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Long-Run Inequality in Communist Countries: Before, During and After

Abstract

This chapter provides comprehensive evidence on the long-run evolution of inequality in former communist countries in comparative perspective. We document a marked U-shaped evolution of income inequality since the beginning of the twentieth century until today. We analyse these trends for three periods, before, during and after communism, and make comparison with non-communist countries. A broad synchronisation of inequality in communist and non-communist countries presents a compelling argument against the “natural” decline of inequality during the development process. Rather, it points to the critical role of policies and institutions in shaping inequality in the long run.

Keywords

  • Income and wealth inequality
  • Comparative development
  • Transition

This chapter draws on Novokmet (2017, 2018), Bukowski and Novokmet (2019), Novokmet et al. (2018a, b), Kump and Novokmet (2018), Milanović et al. (2020)

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Fig. 9.1
Fig. 9.2
Fig. 9.3
Fig. 9.4
Fig. 9.5
Fig. 9.6
Fig. 9.7
Fig. 9.8
Fig. 9.9
Fig. 9.10
Fig. 9.11
Fig. 9.12
Fig. 9.13
Fig. 9.14
Fig. 9.15
Fig. 9.16
Fig. 9.17
Fig. 9.18

Notes

  1. 1.

    Recently, research using income tax data to construct top incomes has provided a broad historical perspective of income inequality in the international context (Kuznets 1953; Piketty 2001, 2003, 2014; Atkinson and Piketty 2007, 2010; Atkinson et al. 2011; Roine and Waldenström 2015).

  2. 2.

    Piketty has attributed the key role in shaping inequality to fiscal institutions and redistributive policies. For example, the introduction of steeply progressive taxation prevented the recovery of top wealth holdings after WWII. The recent rise of inequality has been explained by factors such as changing remuneration social norms, reduced income tax progressivity, stagnant minimum wage and the demise of trade unions. Piketty’s finding has been confirmed in other developed countries (Atkinson and Piketty 2007, 2010; Atkinson et al. 2011; Roine and Waldenström 2015).

  3. 3.

    For example, Nikolić and Novokmet (2017) compare historical inequality trajectories in the former Czechoslovakia and Bulgaria, countries at markedly different levels of economic development before the Communist seizure of power after WWII (ibid., T.2). Accordingly, the two countries that had previously displayed notably different inequality levels all of a sudden became characterised by the most egalitarian income distribution in the post-WWII decades.

  4. 4.

    Piketty and Saez (2014, p. 842) note in this respect that “the Kuznets’ overly optimistic theory of a natural decline in income inequality in market economies largely owed its popularity to the Cold War context of the 1950s as a weapon in the ideological fight between the market economy and Socialism”.

  5. 5.

    For example, with the super-rapid (“voucher”) privatisation or shrinking social state, evidenced in declining social transfers or minimum wage and so on.

  6. 6.

    The top shares methodology is used in much of historical distributional research. The methodological approach consists in relating information in tax statistics to reference totals for population and income (Kuznets 1953; Piketty 2001; Atkinson 2007).

  7. 7.

    For details on the Distributional National Accounts (DINA) methodology, see Alvaredo et al. (2016).

  8. 8.

    But shocks to capital income played an important role even before the arrival of communism, corresponding again to Western experience (Piketty 2001). This is suggested by the “structural” decline after WW1 in Central Europe (see Fig. 9.1 the Czech or Polish series; for Germany, see Dell 2007).The post-war situation worldwide opened a new page in the distributional history (e.g. Piketty 2014; Milanović 2016).

  9. 9.

    Broadly covering dividends, interests, business profits, rents, land income and so on.

  10. 10.

    This is revealed from the breakdown of the business income in top shares according to economic branches, which shows that bulk of high business incomes were earned in industry (Novokmet 2018, Fig. 15).

  11. 11.

    The Czech Lands are Bohemia, Moravia and Silesia, and formed the Czech part of former Czechoslovakia and since 1993 the Czech Republic.

  12. 12.

    First, Poland was still dominantly an agrarian economy before WWII and markedly less industrialised than Czechoslovakia, or even Hungary. Second, Poland was characterised by large land concentration in the hands of nobility, especially “Prussian Poland”, which, like the Czech Lands, experienced a rapid development of commercial agriculture. Bukowski and Novokmet (2019) find that the “agricultural revolution” in Prussian Poland in the two decades preceding WW1 was accompanied by a notable increase in top incomes, which were almost exclusively concentrated in the countryside.

  13. 13.

    For example, Czechoslovakia succumbed to the “gold orthodoxy” and adhered relatively longer to the French-led Gold bloc, while it managed to free itself from the consequent deflation by rather late devaluations in 1934 and 1936 (Eichengreen 1992).

  14. 14.

    In contrast to Czech Lands, top incomes in Slovakia rose during the Great Depression, probably as a result of the rising urban-rural gap (see Novokmet 2018, T.21)

  15. 15.

    Rough estimates indicate that cartels controlled more than half of the industrial output in Poland in the 1930s (Landau 1978). The Czechoslovak industry had shown substantial cartelisation before, but only after the introduction of compulsory cartelisation in 1933, it became the dominant feature.

  16. 16.

    There is rich historical evidence pointing to a marked enrichment of particular layers of society, in the first place of large industrialists who collaborated with the Nazi regime. In addition, wartime often offered various means for rapid and spectacular enrichment, for example, the infamous process of “Ariyanisation” through which Jewish property was confiscated Novokmet (2018, Table 2).

  17. 17.

    Lampe and Jackson (1982, p. 240) comment that “previous economic centres suffered … for being far from the seat of political power”.

  18. 18.

    This is a plausible feature of “industrial laggards”. Namely, a relative backwardness of CEE in the nineteenth century entailed significant state intervention in promoting industrialisation (acting as Gerschenkron’s “substitutes for prerequisites”), and here banks especially had a prominent role in pooling funds, thereby promoting cartelisation to minimise risk (Hilferding 1923; Rudolph 1976), which lead to oligopolistic structures in the heavy industry, engineering, banking and finance, and so on (Teichova 1974 ).

  19. 19.

    Similarly, Handbuch der Millionäre suggests that most of the German millionaires before WWI were large landowners (Baten and Schulz 2005). Yet, it should be mentioned that big landed wealth had already been under the attack notably with the land reforms implemented after WW1 in the newly formed “nation” states of Central Eastern Europe.

  20. 20.

    Other authors have pointed to similar trends elsewhere: for example, the abolishment of zaibatsu or the land reforms in Japan (Moriguchi and Saez 2008), nationalisations in France (e.g. of Renault in 1946, see Piketty 2001), etc.

  21. 21.

    Moreover because, as said above, there was an important reduction in capital income inequality in Western countries during the twentieth century.

  22. 22.

    For example, even the expansion of education, which is typically seen as one of the key economic mechanisms determining the wage distribution, could be seen as driven by the political domain.

  23. 23.

    Flakierski (1992, p. 12) notes that “the socialist state had to reconcile the need for economic efficiency with ethical considerations of social justice in the field of distribution, which obviously was not easy”.

  24. 24.

    The long-term evidence on the wage distribution by percentile ranks is obtained from employer surveys. Comparable and exhaustive surveys were introduced in the Soviet Union in the 1920s and in CEE countries in the 1950s. Bergson (1942, 1944) is the seminal assessment of inequality of earnings in the Soviet Union in 1928 and 1934. Atkinson and Micklewright (1992) extensively analysed employer surveys in Czechoslovakia, Hungary, Poland and the Soviet Union since the 1950s until the late 1980s. Flakierski looked in detail at evidence for Poland and Hungary (1986), former Soviet Union and Yugoslavia (1989). We extend their analysis back to the pre-communist period.

  25. 25.

    This striking development has been confirmed by Brainerd (1998), Flemming and Micklewright (2000) and so on.

  26. 26.

    This decline is gauged from available data on the distribution among wage earners in industry, though these are a good predictor for all sectors. The comparison of decile ratios in periods when both estimates of the distribution for all workers and wage earners are available suggests that the distribution for industrial wage earners is representative of developments in the earnings distribution before WWII (Bergson 1984, p. 1077; evidence for Poland).

  27. 27.

    It is true that a more significant reduction in earnings inequality occurred between 1980 and 1982—coinciding thus with the emergence of the Solidarity movement—yet it was short-lived, and earnings dispersion increased again after 1982. Moreover, there is considerable doubt about the data quality during the 1980s, given the prevalent economic turmoil (Flakierski 1986).

  28. 28.

    The difference between today and interwar Poland is more compressed upper- and lower-tail inequalities. Thus, while in 1929, P10 was barely 37% of median wage, in 2016 it is 54. On the other hand, P90 was 235% of median wage, while today is 205%.

  29. 29.

    The data for Warsaw refers to the distribution of weekly wage among manual workers in medium-sized and large establishment.

  30. 30.

    Landau (1933, p. 120) notes that a strong fall in wages had first occurred in small industry, while “in big industry the process was checked by collective contract”. However, Landau adds that a major fall in wages eventually occurred in big industry after 1932. This plausibly contributed to a fall of upper-tail inequality, as indicated by the development of P90/P50 for manual workers in Warsaw.

  31. 31.

    Evidence on the wage distribution for Czechoslovakia in the late 1920s/1930s and the late 1940s is based on insurance statistics. The evolution of the P90 ratio suggests that a significant narrowing of upper-tail inequality had already occurred before the communist coup of 1948. Maňák (1967) documented the first post-war wage regulation implemented in December 1945 (Večerník 1991), though the true “wage revolution” took place between 1948 and 1953, with a dramatic decline in wage inequality.

  32. 32.

    Although, as said, there are doubts about the reliability of data during this period of inflation and widespread shortages, a large part of the decline should be directly attributed to the demand of Solidarity from the Gdansk Agreement (Flakierski 1991).

  33. 33.

    Phelps Brown (1977, p. 81) succinctly explains that “most of the white-collar occupations are distinguished from the manual by the level of education required by entrants, and the graduations of their pay are fairly closely associated with gradations of that level”.

    The white-collar premium has proved robust proxy for earnings inequality, but the two groups should not be assumed as uniform “classes”. For example, historical evidence on the “labour aristocracy” suggests a heterogeneity within the class of manual workers, Hobsbawm or Gray). See also Fig. 9.11a.

  34. 34.

    Arguably, the much sharper post-war reduction in skill gap in Czechoslovakia and Poland compared to the USSR should be related to the timing of the communist accession.

  35. 35.

    Kalecki (1964) summarised this development as follows: “a white-collar worker, who in pre-war Poland belonged to the privileged class compared to the manual worker, in 1960 earned on average little more than the manual worker”.

  36. 36.

    Although the white-collar premium had been lower in the interwar Czechoslovakia than in Poland, it was nonetheless substantial by international standards. In Czechoslovakia, skills were not in limited supply. Actually, the Czech Lands had one of the highest educational attainments in Europe at the time (Teichova 1988).

  37. 37.

    According to Kocka, the collar division was finally “institutionalised” in Germany with a legal separation of insurance schemes for white-collar and manual workers. An equivalent development had taken place in Imperial Austria (ibid., p. 466), and the separate insurance schemes persisted into the new nation states in Central Eastern Europe that emerged from the German Empire and Austria-Hungary.

  38. 38.

    The First Republic, in particular, is frequently seen as the golden age for salaried workers and civil servants, and often these are identified with the ascendant Czech bourgeoisie (Teichova 1988).

  39. 39.

    Communists shared a suspicion of the “reliability” of intellectuals with the Nazis and saw the intelligentsia as natural enemies. During the occupation of Poland and Czech Lands, the Nazis pursued policies discriminating white-collar workers. Largely in consequence of the intelligentsia’s pronounced role as the backbone of national consciousness—which had in part underlaid their higher social status during the interwar era—intelligentsia suffered the most during WWII (Gella 1989). Snyder (2011) argues that both the Nazi and Soviet occupational forces especially targeted the Polish intelligentsia during their respective invasions following the Molotov-Ribbentrop Pact. One mournful illustration is the fate of two brilliant interwar economists, the pioneers of the statistical investigation of economic and social inequality, Ludwyk Landau and Jan Wisniewski. The first was murdered by the Gestapo, while the second ended his life in Katyn.

  40. 40.

    For example, the Czechoslovak Communist Party (KSČ) kept a strong anti-intellectual stance until the very end of its rule (Grzymala-Busse 2002, p. 31).

  41. 41.

    Phelps Brown (1977, p. 66) writes: “As far back as the 1840s, John Stuart Mill thought that the spread of literacy would have brought down the relative pay of clerks had it not been for the traditional valuation of their status; and the effective reason for the comparatively low position of clerical pay in the Soviet structure may be that this tradition was destroyed by revolution, so that market forces could take the effect that continued to be denied them by customary attitudes in the West”.

  42. 42.

    To quote Bergson (1944, p. 209): “in view of the pressure of the Soviet five-year program for industrial expansion, the abandonment of egalitarianism in 1931 is not difficult to explain on other grounds”.

  43. 43.

    As noted, comprehensive enterprise surveys carried out in socialist countries allow us to chart the wage distribution over the longer time span (Atkinson and Micklewright 1992; Atkinson 2008; Rutkowski 2001).

  44. 44.

    Keane and Prasad (2006) find that earnings dispersion in Poland took place within both the public and private sectors, and thus within-sector inequalities were the dominant force behind the overall de-levelling trend.

  45. 45.

    The P90/50 ratio jumped over 300% in 2001 and then saw a gradual decline attain levels around 250% in 2015. The P10/50 ratio fell to less than 15% in 1995 and then continually increased to 40% in 2015.

  46. 46.

    Keane and Prasad (2002) have argued that this provided the general political support for market reforms and enterprise restructuring in Poland.

  47. 47.

    Unfortunately, the tax data on high-income individuals used to correct the top of the income distribution in Russia and China do not allow us to distinguish different income sources at the top of the income distribution.

  48. 48.

    However, it should be mentioned that business income includes both return to physical and human (entrepreneurial) capital.

  49. 49.

    In particular, the fact the holders of top capital incomes tend to be foreigners rather than domestic residents contributes to lower top income shares in countries like the Czech Republic or Hungary (Fig. 9.17b).

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  1. Institute for Macroeconomics and Econometrics, University of Bonn, Bonn, Germany

    Filip Novokmet

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  1. Filip Novokmet
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  1. School of Slavonic and East European Studies, University College London, London, UK

    Dr. Elodie Douarin

  2. Carleton University, Ottawa, ON, Canada

    Prof. Oleh Havrylyshyn

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Novokmet, F. (2021). Long-Run Inequality in Communist Countries: Before, During and After. In: Douarin, E., Havrylyshyn, O. (eds) The Palgrave Handbook of Comparative Economics. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-50888-3_9

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