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Economic Consequences of the 1933 Soviet Famine

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Stockholm Institute of Transition Economics
Stockholm Institute of Transition Economics

Presented by Natalya Naumenko during the Academic Conference 2019.

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Economic Consequences of the 1933 Soviet Famine Natalya Naumenko George Mason University December 16, 2019 1 / 46
Introduction Krugman (1991): Fixed land, rural population is located in accordance with marginal productivity of land Multiple urbanization equilibria are possible due to mobility of urban capital and increasing returns Temporary shock to urban population or capital can have a persistent impact Empirical question Do multiple equilibria exist? 2 / 46
Literature 1/2 No persistent effects from temporary population and capital losses: Davis and Weinstein (2002), Davis and Weinstein (2008) – Japan, WW2 Brakman et al. (2004), Bosker et al. (2007) – Germany, WW2 Redding and Sturm (2008) – partition and reunification of Germany Miguel and Roland (2011) – Vietnam 3 / 46
Literature 2/2 Location characteristics affect long-term urban development: Nunn and Puga (2012) – terrain ruggedness in Africa Bleakley and Lin (2012) – portage sites in the U.S. Michaels and Rauch (2018) – Roman cities in contemporary England and France Russia: Acemoglu et al. (2011) – holocaust changed social structure and therefore had a detrimental effect Mikhailova (2018) – some persistence due to evacuation, but economically small 4 / 46
This paper Studies 1933 famine consequences Rural population recovers Persistent negative impact on urbanization Not explained by differential natural increase Timing of the shock to population might be important: lack of labor during rapid construction of new cities 5 / 46
Outline Background Data Empirical strategy Results Province population Rural and urban economy Urban settlements Mechanism: natural population increase v. migration 6 / 46
Chronology 1917 Revolution 1928 Start of the first 5-year plan; Rapid industrialization and urbanization, especially after 1933 1933 Famine; Victims: 6 – 8 million 7 / 46
Before 1928: NEP New Economic Policy: Private rural economy Private small-scale urban enterprises Large-scale industry under government control Unrestricted migration 8 / 46
Starting in 1928: 5-year plans 5-year plans for industrialization of the country: All industry and trade are nationalized Large-scale capital investment Collectivization of agriculture 9 / 46
Collectivization and the 1933 famine 1/2 Until 1933 Land, livestock, and implements belong to the collectives Peasants work together on collective farms After the harvest, grain is put in kolkhoz storages The government takes its share Procurement is unpredictable as officials struggle to fulfill the plan The remainder is distributed among kolkhoz members Trading of foodstuffs is banned, food is rationed in the cities As a result: Production drops, the government overprocures, famine in 1933 10 / 46
Collectivization and the 1933 famine 2/2 After 1933 Procurement quotas are fixed in advance Kolkhoz members allowed to work small individual plots and to keep some livestock Peasants can trade food on kolkhoz markets with free prices As a result Peasants are guaranteed subsistence 11 / 46
Mortality Belarus, Russia, and Ukraine. Constant administrative borders. Territories added in 1939 are not included. 12 / 46
A note on passport system Was introduced in 1932 Designed to remove β€˜undesirable elements’ (criminals, refugees, β€˜class enemies’) from important cities Under control of MVD, not NKVD MVD keeps decentralized catalogues, no evidence of exchange of information between cities Employed urban dwellers are eligible for a passport If a person is denied a passport, no mark is made in her documents 13 / 46
Rapid urbanization 1927 – 18% 1932 – 22% 1939 – 34% Belarus, Russia, and Ukraine. Constant administrative borders. Territories added in 1939 are not included. 14 / 46
Outline Background Data Empirical strategy Results Province population Rural and urban economy Urban settlements Mechanism: natural population increase v. migration 15 / 46
Data 1/2 Province-level population panel 81 provinces (contemporary Belarus, Russia, Ukraine) All censuses: 1897, 1926, 1939, 1959, 1970, 1979, 1989, 2002, 2010 1913 from statistical yearbook 1939 corrected for centralized additions 1949, 1950 from the Russian State Archive of the Economy Urban settlement panel 525 settlements All census years 1946, 1947, 1950 from the archives Selected sample: only settlements that achieved β€œtown” status by 1989 Yearly mortality and natality data 25 large administrative units 16 / 46
Data 2/2 Famine severity: Province-level 1933 excess mortality from the archives: 1933 excess mortality = 1933 mortaliyβˆ’ 1 4 (1928 mortality + 1937-1939 mortality) 1933 mortality in 50 km radius around each urban settlement using district-level 1933 mortality WW2 losses: WW2 losses = 1 βˆ’ actual population 1949 projected population 1949 17 / 46
1933 excess mortality WW2 losses 18 / 46
Outline Background Data Empirical strategy Results Province population Rural and urban economy Urban settlements Mechanism: natural population increase v. migration 19 / 46
Empirical strategy OLS Use cross-sectional variation in 1933 famine severity IV Idea: weather β†’ [ harvest ] β†’ famine Use 1932 weather 20 / 46
Demeaned 1932 weather and 1933 excess mortality Dependent variable: Excess mortality 1933 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Fall temp -0.009 -0.010 -0.001 (0.006) (0.006) (0.008) precip 0.000 0.000 0.001βˆ— (0.000) (0.000) (0.000) Winter temp -0.000 -0.000 0.000 (0.000) (0.000) (0.001) precip 0.000 0.000 0.000 (0.000) (0.000) (0.000) Spring temp -0.015βˆ—βˆ— -0.017βˆ—βˆ— -0.018βˆ—βˆ— -0.016βˆ—βˆ—βˆ— (0.007) (0.007) (0.008) (0.006) precip 0.000 0.000βˆ— 0.000 (0.000) (0.000) (0.000) Summer temp -0.005 -0.001 -0.001 (0.005) (0.004) (0.006) precip 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— (0.000) (0.000) (0.000) (0.000) N 77 77 77 77 77 77 77 77 77 77 77 77 77 77 R2 0.588 0.585 0.603 0.581 0.573 0.582 0.603 0.584 0.621 0.579 0.689 0.690 0.742 0.723 All regressions control for grain suitability, grain volatility, capital province indicator, WW2 losses, Nazi occupation indicator, Ln distance to Moscow, 1932 number of RR stations per km2 , republic FE, and region FE. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 21 / 46
Col 14 scatter plots [Two conditional scatter plots from the same regression] (a) Demeaned spring 1932 temperature (b) Demeaned summer 1932 precipitation 22 / 46
1932 weather did matter [Two sets of coefficients from one regression] (a) Demeaned spring temperature (b) Demeaned summer precipitation 23 / 46
Outline Background Data Empirical strategy Results Province population Rural and urban economy Urban settlements Mechanism: natural population increase v. migration 24 / 46
Empirical specification (1) yi,t = Ξ²fami Ipost t + Xi,tΞ³ + Ξ±i + Ξ΄t + i,t i – province, t – year yit – outcome of interest (Ln population etc) fami – excess 1933 mortality in province i Ipost t – post-famine indicator, Ipost t = 1 if t > 1933 Xi,t – province characteristics (grain suitability Γ— Post-famine, grain volatility Γ— Post-famine, capital province indicator Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, Ln distance to Moscow Γ— Post-famine, 1932 number of RR stations per km2 Γ— Post-famine) Ξ±i , Ξ΄t – province and year FE 25 / 46
1933 famine and population Panel A: Panel data estimation Dependent variable: Ln population Ln rural population Ln urban population Model: OLS IV OLS OLS IV OLS OLS IV OLS (1) (2) (3) (4) (5) (6) (7) (8) (9) Excess mortality 1933 -8.687βˆ—βˆ—βˆ— -8.588βˆ—βˆ—βˆ— -1.819 -2.186 -10.069βˆ—βˆ—βˆ— -10.206βˆ—βˆ— Γ— Post-famine (1.863) (3.215) (1.941) (3.371) (2.770) (4.179) Excess mortality 1933 -9.615βˆ—βˆ—βˆ— -5.443βˆ—βˆ— -10.383βˆ—βˆ—βˆ— Γ— 1939 (2.375) (2.701) (3.671) Excess mortality 1933 -8.560βˆ—βˆ—βˆ— -1.325 -10.027βˆ—βˆ—βˆ— Γ— Post-1949 (1.914) (1.983) (2.762) Ln rural population Observations 972 924 972 972 924 972 972 924 972 R2 0.638 0.868 0.639 0.634 0.837 0.636 0.925 0.947 0.925 Provinces 81 77 81 81 77 81 81 77 81 Panel B: First stages of the corresponding 2SLS panel regressions Dependent variable: Excess mortality 1933 Γ— Post-famine Demeaned spring 1932 -0.012βˆ—βˆ—βˆ— -0.012βˆ—βˆ—βˆ— -0.012βˆ—βˆ—βˆ— temp Γ— Post-famine (0.004) (0.004) (0.004) Demeaned summer 1932 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— precip Γ— Post-famine (0.000) (0.000) (0.000) F 22.782 22.782 22.711 All regressions control for province and year FE, grain suitability Γ— Post-famine, grain volatility Γ— Post-famine, capital province indicator Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, Ln distance to Moscow Γ— Post-famine, 1932 number of RR stations per km2 Γ— Post-famine, republic-year FE, and region-year FE. Standard errors clustered at the province level separately before and after the famine. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 26 / 46
Population by quartiles of 1933 excess mortality 27 / 46
Rural population by quartiles of 1933 excess mortality 28 / 46
Urban population by quartiles of 1933 excess mortality 29 / 46
Empirical specification (2) yi,t = t=1926 Ξ²tfami Β· 1[year = t] + Xi,tΞ³t + Ξ±i + Ξ΄t + i,t i – province, t – year yit – outcome of interest (Ln population etc) fami – excess 1933 mortality in province i Xi,t – province characteristics (grain suitability Γ— Post-famine, grain volatility Γ— Post-famine, WW2 losses Γ— Post-WW2) Ξ±i , Ξ΄t – province and year FE 30 / 46
1933 famine and population 31 / 46
1933 famine and rural population 32 / 46
1933 famine and urban population 33 / 46
Robustness checks Additional geographic controls: latitude and longitude Natural resources: Check Political repressions and Gulag camps: Check Political preferences of the population Ethnic deportations Holocaust Evacuation 1947 famine 34 / 46
Outline Background Data Empirical strategy Results Province population Rural and urban economy Urban settlements Mechanism: natural population increase v. migration 35 / 46
Rural economy Dependent variable: Ln grain Ln sown area Ln cattle (1) (2) (3) (4) (5) (6) Excess mortality 1933 -1.128 -1.098 -2.897 Γ— Post-famine (1.625) (2.119) (1.917) Excess mortality 1933 -9.031βˆ—βˆ—βˆ— -8.230βˆ—βˆ— -4.720βˆ— Γ— [1934,1940] (2.620) (3.235) (2.836) Excess mortality 1933 1.736 1.063 -2.760 Γ— Post-1949 (1.881) (2.315) (1.950) Observations 3413 3413 4957 4957 1500 1500 R2 0.594 0.609 0.563 0.572 0.881 0.881 Provinces 77 77 77 77 60 60 All regressions control for province and year FE, grain suitability Γ— Post-famine, grain volatility Γ— Post-famine, capital province indicator Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, Ln distance to Moscow Γ— Post-famine, 1932 number of RR stations per km2 Γ— Post-famine, republic-year FE, and region-year FE. Standard errors clustered at the province level separately before and after the famine. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 36 / 46
Urban economy Dependent variable: Ln power plants Ln electricity Ln industrial capacity produced output (1) (2) (3) (4) (5) (6) Excess mortality 1933 -2.442 -7.072βˆ—βˆ—βˆ— -5.833βˆ—βˆ—βˆ— Γ— Post-famine (2.314) (2.592) (1.790) Excess mortality 1933 -3.019 -6.384βˆ—βˆ— -4.681βˆ—βˆ— Γ— [1934,1940] (2.669) (3.055) (1.896) Excess mortality 1933 -2.203 -7.357βˆ—βˆ—βˆ— -6.912βˆ—βˆ—βˆ— Γ— Post-1946 (2.442) (2.748) (2.042) Observations 1408 1408 1408 1408 898 898 R2 0.891 0.891 0.894 0.894 0.922 0.922 Provinces 79 79 79 79 78 78 All regressions control for province and year FE, grain suitability Γ— Post-famine, grain volatility Γ— Post-famine, capital province indicator Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, Ln distance to Moscow Γ— Post-famine, 1932 number of RR stations per km2 Γ— Post-famine, republic-year FE, and region-year FE. Standard errors clustered at the province level separately before and after the famine. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 37 / 46
Outline Background Data Empirical strategy Results Province population Rural and urban economy Urban settlements Mechanism: natural population increase v. migration 38 / 46
Urban settlements 39 / 46
1933 mortality and population of urban settlements Panel A: Panel data estimation Dependent variable: Ln population Model: OLS IV Sample: All Belarus Russia Ukraine All (1) (2) (3) (4) (5) Mortality 1933 Γ— Post-famine -7.158βˆ—βˆ—βˆ— 1.531 -9.380βˆ—βˆ— -7.648βˆ—βˆ— -9.245 (2.681) (23.235) (3.693) (3.306) (8.142) Observations 4802 630 2181 1991 4161 R2 0.809 0.625 0.875 0.764 0.395 Settlements 525 98 205 222 426 Panel B: First stages of the corresponding 2SLS panel regressions Dependent variable: Mortality 1933 Γ— Post-famine Demeaned spring 1932 -0.010βˆ—βˆ—βˆ— temp Γ— Post-famine (0.002) Demeaned summer 1932 0.000βˆ—βˆ— precip Γ— Post-famine (0.000) F 19.751 All regressions control for settlement and year FE, grain suitability Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, and province-year FE. Standard errors clustered at the settlement level. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 40 / 46
1933 mortality and population of urban settlements 41 / 46
Outline Background Data Empirical strategy Results Province population Rural and urban economy Urban settlements Mechanism: natural population increase v. migration 42 / 46
The correlation between 1933 excess mortality and natural population increase No evidence that rural population recovered due to differential birth and death rates =β‡’ recovery must be due to migration Dependent variable: Total, 1899 – 1990 Rural, 1928 – 1990 Birth rate Death rate Natural increase Birth rate Death rate Natural increase (1) (2) (3) (4) (5) (6) Excess mortality 1933 Γ— [1934,1940] 0.002 -0.063βˆ—βˆ—βˆ— 0.061 0.076 0.041 0.032 (0.043) (0.019) (0.036) (0.060) (0.031) (0.068) Excess mortality 1933 Γ— [1946,1990] -0.048 -0.022 -0.027 0.027 0.080βˆ—βˆ— -0.054 (0.039) (0.013) (0.033) (0.028) (0.032) (0.043) Observations 1470 1491 1470 1130 1151 1130 R2 0.964 0.969 0.895 0.950 0.904 0.930 Administrative units 25 25 25 25 25 25 All regressions control for province and year FE, grain suitability Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, urbanization rate, and republic-year FE. Natural increase is birth rate minus death rate. Robust standard errors. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 43 / 46
The correlation between 1933 excess mortality and natural population increase, by 5 – 10 year periods (a) Natality (b) Mortality (c) Natural increase (d) Rural natality (e) Rural mortality (f) Rural natural increase Yearly data 44 / 46
Impact of famine on urban settlements by settlement size Dependent variable: Ln population Sample: 1926 population ≀ 25K 1926 population β‰₯ 25K (1) (2) Mortality 1933 Γ— Post-famine -9.284βˆ—βˆ—βˆ— -2.736 (3.528) (5.181) WW2 losses Γ— Post-war Observations 2909 1893 R2 0.814 0.888 Towns 320 205 All regressions control for town and year FE, grain suitability Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, and province-year FE. Standard errors clustered at the town level. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 45 / 46
Conclusion 1933 famine had a strong persistent negative impact on urban population Recovery of rural population must be explained by differential migration Smaller urban settlements were more affected For the future: Compare plan and the actual urban development Add omitted urban settlements Complete robustness checks Mechanism? 46 / 46
Backup slides 1 / 8
WW2 losses estimates Back 2 / 8
1933 famine and pop: controlling for natural resources 1/2 Panel A: Panel data estimation Dependent variable: Ln population Ln rural population Ln urban population Model: OLS IV OLS OLS IV OLS OLS IV OLS (1) (2) (3) (4) (5) (6) (7) (8) (9) Excess mortality 1933 -7.202βˆ—βˆ—βˆ— -8.521βˆ—βˆ—βˆ— -1.489 -2.622 -8.201βˆ—βˆ—βˆ— -9.290βˆ—βˆ— Γ— Post-famine (1.690) (3.051) (1.963) (3.226) (2.358) (3.922) Excess mortality 1933 -8.381βˆ—βˆ—βˆ— -5.129βˆ— -8.850βˆ—βˆ—βˆ— Γ— 1939 (2.265) (2.720) (3.283) Excess mortality 1933 -7.036βˆ—βˆ—βˆ— -0.978 -8.111βˆ—βˆ—βˆ— Γ— Post-1949 (1.742) (2.009) (2.352) Natural resources Ln rural population Observations 960 912 960 960 912 960 960 912 960 R2 0.660 0.876 0.660 0.637 0.839 0.639 0.930 0.951 0.930 Provinces 80 76 80 80 76 80 80 76 80 Panel B: First stages of the corresponding 2SLS panel regressions Dependent variable: Excess mortality 1933 Γ— Post-famine Demeaned spring 1932 -0.014βˆ—βˆ—βˆ— -0.014βˆ—βˆ—βˆ— -0.013βˆ—βˆ—βˆ— temp Γ— Post-famine (0.004) (0.004) (0.004) Demeaned summer 1932 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— precip Γ— Post-famine (0.000) (0.000) (0.000) F 22.662 22.662 22.554 All regressions control for province and year FE, grain suitability Γ— Post-famine, grain volatility Γ— Post-famine, capital province indicator Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, Ln distance to Moscow Γ— Post-famine, 1932 number of RR stations per km2 Γ— Post-famine, republic-year FE, and region-year FE. Natural resources are oil 2006 production Γ— Post-famine, and coal 2006 production Γ— Post-famine. Standard errors clustered at the province level separately before and after the famine. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 3 / 8
Impact of 1933 famine by the 1926 settlement size Dependent variable: Ln population Sample: 1926 pop ≀ 20K 20K < 1926 pop ≀ 30K 30K < 1926 pop ≀ 40K 1926 pop > 40K (1) (2) (3) (4) Mortality 1933 -8.695βˆ—βˆ— -3.214 17.937βˆ— 1.860 Γ— Post-famine (3.615) (22.864) (10.514) (8.017) Observations 2649 467 302 1384 R2 0.818 0.969 0.972 0.893 Settlements 295 45 28 157 All regressions control for settlement and year FE, grain suitability Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, and province-year FE. Standard errors clustered at the settlement level. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 4 / 8
1933 famine and pop: controlling for natural resources 2/2 (a) Population (b) Rural population (c) Urban population Back 5 / 8
Famine and pop: controlling for political repressions 1/2 Panel A: Panel data estimation Dependent variable: Ln population Ln rural population Ln urban population Model: OLS IV OLS OLS IV OLS OLS IV OLS (1) (2) (3) (4) (5) (6) (7) (8) (9) Excess mortality 1933 -8.470βˆ—βˆ—βˆ— -9.082βˆ—βˆ—βˆ— -1.760 -2.493 -9.688βˆ—βˆ—βˆ— -10.112βˆ—βˆ— Γ— Post-famine (2.000) (3.076) (2.071) (3.156) (2.763) (3.937) Excess mortality 1933 -9.376βˆ—βˆ—βˆ— -5.374βˆ— -9.989βˆ—βˆ—βˆ— Γ— 1939 (2.467) (2.764) (3.640) Excess mortality 1933 -8.347βˆ—βˆ—βˆ— -1.270 -9.648βˆ—βˆ—βˆ— Γ— Post-1949 (2.051) (2.117) (2.759) Political repressions Ln rural population Observations 972 924 972 972 924 972 972 924 972 R2 0.644 0.871 0.644 0.640 0.840 0.642 0.925 0.948 0.925 Provinces 81 77 81 81 77 81 81 77 81 Panel B: First stages of the corresponding 2SLS panel regressions Dependent variable: Excess mortality 1933 Γ— Post-famine Demeaned spring 1932 -0.010βˆ—βˆ—βˆ— -0.010βˆ—βˆ—βˆ— -0.010βˆ—βˆ—βˆ— temp Γ— Post-famine (0.004) (0.004) (0.004) Demeaned summer 1932 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— precip Γ— Post-famine (0.000) (0.000) (0.000) F 26.641 26.641 26.397 All regressions control for province and year FE, grain suitability Γ— Post-famine, grain volatility Γ— Post-famine, capital province indicator Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, Ln distance to Moscow Γ— Post-famine, 1932 number of RR stations per km2 Γ— Post-famine, republic-year FE, and region-year FE. Political repressions are Ln number of convicted and Ln number of executed individuals under Article 58 Γ— Post-famine. Standard errors clustered at the province level separately before and after the famine. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 6 / 8
Famine and pop: controlling for political repressions 2/2 (a) Population (b) Rural population (c) Urban population Back 7 / 8
The correlation between 1933 excess mortality and natural population increase, yearly data (a) Natality (b) Mortality (c) Natural increase (d) Rural natality (e) Rural mortality (f) Rural natural increase Back 8 / 8

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Economic Consequences of the 1933 Soviet Famine

  • 1. Economic Consequences of the 1933 Soviet Famine Natalya Naumenko George Mason University December 16, 2019 1 / 46
  • 2. Introduction Krugman (1991): Fixed land, rural population is located in accordance with marginal productivity of land Multiple urbanization equilibria are possible due to mobility of urban capital and increasing returns Temporary shock to urban population or capital can have a persistent impact Empirical question Do multiple equilibria exist? 2 / 46
  • 3. Literature 1/2 No persistent effects from temporary population and capital losses: Davis and Weinstein (2002), Davis and Weinstein (2008) – Japan, WW2 Brakman et al. (2004), Bosker et al. (2007) – Germany, WW2 Redding and Sturm (2008) – partition and reunification of Germany Miguel and Roland (2011) – Vietnam 3 / 46
  • 4. Literature 2/2 Location characteristics affect long-term urban development: Nunn and Puga (2012) – terrain ruggedness in Africa Bleakley and Lin (2012) – portage sites in the U.S. Michaels and Rauch (2018) – Roman cities in contemporary England and France Russia: Acemoglu et al. (2011) – holocaust changed social structure and therefore had a detrimental effect Mikhailova (2018) – some persistence due to evacuation, but economically small 4 / 46
  • 5. This paper Studies 1933 famine consequences Rural population recovers Persistent negative impact on urbanization Not explained by differential natural increase Timing of the shock to population might be important: lack of labor during rapid construction of new cities 5 / 46
  • 6. Outline Background Data Empirical strategy Results Province population Rural and urban economy Urban settlements Mechanism: natural population increase v. migration 6 / 46
  • 7. Chronology 1917 Revolution 1928 Start of the first 5-year plan; Rapid industrialization and urbanization, especially after 1933 1933 Famine; Victims: 6 – 8 million 7 / 46
  • 8. Before 1928: NEP New Economic Policy: Private rural economy Private small-scale urban enterprises Large-scale industry under government control Unrestricted migration 8 / 46
  • 9. Starting in 1928: 5-year plans 5-year plans for industrialization of the country: All industry and trade are nationalized Large-scale capital investment Collectivization of agriculture 9 / 46
  • 10. Collectivization and the 1933 famine 1/2 Until 1933 Land, livestock, and implements belong to the collectives Peasants work together on collective farms After the harvest, grain is put in kolkhoz storages The government takes its share Procurement is unpredictable as officials struggle to fulfill the plan The remainder is distributed among kolkhoz members Trading of foodstuffs is banned, food is rationed in the cities As a result: Production drops, the government overprocures, famine in 1933 10 / 46
  • 11. Collectivization and the 1933 famine 2/2 After 1933 Procurement quotas are fixed in advance Kolkhoz members allowed to work small individual plots and to keep some livestock Peasants can trade food on kolkhoz markets with free prices As a result Peasants are guaranteed subsistence 11 / 46
  • 12. Mortality Belarus, Russia, and Ukraine. Constant administrative borders. Territories added in 1939 are not included. 12 / 46
  • 13. A note on passport system Was introduced in 1932 Designed to remove β€˜undesirable elements’ (criminals, refugees, β€˜class enemies’) from important cities Under control of MVD, not NKVD MVD keeps decentralized catalogues, no evidence of exchange of information between cities Employed urban dwellers are eligible for a passport If a person is denied a passport, no mark is made in her documents 13 / 46
  • 14. Rapid urbanization 1927 – 18% 1932 – 22% 1939 – 34% Belarus, Russia, and Ukraine. Constant administrative borders. Territories added in 1939 are not included. 14 / 46
  • 15. Outline Background Data Empirical strategy Results Province population Rural and urban economy Urban settlements Mechanism: natural population increase v. migration 15 / 46
  • 16. Data 1/2 Province-level population panel 81 provinces (contemporary Belarus, Russia, Ukraine) All censuses: 1897, 1926, 1939, 1959, 1970, 1979, 1989, 2002, 2010 1913 from statistical yearbook 1939 corrected for centralized additions 1949, 1950 from the Russian State Archive of the Economy Urban settlement panel 525 settlements All census years 1946, 1947, 1950 from the archives Selected sample: only settlements that achieved β€œtown” status by 1989 Yearly mortality and natality data 25 large administrative units 16 / 46
  • 17. Data 2/2 Famine severity: Province-level 1933 excess mortality from the archives: 1933 excess mortality = 1933 mortaliyβˆ’ 1 4 (1928 mortality + 1937-1939 mortality) 1933 mortality in 50 km radius around each urban settlement using district-level 1933 mortality WW2 losses: WW2 losses = 1 βˆ’ actual population 1949 projected population 1949 17 / 46
  • 18. 1933 excess mortality WW2 losses 18 / 46
  • 19. Outline Background Data Empirical strategy Results Province population Rural and urban economy Urban settlements Mechanism: natural population increase v. migration 19 / 46
  • 20. Empirical strategy OLS Use cross-sectional variation in 1933 famine severity IV Idea: weather β†’ [ harvest ] β†’ famine Use 1932 weather 20 / 46
  • 21. Demeaned 1932 weather and 1933 excess mortality Dependent variable: Excess mortality 1933 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) Fall temp -0.009 -0.010 -0.001 (0.006) (0.006) (0.008) precip 0.000 0.000 0.001βˆ— (0.000) (0.000) (0.000) Winter temp -0.000 -0.000 0.000 (0.000) (0.000) (0.001) precip 0.000 0.000 0.000 (0.000) (0.000) (0.000) Spring temp -0.015βˆ—βˆ— -0.017βˆ—βˆ— -0.018βˆ—βˆ— -0.016βˆ—βˆ—βˆ— (0.007) (0.007) (0.008) (0.006) precip 0.000 0.000βˆ— 0.000 (0.000) (0.000) (0.000) Summer temp -0.005 -0.001 -0.001 (0.005) (0.004) (0.006) precip 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— (0.000) (0.000) (0.000) (0.000) N 77 77 77 77 77 77 77 77 77 77 77 77 77 77 R2 0.588 0.585 0.603 0.581 0.573 0.582 0.603 0.584 0.621 0.579 0.689 0.690 0.742 0.723 All regressions control for grain suitability, grain volatility, capital province indicator, WW2 losses, Nazi occupation indicator, Ln distance to Moscow, 1932 number of RR stations per km2 , republic FE, and region FE. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 21 / 46
  • 22. Col 14 scatter plots [Two conditional scatter plots from the same regression] (a) Demeaned spring 1932 temperature (b) Demeaned summer 1932 precipitation 22 / 46
  • 23. 1932 weather did matter [Two sets of coefficients from one regression] (a) Demeaned spring temperature (b) Demeaned summer precipitation 23 / 46
  • 24. Outline Background Data Empirical strategy Results Province population Rural and urban economy Urban settlements Mechanism: natural population increase v. migration 24 / 46
  • 25. Empirical specification (1) yi,t = Ξ²fami Ipost t + Xi,tΞ³ + Ξ±i + Ξ΄t + i,t i – province, t – year yit – outcome of interest (Ln population etc) fami – excess 1933 mortality in province i Ipost t – post-famine indicator, Ipost t = 1 if t > 1933 Xi,t – province characteristics (grain suitability Γ— Post-famine, grain volatility Γ— Post-famine, capital province indicator Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, Ln distance to Moscow Γ— Post-famine, 1932 number of RR stations per km2 Γ— Post-famine) Ξ±i , Ξ΄t – province and year FE 25 / 46
  • 26. 1933 famine and population Panel A: Panel data estimation Dependent variable: Ln population Ln rural population Ln urban population Model: OLS IV OLS OLS IV OLS OLS IV OLS (1) (2) (3) (4) (5) (6) (7) (8) (9) Excess mortality 1933 -8.687βˆ—βˆ—βˆ— -8.588βˆ—βˆ—βˆ— -1.819 -2.186 -10.069βˆ—βˆ—βˆ— -10.206βˆ—βˆ— Γ— Post-famine (1.863) (3.215) (1.941) (3.371) (2.770) (4.179) Excess mortality 1933 -9.615βˆ—βˆ—βˆ— -5.443βˆ—βˆ— -10.383βˆ—βˆ—βˆ— Γ— 1939 (2.375) (2.701) (3.671) Excess mortality 1933 -8.560βˆ—βˆ—βˆ— -1.325 -10.027βˆ—βˆ—βˆ— Γ— Post-1949 (1.914) (1.983) (2.762) Ln rural population Observations 972 924 972 972 924 972 972 924 972 R2 0.638 0.868 0.639 0.634 0.837 0.636 0.925 0.947 0.925 Provinces 81 77 81 81 77 81 81 77 81 Panel B: First stages of the corresponding 2SLS panel regressions Dependent variable: Excess mortality 1933 Γ— Post-famine Demeaned spring 1932 -0.012βˆ—βˆ—βˆ— -0.012βˆ—βˆ—βˆ— -0.012βˆ—βˆ—βˆ— temp Γ— Post-famine (0.004) (0.004) (0.004) Demeaned summer 1932 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— precip Γ— Post-famine (0.000) (0.000) (0.000) F 22.782 22.782 22.711 All regressions control for province and year FE, grain suitability Γ— Post-famine, grain volatility Γ— Post-famine, capital province indicator Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, Ln distance to Moscow Γ— Post-famine, 1932 number of RR stations per km2 Γ— Post-famine, republic-year FE, and region-year FE. Standard errors clustered at the province level separately before and after the famine. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 26 / 46
  • 27. Population by quartiles of 1933 excess mortality 27 / 46
  • 28. Rural population by quartiles of 1933 excess mortality 28 / 46
  • 29. Urban population by quartiles of 1933 excess mortality 29 / 46
  • 30. Empirical specification (2) yi,t = t=1926 Ξ²tfami Β· 1[year = t] + Xi,tΞ³t + Ξ±i + Ξ΄t + i,t i – province, t – year yit – outcome of interest (Ln population etc) fami – excess 1933 mortality in province i Xi,t – province characteristics (grain suitability Γ— Post-famine, grain volatility Γ— Post-famine, WW2 losses Γ— Post-WW2) Ξ±i , Ξ΄t – province and year FE 30 / 46
  • 31. 1933 famine and population 31 / 46
  • 32. 1933 famine and rural population 32 / 46
  • 33. 1933 famine and urban population 33 / 46
  • 34. Robustness checks Additional geographic controls: latitude and longitude Natural resources: Check Political repressions and Gulag camps: Check Political preferences of the population Ethnic deportations Holocaust Evacuation 1947 famine 34 / 46
  • 35. Outline Background Data Empirical strategy Results Province population Rural and urban economy Urban settlements Mechanism: natural population increase v. migration 35 / 46
  • 36. Rural economy Dependent variable: Ln grain Ln sown area Ln cattle (1) (2) (3) (4) (5) (6) Excess mortality 1933 -1.128 -1.098 -2.897 Γ— Post-famine (1.625) (2.119) (1.917) Excess mortality 1933 -9.031βˆ—βˆ—βˆ— -8.230βˆ—βˆ— -4.720βˆ— Γ— [1934,1940] (2.620) (3.235) (2.836) Excess mortality 1933 1.736 1.063 -2.760 Γ— Post-1949 (1.881) (2.315) (1.950) Observations 3413 3413 4957 4957 1500 1500 R2 0.594 0.609 0.563 0.572 0.881 0.881 Provinces 77 77 77 77 60 60 All regressions control for province and year FE, grain suitability Γ— Post-famine, grain volatility Γ— Post-famine, capital province indicator Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, Ln distance to Moscow Γ— Post-famine, 1932 number of RR stations per km2 Γ— Post-famine, republic-year FE, and region-year FE. Standard errors clustered at the province level separately before and after the famine. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 36 / 46
  • 37. Urban economy Dependent variable: Ln power plants Ln electricity Ln industrial capacity produced output (1) (2) (3) (4) (5) (6) Excess mortality 1933 -2.442 -7.072βˆ—βˆ—βˆ— -5.833βˆ—βˆ—βˆ— Γ— Post-famine (2.314) (2.592) (1.790) Excess mortality 1933 -3.019 -6.384βˆ—βˆ— -4.681βˆ—βˆ— Γ— [1934,1940] (2.669) (3.055) (1.896) Excess mortality 1933 -2.203 -7.357βˆ—βˆ—βˆ— -6.912βˆ—βˆ—βˆ— Γ— Post-1946 (2.442) (2.748) (2.042) Observations 1408 1408 1408 1408 898 898 R2 0.891 0.891 0.894 0.894 0.922 0.922 Provinces 79 79 79 79 78 78 All regressions control for province and year FE, grain suitability Γ— Post-famine, grain volatility Γ— Post-famine, capital province indicator Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, Ln distance to Moscow Γ— Post-famine, 1932 number of RR stations per km2 Γ— Post-famine, republic-year FE, and region-year FE. Standard errors clustered at the province level separately before and after the famine. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 37 / 46
  • 38. Outline Background Data Empirical strategy Results Province population Rural and urban economy Urban settlements Mechanism: natural population increase v. migration 38 / 46
  • 40. 1933 mortality and population of urban settlements Panel A: Panel data estimation Dependent variable: Ln population Model: OLS IV Sample: All Belarus Russia Ukraine All (1) (2) (3) (4) (5) Mortality 1933 Γ— Post-famine -7.158βˆ—βˆ—βˆ— 1.531 -9.380βˆ—βˆ— -7.648βˆ—βˆ— -9.245 (2.681) (23.235) (3.693) (3.306) (8.142) Observations 4802 630 2181 1991 4161 R2 0.809 0.625 0.875 0.764 0.395 Settlements 525 98 205 222 426 Panel B: First stages of the corresponding 2SLS panel regressions Dependent variable: Mortality 1933 Γ— Post-famine Demeaned spring 1932 -0.010βˆ—βˆ—βˆ— temp Γ— Post-famine (0.002) Demeaned summer 1932 0.000βˆ—βˆ— precip Γ— Post-famine (0.000) F 19.751 All regressions control for settlement and year FE, grain suitability Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, and province-year FE. Standard errors clustered at the settlement level. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 40 / 46
  • 41. 1933 mortality and population of urban settlements 41 / 46
  • 42. Outline Background Data Empirical strategy Results Province population Rural and urban economy Urban settlements Mechanism: natural population increase v. migration 42 / 46
  • 43. The correlation between 1933 excess mortality and natural population increase No evidence that rural population recovered due to differential birth and death rates =β‡’ recovery must be due to migration Dependent variable: Total, 1899 – 1990 Rural, 1928 – 1990 Birth rate Death rate Natural increase Birth rate Death rate Natural increase (1) (2) (3) (4) (5) (6) Excess mortality 1933 Γ— [1934,1940] 0.002 -0.063βˆ—βˆ—βˆ— 0.061 0.076 0.041 0.032 (0.043) (0.019) (0.036) (0.060) (0.031) (0.068) Excess mortality 1933 Γ— [1946,1990] -0.048 -0.022 -0.027 0.027 0.080βˆ—βˆ— -0.054 (0.039) (0.013) (0.033) (0.028) (0.032) (0.043) Observations 1470 1491 1470 1130 1151 1130 R2 0.964 0.969 0.895 0.950 0.904 0.930 Administrative units 25 25 25 25 25 25 All regressions control for province and year FE, grain suitability Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, urbanization rate, and republic-year FE. Natural increase is birth rate minus death rate. Robust standard errors. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 43 / 46
  • 44. The correlation between 1933 excess mortality and natural population increase, by 5 – 10 year periods (a) Natality (b) Mortality (c) Natural increase (d) Rural natality (e) Rural mortality (f) Rural natural increase Yearly data 44 / 46
  • 45. Impact of famine on urban settlements by settlement size Dependent variable: Ln population Sample: 1926 population ≀ 25K 1926 population β‰₯ 25K (1) (2) Mortality 1933 Γ— Post-famine -9.284βˆ—βˆ—βˆ— -2.736 (3.528) (5.181) WW2 losses Γ— Post-war Observations 2909 1893 R2 0.814 0.888 Towns 320 205 All regressions control for town and year FE, grain suitability Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, and province-year FE. Standard errors clustered at the town level. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 45 / 46
  • 46. Conclusion 1933 famine had a strong persistent negative impact on urban population Recovery of rural population must be explained by differential migration Smaller urban settlements were more affected For the future: Compare plan and the actual urban development Add omitted urban settlements Complete robustness checks Mechanism? 46 / 46
  • 49. 1933 famine and pop: controlling for natural resources 1/2 Panel A: Panel data estimation Dependent variable: Ln population Ln rural population Ln urban population Model: OLS IV OLS OLS IV OLS OLS IV OLS (1) (2) (3) (4) (5) (6) (7) (8) (9) Excess mortality 1933 -7.202βˆ—βˆ—βˆ— -8.521βˆ—βˆ—βˆ— -1.489 -2.622 -8.201βˆ—βˆ—βˆ— -9.290βˆ—βˆ— Γ— Post-famine (1.690) (3.051) (1.963) (3.226) (2.358) (3.922) Excess mortality 1933 -8.381βˆ—βˆ—βˆ— -5.129βˆ— -8.850βˆ—βˆ—βˆ— Γ— 1939 (2.265) (2.720) (3.283) Excess mortality 1933 -7.036βˆ—βˆ—βˆ— -0.978 -8.111βˆ—βˆ—βˆ— Γ— Post-1949 (1.742) (2.009) (2.352) Natural resources Ln rural population Observations 960 912 960 960 912 960 960 912 960 R2 0.660 0.876 0.660 0.637 0.839 0.639 0.930 0.951 0.930 Provinces 80 76 80 80 76 80 80 76 80 Panel B: First stages of the corresponding 2SLS panel regressions Dependent variable: Excess mortality 1933 Γ— Post-famine Demeaned spring 1932 -0.014βˆ—βˆ—βˆ— -0.014βˆ—βˆ—βˆ— -0.013βˆ—βˆ—βˆ— temp Γ— Post-famine (0.004) (0.004) (0.004) Demeaned summer 1932 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— precip Γ— Post-famine (0.000) (0.000) (0.000) F 22.662 22.662 22.554 All regressions control for province and year FE, grain suitability Γ— Post-famine, grain volatility Γ— Post-famine, capital province indicator Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, Ln distance to Moscow Γ— Post-famine, 1932 number of RR stations per km2 Γ— Post-famine, republic-year FE, and region-year FE. Natural resources are oil 2006 production Γ— Post-famine, and coal 2006 production Γ— Post-famine. Standard errors clustered at the province level separately before and after the famine. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 3 / 8
  • 50. Impact of 1933 famine by the 1926 settlement size Dependent variable: Ln population Sample: 1926 pop ≀ 20K 20K < 1926 pop ≀ 30K 30K < 1926 pop ≀ 40K 1926 pop > 40K (1) (2) (3) (4) Mortality 1933 -8.695βˆ—βˆ— -3.214 17.937βˆ— 1.860 Γ— Post-famine (3.615) (22.864) (10.514) (8.017) Observations 2649 467 302 1384 R2 0.818 0.969 0.972 0.893 Settlements 295 45 28 157 All regressions control for settlement and year FE, grain suitability Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, and province-year FE. Standard errors clustered at the settlement level. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 4 / 8
  • 51. 1933 famine and pop: controlling for natural resources 2/2 (a) Population (b) Rural population (c) Urban population Back 5 / 8
  • 52. Famine and pop: controlling for political repressions 1/2 Panel A: Panel data estimation Dependent variable: Ln population Ln rural population Ln urban population Model: OLS IV OLS OLS IV OLS OLS IV OLS (1) (2) (3) (4) (5) (6) (7) (8) (9) Excess mortality 1933 -8.470βˆ—βˆ—βˆ— -9.082βˆ—βˆ—βˆ— -1.760 -2.493 -9.688βˆ—βˆ—βˆ— -10.112βˆ—βˆ— Γ— Post-famine (2.000) (3.076) (2.071) (3.156) (2.763) (3.937) Excess mortality 1933 -9.376βˆ—βˆ—βˆ— -5.374βˆ— -9.989βˆ—βˆ—βˆ— Γ— 1939 (2.467) (2.764) (3.640) Excess mortality 1933 -8.347βˆ—βˆ—βˆ— -1.270 -9.648βˆ—βˆ—βˆ— Γ— Post-1949 (2.051) (2.117) (2.759) Political repressions Ln rural population Observations 972 924 972 972 924 972 972 924 972 R2 0.644 0.871 0.644 0.640 0.840 0.642 0.925 0.948 0.925 Provinces 81 77 81 81 77 81 81 77 81 Panel B: First stages of the corresponding 2SLS panel regressions Dependent variable: Excess mortality 1933 Γ— Post-famine Demeaned spring 1932 -0.010βˆ—βˆ—βˆ— -0.010βˆ—βˆ—βˆ— -0.010βˆ—βˆ—βˆ— temp Γ— Post-famine (0.004) (0.004) (0.004) Demeaned summer 1932 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— 0.001βˆ—βˆ—βˆ— precip Γ— Post-famine (0.000) (0.000) (0.000) F 26.641 26.641 26.397 All regressions control for province and year FE, grain suitability Γ— Post-famine, grain volatility Γ— Post-famine, capital province indicator Γ— Post-famine, WW2 losses Γ— Post-war, Nazi occupation indicator Γ— Post-war, Ln distance to Moscow Γ— Post-famine, 1932 number of RR stations per km2 Γ— Post-famine, republic-year FE, and region-year FE. Political repressions are Ln number of convicted and Ln number of executed individuals under Article 58 Γ— Post-famine. Standard errors clustered at the province level separately before and after the famine. βˆ— p < .10, βˆ—βˆ— p < .05, βˆ—βˆ—βˆ— p < .01 6 / 8
  • 53. Famine and pop: controlling for political repressions 2/2 (a) Population (b) Rural population (c) Urban population Back 7 / 8
  • 54. The correlation between 1933 excess mortality and natural population increase, yearly data (a) Natality (b) Mortality (c) Natural increase (d) Rural natality (e) Rural mortality (f) Rural natural increase Back 8 / 8