Decreasing labor intensity in agriculture and the accessibility of major cities shape the rural population decline in postsocialist Russia

Figures & data

Figure 1. Ecozones (Olson et al. 2001), rivers, settlements, and major transport routes in the study area

Notes: Cities and rayon centers are marked with open circles. The railway connecting Tyumen and Ishim is part of the Trans-Siberian Railroad.

Figure 2. Total population of Tyumen Province, 1981–2018

Notes: “Rural” and “urban” are defined as in official Russian statistics from Rosstat documents. The gray shading marks the study period. The sharp changes in 1991, 2004, 2009, and 2014 reflect the administrative reorganization of settlements.

Figure 3. Patterns of population change in Tyumen Province (the circle size indicates the initial size of the population, while the colors signal changes in population)

Figure 4. Number of people (a) and share of the working-age population (b) involved in agrarian production in agricultural enterprises and commercially oriented family farms in 2006

Table 1. Results of the linear mixed-effects model with the percent of the initial population at the end of the period as the dependent variable

	Regression coefficients
	1990–2002	2002–2010
Initial population (log)	7.18 (0.53)	7.85 (0.44)
Distance to Tyumen (10 km)	−0.07 (0.14)	−0.39 (0.13)
Distance to rayon center (10 km)	−1.01 (0.66)	−1.38 (0.61)
Constant	89.9 (5.86)	100.7 (4.69)
Observations	1,247	1,221
Root mean square deviation (RMSD)	26.0	21.5
R^2m	0.15	0.26
R^2c	0.28	0.37

Notes: Standard errors are in parentheses. R²m (marginal R²) represents the variance explained by the fixed effects, and R²_c (conditional R²) is interpreted as the variance explained by the entire model, i.e. by both fixed and random effects.

Figure 5. Population change in individual settlements plotted as a function of distance to the regional capital

Notes: Cities and rayon centers are plotted as open circles. The trend lines were created by smoothing the raw data with the LOESS method.

Table A1. Descriptive statistics on variables for the linear mixed effects regression with rayon as a grouping variable

Variable	Period	Min	1Q	Mean	Median	3Q	Max	sd	n
% of initial population at end of period	1990–2002	0.0	70.9	82.8	87.1	100.0	153.4	30.1	1247
	2002–2010	0.0	71.4	81.2	86.0	97.9	142.9	26.9	1221
Initial population	1990–2002	1	83	1048	184	452	487,000	14,259	1247
	2002–2010	3	69	1070	169	426	552,755	16,210	1221
Distance to Tyumen (km)	1990–2002	0.0	148.4	251.3	266.9	345.0	595.6	123.9	1247
	2002–2010	0.0	146.2	251.2	266.5	348.5	617.2	125.6	1221
Distance to rayon center (km)	1990–2002	0.0	18.9	35.1	31.2	46.0	281.9	25.4	1247
	2002–2010	0.0	19.4	31.4	35.0	46.2	278.1	23.8	1221

Notes: Outliers have been removed. 1Q – first quartile, 3Q – third quartile, sd – standard deviation, n – number of observations.

Figure A1. Actual and predicted values (RIRS model) against distance to Tyumen

Notes: Actual values are marked with gray points. Predicted values for different rayons are marked with colored circles. RIRS – random intercept and random slope model.

Figure A2.1. Actual and predicted (RIRS model) values against distance to rayon centers

Notes: Actual values are marked with gray points. Predicted values for different rayons are marked with colored circles.

Figure A2.2. Actual and predicted (RIRS model) values against distance to rayon centers

Notes: Actual values are marked with gray points. Predicted values for different rayons are marked with colored circles.

Figure A2.3. Actual and predicted (RIRS model) values against distance to rayon centers

Notes: Actual values are marked with gray points. Predicted values for different rayons are marked with colored circles.

Figure A3. Agricultural dynamics in Tyumen province in 1990–2010

Figure A4. Structural changes in cattle farming in Tyumen province in 1990–2010

Notes: “Corporate” refers to agricultural enterprises, “peasant” refers to commercially oriented family farms (“krest’yansko-fermerskie khozyaistva”), and “household” refers to private small-scale farming (“lichnye podsobnye khozyaistva”).

Olson, D. M., E. Dinerstein, E. D. Wikramanayake, N. D. Burgess, G. V. N. Powell, E. C. Underwood, J. A. D’amico, et al. 2001. “Terrestrial Ecoregions of the World: A New Map of Life on Earth: A New Global Map of Terrestrial Ecoregions Provides an Innovative Tool for Conserving Biodiversity.” BioScience 51 (11): 933–938. DOI:10.1641/0006-3568(2001)051[0933:TEOTWA]2.0.CO;2.

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