.
Using education to measure social mobility has five advantages. First, education is a broad measure of living standards, reflecting not just income, but also aspirations and capabilities. Second, unlike income, much of which is informal and therefore under-reported in poor countries, schooling can be easily measured. Third, education, once completed, remains fixed and so intergenerational mobility can be assessed early in life. Fourth, “Mincerian returns” – how much extra income one more year of schooling commands in the labor market – seem to be especially high in Africa (Young 2012; Psacharopoulos 1994; Caselli, Ponticelli, and Rossi 2014), suggesting that education is a meaningful proxy of income. Finally, more schooling is correlated with many positive outcomes: household asset ownership, lower fertility, and even support for democracy. These correlations hold strongly comparing two individuals living in the same place, which means that education “quantity” is a useful stand-in-measure of living standards, even if the quality of schooling differs from place to place.
Main data patterns
The census data give us millions of individual observations to accurately measure intergenerational mobility over time (birth-cohorts) and in small geographic areas. First and most prominently, the descriptive analysis reveals differences in mobility both across and within countries. Figure 1 shows the geography of upward mobility across the 26 countries. Darker regions indicate places with lower mobility – children of illiterate parents are less likely to finish primary school.
Figure 1. Upward mobility across Africa
Source: Alesina et al. 2018
Country-differences are clearly important – South Africa is more mobile than Mozambique. Still, even within countries, there are vast differences as figure 2, which zooms in on Ghana, illustrates.
Figure 2. Upward mobility in Ghana
Source: (Alesina et al. 2018)
In some regions in Northern Ghana, average mobility is below .2 while it exceeds .8 in Accra, the capital. Second, while mobility does increase over time, these increases are modest and most pronounced in the most recent decades. This is still consistent with overall rising education, since average schooling in Africa was low until recently. Taking patterns one and two together, the persistent variation in mobility between places is more important than changes in mobility over time.
What accounts for differences in mobility across space? By far the strongest correlate of intergenerational mobility is the average literacy in the same place in the generation of the parents. This means that, comparing two individuals that grew up as children of illiterate parents in different regions, the individual that grew up in the region that has higher literacy in her parents’ generation has a greater chance of completing at least primary school. Several explanations might account for this pattern. Most simply, some regions have more schools than others, and can educate more individuals “per period”. One alternative story are peer effects: even though my parents are uneducated, I learn by example from the people around me that going to school is possible and desirable.
Beyond the correlation with initial education, we find that geography, colonial history, and at-independence development matter for intergenerational mobility. There are two important caveats to these results. First, pinning down the mechanism of why initial literacy and mobility are related remains a challenge. Second, these results represent correlations and not causally identified effects.
Causal effects of regions
To make causal inferences, we use data on families that have moved between two regions within a country in two ways. First, we compare siblings from migrant households, one child born in the origin of migration, the other in the destination. Figure 3 shows a (binned) scatter plot of the association between average birth-region upward mobility (computed among non-migrants) on the horizontal and individual likelihood of upward mobility on the vertical axis, conditional on household as well as birth-cohort effects. The slope indicates that kids born in a region with a ten percent higher mobility are 2.65 percent more likely to complete primary school compared to their siblings born in a different region with lower mobility.
Figure 3. Migrant vs non-migrant siblings
Source: (Alesina et al. 2018)
Second, we compare migrants that moved at different ages during childhood. Figure 4 plots the effects on individual outcomes of moving from a place of on average zero mobility to a place where all children of uneducated parents become educated against the age of the child at which the move occurred, once again comparing individuals within the same household. As intuition would suggest, earlier moves to better regions have larger positive effects than later moves, and effects turn insignificant towards the end of the period relevant for primary school.
For both empirical strategies, the sibling comparisons (enabled by household fixed effects) are crucial to separate treatment effects of regions from sorting whereby illiterate parents that may be more motivated/capable in educating their children move to regions with greater average opportunities.
Figure 4. Migration exposure effects
Source: (Alesina et al. 2018)
Conclusion
New research points to the importance of “places” in shaping individual social mobility. Complementing several recent works on developed economies, we document that opportunities for educational advancement vary widely within and across African countries. The strongest correlate of differences in mobility between places are differences in the initial education level in the generation of the parents, with more educated places showing higher mobility. Using information on migrants, we find that regions have a causal impact on individual outcomes. Taken together, our results suggest that initial conditions have persistent effects on the transmission of human capital between generations and that overall regional differences in human capital transmission in turn matter for who “makes it” in Africa.
References
- Alesina, Alberto, Sebastian Hohmann, Stelios Michalopoulos, and Elias Papaioannou. 2018. “Intergenerational Mobility in Africa.” Centre for Economic Policy Research Discussion Paper 13497 https://cepr.org/active/publications/discussion_papers/dp.php?dpno=13497
- Asher, Sam, Paul Novosad, and Charlie Rafkin. 2018. “Intergenerational Mobility in India: Estimates from New Methods and Administrative Data.” Mimeo, Dartmouth College.
- Azam, Mehtabul, and Vipul Bhatt. 2015. “Like Father, Like Son? Intergenerational Educational Mobility in India.” Demography 52 (6): 1929–59. https://doi.org/10.1007/s13524-015-0428-8.
- Black, Sandra E., and Paul J. Devereux. 2011. “Recent Developments in Intergenerational Mobility.” In Handbook of Labor Economics, 4B:1487–1541. Elsevier.
- Card, David, Ciprian Domnisoru, and Lowell Taylor. 2018. “The Intergenerational Transmission of Human Capital: Evidence from the Golden Age of Upward Mobility,” 102.
- Caselli, Francesco, Jacopo Ponticelli, and Federico Rossi. 2014. “A New Dataset on Mincerian Returns.” Unpublished.
- Chetty, Raj, and Nathaniel Hendren. 2018a. “The Impacts of Neighborhoods on Intergenerational Mobility I: Childhood Exposure Effects.” The Quarterly Journal of Economics 133 (3): 1107–62. https://doi.org/10.1093/qje/qjy007.
- ———. 2018b. “The Impacts of Neighborhoods on Intergenerational Mobility II: County-Level Estimates.” The Quarterly Journal of Economics 133 (3): 1163–1228. https://doi.org/10.1093/qje/qjy006.
- Chetty, Raj, Nathaniel Hendren, and Lawrence F. Katz. 2016. “The Effects of Exposure to Better Neighborhoods on Children: New Evidence from the Moving to Opportunity Experiment.” American Economic Review 106 (4): 855–902. https://doi.org/10.1257/aer.20150572.
- Chyn, Eric. 2018. “Moved to Opportunity: The Long-Run Effects of Public Housing Demolition on Children.” American Economic Review 108 (10): 3028–56. https://doi.org/10.1257/aer.20161352.
- Deutscher, Nathan. 2018. “Place, Jobs, Peers and the Teenage Years: Exposure Effects and Intergenerational Mobility.” Mimeo.
- Doepke, Matthias, and Fabrizio Zilibotti. 2017. “Parenting With Style: Altruism and Paternalism in Intergenerational Preference Transmission.” Econometrica 85 (5): 1331–71. https://doi.org/10.3982/ECTA14634.
- Economist, The. 2016. “1.2 Billion Opportunities.” The Economist.
- Eriksen, Jesper. 2018. “Finding the Land of Opportunity Intergenerational Mobility in Denmark.” Mimeo.
- Laliberte, Jean-William. 2018. “Long-Term Contextual Effects in Education: Schools and Neighborhoods.” Mimeo.
- Narayan, Ambar, Roy Van der Weide, Alexandru Cojocaru, Silvia Redaelli, Christoph Lakner, Daniel Gerszon Mahler, Rakesh Ramasubbaiah, and Stefan Thewissen. 2018. Fair Progress?: Economic Mobility Across Generations Around the World. World Bank Publications.
- Psacharopoulos, George. 1994. “Returns to Investment in Education: A Global Update.” World Development 22 (9): 1325–43. https://doi.org/10.1016/0305-750X(94)90007-8.
- Sacerdote, Bruce. 2002. “The Nature and Nurture of Economic Outcomes.” American Economic Review 92 (2): 344–48. https://doi.org/10.1257/000282802320191589.
- ———. 2004. “What Happens When We Randomly Assign Children to Families?” NBER Working Paper 10894. https://www.nber.org/papers/w10894.
- Young, Alwyn. 2012. “The African Growth Miracle.” Journal of Political Economy 120 (4): 696–739. https://doi.org/10.1086/668501.
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.
Development of Belarusian Higher Education Institutions Based on the Entrepreneurial University Framework
In contrast to developed Western countries, higher education institutions (HEIs) in transition economies such as Belarus do not have the pretension to being key actors in cutting-edge innovation and in creating entrepreneurship capital. Rather, they tend to educate job seekers or knowledge workers, as well as to adapt, redevelop and disseminate existing knowledge and technologies. At the same time, policy makers in Belarus have realized that transformation of HEIs is needed to respond to the global challenges. In this regard, this policy brief discusses prerequisites and factors conditioning the development of entrepreneurial HEIs in Belarus.
Capitalizing on state-of-the-art academic research, as well as on the custom-made survey of Belarusian faculty members, the brief concludes that Belarusian policy makers need to create a supportive institutional environment before requiring from HEIs outcomes of the entrepreneurial mission. First-priority measures for the current stance are delineated.
Entrepreneurial University and University 3.0
As a productivity factor, entrepreneurial activities started appearing in economic growth models at the beginning of the twenty-first century (Wennekers & Thurik, 1999; Wong et al., 2005). Consequently, the role of HEIs broadened from educating labor force and knowledge creation to development of “entrepreneurial thinking, action and institutions” (Audretsch, 2014) – HEIs took on the third “entrepreneurial” mission.
Well-studied outcomes of this mission are new firms (academic spin-offs, spin-outs, student-led start-ups), patenting, licensing and the development of entrepreneurial culture and attitudes among graduates and academics.
The concept of an entrepreneurial HEI is multifaceted and is explored within different research streams: from knowledge transfer to entrepreneurship education and HEI management. Consequently, there is no consensus in the understanding of the term “entrepreneurial university” that can, for this policy brief, be broadly defined as a HEI that acts entrepreneurially and is a natural incubator, creating a supportive environment for the startup of businesses by faculty and students, promoting an entrepreneurial culture and attitude for the purpose of responding to challenges of the knowledge-based economy, and facilitating economic and social development.
Figure 1. Evolution of the HEIs’ missions
Source: Adapted from Guerrero & Urbano (2012)
Meanwhile, the concept of “University 3.0” –mostly corresponding to the concept of “Entrepreneurial university” and adopted from J.G. Wissema – started appearing in Russian publications, where the number ‘3’ corresponds to the three HEI missions or to the third generation of HEIs. A possible explanation of this renaming is that, on the one hand, in the post-Soviet context entrepreneurship per se still does not have a positive meaning in a broader society and it is not associated to HEIs. On the other hand, it was expected that such numbering makes the evolution visible. However, this led to speculation on this numbering and gave rise to publications on University 4.0 that should correspond somehow to Industry 4.0 – the current trend of automation and data exchange in manufacturing technologies.
Admittedly, the entrepreneurial mission of HEIs is not associated or equaled to start-ups and knowledge transfer any more, but is increasingly considered as a procedural framework for HEI’s and individual’s behavior.
Belarusian Context
Political, economic, social, technological and legal conditions determine the path and the speed of the evolution of HEIs as well as their contribution to national economies in different stages of economic development. Thus, in Belarus – an efficiency-driven economy, i.e., a country growing due to more efficient production processes and increased product quality (World Economic Forum, 2017), – HEIs are considered to contribute to economic development if they successfully fulfill teaching and research missions. While the outcomes of the third mission are supposed not to be relevant at this stage (Marozau et al., 2016).
However, trying to replicate the success of Western HEIs in the development of the entrepreneurial mission, the Ministry of Education of Belarus initiated the Experimental project on implementation of the “University 3.0” model aimed at the development of research, innovation and entrepreneurial infrastructure of HEIs for the creation of innovative products and commercialization of intellectual activities.
In general, Belarus has a state-dominated well-developed, by some estimates, oversaturated higher education sector that remains mostly rigid and unreformed since the Soviet times. Belarus outperformed all CIS and EU countries except Finland in terms of the number of students per 10,000 population in 2014 (Belstat, 2017) and according to the World Bank has one of highest enrollment rates in tertiary education of about 90%.
Belarusian students have quite high entrepreneurial potential in comparison to other countries participating in the Global University Entrepreneurial Spirit Students‘ Survey (GUESSS). Thus, in five years after graduation, 56.8% intend to be entrepreneurs, while the global average level is 38,2% (Marozau and Apanasovich, 2016). However, curricula of most specialties majors provided by Belarusian HEIs are not supplemented with formal and experiential entrepreneurship education to equip students with entrepreneurial competencies. Innovative methodologies and entrepreneurial approaches to teaching as well as faculty entrepreneurial role models are rare. Moreover, all changes in degree syllabuses need state approval that makes HEIs less flexible and nimble. The situation is further complicated by the fact that supporting entrepreneurial activity has not been an important part of the HEI culture.
Methodological Approach
We conducted online and face-to-face surveys of 48 Belarusian HEI authorities and faculty members that were based on HEInnovate self-assessment tool widely used by policy makers and HEI authorities (see Marozau, 2018).
Overall, emails were sent out to a population of 284 pro-active and advanced representatives of the Belarusian academic community whose email addresses were available in the databases of BEROC and the Association of Business Education. We benefitted from open-ended questions included in the questionnaire to study how representatives of Belarusian HEIs perceived the Entrepreneurial university (University 3.0) concept as well as its conditioning factors and potential outcomes.
Main Findings
First of all, we revealed that the Belarusian academic community is not unanimous in understanding the concept “Entrepreneurial university”. According to the main emphasis provided by respondents, we got the following distribution of answers about what an entrepreneurial is: 12 respondents associated the concept with knowledge transfer and commercialization; 7 respondents stressed the interrelation of teaching, research and innovations; 5 respondents believed that the concept is about earning money; 1 respondent indicated that an entrepreneurial university means developing entrepreneurial competences.
These findings demonstrate the general misunderstanding or fragmented understanding of the phenomenon that may lead to a negative attitude from both HEI staff and policy makers and stress the importance of raising awareness and providing training at least for decision makers and spokesmen.
Figure 2 demonstrates the results of the assessment of Belarusian HEIs against the categories proposed by HEInnovate (1 – very low; 5 – very high).
Figure 2. Assessment of HEIs
Source: Author’s own elaborations
We distinguished pairwise between (i) HEIs that participated in the Experimental project and those that did not: (ii) estimates of faculty members that were aware of the concept and those who were not.
Surprisingly, the representatives of HEIs that were left beyond the scope of the Experimental project and those who were aware of the concept perceived their HEIs more advanced in all the areas.
To understand this paradox, we used the chi-square test for independence to discover if there was a relationship between two categorical variables – awareness of the concept and employment at a HEI participating in the Experimental project. Surprisingly, no statistically significant relationship was identified evidencing that implementation of the Experimental project went without raising awareness and wider involvement of faculty.
The analyses of answers to open-ended questions showed that many environmental factors are not only unsupportive to the HEI entrepreneurial development but jeopardize the sustainability of the higher education system in general.
Conclusions
The main conclusions from the study are as follows:
- Belarus has not reached the stage of institutional development to foster entrepreneurial HEIs and to expect outcomes of the entrepreneurial mission. To some extent, this explains the skepticism and misunderstanding of the concept of “Entrepreneurial university” (University 3.0).
- The main omission of the Experimental project is that the education and training of HEI authorities and faculty are not defined as first-priority measures. Such policy initiatives need to be clear in their objectives, tools, benefits and outcomes as well as evidence-based and open for discussion.
- Comprehensive initiatives in this sphere should be developed and implemented in close collaboration with the Ministry of Economy that is responsible for entrepreneurship, the business environment, entrepreneurial infrastructure as well as the State Committee for Science and Technology that is subordinated to the Council of Ministers and deals with the state policy in its sphere.
An important concern here is whether it is currently feasible to have the measures that are relevant and not-for-show rather than half-way initiatives and sticking plaster solutions despite the lack of funding, and absence of elaborate study in the field.
- Since the weakest area of Belarusian HEIs according to the HEInnovate tool is the problem of ‘Measuring impact’, the state should reconsider short-term target indicators for HEIs such as export growth rate and workforce productivity growth rate to stimulate investments the entrepreneurial transformation. It is worth monitoring such indicators as number of start-ups/spin-offs founded by graduates/faculty members; number of patents, licenses, trademarks co-owned by a HEI, income from intellectual property; number of R&D projects funded by enterprises etc. Alternatively, the Ministry of Education could adopt the ranking of entrepreneurial and inventive activity of universities used in Russia.
- Development of entrepreneurship centers as organizational units at HEIs – ‘one-stop shops’ or ‘single front doors’ for students, faculty, businesses – could be an initial step towards both raising awareness and the integration and coordination of entrepreneurship-related activities within a HEI in order to increase their impact and visibility of these activities.
References
- Audretsch, David B., 2014. “From the entrepreneurial university to the university for the entrepreneurial society.” The Journal of Technology Transfer 39(3), 313-321.
- Belstat (2017). Education in the Republic of Belarus. Statistical book.
- Guerrero, Maribel, and David Urbano, 2012. “The development of an entrepreneurial university.” The journal of technology transfer 37(1), 43-74.
- Marozau, Radzivon, Maribel Guerrero, and David Urbano, 2016 “Impacts of universities in different stages of economic development.” Journal of the Knowledge Economy, 1-21.
- Marozau, Radzivon and Vladimir Apanasovich, 2016. National GUESSS Report of the Republic of Belarus. http://www.guesssurvey.org/resources/nat_2016/GUESSS_Report_2016_Belarus.pdf
- Radzivon Marozau, 2018. Modernization and development of Belarusian higher education institutions based on the entrepreneurial university framework. BEROC Policy Paper Series, PP no.63.
- Wennekers, Sander, and Roy Thurik, 1999. “Linking entrepreneurship and economic growth.” Small business economics 13(1), 27-56.
- World Economic Forum, 2017. “Global Competitiveness Report 2017-2018”, edited by Klaus Schwab.
- Wong, Poh Kam, Yuen Ping Ho, and Erkko Autio, 2005. “Entrepreneurship, innovation and economic growth: Evidence from GEM data.” Small business economics 24(3) 335-350.
Acknowledgments: The author expresses gratitude to Prof. Maribel Guerrero from Newcastle Business School, Northumbria University for her valuable comments and reviews as well as to Yaraslau Kryvoi and Volha Hryniuk from the Ostrogorski Centre (Great Britain) for coordinating the research project that has resulted in this policy brief.
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.
Sex, Drugs, and Bitcoin: How Much Illegal Activity Is Financed Through Cryptocurrencies?
Using novel approaches that exploit the blockchain to identify illegal activity, we estimate that around $76 billion of illegal activity per year is financed through payments in bitcoin (46% of bitcoin transactions). This staggering number is close to the scale of the US and European markets for illegal drugs and suggest that cryptocurrencies are transforming the black markets by enabling “black e-commerce.”
Cryptocurrencies have grown rapidly in price, popularity, and mainstream adoption. The total market capitalization of bitcoin alone exceeds $150 billion as of July 2018, with a further $150 billion in over 1,800 other cryptocurrencies. The numerous online cryptocurrency exchanges and markets have a daily dollar volume of around $50 billion. Over 170 ‘cryptofunds’ have emerged (hedge funds that invest solely in cryptocurrencies), attracting around $2.3 billion in assets under management. Recently, bitcoin futures contracts have commenced trading on the major US derivatives exchanges (CME and CBOE), catering to institutional demand for trading and hedging bitcoin. What was once a fringe asset is quickly maturing.
The rapid growth in cryptocurrencies and the anonymity that they provide users has created considerable regulatory challenges, including the use of cryptocurrencies in illegal trade (drugs, hacks and thefts, illegal pornography, even murder-for-hire), potential to fund terrorism, launder money, and avoid capital controls. There is little doubt that by providing a digital and anonymous payment mechanism, cryptocurrencies such as bitcoin have facilitated the growth of ‘darknet’ online marketplaces in which illegal goods and services are traded. The recent FBI seizure of over $4 million of bitcoin from one such marketplace, the ‘Silk Road’, provides some idea of the scale of the problem faced by regulators.
In a recent research paper (Foley, Karlsen, and Putnins, 2018), which is forthcoming in the Review of Financial Studies, we quantify the amount of illegal activity that involves the largest cryptocurrency, bitcoin. As a starting point, we exploit several recent seizures of bitcoin by law enforcement agencies (including the US FBI’s seizure of the Silk Road marketplace) to construct a sample of known illegal activity. We also identify the bitcoin addresses of major illegal darknet marketplaces. The public nature of the blockchain allows us to work backwards from the law enforcement agency bitcoin seizures and the darknet marketplaces through the network of transactions to identify those bitcoin users that were involved in buying and selling illegal goods and services online. We then apply two econometric methods to the sample of known illegal activity to estimate the full scale of illegal activity. The first exploits the trade networks of users to identify two distinct ‘communities’ in the data—the legal and illegal communities. The second exploits certain characteristics that distinguish between legal and illegal bitcoin users, for example, the extent to which individual bitcoin users take actions to conceal their identity and trading records, which is a predictor of involvement in illegal activity.
We find that illegal activity accounts for a substantial proportion of the users and trading activity in bitcoin. For example, approximately one-quarter of all users (26%) and close to one-half of bitcoin transactions (46%) are associated with illegal activity. The estimated 27 million bitcoin market participants that use bitcoin primarily for illegal purposes (as at April 2017) annually conduct around 37 million transactions, with a value of around $76 billion, and collectively hold around $7 billion worth of bitcoin.
To give these numbers some context, the total market for illegal drugs in the US (Kilmer et al, 2014) and Europe (EMCDDA, 2013) is estimated to be around $100 billion and €24 billion annually. Such comparisons provide a sense that the scale of the illegal activity involving bitcoin is not only meaningful as a proportion of bitcoin activity, but also in absolute dollar terms. The scale of illegal activity suggests that cryptocurrencies are transforming the way black markets operate by enabling ‘black market e-commerce’. In effect, cryptocurrencies are facilitating a transformation of the black market much like PayPal and other online payment mechanisms revolutionized the retail industry through online shopping.
In recent years (since 2015), the proportion of bitcoin activity associated with illegal trade has declined. There are two reasons for this trend. The first is an increase in mainstream and speculative interest in bitcoin (rapid growth in the number of legal users), causing the proportion of illegal bitcoin activity to decline, despite the fact that the absolute amount of such activity has continued to increase. The second factor is the emergence of alternative cryptocurrencies that are more opaque and better at concealing a user’s activity (e.g., Dash, Monero, and ZCash). Despite these two factors affecting the use of bitcoin in illegal activity, as well as numerous darknet marketplace seizures by law enforcement agencies, the amount of illegal activity involving bitcoin at the end of our sample in April 2017 remains close to its all-time high.
In shedding light on the dark side of cryptocurrencies, we hope this research will reduce some of the regulatory uncertainty about the negative consequences and risks of this innovation, facilitating more informed policy decisions that assess both the costs and benefits. In turn, we hope this contributes to these technologies reaching their potential. Our work also contributes to understanding the intrinsic value of bitcoin, highlighting that a significant component of its value as a payment system derives from its use in facilitating illegal trade. This has ethical implications for bitcoin as an investment. Third, the techniques developed in the paper this brief is based on can be used in cryptocurrency surveillance in a number of ways, including monitoring trends in illegal activity, its response to regulatory interventions, and how its characteristics change through time. The methods can also be used to identify key bitcoin users (e.g., ‘hubs’ in the illegal trade network) which, when combined with other sources of information, can be linked to specific individuals.
References
- EMCDDA, 2013. “EU drug markets report: a strategic analysis.” Lisbon, January 2013.
- Foley, Sean; Jonathan R. Karlsen; and Talis J. Putnins, 2018. “Sex, Drugs, and Bitcoin: How Much Illegal Activity Is Financed Through Cryptocurrencies?” (October 21, 2018), forthcoming in the Review of Financial Studies.
- Kilmer, Beau; Susan S. Sohler Everingham; Jonathan P. Caulkins; Greg Midgette; Rosalie Liccardo Pacula; Peter H. Reuter; Rachel M. Burns; Bing Han; and Russell Lundberg, 2014. “What America’s Users Spend on Illegal Drugs: 2000–2010.” Santa Monica, CA: RAND Corporation, 2014.
Acknowledgment: This Policy Brief is based on a recent research paper (Foley, Karlsen, and Putnins, 2018), which is forthcoming in the Review of Financial Studies, published by Oxford University Press and the Society for Financial Studies.
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.