The Political Legacy of the Gulag Archipelago Natalia Kapelko and Andrei … · 2014. 8. 3. · The...

The Political Legacy of the Gulag

Archipelago

Natalia Kapelko

and

Andrei Markevich1

1 Natalia Kapelko is from Yandex corporation (Moscow, Russia); Andrei Markevich

is from New Economic School (Moscow, Russia), and HSE/NES Laboratory on

Russian Economic History, Higher School of Economics (Moscow, Russia).

Address for correspondence: [email protected]; New Economic School, Office

1902, Nakhimovsky pr. 47. Moscow, Russia.

This paper is part of the research agenda at the HSE/NES Laboratory on Russian

Economic History (Moscow, Russia). We would like to thank Paul Castaneda Dower,

Simeon Djankov, Mark Harrison and Ekaterina Zhuravskaya for their comments.

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Abstract.

We study the long-run consequences of the Gulag on political preferences in modern

Russia. We find that the location of a Gulag camp in a district is positively associated

with anti-communist voting during the last Soviet 1991 referendum and the first post-

Soviet 1996 presidential election. We interpret these results causally, arguing that

Gulag camps provided evidence on Soviet political repression, which, in turn,

affected the elections’ results. We provide additional evidence on the validity of the

“information” channel.

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1. Introduction

Rapidly growing empirical research on the long-run consequences of history provides

many convincing examples that past experience affects development today (Nunn

2009). The question how history matters remains less clear. Institutions and culture

are the two most often cited mechanisms of persistence because they are stable and

slowly changing (North 1990; Greif 2006; Tabelini 2008). However, the literature

suggests limited explanation what makes them persistent; in what environment they

could change; what the effect of particular historical events and phenomenon on

formation of institutions, cultural norms and preferences is. Potential endogeneity of

historical episodes to previous development creates further difficulties to address

these questions empirically. We take advantage of the history of the Soviet command

system as the largest modern social experiment to study this problem (Djankov et al.

2003). We explore how the Gulag, a system of forced labor camps initiated by Stalin

in 1929, affected local political preferences in Russia during the transition from

communism to capitalism. We argue that the vivid historical memory and tangible

information about the Gulag in the districts where camps were set up increased anti-

communist voting half a century later. The past location of a Gulag camp in a district

cut communist share of voters by 2 percentage points at the 1996 presidential

election, the only election in Post-Soviet Russian history when the communist

candidate Genadij Zuganov had a chance to win. We view this 2 percentage points as

lower bound estimation of the costs since we can identify only the local effect of the

Gulag on political preferences, but there would also be a general national effect that

we cannot pick up with our data.

Repression and the forced labor system were important tools of Stalin’s

internal policy, which he widely used to penalize alleged dissidents and to get cheap

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labor for Soviet industrialization projects. The administration of forced labor camps,

known by the Russian acronym GULAG (Glavnoe Upravlenie Lagerej), consisted of

several hundreds camps. Camps population varied between one and two and a half

million, i.e. about one percent of the Soviet population at that time. The flow of

prisoners passed through the Gulag system over the decades of Stalin’s rule was much

larger, compassing between fifteen eighteen million people. The system had limited

scale before Stalin and was dismantled by his successor Khrushchev (Gregory and

Lazarev, 2007).

Alexander Solzhenitsyn (1974) used the expression “the Gulag archipelago” to

characterize camps' geography. Indeed, Soviet penal labor system represented isolated

camp settlements distributed over the whole territory of the USSR without clear

spatial pattern (figure 1). Stalin chose the precise camps’ locations without consulting

local interests, i.e. camps construction was exogenous to local preferences. The main

factor affecting the shape of the archipelago was labor demand defined by Stalin’s

industrialization program (Khlevnuk 2004). On the one hand, industrialization

initiated mass scale construction of new plants and factories in remote areas

(Markevich and Mikhailova 2013) that led to Gulag camp construction there. On the

other hand, Gulag camps appeared in old industrialized centers – like Moscow, the

Urals etc. - because of the Gulag ability to concentrate labor resources rapidly. The

overall effect was that, as Mikhailova (2012) commented, “a Gulag map looks much

like the map of population density”.

Figure 1 somewhere here.

In this paper we explore the long-run consequences of the Gulag geography on

political preferences in modern Russia, namely onto the last Soviet 1991 referendum

on preservation of the Union and the first post-Soviet 1996 presidential election – the

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two key elections when Russia made its choice between communist and capitalist

development paths. Due to data quality we concentrate primarily on the 1996 election

for which we have district level data, in contrast to the regional level 1991 dataset.2

We find that past presence of a Gulag camp in an area was positively

associated with anti-communist voting in the 1990s. Because of exogenous Gulag’s

geography we interpret this correlation causally. We argue that location of a Gulag

camp in a district improved local knowledge on Soviet political repression both via

both “inside” (memories of released Gulag detainees settled locally) and “outside”

(historical experience of local population witnessed the Gulag from beyond the fence)

information channels. While we cannot rule out the omitted variable problem

completely, the overall effect we find appears robust across various specifications and

datasets. In particular, in case of the 1996 election, for which we have district level

dataset, we use region fixed effects to control for locally invariant omitted variables.

Our results hold if we control for current wages, i.e. potential location of Gulag camps

in areas that had more economic prospects cannot fully explain the main finding.

With this finding we contribute to the literature on the importance of history

for the long-run development and persistency in preferences. A wide variety of papers

have documented distinct stability of social and cultural norms and beliefs over time.

Among the most recent studies, there are Voigtländer and Voth (2012), Guiso et al.

(2013) and Grosjean (2014). Voigtländer and Voth (2012) find stability of anti-

semitism patterns in Germany in the second millennia; Guiso et al. (2013) provide

evidences on persistence in civic capital in Italy over the same time span; Grosjean

(2014) demonstrates constancy of the culture of honor in the US South etc. We

2 The 1996 dataset consists of more than two thousand voting districts, one district for

each local voting commission, while the 1991 dataset covers 83 regions only.

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develop one of the lines of this research, by investigating the effect of history on

current political preferences. Analysing outcomes of elections in contemporary

Poland, Grosfeld and Zhuravskaya (2013) uncover the causal effect of the more-than-

a-century partition of the country between three empires on modern political

preferences. In another paper Grosfeld et. al. (2013) find further evidences of

persistency in political preferences in modern Eastern Europe, in particular strong

socialist anti-market culture in the former Pale of Settlement - the area where Jewish

population was confined to in the Russian empire. Similar, Acharya et. al (2014)

document the political legacy of slavery in the US. In contrast to these papers, we

look at relatively short-lasting historical shock that had long lasting consequences. In

this respect our paper is similar to the study by Acemoglu et al. (2011) who

investigate economic and political consequences of the Holocaust. Finally, our results

support the analysis by Castaneda Dower and Markevich (2014) who study the

connection between privatization imperial and post-communist Russia and find that

historical precedent impacts modern attitudes towards policy reforms.

These results improve our understanding of voting behavior and outcomes

during the transition period, with voters who remembered the experience of living

under communism. Past experience affected voting outcomes in favor of democratic

values in a new Post-Soviet reality (Rose and Mishler 1996). Specifically in the

Russian context Rose, Tikhomirov and Mishler (1997) argue that it is too naive to

focus exclusively on current events to explain Russian election outcomes. We provide

quantitative evidence for this claim and add a substantial nuance into the dominant

picture of widespread nostalgia for the communist era after the first decade of

transition hardships (Mason 1997, Sullivan 2013).

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Finally, we contribute to the Russian economic history literature by shedding

additional light on the cost of repressions in the Gulag system. The dominant

narrative draws a picture where the dictator Stalin managed to construct and run a

system of forced labor, successfully destroying protests and alleged opposition

(Gregory and Lazarev 2007; Khelvnuk 2004). Our results suggest that his successors

eventually paid the costs.

The rest of the paper is organized as follows. The next section provides a

historical overview of Gulag archipelago history. Then, we formulate hypotheses

(section 3) and describe our data and methods (section 4). The fifth section presents

our analysis and results. Section six concludes.

2. A history of the Gulag archipelago

The Gulag origin goes back to the early Soviet years. Already in 1918, less than a

year after the Bolshevick’s revolution, Lenin suggested to imprison those who

opposed the regime in forced labor camps near big cities. There were 84 forced labor

camps in 34 provinces by the year of 1921 (Applebaum, 2003). The system of forced

labor shrank with the end of the Civil war in 1920, being limited to only the

Solovestky camp during the 1920s. It got a new life after Stalin’s Politburo resolution

issued on June 27, 1929 “On the Use of Labor of Convicted Criminals” that changed

its aim from punishment to providing cheap labor for economic projects (Ivanova

2006; Khlevnuk 2004). The Chief administration of labor camps – the Gulag

administration – was established in 1930 to run these camps. This Gulag

administration was one of several Soviet industrial units and got annual plans like the

others. The only main difference was that it exploited forced labor and because of that

was a part of the Soviet secret police ministry and did not belong to the civic

industrial ministries.

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The Gulag archipelago saw a rapid growth during the 1930s that accompanied

the first five-years Soviet industrialization plans with their constantly increasing

demand for industrial labor. There were only 179 thousand Gulag forced laborers in

1930; the number increased more than ten times by the end of the decade to about 1.9

million in 1938. The growth continued until the year of Stalin’s death, with the peak

of 2.5 million forced laborers in early 1950s (Zemskov 1991; Applebaum 2003;

Khlevnuk 2004). By that time the Gulag accumulated about two percent of Soviet

labor force and produced arguably the same share of national income (Gregory and

Lazarev 2007). In terms of the number of labor camps, the Soviet government

organized more than three hundred separate camps over the years of Stalin’s reign

(calculated from Smirnov 1998); the peak was achieved in early 1950s when 158

labor camps operated simultaneously (Gregory and Lazarev 2003, p. 12).3

Mikhailova (2012), who specifically analyzed the Gulag geography,

concluded that “camps eventually were organized in practically all areas of the

country”. There was no clear geographical pattern in the Gulag archipelago

geography. Many camps were established with a labor-shortage motivation

(Khlevnuk 2004); but these shortages of labor were themselves caused by the rapid

industrialization plans, which initiated many new industrial projects all over the

Soviet Union. The only systematic outcome found by Mikhailova (2012) was that the

3 We employ the term «camp» to summarize the whole variety of the Gulag units,

separated from each other in terms of geography, including corrective labor Camps

(ITL), territorial department of corrective labor colonies (OITK), special camps

(Osoblagi), camp departments (lagernoe otdelenie), separated camp points (otdelnij

lagernij punkt), labor colonies, camps for political prisoners, camps for women and

children, transit camps etc. We do not count Soviet prisons as camps.

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Gulag appeared as mainly urban phenomena because of industrial projects location.

Mikhailova (2012) estimated that “83% of all camps were located no more than 35

kilometers from a settlement with city status now, and 66% of all camps were no

more than 35 kilometers from a city of at least 10,000 inhabitants in 1939”.

Political victims of Stalin’s repressions as well as criminals composed the

Gulag population. Many political prisoners were victims of random repressions. It is

hardly possible to separate innocent people convicted because of political reasons

from those who were sentenced to the Gulag because of criminal actions. First, Stalin

introduced many criminal laws, like criminal penalty for violation of the labor code,

that would hardly get anything else than an administrative sanction in a more

democratic environment (Belova and Gregory 2011). Second, we do not have detailed

data on the distribution of the Gulag population along even these biased lines. If one

counts only those who were repressed for so called counter-revolution activities (the

lower bound), this gives a share of about twenty percent (Zemskov 1991). Anecdotal

evidence suggests that this share was up to a half of the Gulag population (Lazarev

and Gregory 2007). Irrespective of the initial reasoning, life in a Gulag camp was

very difficult for both criminals and political victims; mortality rate during the Second

World War jumped up to twenty – twenty five percent of the Gulag population

(Zemskov 1991).

A shift in internal policy after Stalin’s death and the ban on further political

repressions led to gradual dismantling of the Gulag archipelago during the 1950s.

Already in 1953 – the year of Stalin’s death - the new Soviet government conducted a

wide amnesty for prisoners, which halved their number. Many industrial projects and

corresponding camps were shut down. The Gulag chief administration itself was

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closed and reorganized in 1960. However, some of the former Gulag camps continued

their existence as a part of the Soviet penal system until the 1980s.

Former Gulag prisoners were severely limited in their choice of living even

after the end of their sentences, both legally and economically. Many of political

prisoners got a court ban to live closer than 101 km from big cities like Moscow,

Saint-Petersburg, Kiev etc. or were sent into exile in remote areas (usually close to

former camps) after their exit from the Gulag. Even those, who could choose, often

had to settle down in the same areas where they were prisoners and continue to work

at the same industrial projects as free laborers because their outside options were

heavily limited (Cohen 2010, P. 50). Local authorities encouraged them not to out-

leave. In other words, descendants of former Gulag prisoners often continued to live

in the districts of past camp location.

Local population in districts with the Gulag camps were better aware of the

Soviet system of forced labor because of both contacts with former Gulag prisoners

and their descendants as well as general experience of witnessing the Gulag from

beyond the fence. In particular, the Gulag forced labor constructed tangible

infrastructure extensively used by local population (Latypov 2011). In contrast, at

national level all Soviet propaganda denied mass political repressions and exploitation

of the forced labor in the USSR up to the late 1980s. The government put

extraordinary efforts to block alternative information channels about the past. In

particular, reading and dissemination of Solzhenitsyn “Gulag archipelago” was a

criminal offence.

3. Hypotheses

Our main hypothesis is that there is an association between the Gulag camps’ location

in the past and modern political preferences, in particular a positive link with anti-

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communist voting during the early post-communist period. We expect this correlation

mainly because of individual perceptions of life in the Soviet Union caused by the

knowledge of history of Stalin’s political repression that shaped their modern attitudes

against the communist regime. In the districts where camps were located, these

perceptions were more negative due to better knowledge on the repression of

innocents and Gulag hardships either via personal experience and contacts with

former Stalin’s victims4 or historical experience of free population which observed

the Gulag in operation from outside the camps. Relatively low out-migration of

former Gulag prisoners concentrated contacts with them in these districts. Physical

remains of former camps like barracks, guard towers as well as industrial projects

constructed by prisoners were an important reminder of local forced labor history

(Latypov 2011). We expect that both “inside” (experience and contacts with former

prisoners) and “outside” (experience of local population) information channels on the

Gulag operated, while with our data we cannot distinguish between the two.

In addition, we expect that voting was more anti-communist in the districts

where local civil activists put additional efforts to keep historical memory on political

terror, organizing local civil rights organization that preserved memory about the

Gulag (“Memorial” foundations) and provided more information on the Soviet history

of repressions to citizens.

We expect that the negative perceptions about the Soviet past were especially

pronounced during the key elections, when the choice of the future political

development path was on the table, such as the 1991 referendum on preservation of

the Soviet Union and the 1996 presidential election in Russia. Indeed, both elections

4 According to public polls, 27 percent of Russians said that had relatives who were

penalized under Stalin (Cohen 2010, P. 150).

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had a strong ideological component and appealed to the country’s past experience.

The 1991 referendum took place on March, 17 and was the last attempt of the Soviet

leadership to keep the unity of the Soviet Union and secure the socialist development

path. More than two thirds of voters answered positively to the referendum’s question

“Are you for the preservation of the Union of Soviet Socialist Republics as a renewed

federation of equal sovereign republics where the rights and freedom of all

individuals of any ethnicity will be fully guaranteed?” We interpret negative answers

as at least partially driven by anti-communist views and a desire to abolish the non-

democratic communist state established seventy years earlier.

Similarly, the whole 1996 presidential campaign was structured around the

debate of potential reversal of transition reforms and the choice of political regime.

As White, Rose, McAllister (1997) underlined

“The 1996 presidential election offered voters a choice between candidates

offering competing regimes. President Boris Yeltsin … chief opponent,

Communist Party leader Gennady Zyuganov, was heir to the tradition in

which the end justified the means; the party had created Soviet-style

"socialist legality" in which millions of Russians had been killed or

imprisoned in Siberia on political grounds.”

We analyze the results of the second round of the election, which took place

on July, 3 1996, when the communist opposition leader Gennady Zyuganov

challenged the incumbent candidate Boris Yeltsin (in the first round of the election on

June, 16 1996 Genady Zyuganov got 32 per cent of voters and Boris Yeltsin got 35).

Yeltsin won with 54 percent of the votes. He structured his campaign along

ideological anti-communist lines. His main slogan was «vote or lose» that appealed to

those who would be worse off if the communist candidate had won. He tried to

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present himself as a populist leader, running intentionally as non-party candidate in

contrast to the communist boss Genadij Zuganov who was presented as an apparent

heir and potential re-constructor of the communist regime, which collapsed only five

years earlier.

An alternative interpretation of potential association between the Gulag

location and anti-communist voting could be that the Gulag camps and industrial

projects they realized created some economic “benefits”, which, in turn, affected

voting behavior. Indeed, the Gulag appeared to realize Stalin’s industrialization

projects. The Gulag geography was positively correlated with Stalin’s

industrialization (Khlevnuk 2004) and, correspondingly, with the economic prospects

of an area. This would create an “economic” channel of the Gulag effect. Wealthier

citizens were potential winners of transitional reforms and because of that would be

strongly against their reversal (Denisova et al. 2013).

4. Data and methodology

To test our hypotheses we construct a unique dataset matching forced labor camps’

locations in the past with modern election outcomes and current social and economic

variables. Using the variation in the geography of the Gulag we estimate the impact of

the Gulag legacy on post-Soviet political preferences. With regional fixed effects and

economic present-day variables we control for potential economic channel of the

Gulag legacy, highlighting the information effect.

We combine information gathered from recent publications on the history of

the Gulag extracted from the former Soviet archives and official statistical sources

(official results of the 1991 and 1996 elections and municipality level statistics

collected by the Russian Ministry of finance) to construct our dataset. On top of that,

we collect data on present-day prisons and labor camps from the reference book “Vse

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Turmy Rossii” [All Russian prisons] (2005) and location of “Memorial” regional

branches (one of the main aims of which is to preserve memory on the Gulag) from

the “Memorial” website.

We extract details on the geographical location of 352 forced labor camps

from Smirnov (1998) who in his turn collected them from original archival sources

located in the State Archive of Russian Federation (the fund of the Chief

Administration of labor camps at the Ministry of Internal Affairs). We then match the

Gulag locations with the 1991 Russian regions (former union republics are excluded)

and the 1996 Russian election districts.

There are 2347 election districts in the original 1996 Russian presidential

election dataset. We had to exclude 131 districts either because of duplicate voting

information (districts with identical voting outcomes but different in terms of

location) or because of lack of their geographical identification. There was at least

one Gulag camp in 210 out of 2204 1996 election districts in our sample. Only 6

districts had more than four camps and another ten had four; fifteen had three and

forty four had two; we suspect that there may be double counting in some cases in the

original source, when for example a camp changed its status or name.

Table 1 presents summary statistics of the 1996 dataset for Gulag and non-

Gulag districts, correspondingly. In 1996 in an average election district Boris Yeltsin

got 45.5 percent of voters, and the communist leader Zuganov got 48.9 percent, 4.23

percent of citizens voted against both candidates (but because of differences in

election districts size Yeltsin won with 54 percent of votes at national level). The

shares were very different in the Gulag districts – 54.2, 39.3 and 5.4, respectively. In

contrast, in an average non-Gulag district Zuganov won, getting a bit more than 50

per cent of votes (the difference between the Gulag and no-Gulag districts is

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statistically significant at the one percent level). Figure 2 shows variation in the 1996

election outcomes and the Gulag camps’ location.

There are other differences in the characteristics of Gulag and non-Gulag

districts that might affect the election outcome, and for which it is important to

account. First, another important election variable – the turnout – differed

substantially, being higher in non-Gulag districts: 72.7 percent as opposed to 68.8 in

the Gulag districts (the difference is statistically significant at the one percent level).

Previous political science studies found that settlement status as well as welfare and

population age structure, in particular share of the elderly, affected strongly Russian

elections in the 1990s (Brudny 1997; Clem and Craumer 1997; Gehlbach 2000;

Sullivan 2013; Mason and Sidorenko-Stephenson 1997; McFaul, 1996; White 2010;

White, Rose and McAllister 1997). The Gulag districts were more urban (urban share

composed 58.2 percent in the Gulag districts vs 42.0 in the non-Gulag ones; the

difference is statistically significant at the one percent level) and wealthier (wages

were about 850 and 586 thousand rubles per month; the difference is statistically

significant at the one percent level), had smaller number of retired citizens (25.1 vs.

27.6 percent; the difference is statistically significant at the one percent level) and

larger number of citizens with high education (7.1 vs. 5.8 percent; the difference is

statistically significant at the one percent level). In terms of population density, the

Gulag districts were a bit more populated on average. Finally, because of the

historical legacy of the Soviet forced labor system and its slow transformation the

Gulag districts had more present-day prisons located on their territory. They also have

more regional branches of the Memorial civil rights organization, which aims to

preserve the memory about the Gulag.

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Table 2 reports descriptive statistics of the 1991 referendum for Russian

regions with and without Gulag labor camps. There were six camps in the average

Gulag region. Regions with Gulag camps voted less for the preservation of the Soviet

Union in 1991 – 73.6 percent against 79.7 (the difference is statistically significant at

the one percent level). Similar to the 1996 districts with camps, 1991 regions with

camps had smaller turnout and share of pensioners on average; they were more urban

and prosperous. Finally, they had larger share of citizens with higher education and

more preset-day prisons.

To test our hypothesis on the political legacy of the Gulag archipelago we

employ the geographical variation in camps, regressing the shares of anti-communist

voting in 1991 and 1996 on the Gulag variables. We prefer to work with shares to

make election districts comparable to each other. To be precise we estimate the

following equation:

ShareAnti-communisti = α + β*Gulagi + Ω* (Controlsi) + (Regioni) + εi (1)

where i denotes the unit of observation, either region for the 1991 referendum or

election district for the 1996 election. ShareAnti-communist is the dependent

variable, either the share of voters against the preservation of the Soviet Union at the

1991 March referendum or the share of voters against the communist leader Zuganov

in the second round of the 1996 presidential election (defined as the sum of shares of

voters for the incumbent candidate Yeltsin and against all candidates). Gulag is our

main variable of interest characterizing either presence of the Gulag camps in an area

(dummy variable) or their number. Controls denote control variables we use in

various specifications. We include voter turnout and urban shares, which are standard

controls for political science literature, in all specifications. We gradually expand our

list of controls adding parameters that might affect voting outcomes and would help

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us to fix potential economic channel of the Gulag effect, in particular we account for

present-day prisons, average wages in logarithms, shares of pensioners and citizens

with high education. For the 1996 election we control also for population density in

all specifications. Finally, to account for potential spatial patterns and regional macro

variables we use mega-regions fixed effects for the 1991 referendum and regional

fixed effects for the 1996 election that is denoted by Region. For the 1996 election we

adjust standard errors by clustering at the region level.

To provide further evidence that knowledge on Stalin’s labor force camps

drives the Gulag results for the 1996 presidential election, we adjust equation (1) to

explore how the proximity to potential sources of information affects the results.

5. Empirical results

Table 3 presents our results for the 1996 presidential election. We employ the Gulag

dummy as our variable of interest because of little variation in number of camps in the

Gulag districts (135 out of 210 Gulag districts had one camp). This also allows us to

avoid the problem of the potential double counting of Gulag camps.

The results of our basic specification are in column 1. The coefficient on the

Gulag dummy is positive and highly significant. The location of a Gulag camp in the

district is positively associated with the anti-communist share of votes at the 1996

presidential election. Ceteris paribus the share of anti-communist votes is 2.5

percentage points larger in the Gulag districts than in the districts without camps. The

coefficients on the control variables demonstrate that anti-communist voting was

more revealed in the urban densely populated districts. In the basic specification we

already control for regional fixed effects that allows us to account for non-observable

region invariant variables. In particular, with region fixed effects we account for

Stalin’s industrialization strategy to a huge extent, given that the Soviet government

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did not specify national plans at district level, compiling them at regional level as

maximum (Gregory and Stuart 1999). To account for other variables that might affect

election outcome and to fix potential economic channel of the Gulag effect we

employ additional controls (columns 2-6).

In column 2 and 3 we add dummies for present-day prisons (sizo) and labor

camps (ITL), which location is path dependent and because of that is correlated with

the Gulag geography. Because of an extensive debate on the potential falsification of

election outcomes in favor of incumbent candidates in post-Soviet Russia (Myagkov

and Ordeshook 2008), one could argue that incumbent candidates could get more

votes in the election districts with present-day prisons, as it was easier to falsify the

outcome since prisons are closed institutions under tight control of administration.

Indeed, the coefficients on both dummies are positive and significant at the one

percent level, which suggests a positive association between post-Soviet prisons and

camps and voting against the communist leader, yet the coefficient on our main

variable of interest remains positive and significant at the one percent level.

In column 4 we report the results of the regression analysis with average

district wage variable. With wages we control for current wealth in a district that

might be affected by the Soviet industrialization where Gulag labor forced was widely

used, i.e. we narrow down potential economic channel of the Gulag effect. Even if

there is no economic channel of the Gulag effect, current wages is still an important

variable that shapes voting behavior. Indeed, the coefficient on wages is positive and

highly significant, but the coefficient on the Gulag dummy remains positive and

significant as well, while diminishing in magnitude by one third. I.e. we cannot reject

an economic channel hypothesis, but this channel cannot rule out our main finding.

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We interpret this as further evidence supporting the information channel of the Gulag

effect.

Column 5 and 6 present the results of the specifications with shares of

pensioners and citizens with high education. First, the existed literature (Sullivan

2013; White 2010; White, Rose and McAllister 1997) argues that these variables are

important voting determinants in modern Russia; second, the Soviet industrialization

affected both parameters, and we could pin down potential economic channel. Our

results corroborate previous findings that the share of pensioners is negatively

associated with anti-communist voting, and the share of citizens with high education

is associated positively. Missing values of these controls cut our sample substantially,

but the main correlation between the Gulag presence and anti-communist share

survives.

Table 4 provides further evidence that the correlation between 1996 voting

outcome and the camps geography reveals the political legacy of the Gulag. In

column 1 we adjust our main specification controlling for election district area taken

in logs and adding an interaction term between this variable and the Gulag dummy.

The coefficient on the interaction term is negative and significant, i.e. the legacy of

the past is more pronounced in small districts. Indeed, in sufficiently large districts

citizens could be unaware of past events if they took place in a distant part of the

district. Because district size could be correlated with urbanization level as well as

local prosperity, this finding could be interpreted in support of the economic channel

of the Gulag effect. To explore information channel effect further we employ linear

distance from the center of an election district to the nearest Gulag camp (column 2).

The coefficient on this variable is negative and highly significant. One standard

deviation increase in a distance to a Gulag camp (0.96) decreased the distance to

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Gulag effect by 0.02 percentage points or about eight per cent. In column 3 we allow

the Gulag effect to vary in the number of camps, adding dummies for districts with

more than one camp and more than two camps, respectively. Positive coefficients on

these dummies suggest that the correlation between Gulag camps and modern

political preferences increases with the number of camps in a district, while these

coefficients are imprecisely estimated. We interpret these results as evidence of the

information channel effect. Citizens were more likely aware about Stalin’s

repressions, if they had more tangible evidence on that, i.e. the closer a Gulag camp

was located, the higher density of camps was, and this knowledge on Soviet history

affected their voting behavior. Results presented in columns 4 and 5 support such

interpretation where we add Memorial regional branch dummy and its interaction

with the Gulag dummy. Coefficients on the Memorial dummy are positive and

significant. One of the aims of the Memorial civil rights organization is to preserve

memory of Stalin’s repressions; its presence in a district is positively associated with

anti-communist voting behavior. While one could argue that the Memorial geography

is endogenous to political preference, this is less likely for the interaction term. The

coefficient on the interaction is positive while imprecisely estimated; Gulag districts

with Memorial branches voted less for communists potentially because of Memorial

efforts to preserve the historical memory of repressions.

Table 5 reports our results for the 1991 referendum. Similar to the 1996

election, we first run our basic specification with minimum controls and then expand

their list gradually (while this cuts our sample from 83 to 69 regions). In contrast to

the 1996 exercise we employ number of Gulag as our variable of interest (not a Gulag

dummy). The 1991 regions are much larger in terms of territory than the 1996

election districts because of that there is substantial variation in number of camps in

21

the Gulag regions; there are also only a limited number of regions without camps. The

coefficient on the Gulag variable is negative and significant in all specifications, i.e.

Soviet citizens were less for preservation of the Union in regions where there were

more Gulag camps during Stalin’s reign. A one standard deviation increase in the

number of camps in a region (5.54) is associated with 0.02 percentage points decrease

in the share of votes for the preservation of the Soviet union. Given the limited

sample, we view this result as supportive evidence on the political legacy of the

Gulag which we found for the 1996 election.

Finally, for the 1996 election we do a number of robustness exercises to check

how stable our results are. First, we repeat our basic specification in logs instead of

shares controlling for population size. Second, instead of regional dummies we use

controls for longitude and latitude. Third, we replace the anti-communist share of

votes for the communist share, i.e. not counting abstain votes. Our main results hold.

6. Conclusions

We find a positive correlation between the presence of the Gulag in a district and

present-day political preferences. The identification of the effect is based on within

regions geographical variation of the Gulag camps. While we cannot rule out the

omitted variable problem completely, this finding is very stable in various

specifications. We interpret this correlation causally, as the political legacy of the

Gulag, arguing that in the former Gulag districts citizens were better aware of the

Soviet past and Stalin’s repressions (information channel), and this affected their

voting when the choice on the future development paths was on the table in the 1990s.

With regional fixed effects and present-day economic variables we fix potential

economic channel of the Gulag effect, while cannot reject its existence.

22

At the 1996 presidential election the communist opposition leader Genadij

Zuganov got 2.5 per cent less votes in the Gulag districts than in non-Gulag districts.

Counterfactually it means, that if there was no Gulag under Stalin, the anti-communist

share at the national level would be about 0.5 percentage points less than it actually

was. That would not change the 1996 election outcome and Boris Yeltsin’s second

presidential term, but one should view this estimation as a low bound of the political

legacy of the Gulag because information on Stalin’s repressions was available for

citizens in non-Gulag districts as well.

23

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27

Figure 1. The Gulag archipelago geography.

Source: Smirnov (1998), available also online at www.memo.ru .

28

Figure 2. The Gulag archipelago geography and anti-communist voting at 1996

Russian presidential elections.

29

Table 1. Summary statistics of 1996 Russian presidential elections for election

districts with and without Gulag camps.

A. Gulag camps districts.

Variable Obs Mean Std. Dev. Min Max Share of votes for Zuganov 210 0.393 0.142 0.128 0.758 Share of votes for Yeltsin 210 0.542 0.139 0.190 0.827

Share of votes “against all” 210 0.054 0.017 0.014 0.135 Turnout share 210 0.688 0.074 0.494 0.971 Urban share 210 0.582 0.342 0 1

Population density (per sq km) 210 0.316 1.092 0.000 8.882

Present-day prisons (Sizo) dummy 210 0.143 0.351 0 1

Present-day labor camps dummy 210 0.381 0.487 0 1

Wage (1996 rubles) 163 846992 489889 282600 2590930 Share of pensioners 142 0.251 0.053 0.070 0.406

Share of citizens with high education 85 0.071 0.039 0.022 0.199

Memorial branch dummy 210 0.138 0.346 0 1 B. No Gulag camps districts.

Variable Obs Mean Std. Dev. Min Max Share of votes for Zuganov 1994 0.500 0.153 0.056 0.811 Share of votes for Yeltsin 1994 0.445 0.147 0.158 0.936

Share of votes “against all” 1994 0.041 0.018 0.000 0.106 Turnout share 1994 0.727 0.080 0.506 1.000 Urban share 1994 0.420 0.368 0 1

Population density (per sq km) 1994 0.288 0.995 0.000 15.603

Present-day prisons (Sizo) dummy 1994 0.070 0.255 0 1

Present-day labor camps dummy 1994 0.158 0.365 0 1

Wage (1996 rubles) 1736 585843 389116 127000 3671000 Share of pensioners 1555 0.276 0.067 0.048 0.550


Memorial branch dummy 1994 0.016 0.126 0 1

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Table 2. Summary statistics of 1991 referendum on preservation of the Soviet Union.

Regions with and without Gulag camps.

A. Region with Gulag camps.

Variable Obs Mean Std. Dev. Min Max Share of votes for preservation

of the Union 57 0.736 0.074 0.493 0.914 Number of Gulag camps 57 6.158 5.738 1 26

Turnout share 57 0.760 0.046 0.664 0.852 Urban share 49 0.711 0.095 0.468 0.920

Number of present-day prisons and labor camps 57 29.789 15.363 6 80

Wage (in 1990 rubles) 49 317.331 78.710 237 639 Share of pensioners 49 0.175 0.038 0.050 0.231


B. Region without Gulag camps.

Variable Obs Mean Std. Dev. Min Max Share of votes for preservation

of the Union 26 0.797 0.071 0.626 0.919 Number of Gulag camps 26 0 0 0 0

Turnout share 26 0.794 0.076 0.588 0.881 Urban share 20 0.618 0.122 0.383 0.815

Number of present-day prisons and labor camps 26 20.769 14.214 3 51

Wage (in 1989 rubles) 20 305.746 108.972 188 589 Share of pensioners 20 0.182 0.060 0.067 0.246


31

Table 3. The 1996 Russian presidential election and the Gulag legacy.

(1) (2) (3) (4) (5) (6) VARIABLES Share of anti-communist votes Gulag dummy 0.025*** 0.023*** 0.020*** 0.016** 0.011* 0.019*

[0.007] [0.007] [0.007] [0.007] [0.007] [0.010]

Turnout share -0.005 0.005 0.017 0.085 0.124 0.162

[0.103] [0.103] [0.103] [0.081] [0.086] [0.123]

Urban share 0.099*** 0.094*** 0.092*** 0.030*** 0.025** -0.002

[0.009] [0.009] [0.010] [0.011] [0.012] [0.017]

Population density 0.012*** 0.009** 0.009** 0.006* 0.004 0.005

[0.004] [0.004] [0.004] [0.003] [0.005] [0.004]

Present-day prisons (Sizo) dummy

0.032*** 0.027*** 0.029*** 0.030*** 0.003

[0.008] [0.009] [0.007] [0.008] [0.008]

Present-day labor camps dummy

0.016*** 0.014*** 0.012** 0.012

[0.005] [0.005] [0.005] [0.008]

Log wage

0.156*** 0.149*** 0.154***

[0.013] [0.013] [0.016]

Share of pensioners

-0.260*** -0.268***

[0.062] [0.096]

Share of citizens with high education

0.662***

[0.226]

Region fixed effects YES YES YES YES YES YES Constant 0.298*** 0.289*** 0.274*** -1.749*** -1.611*** -1.660***

[0.069] [0.069] [0.069] [0.162] [0.170] [0.254]

Observations 2,204 2,204 2,204 1,899 1,672 750 R-squared 0.738 0.740 0.742 0.797 0.796 0.750

Robust standard errors in brackets. *** p

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Table 4. Proximity to the Gulag and the 1996 presidential election.

VARIABLES (1) (2) (3) (4) (5) Share of anti-communist votes

Gulag dummy 0.288***

0.022** 0.021*** 0.020***

[0.089]

[0.008] [0.007] [0.008]

Log distance to nearest Gulag camp

-0.020***

[0.004]

Turnout share -0.008 -0.001 -0.005 -0.001 -0.001

[0.103] [0.101] [0.103] [0.103] [0.103]

Urban share 0.097*** 0.093*** 0.099*** 0.099*** 0.099***

[0.010] [0.009] [0.010] [0.009] [0.009]

Population density 0.010** 0.009** 0.012*** 0.010*** 0.010**

[0.004] [0.004] [0.004] [0.004] [0.004]

Log district area -0.012***

[0.004]

Gulag dummy* Log district area

-0.001 [0.003] 2 and more Gulag

camps dummy 0.005

[0.014] 3 and more Gulag

camps dummy 0.011

[0.017] Memorial branch

dummy 0.035*** 0.033**

[0.012] [0.016]

Gulag dummy* Memorial branch

dummy

0.005

[0.020]

Region fixed effects YES YES YES YES YES Constant 0.307*** 0.498*** 0.274*** 0.273*** 0.274***

[0.079] [0.076] [0.069] [0.069] [0.069]

Observations 2,204 2,204 2,204 2,204 2,204 R-squared 0.743 0,748 0,742 0.742 0.742


33

Table 5. The 1991 referendum on the preservation of the Soviet Union and the Gulag

legacy.

(1) (2) (3) (4) (5) (6)

VARIABLES Share of votes for preservation of the Union Number of Gulag

camps -0.004** -0.003** -0.003* -0.003* -0.003** -0.003* [0.002] [0.001] [0.001] [0.001] [0.001] [0.001]

Turnout share 0.731*** 0.457* 0.455* 0.439* 0.525** 0.573**

[0.141] [0.233] [0.231] [0.232] [0.233] [0.253]

Urban share -0.285** -0.288** -0.288** -0.220* -0.153

[0.112] [0.115] [0.116] [0.119] [0.130]

Number of present-day prisons and labor camps

-0.000 -0.000 -0.000 -0.000

[0.001] [0.001] [0.001] [0.001]

Log wage

-0.009 -0.101 -0.111*

[0.042] [0.061] [0.064]

Share of pensioners

-0.617** -0.758**

[0.263] [0.300]

Share of citizens with high education

-1.120**

[0.522]

Mega-regions fixed effects

YES YES YES YES YES YES

Constant 0.212* 0.63** 0.62** 0.69* 1.21*** 1.29***

[0.113] [0.247] [0.243] [0.353] [0.430] [0.450]

Observations 83 69 69 69 69 69 R-squared 0.520 0.581 0.583 0.583 0.621 0.644


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