Property confiscation and the intergenerational transmission of education in post-1948 Eastern Europe

Abstract

Using regression methods and propensity score matching applied to two different retrospective samples, this study finds evidence of a positive “property confiscation” effect on educational attainment. We use a 1993 survey of adults (aged 20–69) in the post-transition Eastern European countries of Bulgaria, the Czech Republic, Hungary, Poland and Slovakia. In countries experiencing the most private property losses, regression results indicate that years of schooling increase by about 0.19 for each member of an affected extended family (parents, maternal grandfathers, or paternal grandfathers). When all three sets of family members lost property, we find an increase in years of educational attainment of about 0.6. We also find an increase in the probability of post-high school education of about 0.02 for each extended family member whose property was confiscated. Those findings are confirmed using propensity score matching, which provides a larger and more pervasive positive confiscation effect. We also test our hypothesis using current and retrospective microeconomic panel data from Europe’s Survey of Health, Aging and Retirement (SHARE), a dataset that covers countries in Eastern and Western Europe. We again find that property confiscation leads to greater educational attainment in the children of the affected households. We apply propensity score matching to the data and find, again, positive and statistically significant evidence of a confiscation effect on years of educational attainment. Auxiliary work indicates a separate channel for property confiscation’s effects. Our explanation for the empirical results reported herein can be found in families’ ability to pay bribes to advance their children’s education.

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Notes

  1. 1.

    For example, Goldberger (1989) examines several models of intergenerational transmission. O’Brien and Jones (1999) use English data to establish factors at work in the intergenerational transmission of educational advantage. Using US data, Currie and Moretti (2003) examine four channels through which maternal education may affect the intergenerational transmission of human capital. Sacerdote (2005) examines the span of time required for the educational attainment of the descendants of slaves to rival the educational attainment of free black men and women. Using data for Greece, Daouli et al. (2010) find substantial educational mobility across generations. Pronzato (2012) examines the relative importance of paternal and maternal educational attainment using a sample of Norwegian twins. Riphahn and Trubswetter (2013) find that educational mobility in East Germany lags behind West Germany, even after unification. Using Swedish data, Lindahl et al. (2014) examine the intergenerational transmission of education across three generations. Also using Swedish data, Amin et al. (2015) ask whether the transmission mechanism is stronger for fathers than for mothers. Lastly, using a three-generation sample of US women during the twentieth century, Kroeger and Thompson (2016) find strong educational persistence, especially between grandmothers and granddaughters.

  2. 2.

    Our extension of Gandelman’s model, which forms the basis for our empirical work, is given in “Appendix 1”.

  3. 3.

    A brief history of property confiscations is provided in “Appendix B”.

  4. 4.

    The UCLA project is titled “Social Stratification in Eastern Europe after 1989: General Population Survey”, and can be found at http://www.library.ucla.edu/social-science-data-archive/sseehome. Using a questionnaire common to all five countries, national probability samples of approximately 5000 adults were surveyed in Bulgaria, the Czech Republic, Hungary and Slovakia in 1993. Data collection in Poland was delayed until 1994 and reduced to a sample of approximately 3500 owing to a lack of local funds. The survey’s design called for exactly comparable wording of questions, and variation in the response categories only when national variations in circumstances (e.g., different religious distributions) warranted other wording. Country-specific survey teams were free to add local questions at the questionnaire’s end. To ensure comparability, the questionnaire was translated into each local language and then retranslated into English; the retranslated versions were compared as a group by a multi-lingual team, and discrepancies in wording were corrected.

  5. 5.

    In our model, we include information on individuals’ motivation to seek education and individuals’ family environments, particularly parents’ educational background and parents’ position in society. The current investigation is, however, likely somewhat hindered by the possibility that the sample is biased owing to emigration from the countries taking place during the mid-twentieth century, before the UCLA project was initiated. The direction of the potential bias depends on whether people fleeing the countries had less property confiscated and were more highly educated than others who did not emigrate. As such, the bias that is likely present in the present sample can work for or against our hypothesis. We thank an anonymous referee for pointing this out.

  6. 6.

    This empirical approach to human capital investment follows Mixon and Salter (2008).

  7. 7.

    We interpret responses of “yes” to questions to imply that respondents incurred property losses, confiscation, or collectivization by newly communist-dominated governments since 1948.

  8. 8.

    Employment may be associated with more than one category.

  9. 9.

    According to Glenn (1995), education was very important to the communist parties in Eastern Europe, but primarily as a method of indoctrination and control.

  10. 10.

    For Bulgaria, the ethnic categories were Armenian, Bulgaro-mohamedani, Vlassi, Gagauzi, Greek, Jewish, Karachani, Macedonian, Russian, Turkish, Roma and other. For Czechoslovakia, the options were Czech, Slovak, Moravian, Silesian, Jewish, Polish, Hungarian, Russian, German, gypsy, Ukrainian and other. For Hungary, the options were German, Slovak, Jewish, Romanian, Serbian, Croatian, gypsy, Ukrainian and other. Lastly, for Poland, the options were German, Jewish, Ukrainian, Byelorussian, Lithuanian, Russian, Slovak and other.

  11. 11.

    A more complete set of results omitting only the ethnic dummy variables is provided in “Appendix 3”, Tables 13, 14, 15 and 16.

  12. 12.

    We split the sample in that way so our analysis is based only on individuals owning property who suffered no property losses after 1947.

  13. 13.

    All models in the empirical section are estimated by OLS. In studies of the intergenerational transmission concerns arise often about the confounding effects of parents’ education and income, which introduces the possibility of bias owing to the transmission of unmeasured ability. We believe that such possible biases are offset by the fact that education is widely available and nominally free and that we have no measure of parental income as we use retrospective data. Our model does include the number of the respondent’s brothers and sisters, which can be taken as a proxy for “cost” of education in a Beckerian sense. We likewise enter several independent variables that are proxies for unmeasured ability, such as our group of attitudinal variables: Ambit, Work, Net, Pol, Risk, Edu88, and Edu93.

  14. 14.

    The use of propensity score matching should help reduce any selectivity biases in the previous estimations (Caliendo and Kopeinig 2008).

  15. 15.

    The first wave of SHARE data collection started in 2004 and covered 11 European countries (Austria, Belgium, Denmark, France, Germany, Greece, Italy, Netherlands, Spain, Sweden and Switzerland). SHARE collected a wide range of information, including the respondent’s age, education, marital status, health, income, housing and financial assets. Wave 2 took place in 2006 and added two countries to the panel—Poland and the Czech Republic. Wave 3 (known as SHARELIFE) was conducted in 2008 and collected retrospective early-life data about the survey participants from the above 13 countries. SHARELIFE covers childhood health history, school performance, immunizations, detailed family information, such as occupation of the family bread-winner and household net worth, housing (location, amenities, ownership), number of siblings, and number of books in the house. We use Waves 1–3 of the SHARE data in our analysis. We also incorporate the data on combat operations compiled by Kesternich (2014), which combined locations of the combat operations with information about the region where the survey respondents lived during each year of the war. For additional information on the SHARE dataset, see Börsch-Supan, et al. (2013) and Börsch-Supan. (2018a, b, c).

  16. 16.

    We note some of the differences between the UCLA dataset and the SHARE dataset. First, the SHARE dataset is much larger and follows individuals throughout their lives, which should greatly reduce any biases associated with emigration that may be present in the UCLA data. As noted previously, the SHARE dataset also contains information on some Western European countries. The confiscation variable in the SHARE dataset is defined somewhat differently than in our earlier analysis. In particular, in the SHARE dataset the variable is Dispossession which is based on respondents’ answers to the following question, “There may be cases when individuals and their families are dispossessed of their property as a result of war or persecution. Were you or your family ever dispossessed of any property as a result of war or persecution?” Thus, no information is available as to which family member suffered the dispossession. The set of SHARE-based empirical results thus has more in common with those reported earlier in Table 2, which estimated the effects of Anyloss. The SHARE data used in this study do not contain information on family ethnicity, parents’ Communist Party membership status, or parents’ and grandfathers’ educational attainment. However, the dataset reports information sufficient for measuring family status; the large sample size allows us to include a set of birth year dummy variables not possible for the UCLA sample. We are confident that the explanatory variables available to us in the combined UCLA-SHARE dataset allow us to obtain alternative estimates of the impact of confiscation on educational attainment.

  17. 17.

    For example, respondents were asked the following question(s) about their position relative to other children at age 10 in terms of their mathematics (language) skills: Compared to other children in your class, did you perform in mathematics (your country’s language) much better, better, about the same, worse, or much worse than the average? We construct dummy variables from those responses.

  18. 18.

    The results for the full model including the birth year dummy variables and the country dummy variables are available upon request.

  19. 19.

    Government transfers, as a part of the property taxed or confiscated, can be added to the model but they do not change the qualitative results.

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Acknowledgements

The authors would like to thank Bettina Siflinger for providing data on World War II combat operations; two anonymous reviewers and Arye Hillman supplied helpful comments on prior versions. This paper uses data from SHARE Waves 1, 2, and 3 (SHARELIFE) (DOIs: https://doi.org/10.6103/share.w1.611, https://doi.org/10.6103/share.w2.611, https://doi.org/10.6103/share.w3.611). The SHARE data collection was funded primarily by the European Commission through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812) and FP7 (SHARE-PREP: No211909, SHARE-LEAP: No227822, SHARE M4: No261982). Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the US National Institute on Aging and from various national funding sources is gratefully acknowledged (see www.share-project.org). The usual caveat applies.

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Appendices

Appendix 1: Two-period model of the impact of property confiscation

Below we develop and solve the problem of a utility-maximizing representative household willing to provide education to their offspring in a socialist country. Parents earn income (from unskilled and/or skilled labor), pay taxes, spend on consumption, and may have their property confiscated. Parents also save and bequest, and both are subject to seizure and taxation.

The model has a similar structure as the bequest models of Araújo and Martins (1999), Faria and Wu (2012) and the intergenerational model of Gandelman (2016). Gandelman (2016) analyzes the case in which, with uncertain house property rights, parents may invest in children's education or in their own homes. He derives and analyzes income and substitution effects. We also address similar kinds of choices in our model, however the trade-off involves education of present versus future generations, under the ever-present threat of property confiscation.

In line with the literature (e.g., Checchi 2006), the representative household maximizes a two-period utility function that takes into account parents’ and children's education and reflects bequest motives under the risk of property confiscation. The model yields a number of important results. First, it is consistent with two stylized facts of a socialist economy: the gradual erosion of the standard of living and the ever-present risk of famine. In addition, it shows that increases in bequest confiscation increase the education of parents and reduce the education of children. Finally, it shows that education of parents and children are complements, and that confiscation of capital amplifies this effect.

The model notation is as follows: C = consumption, K = capital, H = education, L = labor, σ = tax on bequests, r = interest rate, δ = discount factor, η = tax on capital, G = government transfers, and p = relative price of education.

In our construct, education is a good that increases utility

$$Max U\left( {C_{t} ,C_{t + 1} ,L_{t} ,H_{t} ,H_{t + 1} } \right) = \ln C_{t} + \delta \ln C_{t + 1} - \lambda \left( {L_{t} } \right) + v\left( {H_{t} } \right) + V\left( {H_{t + 1} } \right)$$
(3)

with \(\nu ', V', \lambda ' > 0; \nu '',\, V''\left\langle {0,\, \lambda ''} \right\rangle 0\).

The utility maximization is subject to the budget constraints for periods t and t + 1. In period t, parents consume, \([C_{t} ],\) and invest in their own education, \([p_{t} H_{t} ]\). Their sources of income are unskilled labor earnings, [\(w_{t} L_{t} ]\), and the return on capital inherited from a previous generation that was not confiscated, but was heavily taxed, [\(r_{t} \left( {1 - \eta } \right)K_{t}\)]

$$C_{t} + p_{t} H_{t} = w_{t} L_{t} + r_{t} \left( {1 - \eta } \right)K_{t} .$$
(4)

In period t + 1 parents earn income from work using the education acquired in period t, [\(W_{t + 1} H_{t}\)].Footnote 19 These funds are used for consumption, [Ct+1], to accumulate capital to leave as a bequest, [\(\left( {1 - \sigma } \right)K_{t + 1}\)], and investment in the education of their offspring, [\(p_{t + 1} H_{t + 1}\)]

$$C_{t + 1} + \left( {1 - \sigma } \right)K_{t + 1} + p_{t + 1} H_{t + 1} = W_{t + 1} H_{t} .$$
(5)

Capital stock in period t + 1 is the capital stock left (salvaged) after government confiscation

$$K_{t + 1} = \left( {1 - \eta } \right)K_{t} .$$
(6)

What makes the above model suitable to analyze a socialist economy is the fact that taxation is almost sure to be high, or as high as possible (i.e., confiscation). This means that the values of σ, the tax on bequests, and η, the tax on capital, are close to or equal to one. These cases are analyzed ahead.

Maximizing (3) taking into account the constraints (4), (5) and (6) yields the following first order conditions

$$L_{t} :\frac{{w_{t} }}{{C_{t} }} - \lambda '\left( {L_{t} } \right) = 0,$$
(7)
$$H_{t} : - \frac{{p_{t} }}{{C_{t} }} + \delta \frac{{W_{t + 1} }}{{C_{t + 1} }} + \nu '\left( {H_{t} } \right) = 0,$$
(8)
$$H_{t + 1} : - \delta \frac{{p_{t + 1} }}{{C_{t + 1} }} + V'\left( {H_{t + 1} } \right) = 0,$$
(9)

and

$$K_{t + 1} : \frac{{r_{t} }}{{C_{t} }} - \frac{{\delta \left( {1 - \sigma } \right)}}{{C_{t + 1} }} = 0.$$
(10)

Any model of a socialist economy has to be consistent with two stylized facts: (1) the gradual erosion of the standard of living, and (2) the ever-present risk of famine. Our model yields both results. We can see this by rewriting the Euler equation (10)

$$\frac{{C_{t + 1} }}{{C_{t} }} = \frac{{\delta \left( {1 - \sigma } \right)}}{{r_{t} }} = \frac{{\left( {1 - \sigma } \right)}}{{r_{t} \left( {1 + \rho } \right)}} < 1.$$
(11)

Given that the rate of time preference ρ is positive, the above result implies that consumption at t + 1 is smaller than consumption at period t, \(C_{t + 1} < C_{t} ,\) showing the gradual erosion of the standard of living. In addition, if bequests are heavily taxed/confiscated (one of the recommendations of Karl Marx and Friedrich Engels in the Communist Manifesto), which implies values of σ close to 1, (11) implies that consumption will be close to zero-there is famine. The best examples of this phenomenon are the Holodomor holocaust in Ukraine (1931–1933) and the famine in China (1958–1962) (e.g., see Nove 1992; Dikӧtter 2010; Bianco 2016).

We now wish to examine the impact of bequest confiscation on education. Substituting (8) and (9) into (10) yields

$$\frac{{\nu '\left( {H_{t} } \right)}}{{p_{t} }} = \frac{{V'\left( {H_{t + 1} } \right)}}{{p_{t + 1} }}\left( {1 - \sigma - \frac{{W_{t + 1} }}{{p_{t} }}} \right).$$
(12)

The impact of bequest confiscation is seen in (12). Increases in confiscation increase the education of parents and reduce the education of children. If the government confiscates a share of the bequests so that \(\sigma \in \left( {0,1} \right),\) (12) can differentiated to evaluate the impact of the tax on bequests on parents’ education

$$\frac{{dH_{t} }}{d\sigma } = - \frac{{p_{t} V'\left( {H_{t + 1} } \right)}}{{p_{t + 1} \nu ''\left( {H_{t} } \right)}} > 0.$$
(13)

Since \(\nu '' < 0\), (13) shows that a positive tax on bequests increases parents stock of human capital or education. A similar analysis holds for the education of children Ht+1, which is impacted negatively by bequest taxes. From) (12) we have

$$\frac{{dH_{t + 1} }}{d\sigma } = \frac{{V'\left( {H_{t + 1} } \right)}}{{\left( {1 - \sigma - \frac{{W_{t + 1} }}{{p_{t} }}} \right)V''\left( {H_{t + 1} } \right)}} < 0.$$
(14)

Given that \(V'' < 0\), (14) shows that a positive tax on bequests reduces children education.

We now examine the impact on education of the confiscation of Kt. For simplicity, assume property is seized, that is η = 1. In this case Kt+1 = 0. Taking this into account, the budget constraints become

$$C_{t} + p_{t} H_{t} = w_{t} L_{t}$$
(15)

and

$$C_{t + 1} + p_{t + 1} H_{t + 1} = W_{t + 1} H_{t} .$$
(16)

Substituting (15) and (16) into the Euler equation, (11), and differentiating, yields the maximum positive impact of parents’ education on children education

$$\frac{{dH_{t + 1} }}{{dH_{t} }} = \frac{{W_{t + 1} + \delta \left( {1 - \sigma } \right)p_{t} }}{{p_{t + 1} }} > 0.$$
(17)

Equation (17) shows that education of parents and children are complements, and that confiscation of capital amplifies this effect. Finally, we should note that our model has implications for nonsocialist countries. One implication is that increases in the tax on bequests should decrease investments in education by both parents and children.

Appendix 2: Property loss in Eastern Europe

During WWII and the postwar period, many property-owners, businesses, and employees in Eastern Europe experienced deep disruptions to their wealth and income. Properties and businesses were physically destroyed by war, or under post-WWII communism were confiscated or collectivized with full, partial, or no compensation, or regulated such that owners lost practical control and the properties and businesses lost all their value. Many employees similarly lost their jobs or experienced punitive taxes. Effects varied across countries and regions, ethnic groups, types of property (e.g., farmland vs. apartments), and time periods. Many people, of course, in particular Jews, were killed during WWII and lost their lives along with their property.

Private property rights had been in flux throughout Eastern Europe before the advent of communist regimes in the late 1940s. Invasions, first by Germany and other countries during WWII, and then by the Soviet Union, destroyed much physical property and resulted in property confiscations and population movements. Many, whether fleeing or being expelled, “abandoned” properties, which were formally reassigned to invading governments, to private parties of the invading countries, or to local collaborators (Herman 1951).

The main target of confiscation by Germany was Jewish property. Other targets included foreign capital and large stock-owned companies such as banks. Germany also engaged in massive confiscations of all kinds of property of ethnic Poles in Western Poland, including land, farms, furniture, and tools. Confiscation of economic value, of course, was not limited to property, but could also affect labor, through punitive labor taxes, forced labor, and deportation (Wachenheim 1942; Herman 1951; Blacksell and Born 2002).

There were many differences across the countries of Eastern Europe prior to WWII. Czechoslovakia was a developed industrial democracy, whereas Bulgaria was a poor agricultural monarchical dictatorship. There were also differences under communism. Both Hungary, which collectivized farming during the communist period (Swain 1985; Berend 1990), and Poland, which largely maintained private agriculture (Dadak 2004), were somewhere between Bulgaria and Czechoslovakia in terms of economic development (Katchanovski 2000). Countries also differed considerably in the percentage of Jews and other minorities in the population and in the extent of discrimination against these groups. Also, some of these countries were part of the Allies during WWII, while others were part of the Axis (Pearcy and Dickson 1996).

While there were devastating effects throughout, the extent of property loss varied greatly. Poland and Hungary incurred more physical damage to property, while Czechoslovakia and Bulgaria incurred less (Herman 1951; Enyedi 1967). Not being invaded by Germany, some German allies, such as Hungary, experienced fewer confiscation-related upheavals in property rights during the war, with confiscations largely restricted to Jewish property (Spulber 1954).

During WWII, there were large population transfers. Transfers aimed to create more ethnically homogeneous territories and to reduce perceived “fifth columns”. Thus, German minorities left Italy. There were population transfers out of the Baltics and modern-day Moldova. Croatia expelled its Slovene population. Bulgaria and Romania forcibly swapped each other’s minority populations. Hungary and Romania permitted voluntary swaps of each other’s minority populations. The Soviet Union transferred Ukrainians out of Eastern Poland. Jewish and Roma (Gypsy) populations throughout Eastern Europe were transferred to concentration camps and murdered (Wachenheim 1942; Sieradzka and Lerman 1994; Blacksell and Born 2002).

The treatment of the properties of the “transferred” populations varied widely. In the most favorable cases, the transferred persons were allowed to take moveable personal belongings, including automobiles, livestock, professional tools, etc. However, the transferred populations were permitted to take with them only limited amounts of financial assets, such as cash, and, of course, none of their housing or land. The transferred populations were supposed to file for compensation for their foregone property with the receiving government. Foregone properties were sold by trustees or governments to pay for the damages filed by incoming (not outgoing) transferred populations, or for other purposes. Commitments to compensate transferred populations were sometimes largely honored (as in in the case of Germans leaving Italy), but often they were not, as with the population exchanges between Romania and Bulgaria (Wachenheim 1942).

In another example of the variations in population transfers and property confiscations across countries, regions, and ethnic groups, Bulgaria provides the sole example of German-allied territory in Eastern Europe where the Jewish population was not deported or exterminated (Bachvarov 1997). However, Gelber (1946) points out that Jews did suffer persecution in Bulgaria during the war, and Bowman (1986) points out that almost no Jews survived the Bulgarian occupation of northeastern Greece.

During the final stages of WWII and immediately afterward (1944–1948), many countries under the occupation of the Soviet Red Army engaged in radical land reform. While communist parties in the region planned to eventually nationalize or collectivize all farm land, the early postwar land reforms did not involve such steps. Instead, early postwar governments (not yet formally dominated by communist parties) engaged in various land policies that sought to gain the support of formerly landless peasants. Thus, these governments expelled large numbers of ethnic Germans (particularly from Western Poland, from former East Prussia, and the Sudetenland regions of Czechoslovakia that had been invaded and occupied by Germany in 1938) and confiscated their property. Those identified as traitors or collaborators also had their properties confiscated (Herman 1951; Spulber 1954; Schmitt 1993). Land confiscations originally did not affect small landowners from each country’s majority ethnic group (e.g., of Poles in Poland). However, as confiscations proceeded, new laws lowered the boundary above which land holdings were to be confiscated, falling over time and across countries from 575 hectares to 100, 50, and as low as 20 in Bulgaria. These policies, which appear to have been largely popular, reduced the political power of large landowners (Sanders 1950; Spulber 1954; Enyedi 1967).

However, governments throughout Eastern Europe did not nationalize most of the 20 million hectares of land that they confiscated, instead redistributing 12 million hectares of farm land to 65 million peasants, thus yielding large numbers of small farms (averaging one to five hectares). Beyond gaining the support of formerly-landless peasants, a key goal of these policies was to provide incentives for majority-ethnic populations to move to formerly German-held farms and lands (Sanders 1950; Spulber 1954; Enyedi 1967; Schmitt 1993). To receive land, peasants agreed to pay governments the equivalent of 1 year’s harvest, spread over 10–20 years. The proceeds were supposed to be used to compensate nationals (i.e., those not expelled) whose properties had been confiscated. Compensation payments, even though small, were made in some cases, such as Hungary, but not others, such as Poland (Sanders 1950).

While radical, early post-WWII land reforms (i.e., confiscations and redistributions) were not a completely unprecedented break in property rights in Eastern Europe. Rather, they largely continued, if more radically, long ongoing practices in the region. For instance, Austrian-owned latifundia (i.e., very large land holdings) in Czechoslovakia had been confiscated and redistributed among Slavs after World War I (Tomasevich 1958; Enyedi 1967; Schmitt 1993). Moreover, as landholding patterns throughout Eastern Europe varied widely before WWII, the extent of confiscations after WWII also varied. Before WWII, latifundia covered more than 40% of farm and forest land in Poland, Czechoslovakia, and Hungary, but less than 2% in Bulgaria. In all cases, the shares of farmland owned by non-expelled small landowners that were not confiscated were quite large: Poland, 50%; Czechoslovakia, 62%; Hungary, 62%; and, Bulgaria, 98%. The percentages of confiscated land that were redistributed (and not retained by governments) also varied: Poland, 44%; Czechoslovakia, 38%; Hungary, 58%; and, Bulgaria, 72% (Sanders 1950; Spulber 1954; Tomasevich 1958; Enyedi 1967).

A few years after the end of WWII, communist parties throughout Eastern Europe engaged in a variety of actions (largely coups) that replaced somewhat-pluralist governments with governments that were clearly communist-dominated. As the iron curtain was drawn, during 1948-1953 the new governments pushed forward with programs of forced collectivization of the remaining, already small, private farms (Tomasevich 1958; Enyedi 1967; Schmitt 1993). Collectivization, however, did not involve formal confiscation, as individual farmers retained legal title to their land. Moreover, forms of collective farms varied widely. In some cases, farms collectivized only the ownership and use of large farming equipment, implying that returns to individual farmers largely depended on the size of their land holdings and their individual effort. In other cases, farms were almost fully collectivized with returns depending only on the number of hours worked, independent of the legal title to land. In nearly all cases, however, collective farms permitted members to “retain” small plots (e.g., half a hectare) that they could farm for their own consumption (Tomasevich 1958; Enyedi 1967; Fisher and Jaffe 2000).

The degree of pressure to replicate the Soviet centralized economic model also varied across Eastern European countries. For instance, collectivization in Poland never reached 25% of farm land and was being dismantled by the late 1950s. Thus, the percentage of farm land that was operated in manners that could be recognized as privately-owned varied widely and, as late as the 1970s and 1980s, totaled 6.1% in Czechoslovakia, 10% in Bulgaria, 13.7% in Hungary, and 78% in Poland (Tomasevich 1958; Enyedi 1967; Schmitt 1993).

Confiscation of property other than rural land differed even more widely across Eastern European countries. At one extreme, Czechoslovakia formally expropriated stock-owned companies, small businesses, urban land, and apartments, but not single-story homes. In contrast Bulgaria, which expropriated small businesses, permitted families to retain ownership of one residential and one vacation home. In Hungary, housing remained largely in private hands. Nationalization and collectivization reached least deeply in Poland, covering stock-owned companies, but leaving housing and, as discussed above, also farming largely in private hands. In many cases throughout Eastern Europe, small businesses were not formally confiscated. Instead, communist governments eliminated their economic value through high taxes or regulation, such as making it difficult for private business to obtain necessary inputs from state-owned companies that were becoming more economically dominant (Fisher and Jaffe 2000).

Appendix 3: Social stratification in Eastern Europe: complete results

See Tables 13, 14, 15 and 16.

Table 13 Bulgaria
Table 14 Czechoslovakia
Table 15 Hungary
Table 16 Poland

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Caudill, S.B., Crofton, S.O., Faria, J.R. et al. Property confiscation and the intergenerational transmission of education in post-1948 Eastern Europe. Public Choice 184, 1–41 (2020). https://doi.org/10.1007/s11127-019-00698-0

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Keywords

  • Intergenerational transmission of education
  • Property confiscation
  • Property collectivization
  • Propensity score matching

JEL Classification

  • I23
  • I25
  • P26
  • P36
  • Z13