Tag: gulag

Enemies of the People

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From the early days of the Soviet Union, the regime designated the educated elite as Enemies of the People. They were political opponents and considered a threat to the regime. Between the late 1920s and early 1950s, millions of enemies of the people were rounded up and forcedly resettled to remote locations within the GULAG, a system of labor camps spread across the Soviet Union. In recent research (Toews and Vezina, 2021), we show that these forced relocations have long-term consequences on local economies. Places close to camps that hosted more enemies of the people among prisoners are more prosperous today. We suggest that this result can be explained by the intergenerational transmission of education and a resulting positive effect on local development, which can still be observed to this day.

Historical Background

Targeting the educated elite, collectively referring to them as Enemies of the People and advocating their imprisonment, can be traced back to the beginning of the Russian Revolution in 1917. After consolidating power a decade later, Stalin launched the expansion of the GULAG system, which at its peak consisted of more than a hundred camps with over 1.5 million prisoners (see Figure 1). A large number of historians extensively described this dark episode in Russian history (Applebaum (2012), Khlevniuk (2004), and Solzhenitsyn (1974)). During the darkest hours of this episode, the Great Terror, 1.5 million enemies were arrested in just about two years. While half were executed immediately, the other half was forcedly allocated to GULAG camps spread across the Soviet Union and mixed with non-political prisoners (see Figure 2). Enemies accounted for about a third of GULAG prisoners after the Great Terror. As a result, education levels were higher in the GULAG than in society. In 1939, the share of GULAG prisoners withtertiary education was 1.8%, while, according to the Soviet Census of the same year, only 0.6% of the population had tertiary education.

After Stalin’s death, labor camps started closing rapidly, but many ex-prisoners settled close to the campsites. New cities were created and existing cities in the proximity of camps started growing fast (Mikhailova, 2012). Enemies remained once freed for a combination of political, economic, and psychological reasons. Politically, they were constrained in their choice of location by Stalin-era restrictions on mobility. Economically, they had few outside options and could keep on working for the camps’ industrial projects. On the psychological level, prisoners had become attached to the location of the camp, as Solzhenitsyn (1974) clearly puts it: “Exile relieved us of the need to choose a place of residence for ourselves, and so from troublesome uncertainties and errors. No place would have been right, except that to which they had sent us.”.

Figure 1. Location and size of camps in the Soviet Gulag system

Notes: The circles are proportional to the prisoner population of camps. The data is from the State Archive of the Russian Federation (GARF) and Memorial

Enemies of the People and Local Prosperity

At the heart of our analysis is a dataset on GULAG camps which we collected at the State Archive of the Russian Federation (GARF). It allows us to differentiate between prisoners who were imprisoned for political reasons (Enemies of the People) and those arrested for non-political crimes. The share of enemies varied greatly across camps, and we argue that this variation was quasi-random. We back this up by the historical narrative, according to which the resettlement process was driven by political rather than economic forces, suggesting that strategic placements played little role in the allocation of enemies (Khlevniuk (1995) and Ertz (2008)). Moreover, while the forced nature of allocation to camps allows us to rule out endogenous location decisions, we also show that neither economic activities nor geographic attributes, such as climatic conditions, soil quality, or the availability of resources, predict the share of enemies across camps.

To estimate the long-run effects of enemies on local prosperity, we link the location of camps in 1952, the year before Stalin’s death and at the peak of the GULAG system, to post-Soviet data covering the period 2000-2018.

Figure 2. The rise and fall of the Gulag

Notes: The solid line shows the number of Gulag camps while the dashed line shows the total number of prisoners in the Gulag. The two vertical dash lines indicate the years that can define the start and end of the Gulag, starting with Stalin’s 5-year plan in 1928 and ending with Stalin’s death in 1953. The shaded areas show specific periods of marked change for the Gulag, starting with dekulakization in 1929, when when Stalin announced the liquidation of the kulaks as a class and 1.8 million well-off peasants were relocated or executed. The Great Terror of 1936-1938, also referred to as the Great Purge, is the most brutal episode under Stalin’s rule, when 1.5 million enemies were arrested, and half of them executed. The Gulag’s prisoner population went down during WW2, as non-political prisoners were enlisted in the Red Army, and as the conditions in camps deteriorated and mortality increased. Source: Memorial.

In particular, the camp level information is linked to the location of firms from the Russian firm census (2018), data on night-lights (2000-2015), as well as data from household and firm-level surveys (2016 and 2011-2014, respectively). Our results suggest that one standard deviation (28 percentage point) increase in the share of enemies of the people increases night-lights intensity per capita by 58%, profits per employee by 65%, and average wages by 22%. A large number of specifications confirm the relationship depicted in Figure 3, which illustrates the positive association between the share of enemies across camps and night-lights intensity per capita.

Figure 3. Share of enemies vs. night lights per capita across Gulags

Notes: The scatters show the relationship between the share of enemies in camps in 1952 and night lights per capita within 30 km of camps in 2000 and 2015. Each circle is a 30km-radius area around a camp, and the size of the circles is proportional to the camps’ prisoner populations. The biggest circle is Khabarovsk. The solid lines show the linear fit, and the shaded areas show the 95% confidence interval. Areas near camps with a higher share of enemies have brighter night lights per capita both in 2000 and 2015. The data on Gulags is from the State Archive of the Russian Federation (GARF) and the data on night lights is from the DMSP-OLS satellite program and made available by the Earth Observation Group and the NOAA National Geophysical Data Center. The data on population is from the gridded population of the world from SEDAC.

Intergenerational Transmission

We suggest that the relationship between enemies and modern prosperity is due to the long-run persistence of high education levels, notably via intergenerational transmission, and their role in increasing firm productivity. For the identification of the intergenerational link, we rely on a household survey collected by the EBRD in which interviewees are explicitly asked whether their grandparents have been imprisoned for political reasons during Soviet times. Exploiting this information, we show that the grandchildren of enemies of the people are today relatively more educated. We also find that grandchildren of enemies are more likely to be residing near camps that had a higher share of enemies of the people among prisoners in 1952. An alternative explanation for our results could be that the leadership of the Soviet Union may have strategically chosen to invest more during the post-GULAG period in locations that had received more enemies to exploit complementarities between human and physical capital. We find no evidence for this mechanism. We document that Soviet investment in railroads, factories of the defence industry, or universities was, if anything, lower in places with a large share of enemies.


We show that the massive and forced re-allocation of human capital that took place under Stalin had long-run effects on local development. Sixty years after the death of Stalin and the demise of the GULAG, areas around camps that had a higher share of enemies are richer today, as captured by firms’ wages and profits, as well as by night-lights per capita. We argue that the education transferred from forcedly displaced enemies of the people to their children and grandchildren partly explains variation in prosperity across localities of Russia. This can be seen as a historical natural experiment that identifies the long-run persistence of higher education and its effect on long-run prosperity. Sadly, it also highlights how atrocious acts by powerful individuals can shape the development path of localities over many generations.


  • Applebaum, A., Gulag: A History of the Soviet Camps, Penguin Books Limited, 2012.
  • Ertz, Simon. Making Sense of the Gulag: Analyzing and Interpreting the Function of the Stalinist Camp System. No. 50. PERSA Working Paper, 2008.
  • Khlevnyuk, Oleg, “The objectives of the Great Terror, 1937–1938.” In Soviet History, 1917–53, pp. 158-176. Palgrave Macmillan, London, 1995.
  • Khlevnyuk, Oleg, The History of the Gulag: From Collectivization to the Great Terror Annals of Communism, Yale University Press, 2004.
  • Mikhailova, Tatiana, “Gulag, WWII and the long-run patterns of Soviet city growth,” 2012.
  • Solzhenitsyn, Aleksandr, The Gulag Archipelago, 1918-56: An Experiment in Literary Investigation, New York: Harper Row, 1973.
  • Toews, Gerhard, and Pierre-Louis Vézina. “Enemies of the people.” (2021).

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.

Is Regional Policy Effective in the Long Run? Learning from Soviet History

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Regional inequality has been a pressing issue in many countries, and also between the countries of the European Union.  Unequal economic development, where some regions develop successfully and prosper while other regions stagnate, is often viewed as a source of social instability and economic inefficiency. Many kinds of regional policy have been proposed in order to mitigate such a situation by promoting growth in lagging regions. The policies range from subsidies and favorable tax policies for business investment to large-scale government investment projects.  The ultimate goal of all regional policies is to create an environment for sustainable growth in regions that have fallen behind. In theory it might appear that a policy, which is implemented during a specific period of time, would be sufficient to achieve sustainable development:  subsidies or creation of infrastructure would lure firms into a region and create a favorable environment for economic agents (both firms and people). The temporary policy would create agglomeration externalities that would ensure sustainable development even after the policy is discontinued.

However, are such regional policies in fact successful?  Researchers often observe a short-run impact, but it is less clear whether regional policy can make a difference in the long run. From the literature on historical “natural experiments”, we know that spatial structures of economic activity are very resilient to temporary impact. For example, the wholesale destruction and loss of life in WWII seems to have had little or no effect on the regional shares of population and manufacturing in the long run. On the other hand, significant and permanent (or long-lasting) changes to market access, such as the division ofGermanyafter WWII, do reshape the spatial economy in the long run.

Our study looks at the long-run patterns of Soviet city growth in light of Stalin’s industrialization and WWII. The Soviet government’s investment decisions during that period were dictated to a large extent by military strategy and ideology. Massive relocation of productive resources from west to east before, during, and after WWII represents a unique natural experiment, in which production factors were destroyed in some parts of the USSR, while new production facilities and infrastructure were created in other regions of the country. Using a unique dataset, we test whether Gulag camps, wartime evacuation of industry, and location near the war front had a long-run effect on city size.

In the 1930s-1950s, Stalin’s system of penal labor camps (the Gulag) was widely used as a source of cheap labor, especially in remote locations where there was no other available labor force. Penal labor was used in a variety of sectors (logging, mining, manufacturing and construction). Presence of a camp near a city or town usually meant that this location was chosen by the Soviet government for an investment project. We trace the impact of having a camp nearby on city growth from 1930 to the present day.

Evacuation of enterprises from western to eastern regions of the USSR (to avoid their possible capture by the advancing German army) is traditionally named among factors that determined post-war growth of cities in the Urals andSiberia. Indeed, data show that the majority of evacuated enterprises never returned to their original location in the westernUSSR. Western cities that sent enterprises into evacuation often lost their significance in the immediate post-war period. We test whether evacuation affected the growth of cities in the longer run, ceteris paribus.

Unfortunately, no detailed data on deaths and destruction in Soviet cities during WWII are publicly available. We therefore measure the impact of wartime damage by constructing a set of indicators for cities that were occupied or were close to the front line during WWII.

The results show that (controlling for pre-war city size, rate of growth, and geographical location) occupation and location 30 km or 200 km from the front line do have a negative and statistically significant effect on city size by 1959. However, this effect disappears by 1970. This is consistent with findings forJapanandWestern Germany, where pre-war trajectories of city growth were restored after 25-30 years.

Surprisingly, the result is roughly the same for cities which hosted evacuated enterprises. Controlling for pre-war size and growth rate, geography and presence of Gulag camps, cities that received evacuated plants grow faster until 1959, but the difference is not statistically significant in 1970 and later. Thus, contrary to the commonly held belief, the effect of evacuation was only temporary.

By contrast, the presence of a Gulag camp increases city size in a long time horizon. Gulag cities grow faster not only in the 1930s-1950s when the Gulag system was operational, but also in the 1970s and 1980s. On average, the Gulag effect only disappears in the 1989 population census.

Specialization of the camp also makes a difference. Effect on city population from a camp where prisoners were involved in agriculture or logging is short-lived. Such camps were not used to build capital or infrastructure, so the nearby cities did not become more attractive for free labour. However, if a city had a camp where prisoners worked in manufacturing, mining, or construction of production facilities or housing, its population increased permanently. Compared with the best match from a control group (a city of similar characteristics, but without a Gulag camp), such a city accrued 50% more population, and this difference remains statistically significant even until the census of 2010.

Overall, the evidence on Soviet city growth supports the common finding: the direct effects of WWII were relatively short-lived. The experience of enterprise evacuation shows that one-shot relocation of production factors by the state also fails to produce robust changes in the geographical redistribution of economic activity in the long run. However, when the Soviet government established new industrial centers in the eastern parts of theUSSR, and made massive investments in production facilities and infrastructure using Gulag labor, it managed to permanently shift the geography of economic activity. This example illustrates the size and scope of impact that is required to affect economic geography in the long run.