Tomila V. Lankina
The Estate Origins of Democracy in Russia: From Imperial Bourgeoisie to Post-Communist Middle Class
Cambridge University Press, 2021
Online Appendix
OA1
The data have been assembled by Lankina and Libman and based on an earlier publication (Lankina and Libman 2021). The analysis is reproduced and expanded with permission of the co-author A. Libman.
Peasants as a residual group: One concern that Chapter 9 anticipates, following the analysis performed earlier in the paper by Lankina and Libman (2021) is that rather than capturing the legacy of the bourgeois strata per se, what the analysis reveals is a more straightforward mechanism of the urban-rural divide,[1] or, indeed, the relative absence of peasant populations rather than the presence of particular estates.[2] Additional tests corroborating that the results are not driven by a lower share of peasants in districts were therefore performed (Table OA1). To ensure that the positive relationship between "educated estates" and democratic quality was not simply a reflection of a shrinking peasant population, robustness checks were run controlling for the regional share of peasants. Residual group in this case are individuals not ascribed to the main estates, and smaller categories of census groups like nomadic populations. The baseline findings remained robust, confirming that the initial results are not driven by variations in the size of the peasant estate.
Table OA1 Shares of “educated” estates, share of peasants and democratic quality in 1996, rayon level, OLS.
Dep. var.
Vanhanen index
Effective number of candidates
Vanhanen index
Effective number of candidates
Meshchane
0.103*
0.019***
0.078
0.014***
(0.059)
(0.004)
(0.058)
(0.004)
Nobility
0.245
0.029
0.163
0.015
(0.273)
(0.020)
(0.276)
(0.019)
Clergy
1.738*
0.218***
1.429
0.162**
(0.987)
(0.072)
(0.980)
(0.069)
Merchants
-1.419
-0.385***
-1.303
-0.367***
(2.320)
(0.122)
(2.332)
(0.116)
Foreigners
0.015
0.013***
-0.006
0.009***
(0.034)
(0.003)
(0.033)
(0.003)
Peasants
-0.006
0.001
-0.008
0.000
(0.014)
(0.001)
(0.013)
(0.001)
Urbanization
0.034***
0.006***
(0.006)
(0.000)
Constant
33.893***
3.697***
31.720***
3.299***
(4.723)
(0.107)
(5.098)
(0.124)
R2
0.43
0.58
0.44
0.64
N
2,064
2,064
2,061
2,061
Notes: * p<0.1; ** p<0.05; *** p<0.01. Robust standard errors in parentheses. All regressions control for oblast fixed effects.
OA2
The data have been assembled by Lankina and Libman and based on an earlier publication (Lankina and Libman 2021). The analysis is reproduced and expanded with permission of the co-author A. Libman.
Population displacement: Placebo test of the human capital persistence hypothesis: A second set of tests were also performed following the original analysis in Lankina and Libman (2021). These tests help further explore the validity of the hypothesized causal mechanisms, notably the probability of inter-generational transmission of the legacy of Imperial bourgeoisie. As noted in Chapter 9 of the book, a major challenge in analyses of long-term reproduction of the human dimension of legacies is dealing with the issue of geographical and structural underpinnings of development.[3] The causal mechanisms that I unpacked in the book underline the significance of what I call the “institutions of modernity” that constituted hubs of professional expertise, social closure, and autonomy vis-à-vis the state apparatus. I also highlighted intergenerational aspects of value transmission via homologous social networks and familial socialization.[4] For we needed to understand how the legacy survived beyond the generation of professionals at the time of the Revolution. Yet, my analysis also underlined the dilemmas involved in distinguishing this channel of legacy transmission given the appropriative logic of Bolshevik developmentalism. In other words, we have yet to more conclusively distinguish the modernization infrastructure which the Bolsheviks appropriated, expanded and further developed, from the social aspect of legacy transmission—a variant of a dilemma famously summarized in the “people” versus the “institutions” debate among economic historians.[5]
Acemoglu et al. suggest a useful strategy for isolating the effects of specifically social structural—or cognitional—legacies from those of other aspects of development. Analysing the implications of the Holocaust in the Western Pale of Settlement, they find that territories most affected also have the worst developmental and democratic outcomes because of the decimation of the professional and enterprising middle class.[6] However horrific the targeted repressions among the “former people,” the closest that the Soviet regime came to social cleansing was the removal of scores of the most prominent aristocrats from Leningrad to provincial capitals or their exile to Siberia in the 1930s. The mass stratum among what became the foot soldiers of Soviet public sector and the professions, as noted above, were however not the aristocrats but the meshchane or less prominent nobles of modest means who were inconspicuous and will have therefore escaped deportations. Furthermore, we cannot replicate Acemoglu et al.’s test when it comes to the decimation of the Jewish community: territories affected by the Holocaust are largely outside of present-day Russia.
As I write in Chapter 9 of the book, I locate the legacies of ethnic cleansing in the tragic fate of German and other European settlers in the Middle Volga, Siberia and the Caucasus deported to Central Asia. Although Stalin’s “killing of nations” affected other ethnic groups,[7] the high human capital of the mostly Protestant and Catholic German settlers makes this community comparable to Jews. German farms and those of Dutch Mennonite settlers were regarded as exemplars of efficient and innovative production[8]; Germans were prominent in trades and entrepreneurship[9]; and in the urban professions.[10] The 1937 “Stalin census” revealed, shortly before deportation, that Protestants boasted considerably higher literacy rates than those who self-identified as Russian Orthodox.[11] Importantly, former German settlements did not become ghost towns where normal economic activity ceased. They were repopulated with mostly ethnic Russian migrants from neighbouring and other areas. While we may well find a long-term legacy of German settlers,[12] the result would be less likely considering the thoroughness of ethnic cleansing; the latter historical record makes this group suitable for our placebo test.[13] My assumption is that specific territorially-concentrated communities and the inter-generational reproduction of human capital among them, account for legacy persistence, rather than any geographical or other structural variables per se. I therefore expect to see no correlation between the presence of these communities in specific territories in 1897 and developmental outcomes after they were deported in the Soviet period. I test these assumptions below.
The legacy of imperial human capital is further tested by isolating the specific impact of Tsarist-era German settlements. Utilizing Diesendorf’s[14] comprehensive historical database of settlements, the analysis introduces a binary treatment for German settlement locations and a continuous variable for ethnic German population density (number of ethnic German residents in each settlement). The baseline models confirm the expected positive relationship with 1897 literacy rates (Table OA2.1). However, when the meshchane and generic educated estates variables are included, the German settlement variables display no empirical connection to post-Soviet educational patterns (Tables OA2.2 and OA2.3).
The analysis testing for implications for democratic quality in post-Soviet Russia is presented in Tables OA2.4 and OA2.5. The binary treatment yields no statistically significant relationship with the democratic quality variables. While the continuous population measure initially appears significant, this correlation is entirely dependent on five extreme positive outliers—four in Saratov oblast and one in Volgograd oblast—where historical population densities exceeded the sample mean nearly a hundredfold. A rigorous propensity score matching analysis was also performed (Table OA2.6), which pairs proximate districts with equivalent baseline populations, and which corroborates this null finding: the treatment effect on the effective number of candidates is non-existent, and the effect on the Vanhanen index drops out entirely upon outlier exclusion. This empirical reality contrasts sharply with the durable socio-political legacies of the meshchane estate, which had not suffered similar repressions.
Table OA2.1 Correlation of German settlers and imperial literacy, rayon level, OLS.
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
Meshchane
0.701***
0.076**
0.130***
0.042
0.071**
0.081**
0.742***
0.077
(0.040)
(0.033)
(0.030)
(0.034)
(0.033)
(0.032)
(0.076)
(0.089)
Nobility
1.770***
2.121***
1.604***
1.748***
1.995***
1.901***
(0.247)
(0.165)
(0.247)
(0.247)
(0.243)
(0.425)
Clergy
6.597***
2.271***
7.103***
6.826***
4.732***
6.865***
(0.509)
(0.674)
(0.510)
(0.508)
(0.510)
(0.877)
Merchants
11.057***
8.678***
11.901***
11.233***
10.164***
12.700***
(1.076)
(0.756)
(1.107)
(1.076)
(0.872)
(2.878)
Foreigners
0.312***
0.381***
0.325***
0.319***
0.552***
0.212*
(0.027)
(0.034)
(0.025)
(0.026)
(0.062)
(0.109)
Germans (binary variable)
2.921***
(0.596)
Germans (population)
0.357***
(0.103)
Longitude
-0.093***
(0.007)
Latitude
0.113***
(0.041)
Constant
13.738***
10.168***
11.092***
9.770***
9.928***
10.316***
14.986***
10.122***
(0.254)
(0.291)
(0.518)
(0.285)
(0.282)
(1.985)
(0.581)
(0.656)
R2
0.187
0.481
0.846
0.492
0.506
0.564
0.190
0.485
N
2,091
2,091
2,091
2,091
2,091
2,083
413
413
Oblast fixed effects
No
No
Yes
No
No
No
Uyezd-level data
Yes
Yes
Notes: * p<0.1; ** p<0.05; *** p<0.01. Robust standard errors in parentheses.
Table OA2.2 Correlation between particular social and cultural communities and contemporary education levels, rayon level, OLS
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
Meshchane
3.063***
2.623***
2.696***
2.329***
1.206***
2.192***
3.391***
3.054***
3.066***
(0.346)
(0.383)
(0.399)
(0.347)
(0.301)
(0.280)
(0.380)
(0.345)
(0.346)
Industrial employment
0.476***
0.458***
-0.038
0.061
(0.174)
(0.171)
(0.153)
(0.148)
Old Believers
-0.047
-0.198
-0.044
(0.188)
(0.194)
(0.186)
Catholics
2.828
1.720
0.652
(3.667)
(2.942)
(2.605)
Protestants
-0.810
-0.396
-0.125
(1.213)
(0.975)
(0.883)
Jews
-1.792
-1.787
-1.910*
(1.551)
(1.346)
(1.034)
Urbanization
0.786***
0.565***
(0.039)
(0.035)
Housing
0.000***
(0.000)
Doctors per capita
0.012***
(0.003)
Latitude
-1.157
(0.979)
Longitude
-0.501
(0.502)
Income
0.005***
(0.000)
Germans (binary variable)
4.228
(4.149)
Germans (population)
0.133
(0.170)
Constant
129.130***
128.552***
108.125***
63.185***
218.368***
-32.336
112.874***
129.256***
129.085***
(15.938)
(15.910)
(27.144)
(23.349)
(72.064)
(22.421)
(2.207)
(15.937)
(15.944)
R2
0.47
0.47
0.47
0.63
0.74
0.62
0.08
0.47
0.47
N
1,630
1,630
1,629
1,629
1,458
1,629
1,630
1,630
1,630
Oblast fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Notes: * p<0.1; ** p<0.05; *** p<0.01. Robust standard errors in parentheses.
Table OA2.3 Correlation between particular social and cultural communities and contemporary education levels, rayon level, OLS
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
Educated Estates
2.757***
2.451***
2.544***
2.175***
1.167***
1.945***
3.225***
2.749***
2.760***
(0.293)
(0.327)
(0.340)
(0.295)
(0.267)
(0.243)
(0.336)
(0.292)
(0.293)
Industrial employment
0.399**
0.379**
-0.097
0.026
(0.173)
(0.170)
(0.153)
(0.150)
Old Believers
0.028
-0.134
-0.010
(0.190)
(0.201)
(0.191)
Catholics
1.362
0.494
-0.033
(3.570)
(2.864)
(2.567)
Protestants
-0.353
-0.014
0.094
-0.353
-0.014
0.094
Jews
-2.056
-1.962
-2.042**
(1.490)
(1.303)
(1.011)
Urbanization
0.781***
0.563***
(0.038)
(0.035)
Housing
0.000***
(0.000)
Doctors per capita
0.012***
(0.003)
Latitude
-1.128
(0.965)
Longitude
-0.440
(0.500)
Income
0.005***
(0.000)
Germans (binary variable)
4.039
(4.125)
Germans (population)
0.137
(0.170)
Constant
130.941***
129.872***
114.298***
68.618***
210.620***
-34.562
108.956***
131.053***
130.902***
(15.735)
(15.729)
(26.651)
(22.963)
(71.185)
(22.475)
(2.399)
(15.736)
(15.740)
R2
0.477
0.479
0.479
0.630
0.743
0.619
0.104
0.477
0.477
N
1,630
1,630
1,629
1,629
1,458
1,629
1,630
1,630
1,630
Oblast fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Notes: * p<0.1; ** p<0.05; *** p<0.01. Robust standard errors in parentheses.
Table OA2.4 German settlements and democratic quality in 1996, rayon level, OLS.
Dep. var.:
Vanhanen index
Effective number of candidates
Vanhanen index
Effective number of candidates
Vanhanen index
Effective number of candidates
Vanhanen index
Effective number of candidates
Vanhanen index
Effective number of candidates
Vanhanen index
Effective number of candidates
Meshchane
0.100***
0.009***
0.101***
0.009***
(0.038)
(0.002)
(0.038)
(0.002)
Literacy
0.062*
0.004*
0.059*
0.003
(0.034)
(0.002)
(0.034)
(0.002)
Urbanization
0.034***
0.006***
0.033***
0.006***
0.034***
0.006***
0.033***
0.006***
0.036***
0.006***
0.036***
0.006***
(0.006)
(0.000)
(0.006)
(0.000)
(0.006)
(0.000)
(0.006)
(0.000)
(0.006)
(0.000)
(0.006)
(0.000)
Binary variable, German settlement
-0.287
0.008
-0.516
-0.006
-0.258
0.010
(0.550)
(0.036)
(0.549)
(0.036)
(0.554)
(0.037)
German population
0.028
0.005**
0.013
0.004*
0.024
0.005**
(0.031)
(0.002)
(0.029)
(0.002)
(0.031)
(0.002)
Constant
31.956***
3.474***
41.495***
2.959***
31.964***
3.474***
41.187***
2.954***
43.358***
3.897***
43.362***
3.898***
(4.895)
(0.080)
(1.229)
(0.159)
(4.893)
(0.080)
(1.064)
(0.153)
(1.099)
(0.077)
(1.097)
(0.077)
R2
0.442
0.639
0.444
0.637
0.442
0.640
0.444
0.638
0.440
0.636
0.440
0.637
N
2,061
2,061
2,041
2,041
2,061
2,061
2,041
2,041
2,070
2,070
2,070
2,070
Notes: * p<0.1; ** p<0.05; *** p<0.01. Robust standard errors in parentheses. All regressions control for oblast fixed effects.
Table OA2.5 German settlements and democratic quality in 1996, rayon level, OLS.
Dep. var.:
Vanhanen index
Effective number of candidates
Vanhanen index
Effective number of candidates
Vanhanen index
Effective number of candidates
Vanhanen index
Effective number of candidates
Vanhanen index
Effective number of candidates
Vanhanen index
Effective number of candidates
Educated Estates
0.089***
0.007***
0.089***
0.007***
(0.033)
(0.002)
(0.033)
(0.002)
Literacy
0.062*
0.004*
0.059*
0.003
(0.034)
(0.002)
(0.034)
(0.002)
Urbanization
0.034***
0.006***
0.033***
0.006***
0.034***
0.006***
0.033***
0.006***
0.036***
0.006***
0.036***
0.006***
(0.006)
(0.000)
(0.006)
(0.000)
(0.006)
(0.000)
(0.006)
(0.000)
(0.006)
(0.000)
(0.006)
(0.000)
Binary variable, German settlement
-0.299
0.007
-0.516
-0.006
-0.258
0.010
(0.550)
(0.036)
(0.549)
(0.036)
(0.554)
(0.037)
German population
0.028
0.005**
0.013
0.004*
0.024
0.005**
(0.031)
(0.002)
(0.029)
(0.002)
(0.031)
(0.002)
Constant
31.971***
3.478***
41.495***
2.959***
31.980***
3.478***
41.187***
2.954***
43.358***
3.897***
43.362***
3.898***
(4.892)
(0.080)
(1.229)
(0.159)
(4.890)
(0.080)
(1.064)
(0.153)
(1.099)
(0.077)
(1.097)
(0.077)
R2
0.443
0.639
0.44
0.64
0.443
0.640
0.44
0.64
0.44
0.64
0.44
0.64
N
2,061
2,061
2,041
2,041
2,061
2,061
2,041
2,041
2,064
2,064
2,064
2,064
Notes: * p<0.1; ** p<0.05; *** p<0.01. Robust standard errors in parentheses. All regressions control for oblast fixed effects.
Table OA2.6 Propensity score matching: German settlements and present-day democratic quality
Dep. var.:
Vanhanen index
Vanhanen index
Effective number of candidates
Germans (binary 1vs 0)
1.25**
1.103
0.014
(0.736)
(0.709)
(0.06)
N
2,067
2,062
2,067
German pop <40
No
Yes
No
OA3
The data have been assembled by Lankina and Libman and based on an earlier publication (Lankina and Libman 2021). The analysis is reproduced and expanded with permission of the co-author A. Libman.
Age of the city: The old and the new bourgeoisie
Another way of testing the two-pronged middleclass hypothesis advanced in Lankina and Libman (2021) and which I develop in Chapter 9 of the book is to ascertain co-variance between age of the city and region and education of regional workforce. In Table OA3.1 below, I present two sets of regressions, one employing meshchane as a proxy for the “pedigree” bourgeoisie and another one employing the more generic category of “educated estates.” I control for the age of the regional capital city and in one of the specifications for the age of the region which are computed employing the year of establishment as a higher-level administrative entity in the Russian Empire or the Soviet Union. The two datasets are from Petrov.[15] As the Russian historian Vasily Klyuchevsky reminds us, Russia’s regions experienced a form of “colonization” at different times in history. We may conjecture that lands that had been settled for longer periods of time and formed an administratively defined entity had a greater probability of engendering an established educated urban stratum. Nonetheless, when we control for this variable, we do not observe that the results of our estimations change. The results indicate that older regions were indeed more likely to develop a strong educated urban stratum before the Revolution. Nonetheless, we also observe that the variables of age of the capital city and age of the region are not correlated with education in the present, bar in one specification (7) where we observe that the regional age variable appears with a negative sign but is insignificant. I interpret the results broadly as evidence of the mixed legacies of the origins of the white-collar stratum with formal education credentials. Younger cities may boast an educated workforce but, as we know from a battery of tests presented in Lankina and Libman (2021) and the book, the democratic value proclivities of this constituency are likely to be distinct from those of the “old” bourgeoisie. We also see (Table OA3.2) that the overall share of educated estates positively correlate with the capital city age variable (.21) and region age variable (.44). The variable of share of meshchane, we observe, is also positively correlated with both the variables: city age (.17) and region age (.38), but the coefficient is statistically significant only in the second case.
Table OA3.1 Correlation of meshchane and educated estates and post-communist education attainment as measured by share of population with university degree in 2010, oblast level, OLS.
Note: * p<0.1; ** p<0.05; *** p<0.01. Robust standard errors in parentheses.
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
Educated Estates
0.300***
0.208**
0.295***
0.322***
(0.094)
(0.097)
(0.091)
(0.098)
Meshchane
0.315***
0.196*
0.306***
0.321***
(0.118)
(0.112)
(0.115)
(0.119)
Income per capita
0.000***
0.000***
0.000***
0.000***
0.000***
0.000***
0.000***
0.000***
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
Resource extraction share
-0.110***
-0.084***
-0.113***
-0.106***
-0.125***
-0.093***
-0.128***
-0.124***
(0.033)
(0.027)
(0.034)
(0.031)
(0.034)
(0.028)
(0.035)
(0.033)
Share of ethnic Russians
-0.089***
-0.079***
-0.084***
-0.087***
-0.089***
-0.078***
-0.084***
-0.089***
(0.020)
(0.022)
(0.019)
(0.020)
(0.021)
(0.024)
(0.020)
(0.022)
Urbanization
0.097**
0.084**
0.103**
0.098**
0.114**
0.095**
0.120**
0.115**
(0.042)
(0.039)
(0.042)
(0.042)
(0.050)
(0.046)
(0.050)
(0.050)
Distance from Moscow
-0.066
0.109
-0.171
-0.088
-0.079
0.107
-0.180
-0.086
(0.177)
(0.160)
(0.189)
(0.179)
(0.178)
(0.157)
(0.193)
(0.180)
Average annual educational expenditures, 2003-2012
106.362***
0.114***
(21.554)
(0.021)
Age of the capital city
-0.002
-0.002
(0.001)
(0.001)
Age of the region
-0.004
-0.001
(0.005)
(0.005)
Constant
15.744***
18.517***
15.902***
16.061***
14.901***
18.191***
15.074***
14.983***
(2.455)
(2.502)
(2.404)
(2.408)
(2.810)
(2.771)
(2.739)
(2.827)
R2
0.600
0.672
0.610
0.604
0.570
0.653
0.578
0.570
N
77
77
77
77
77
77
77
77
Note: * p<0.1; ** p<0.05; *** p<0.01. Robust standard errors in parentheses.
Table OA3.2 Correlation between the share of meshchane and educated estates and the age of the city and region (significance level in parentheses).
Corr. coefficients
Age of the capital city
Age of the region
Educated Estates
0.2117
0.4363
(0.0646)
(0.0001)
Nobility
0.1380
0.4007
(0.2314)
(0.0003)
Clergy
0.5324
0.4582
(0.0000)
(0.0000)
Merchants
0.2729
0.3471
(0.0163)
(0.0020)
Meshchane
0.1677
0.3751
(0.1449)
(0.0008)
OA4
The data have been assembled by Lankina and Libman and based on an earlier publication (Lankina and Libman 2021). The analysis is reproduced and expanded with permission of the co-author A. Libman.
The analysis below validates the choice of Samara as a region that is not an outlier when compared to other districts of the Russian Empire that are presently administratively part of the Russian Federation. The two sets of figures include districts of the Samara guberniya presently part of Samara and those that were part of the guberniya in the Imperial period but were added to other regions after the Bolshevik Revolution. The figures indicate that districts that remain part of present-day Samara had a comparatively high share of “educated estates,” the key variable of interest, but are otherwise unremarkable when compared to Russia’s other districts (OA4.1). In fact, the share of peasants was comparatively high, something that would challenge simplistic assumptions about structural factors like urbanization per se driving Samara’s status as a fairly educated, developed, and politically open region in post-communist Russia. Old Believers, which in the book are linked to the entrepreneurial channel of value transmission among merchants and meshchane; and Muslims, which are discussed with reference to the significance of the clergy, an educated estate, in fostering superior education among Tatars, have a comparatively high population share in Samara districts (OA4.2). We also see that the heavily Protestant regions, those with a high share of historical German settlements, are largely outside of present-day Samara, and it is these districts that also suffered from decimation of the historically high human capital community, as I discuss in the book.
OA4.1 Literacy
OA4.2 Religion
OA5 Replication codes for statistical analysis in the manuscript
In what follows, codes to replicate statistical analysis are provided for each chapter. All analyses have been performed using Stata 15, and therefore datasets provided separately will be in .dta format. The “codebook_oblast” and “codebook_rayon” files provide a description of variables. The codes below can be copied and pasted in a .do file. Alternatively, the complete .do file will be provided. The latter can be directly run in Stata. An exception is the social network analysis performed in Chapter 3 using Gephi (see below).
Chapter 3
· Social Network Analysis
Social network analysis in chapter 3 has been generated using Gephi 0.9.2. All analyses are static and refer to either 1916 or 1920 data, for both people and organizations. Edges and nodes tables are provided in Excel files for both people and organizations in 1916 and 1920. Gephi project files can be used to reproduce the analysis. Alternatively, the following steps can be used to replicate the analysis in Gephi.
1. In the data laboratory, import the nodes table in the nodes section. Select undirected and static graph type.
2. Import the edges table in the same way.
3. In the overview, run the following statistics: Average Degree, Avg. Weighted Degree, Network Diameter, Graph Density, HITS, Modularity, PageRank, Connected Components, Avg. Clustering Coefficient, Eigenvector Centrality, Avg. Path Length.
4. Select modularity class as nodes’ partition.
5. Select degree as nodes’ ranking.
6. Set the layout. As a starting point, the Circle Pack layout has been used, with the following hierarchies and “noverlap” option:
a. Modularity
b. Degree
c. Betweenness (or centrality)
7. The size of nodes has been set using degree as ranking.
Chapter 4
· Table 4.1
use oblast_complete
gen educclass=mechane_new+Clergy+Nobility+Merchants
reg engshare60 liter_new ethnreg distance, robust
outreg2 using "literacy", se ctitle(I)
reg engshare65 liter_new ethnreg distance, robust
outreg2 using "literacy", se ctitle(II)
reg engshare70 liter_new ethnreg distance, robust
outreg2 using "literacy", se ctitle(III)
reg docshare60 liter_new ethnreg distance, robust
outreg2 using "literacy", se ctitle(IV)
reg docshare65 liter_new ethnreg distance, robust
outreg2 using "literacy", se ctitle(V)
reg docshare70 liter_new ethnreg distance, robust
outreg2 using "literacy", se ctitle(VI)
reg engshare60 mechane_new ethnreg distance, robust
outreg2 using "mechane_new", se ctitle(I)
reg engshare65 mechane_new ethnreg distance, robust
outreg2 using "mechane_new", se ctitle(II)
reg engshare70 mechane_new ethnreg distance, robust
outreg2 using "mechane_new", se ctitle(III)
reg docshare60 mechane_new ethnreg distance, robust
outreg2 using "mechane_new", se ctitle(IV)
reg docshare65 mechane_new ethnreg distance, robust
outreg2 using "mechane_new", se ctitle(V)
reg docshare70 mechane_new ethnreg distance, robust
outreg2 using "mechane_new", se ctitle(VI)
reg engshare60 educclass ethnreg distance, robust
outreg2 using "educclass", se ctitle(I)
reg engshare65 educclass ethnreg distance, robust
outreg2 using "educclass", se ctitle(II)
reg engshare70 educclass ethnreg distance, robust
outreg2 using "educclass", se ctitle(III)
reg docshare60 educclass ethnreg distance, robust
outreg2 using "educclass", se ctitle(IV)
reg docshare65 educclass ethnreg distance, robust
outreg2 using "educclass", se ctitle(V)
reg docshare70 educclass ethnreg distance, robust
outreg2 using "educclass", se ctitle(VI)
· Figure 4.1
use oblast_complete
gen educclass=mechane_new+Clergy+Nobility+Merchants
label var educclass "Educated Estates"
reg engshare60 educclass ethnreg distance, robust
estimates store D
reg engshare65 educclass ethnreg distance, robust
estimates store F
reg engshare70 educclass ethnreg distance, robust
estimates store G
coefplot (D, label(Engineers 1960) msymbol(T) mlcolor(gs0)) ///
(F, label(Engineers 1965) msymbol(S) mlcolor(gs0)) ///
(G, label(Engineers 1970) msymbol(O) mlcolor(gs0)) ///
, drop(_cons ethnreg distance) xline(0) mfcolor(white) msize(large)
reg docshare60 educclass ethnreg distance, robust
estimates store H
reg docshare65 educclass ethnreg distance, robust
estimates store I
reg docshare70 educclass ethnreg distance, robust
estimates store J
coefplot (H, label(Doctors 1960) msymbol(D) mlcolor(gs0)) ///
(I, label(Doctors 1965) msymbol(X) mlcolor(gs0)) ///
(J, label(Doctors 1970) msymbol(A) mlcolor(gs0)) ///
, drop(_cons ethnreg distance) xline(0) mfcolor(white) msize(large)
· Summary statistics chapter IV
use oblast_complete
sum engshare60 engshare65 engshare70 docshare60 docshare65 docshare70 liter_new mechane_new educclass ethnreg distance
Chapter 5
· Figures 5.1-5.3
use rayon
gen educclass = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane
label var educ "University education in the 2010s"
label var literates "Literacy in the Imperial era"
label var perc_estmeshchane "Share of meshchane"
label var educclass "Educated Estates"
graph twoway (lfit educ literates) (scatter educ literates)
graph twoway (lfit educ perc_estmeshchane) (scatter educ perc_estmeshchane)
graph twoway (lfit educ educclass) (scatter educ educclass)
· Table 5.1
use rayon
gen educclass = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane
gen ddd = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane + perc_estkrestyane + perc_foreignnationals + perc_est_other
reg educ perc_estmeshchane dreg1-dreg79 if ddd!=0, robust
outreg2 using "fintabl_educ1", se ctitle(I)
reg educ perc_estmeshchane industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew dreg1-dreg79 if ddd!=0, robust
outreg2 using "fintabl_educ1", se ctitle(II)
reg educ perc_estmeshchane industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "fintabl_educ1", se ctitle(III)
reg educ perc_estmeshchane industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew urbanization housing doctors latitude longitude dreg1-dreg79 if ddd!=0, robust
outreg2 using "fintabl_educ1", se ctitle(IV)
reg educ educclass dreg1-dreg79 if ddd!=0, robust
outreg2 using "fintabl_educ2", se ctitle(I)
reg educ educclass industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew dreg1-dreg79 if ddd!=0, robust
outreg2 using "fintabl_educ2", se ctitle(II)
reg educ educclass industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "fintabl_educ2", se ctitle(III)
reg educ educclass industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew urbanization housing doctors latitude longitude dreg1-dreg79 if ddd!=0, robust
outreg2 using "fintabl_educ2", se ctitle(IV)
· Table 5.2
use oblast_complete
gen educclass=mechane_new+Clergy+Nobility+Merchants
replace eduexp0312av = eduexp0312av/1000
reg educ_2010 mechane_new income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "educ_new", se ctitle(I)
reg educ_2010 mechane_new income_12 natres_share shareruss_2010 urbanization_2012 distance eduexp0312av, robust
outreg2 using "educ_new", se ctitle(II)
reg educ_2010 educclass income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "educ_new2", se ctitle(I)
reg educ_2010 educclass income_12 natres_share shareruss_2010 urbanization_2012 distance eduexp0312av, robust
outreg2 using "educ_new2", se ctitle(II)
replace eduexp0312av=eduexp0312av*1000
· Table 5.3
use oblast_complete
reg no_vuz_76 liter_new ethnreg distance, robust
outreg2 using "fintabl1sept", se ctitle(I)
reg no_stud_40 liter_new ethnreg distance, robust
outreg2 using "fintabl1sept", se ctitle(II)
reg no_ssuz_76 liter_new ethnreg distance, robust
outreg2 using "fintabl1sept", se ctitle(III)
reg no_ssuz_40 liter_new ethnreg distance, robust
outreg2 using "fintabl1sept", se ctitle(IV)
reg no_vuz_76 mechane_new ethnreg distance, robust
outreg2 using "fintabl1sept2", se ctitle(I)
reg no_stud_40 mechane_new ethnreg distance, robust
outreg2 using "fintabl1sept2", se ctitle(II)
reg no_ssuz_76 mechane_new ethnreg distance, robust
outreg2 using "fintabl1sept2", se ctitle(III)
reg no_ssuz_40 mechane_new ethnreg distance, robust
outreg2 using "fintabl1sept2", se ctitle(IV)
reg no_vuz_76 educclass ethnreg distance, robust
outreg2 using "fintabl1sept3", se ctitle(I)
reg no_stud_40 educclass ethnreg distance, robust
outreg2 using "fintabl1sept3", se ctitle(II)
reg no_ssuz_76 educclass ethnreg distance, robust
outreg2 using "fintabl1sept3", se ctitle(III)
reg no_ssuz_40 educclass ethnreg distance, robust
outreg2 using "fintabl1sept3", se ctitle(IV)
· Summary statistics chapter 5
*rayon
sum educclass perc_estmeshchane industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew urbanization housing doctors latitude longitude
*oblast
sum educ_2010 no_vuz_76 no_stud_40 no_ssuz_76 no_ssuz_40 mechane_new income_12 natres_share shareruss_2010 urbanization_2012 distance eduexp0312av educclass ethnreg distance liter_new
Chapter 6
· Table 6.1
use oblast_complete
gen educclass=mechane_new+Clergy+Nobility+Merchants
reg coop_num liter_new income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(I)
reg coop_emp liter_new income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(II)
reg coop_num Merchants income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(I)
reg coop_emp Merchants income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(II)
gen merch_mesh=mechane_new+Merchants
reg coop_num merch_mesh income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(I)
reg coop_emp merch_mesh income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(II)
reg coop_num Nobility income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(I)
reg coop_emp Nobility income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(II)
reg coop_num Clergy income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(I)
reg coop_emp Clergy income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(II)
reg coop_num educclass income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(I)
reg coop_emp educclass income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(II)
· Table 6.2
use oblast_complete
gen educclass=mechane_new+Clergy+Nobility+Merchants
*1) merchants instead of meshchane
reg business Merchants income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl22", se ctitle(I)
reg sme_numb Merchants income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl22", se ctitle(II)
reg empl Merchants income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl22", se ctitle(III)
reg turnover Merchants income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl22", se ctitle(IV)
reg pse Merchants income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl22", se ctitle(V)
*2) merchants+meshchane
reg business merch_mesh income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl23", se ctitle(I)
reg sme_numb merch_mesh income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl23", se ctitle(II)
reg empl merch_mesh income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl23", se ctitle(III)
reg turnover merch_mesh income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl23", se ctitle(IV)
reg pse merch_mesh income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl23", se ctitle(V)
*3)nobles
reg business Nobility income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl24", se ctitle(I)
reg sme_numb Nobility income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl24", se ctitle(II)
reg empl Nobility income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl24", se ctitle(III)
reg turnover Nobility income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl24", se ctitle(IV)
reg pse Nobility income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl24", se ctitle(V)
*4) clergy
reg business Clergy income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl25", se ctitle(I)
reg sme_numb Clergy income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl25", se ctitle(II)
reg empl Clergy income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl25", se ctitle(III)
reg turnover Clergy income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl25", se ctitle(IV)
reg pse Clergy income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl25", se ctitle(V)
*5) educated estates combined
reg business educclass income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl26", se ctitle(I)
reg sme_numb educclass income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl26", se ctitle(II)
reg empl educclass income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl26", se ctitle(III)
reg turnover educclass income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl26", se ctitle(IV)
reg pse educclass income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "fintabl26", se ctitle(V)
· Summary statistics chapter 6
use oblast_complete
gen educclass=mechane_new+Clergy+Nobility+Merchants
sum coop_num coop_emp Merchants income_90 urban_90 distance Nobility mechane_new Clergy educclass business income_12 natres_share shareruss_2010 urbanization_2012 sme_numb empl turnover pse
· Supplementary analysis for the appendix: convictions speculations
use oblast_complete
gen educclass=mechane_new+Clergy+Nobility+Merchants
gen merch_mesh=mechane_new+Merchants
reg spekulation liter_new income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(I)
reg spekulation mechane_new income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(II)
reg spekulation Merchants income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(III)
reg spekulation merch_mesh income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(IV)
reg spekulation Nobility income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(V)
reg spekulation Clergy income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(VI)
reg spekulation educclass income_90 urban_90 distance, robust
outreg2 using "table1ch6", se ctitle(VII)
Chapter 7
· Table 7.2
use Survey_updated
logit qq13_3 qq11_4, robust
outreg2 using "table2_ch7", se bdec(3) ctitle(I)
logit qq13_3 qq11_4 qq11_1 qq11_2 qq11_3 qq11_6, robust
outreg2 using "table2_ch7", se bdec(3) ctitle(I)
logit qq13_4 qq11_4, robust
outreg2 using "table2_ch7", se bdec(3) ctitle(I)
logit qq13_4 qq11_4 qq11_1 qq11_2 qq11_3 qq11_6, robust
outreg2 using "table2_ch7", se bdec(3) ctitle(I)
logit qq13_6 qq11_4, robust
outreg2 using "table2_ch7", se bdec(3) ctitle(I)
logit qq13_6 qq11_4 qq11_1 qq11_2 qq11_3 qq11_6, robust
outreg2 using "table2_ch7", se bdec(3) ctitle(I)
· Summary statistics chapter 7
use Survey_updated
rename qq11_6 foreigners
rename qq13_3 civil_servants
rename qq13_4 intellectual_occupations
rename qq13_6 high_ranked_officials
rename qq11_4 meshchane
rename qq11_1 nobility
rename qq11_2 merchants
rename qq11_3 clergy
sum civil_servants intellectual_occupations high_ranked_officials meshchane nobility merchants clergy foreigners
Chapter 8
· Table 8.1
use rayon
ttest literates, by(lager)
ttest perc_est_dvoryane, by(lager)
ttest perc_est_dukhovenstvo, by(lager)
ttest perc_estate_kuptsy, by(lager)
ttest perc_estmeshchane, by(lager)
ttest perc_estkrestyane, by(lager)
ttest perc_foreignnationals, by(lager)
· Table 8.2
use rayon
ttest literates, by(zato)
ttest perc_est_dvoryane, by(zato)
ttest perc_est_dukhovenstvo, by(zato)
ttest perc_estate_kuptsy, by(zato)
ttest perc_estmeshchane, by(zato)
ttest perc_estkrestyane, by(zato)
ttest perc_foreignnationals, by(zato)
· Summary statistics chapter 8
use rayon
sum literates perc_est_dvoryane perc_est_dukhovenstvo perc_estate_kuptsy perc_estmeshchane perc_estkrestyane perc_estkrestyane lager zato
Chapter 9
· Table 9.2
use rayon
pwcorr perc_est_dvoryane perc_est_dukhovenstvo perc_estate_kuptsy perc_estmeshchane, sig
· Table 9.3
use rayon
gen ddd = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane + perc_estkrestyane + perc_foreignnationals + perc_est_other
reg democ_vanhanen_96 perc_estmeshchane dreg1-dreg79 if ddd!=0, robust
outreg2 using "table3", se ctitle(I)
reg efnumk_96 perc_estmeshchane dreg1-dreg79 if ddd!=0, robust
outreg2 using "table3", se ctitle(II)
reg democ_vanhanen_96 perc_estmeshchane industrial_emp dreg1-dreg79 if ddd!=0, robust
outreg2 using "table3", se ctitle(III)
reg efnumk_96 perc_estmeshchane industrial_emp dreg1-dreg79 if ddd!=0, robust
outreg2 using "table3", se ctitle(IV)
reg democ_vanhanen_96 perc_estmeshchane industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew dreg1-dreg79 if ddd!=0, robust
outreg2 using "table3", se ctitle(V)
reg efnumk_96 perc_estmeshchane industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew dreg1-dreg79 if ddd!=0, robust
outreg2 using "table3", se ctitle(VI)
reg democ_vanhanen_96 perc_estmeshchane industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew latitude longitude dreg1-dreg79 if ddd!=0, robust
outreg2 using "table3", se ctitle(VII)
reg efnumk_96 perc_estmeshchane industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew latitude longitude dreg1-dreg79 if ddd!=0, robust
outreg2 using "table3", se ctitle(VIII)
reg democ_vanhanen_96 perc_estmeshchane industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew latitude longitude urbanization housing doctors dreg1-dreg79 if ddd!=0, robust
outreg2 using "table3", se ctitle(IX)
reg efnumk_96 perc_estmeshchane industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew latitude longitude urbanization housing doctors dreg1-dreg79 if ddd!=0, robust
outreg2 using "table3", se ctitle(X)
· Table 9.4
use rayon
gen ddd = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane + perc_estkrestyane + perc_foreignnationals + perc_est_other
gen educclass = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane
reg democ_vanhanen_96 educclass dreg1-dreg79 if ddd!=0, robust
outreg2 using "table4", se bdec(3) ctitle(I)
reg efnumk_96 educclass dreg1-dreg79 if ddd!=0, robust
outreg2 using "table4", se bdec(3) ctitle(II)
reg democ_vanhanen_96 educclass industrial_emp dreg1-dreg79 if ddd!=0, robust
outreg2 using "table4", se bdec(3) ctitle(III)
reg efnumk_96 educclass industrial_emp dreg1-dreg79 if ddd!=0, robust
outreg2 using "table4", se bdec(3) ctitle(IV)
reg democ_vanhanen_96 educclass industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew dreg1-dreg79 if ddd!=0, robust
outreg2 using "table4", se bdec(3) ctitle(V)
reg efnumk_96 educclass industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew dreg1-dreg79 if ddd!=0, robust
outreg2 using "table4", se bdec(3) ctitle(VI)
reg democ_vanhanen_96 educclass industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew latitude longitude dreg1-dreg79 if ddd!=0, robust
outreg2 using "table4", se bdec(3) ctitle(VII)
reg efnumk_96 educclass industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew latitude longitude dreg1-dreg79 if ddd!=0, robust
outreg2 using "table4", se bdec(3) ctitle(VIII)
reg democ_vanhanen_96 educclass industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew latitude longitude urbanization housing doctors dreg1-dreg79 if ddd!=0, robust
outreg2 using "table4", se bdec(3) ctitle(IX)
reg efnumk_96 educclass industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew latitude longitude urbanization housing doctors dreg1-dreg79 if ddd!=0, robust
outreg2 using "table4", se bdec(3) ctitle(X)
· Table 9.5
use oblast_complete
egen duma_avg = rmean(Duma1 Duma2 Duma3 Duma4)
pwcorr duma_avg mechane_new, sig
pwcorr Duma1 mechane_new, sig
pwcorr Duma2 mechane_new, sig
pwcorr Duma3 mechane_new, sig
pwcorr Duma4 mechane_new, sig
· Table 9.6
use oblast_complete
egen duma_avg = rmean(Duma1 Duma2 Duma3 Duma4)
gen educclass=mechane_new+Clergy+Nobility+Merchants
pwcorr duma_avg educclass, sig
pwcorr Duma1 educclass, sig
pwcorr Duma2 educclass, sig
pwcorr Duma3 educclass, sig
pwcorr Duma4 educclass, sig
pwcorr duma_avg Nobility, sig
pwcorr Duma1 Nobility, sig
pwcorr Duma2 Nobility, sig
pwcorr Duma3 Nobility, sig
pwcorr Duma4 Nobility, sig
pwcorr duma_avg Clergy, sig
pwcorr Duma1 Clergy, sig
pwcorr Duma2 Clergy, sig
pwcorr Duma3 Clergy, sig
pwcorr Duma4 Clergy, sig
pwcorr duma_avg Merchants, sig
pwcorr Duma1 Merchants, sig
pwcorr Duma2 Merchants, sig
pwcorr Duma3 Merchants, sig
pwcorr Duma4 Merchants, sig
· Figures 9.8-9.12
use oblast_complete
label var freepress "Press Freedom Index, 1999"
label var mechane_new "Share of meshchane"
graph twoway (lfit freepress mechane_new) (scatter freepress mechane_new)
gen educclass=mechane_new+Clergy+Nobility+Merchants
label var educclass "Share of educated estates"
graph twoway (lfit freepress educclass) (scatter freepress educclass)
label var docshare65 "Share of Doctors with University Degree)
graph twoway (lfit freepress docshare65) (scatter freepress docshare65)
label var engshare65 "Share of Engineers with University Degree)
graph twoway (lfit freepress engshare65) (scatter freepress engshare65)
label var educ65 "Share of Workforce with University Degree)
graph twoway (lfit freepress educ65) (scatter freepress educ65)
· Supplementary analysis for the appendix: press freedom
use oblast_complete
pwcorr freepress mechane_new, sig
reg freepress mechane_new income_96 urbanization_1996 shareruss educ distance, robust
reg freepress mechane_new income_96 urbanization_1996 shareruss educ distance if mechane_new<15, robust
· Supplementary analysis for the appendix: industrial employment and democratic quality
use rayon
gen ddd = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane + perc_estkrestyane + perc_foreignnationals + perc_est_other
reg democ_vanhanen_96 intel_emp industrial_emp trade_emp dreg1-dreg79 if ddd!=0, robust
outreg2 using "footnote_57", se ctitle(I)
reg efnumk_96 intel_emp industrial_emp trade_emp dreg1-dreg79 if ddd!=0, robust
outreg2 using "footnote_57", se ctitle(II)
reg democ_vanhanen_96 intel_emp industrial_emp trade_emp urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "footnote_57", se ctitle(III)
reg efnumk_96 intel_emp industrial_emp trade_emp urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "footnote_57", se ctitle(IV)
· Summary statistics chapter 9
*rayon
use rayon
gen educclass = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane
sum perc_est_dvoryane perc_est_dukhovenstvo perc_estate_kuptsy perc_estmeshchane intel_emp industrial_emp trade_emp urbanization democ_vanhanen_96 efnumk_96 perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew latitude longitude urbanization housing doctors educclass germans_dummy germans_population income
*oblast
use oblast_complete
egen duma_avg = rmean(Duma1 Duma2 Duma3 Duma4)
gen educclass=mechane_new+Clergy+Nobility+Merchants
sum freepress mechane_new educclass docshare65 engshare65 educ65 Duma1 Duma2 Duma3 Duma4 duma_avg mechane_new Clergy Nobility Merchants eduexp0312av income_12 natres_share shareruss_2010 urbanization_2012 distance age_city age_region
Analysis in Online Appendix
· Table OA1
use rayon
gen ddd = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane + perc_estkrestyane + perc_foreignnationals + perc_est_other
reg democ_vanhanen_96 perc_estmeshchane perc_est_dvoryane perc_est_dukhovenstvo perc_estate_kuptsy perc_foreignnationals perc_estkrestyane dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea1", se bdec(3) ctitle(I)
reg efnumk_96 perc_estmeshchane perc_est_dvoryane perc_est_dukhovenstvo perc_estate_kuptsy perc_foreignnationals perc_estkrestyane dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea1", se bdec(3) ctitle(II)
reg democ_vanhanen_96 perc_estmeshchane perc_est_dvoryane perc_est_dukhovenstvo perc_estate_kuptsy perc_foreignnationals perc_estkrestyane dreg1-dreg79 urbanization if ddd!=0, robust
outreg2 using "tablea1", se bdec(3) ctitle(III)
reg efnumk_96 perc_estmeshchane perc_est_dvoryane perc_est_dukhovenstvo perc_estate_kuptsy perc_foreignnationals perc_estkrestyane dreg1-dreg79 urbanization if ddd!=0, robust
outreg2 using "tablea1", se bdec(3) ctitle(IV)
· Table OA2.1
use rayon
gen ddd = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane + perc_estkrestyane + perc_foreignnationals + perc_est_other
reg literates perc_estmeshchane if ddd!=0, robust
outreg2 using "tablea3", se bdec(3) ctitle(I)
reg literates perc_estmeshchane perc_est_dvoryane perc_est_dukhovenstvo perc_estate_kuptsy perc_foreignnationals if ddd!=0, robust
outreg2 using "tablea3", se bdec(3) ctitle(II)
reg literates perc_estmeshchane perc_est_dvoryane perc_est_dukhovenstvo perc_estate_kuptsy perc_foreignnationals dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea3", se bdec(3) ctitle(III)
reg literates perc_estmeshchane perc_est_dvoryane perc_est_dukhovenstvo perc_estate_kuptsy perc_foreignnationals germans_dummy if ddd!=0, robust
outreg2 using "tablea3", se bdec(3) ctitle(IV)
reg literates perc_estmeshchane perc_est_dvoryane perc_est_dukhovenstvo perc_estate_kuptsy perc_foreignnationals germans_population if ddd!=0, robust
outreg2 using "tablea3", se bdec(3) ctitle(V)
reg literates perc_estmeshchane perc_est_dvoryane perc_est_dukhovenstvo perc_estate_kuptsy perc_foreignnationals longitude latitude if ddd!=0, robust
outreg2 using "tablea3", se bdec(3) ctitle(VI)
*last two specifications
use imperial_full
gen perc_foreign=(FOREIGNNATIONALS*100)/POPULATION_TOTAL
gen perc_nobles=(EST_DVORYANE*100)/POPULATION_TOTAL
gen perc_meshchane=(ESTMESHCHANE*100)/POPULATION_TOTAL
gen perc_clergy=(EST_DUKHOVENSTVO*100)/POPULATION_TOTAL
gen perc_merchants=(ESTATE_KUPTSY*100)/POPULATION_TOTAL
gen perc_peasants=(ESTKRESTYANE*100)/POPULATION_TOTAL
reg LITERATES perc_meshchane
outreg2 using "tablea3_1", se bdec(3) ctitle(1)
reg LITERATES perc_meshchane perc_nobles perc_clergy perc_merchants perc_foreign
outreg2 using "tablea3_1", se bdec(3) ctitle(2)
· Table OA2.2
use rayon
gen ddd = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane + perc_estkrestyane + perc_foreignnationals + perc_est_other
reg educ perc_estmeshchane dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea4", se bdec(3) ctitle(I)
reg educ perc_estmeshchane industrial_emp dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea4", se bdec(3) ctitle(II)
reg educ perc_estmeshchane industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea4", se bdec(3) ctitle(III)
reg educ perc_estmeshchane industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea4", se bdec(3) ctitle(IV)
reg educ perc_estmeshchane industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew urbanization housing doctors latitude longitude dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea4", se bdec(3) ctitle(V)
reg educ perc_estmeshchane income dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea4", se bdec(3) ctitle(VI)
reg educ perc_estmeshchane if ddd!=0, robust
outreg2 using "tablea4", se bdec(3) ctitle(VII)
reg educ perc_estmeshchane dreg1-dreg79 germans_dummy if ddd!=0, robust
outreg2 using "tablea4", se bdec(3) ctitle(VIII)
reg educ perc_estmeshchane dreg1-dreg79 germans_population if ddd!=0, robust
outreg2 using "tablea4", se bdec(3) ctitle(IX)
· Table OA2.3
use rayon
gen ddd = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane + perc_estkrestyane + perc_foreignnationals + perc_est_other
gen educclass = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane
reg educ educclass dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea5", se bdec(3) ctitle(I)
reg educ educclass industrial_emp dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea5", se bdec(3) ctitle(II)
reg educ educclass industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea5", se bdec(3) ctitle(III)
reg educ educclass industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew dreg1-dreg79 urbanization if ddd!=0, robust
outreg2 using "tablea5", se bdec(3) ctitle(IV)
reg educ educclass industrial_emp perc_rel_oldbel perc_rel_cath rel_prot perc_rel_jew dreg1-dreg79 urbanization housing doctors latitude longitude if ddd!=0, robust
outreg2 using "tablea5", se bdec(3) ctitle(V)
reg educ educclass income dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea5", se bdec(3) ctitle(VI)
reg educ educclass if ddd!=0, robust
outreg2 using "tablea5", se bdec(3) ctitle(VII)
reg educ educclass germans_dummy dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea5", se bdec(3) ctitle(VIII)
reg educ educclass germans_population dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea5", se bdec(3) ctitle(IX)
· Table OA2.4
use rayon
gen ddd = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane + perc_estkrestyane + perc_foreignnationals + perc_est_other
reg democ_vanhanen_96 perc_estmeshchane germans_dummy urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea6", se bdec(3) ctitle(I)
reg efnumk_96 perc_estmeshchane germans_dummy urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea6", se bdec(3) ctitle(II)
reg democ_vanhanen_96 literates germans_dummy urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea6", se bdec(3) ctitle(III)
reg efnumk_96 literates germans_dummy urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea6", se bdec(3) ctitle(IV)
reg democ_vanhanen_96 perc_estmeshchane germans_population urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea6", se bdec(3) ctitle(V)
reg efnumk_96 perc_estmeshchane germans_population urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea6", se bdec(3) ctitle(VI)
reg democ_vanhanen_96 literates germans_population urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea6", se bdec(3) ctitle(VII)
reg efnumk_96 literates germans_population urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea6", se bdec(3) ctitle(VIII)
reg democ_vanhanen_96 germans_dummy urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea6", se bdec(3) ctitle(IX)
reg efnumk_96 germans_dummy urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea6", se bdec(3) ctitle(X)
reg democ_vanhanen_96 germans_population urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea6", se bdec(3) ctitle(XI)
reg efnumk_96 germans_population urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea6", se bdec(3) ctitle(XII)
· Table OA2.5
use rayon
gen ddd = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane + perc_estkrestyane + perc_foreignnationals + perc_est_other
gen educclass = perc_est_dvoryane + perc_est_dukhovenstvo + perc_estate_kuptsy + perc_estmeshchane
reg democ_vanhanen_96 educclass germans_dummy urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea10", se bdec(3) ctitle(I)
reg efnumk_96 educclass germans_dummy urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea10", se bdec(3) ctitle(II)
reg democ_vanhanen_96 literates germans_dummy urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea10", se bdec(3) ctitle(III)
reg efnumk_96 literates germans_dummy urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea10", se bdec(3) ctitle(IV)
reg democ_vanhanen_96 educclass germans_population urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea10", se bdec(3) ctitle(V)
reg efnumk_96 educclass germans_population urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea10", se bdec(3) ctitle(VI)
reg democ_vanhanen_96 literates germans_population urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea10", se bdec(3) ctitle(VII)
reg efnumk_96 literates germans_population urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea10", se bdec(3) ctitle(VIII)
reg democ_vanhanen_96 germans_dummy urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea10", se bdec(3) ctitle(IX)
reg efnumk_96 germans_dummy urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea10", se bdec(3) ctitle(X)
reg democ_vanhanen_96 germans_population urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea10", se bdec(3) ctitle(XI)
reg efnumk_96 germans_population urbanization dreg1-dreg79 if ddd!=0, robust
outreg2 using "tablea10", se bdec(3) ctitle(XII)
· Table OA2.6
*** Propensity score matching
use rayon
teffects psmatch (democ_vanhanen_96) (germans_dummy latitude longitude population_total)
teffects psmatch (democ_vanhanen_96) (germans_dummy latitude longitude population_total) if germans_population < 40
teffects psmatch (efnumk_96) (germans_dummy latitude longitude population_total)
· Table OA3.1
use oblast_complete
gen educclass=mechane_new+Clergy+Nobility+Merchants
replace eduexp0312av = eduexp0312av/1000
reg educ_2010 educclass income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "tablea9", se bdec(3) ctitle(I)
reg educ_2010 educclass income_12 natres_share shareruss_2010 urbanization_2012 distance eduexp0312av, robust
outreg2 using "tablea9", se bdec(3) ctitle(II)
reg educ_2010 educclass income_12 natres_share shareruss_2010 urbanization_2012 distance age_city, robust
outreg2 using "tablea9", se bdec(3) ctitle(III)
reg educ_2010 educclass income_12 natres_share shareruss_2010 urbanization_2012 distance age_region, robust
outreg2 using "tablea9", se bdec(3) ctitle(IV)
reg educ_2010 mechane_new income_12 natres_share shareruss_2010 urbanization_2012 distance, robust
outreg2 using "tablea9", se bdec(3) ctitle(V)
reg educ_2010 mechane_new income_12 natres_share shareruss_2010 urbanization_2012 distance eduexp0312av, robust
outreg2 using "tablea9", se bdec(3) ctitle(VI)
reg educ_2010 mechane_new income_12 natres_share shareruss_2010 urbanization_2012 distance age_city, robust
outreg2 using "tablea9", se bdec(3) ctitle(VII)
reg educ_2010 mechane_new income_12 natres_share shareruss_2010 urbanization_2012 distance age_region, robust
outreg2 using "tablea9", se bdec(3) ctitle(VIII)
replace eduexp0312av=eduexp0312av*1000
· Table OA3.2
use oblast_complete
pwcorr age_city mechane_new, sig
pwcorr age_region mechane_new, sig
pwcorr age_city educclass, sig
pwcorr age_region educclass, sig
pwcorr age_city Nobility, sig
pwcorr age_region Nobility, sig
pwcorr age_city Clergy, sig
pwcorr age_region Clergy, sig
pwcorr age_city Merchants, sig
pwcorr age_region Merchants, sig
· Plots OA4
use imperial_full
gen educclass=ESTMESHCHANE+ESTATE_KUPTSY+EST_DVORYANE+EST_DUKHOVENSTVO
label var blue "used to be Samara gubern., are now Samara region"
label var yellow "used to Samara gubern., are now other regions"
sum LITERATES
sum LITERATES if blue==1
sum LITERATES if yellow==1
sum LITERATES if blue_thirdtype==1
gen perc_nobles=(EST_DVORYANE*100)/POPULATION_TOTAL
sum perc_nobles
sum perc_nobles if blue==1
sum perc_nobles if yellow==1
sum perc_nobles if blue_thirdtype==1
gen perc_educclass=(educclass*100)/POPULATION_TOTAL
sum perc_educclass
sum perc_educclass if blue==1
sum perc_educclass if yellow==1
sum perc_educclass if blue_thirdtype==1
gen perc_meshchane=(ESTMESHCHANE*100)/POPULATION_TOTAL
sum perc_meshchane
sum perc_meshchane if blue==1
sum perc_meshchane if yellow==1
sum perc_meshchane if blue_thirdtype==1
gen perc_clergy=(EST_DUKHOVENSTVO*100)/POPULATION_TOTAL
sum perc_clergy
sum perc_clergy if blue==1
sum perc_clergy if yellow==1
sum perc_clergy if blue_thirdtype==1
gen perc_merchants=(ESTATE_KUPTSY*100)/POPULATION_TOTAL
sum perc_merchants
sum perc_merchants if blue==1
sum perc_merchants if yellow==1
sum perc_merchants if blue_thirdtype==1
gen perc_peasants=(ESTKRESTYANE*100)/POPULATION_TOTAL
sum perc_peasants
sum perc_peasants if blue==1
sum perc_peasants if yellow==1
sum perc_peasants if blue_thirdtype==1
*
gen perc_oldbel=(REL_OLDBEL*100)/POPULATION_TOTAL
sum perc_oldbel
sum perc_oldbel if blue==1
sum perc_oldbel if yellow==1
sum perc_oldbel if blue_thirdtype==1
gen perc_jew=(REL_JEW*100)/POPULATION_TOTAL
sum perc_jew
sum perc_jew if blue==1
sum perc_jew if yellow==1
sum perc_jew if blue_thirdtype==1
gen perc_prot=(REL_PROT*100)/POPULATION_TOTAL
sum perc_prot
sum perc_prot if blue==1
sum perc_prot if yellow==1
sum perc_prot if blue_thirdtype==1
gen perc_cath=(REL_CATH*100)/POPULATION_TOTAL
sum perc_cath
sum perc_cath if blue==1
sum perc_cath if yellow==1
sum perc_cath if blue_thirdtype==1
gen perc_musl=(REL_MUSL*100)/POPULATION_TOTAL
sum perc_musl
sum perc_musl if blue==1
sum perc_musl if yellow==1
sum perc_musl if blue_thirdtype==1
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[1] Some of the effects could be associated with serfdom legacies. For a discussion, see (Buggle and Nafziger 2016)
[2] (Zaslavsky 1995)
[3] (Grosfeld, Rodnyansky, and Zhuravskaya 2013; Acemoglu, Johnson, and Robinson 2002; McArthur and Sachs 2001; Glaeser et al. 2004; Charnysh 2019)
[4] For a discussion of such “cognitional” legacies, see(Simpser 2020), p. 5. Available at SSRN: https://ssrn.com/abstract=2241295 or http://dx.doi.org/10.2139/ssrn.2241295 (accessed 18 May 2020); (Simpser, Slater, and Wittenberg 2018)
[5] (Glaeser et al. 2004)
[6] (Acemoglu, Hassan, and Robinson 2011)See also (Akbulut-Yuksel and Yuksel 2015)
[7] (Conquest 1972)
[8] On German and Mennonite agricultural practices, innovation and emulation by native communities, see(Moon 2013), 209-11; 184-87.
[9] (Savchenko and Dubinin 1994)
[10](Vesnina 1995; Dahlmann and Tuchtenhagen 1994).
[11](Zhiromskaya, Kiselyov, and Polyakov 1996), p. 100.
[12] The Germanic communities may well have diffused specific values to neighbouring populations; or their know-how and infrastructures like schools, clinics, or veterinary facilities continued to drive development, in which case we would expect the developmental legacies to persist. Alternatively, the decimation of these communities, consistent with theorizing into social dislocation, may undermine their otherwise positive legacies or have other implications for monitoring and enforcement of social order. (Treyger 2013; Foa and Nemirovskaya 2016)
[13] I thank Volha Charnysh for her suggestion to conceptualise this as a placebo test.
[14](Diesendorf 2006).
[15] (Petrov 2009)