Russia's Birth Rates: The Surprising Economic Links
Wages Show a Moderate Positive Link, Explaining ~14% of Regional Fertility Differences
New research titled ЭКОНОМИЧЕСКИЕ ФАКТОРЫ В ДЕМОГРАФИИ РЕГИОНОВ РОССИИ (2017-2023 гг.) - Economic Factors in the Demography of Russian Regions (2017-2023) by Олег Л. Рыбаковский (I think translates to Oleg L. Rybakovsky) reveals a detailed and sometimes surprising picture of how economic conditions are connected to birth rates, death rates, and migration patterns across Russia. The findings challenge simple assumptions and highlight the unique complexities within Russia's diverse regions.
Why This Matters:
Understanding these intricate connections is vital for Russian policymakers. It helps them develop more effective strategies to tackle major demographic challenges like population decline, shifts in where people live, and uneven development across the country. The study shows that just increasing incomes doesn't automatically lead to predictable population changes, suggesting the need for more targeted and region-specific approaches.
The Big Picture:
Economists and demographers have long studied how a region's economic health relates to its population trends. Historically, theories ranged from basic resource availability (like Malthus) to the idea that people move for better economic opportunities. Analyzing this in a country as large and varied as Russia is complex because regions differ greatly in their economies, climates, geography, and cultures.
This study, led by Oleg L. Rybakovsky, used statistical analysis of data from Russia's state statistics service (Rosstat) to explore these relationships over a recent six-year period.
How the Study Was Done:
The research focused on the permanent population in 85 Russian regions. They looked at three key population indicators:
Life Expectancy at Birth (LE): The average number of years a person is expected to live. Data was averaged over 2017-2019 and 2022-2023 to reduce the impact of the COVID-19 pandemic years (2020-2021).
Total Fertility Rate (TFR): The average number of children a woman is expected to have in her lifetime. Data was averaged over the full 2017-2023 period.
Interregional Migration Efficiency (IME): This measures migration within Russia, calculated as the ratio of people arriving in a region compared to those leaving (specifically, "arrivals per 1000 departures"). This was also averaged over 2017-2019 and 2022-2023, accounting for pandemic-related travel disruptions.
These population indicators were then compared with several economic factors:
Gross Regional Product per capita (GRP/capita): A measure of the average economic output per person in a region. Averaged over 2018-2022.
Average Monthly Nominal Accrued Wages (Wages): The average salary before deductions. Averaged over 2018-2023.
Average Per Capita Monetary Income (Income): The average total income per person. Averaged from Q3 2017 to Q2 2023.
Average Per Capita Monetary Income minus Subsistence Minimum (Income - PM): Income after accounting for basic living costs. Averaged over 2017-2023.
Average Price of 1 sq. meter of Housing on the Secondary Market (Housing Price): The cost of existing homes. Averaged over 2017-2023, considered an indirect economic factor because it's influenced by many things, including economic demand.
Statistical methods, including using natural logarithms to normalize data were used to find the strength and direction of these connections. This helped identify potential outliers (regions with unusually high or low values) that could affect the overall findings.
Key Findings (By the Numbers):
Here's what the study found about the relationships between economic factors and the three population indicators:
Migration (IME):
There is only a weak connection between migration efficiency and direct economic factors like Wages, Income, and GRP/capita.
For example, the correlation coefficient (r) between the logarithm of IME and the logarithm of Wages was just 0.05. For GRP/capita, it was 0.08. The r2 values (which show how much of the variation in one factor is explained by the other) for these direct economic factors are very low, meaning they don't explain much about why migration efficiency differs between regions.
However, there's a moderate positive connection between IME and Housing Prices.
The correlation coefficient (r) between the logarithm of IME and the logarithm of Housing Price is 0.41. This means Housing Prices explain about 17% (r2≈0.412≈0.17) of the differences in migration efficiency between regions. This suggests regions with higher housing costs (which often indicates economic desirability) tend to attract more migrants.
IME also shows a moderate positive link to Life Expectancy.
The correlation coefficient (r) is 0.44, indicating LE explains about 19% (r2≈0.442≈0.19) of the variation in IME. When 10 regions with extreme LE values were excluded, this correlation became significantly stronger (r=0.51, r2≈0.26), showing that in a more typical group of regions, higher life expectancy areas are more attractive to migrants.
Life Expectancy (LE):
Direct economic factors have a moderate, but negative relationship with life expectancy.
The strongest negative correlation is with Wages (r=−0.33, r2≈0.11). This indicates that, on average, regions with higher wages tend to have lower life expectancy.
Correlations with GRP/capita (r=−0.22, r2≈0.05) and Income (r=−0.16, r2≈0.03) are also negative, though weaker.
The connection between LE and Housing Prices (r=0.07) or the Total Fertility Rate (r=−0.10) is minimal at the regional level.
Fertility Rate (TFR):
Unlike life expectancy, the total fertility rate shows a moderate, positive link with direct economic factors.
The strongest positive correlation is with Wages (r=0.38, r2≈0.14). This suggests regions with higher wages tend to have moderately higher birth rates.
Correlations with GRP/capita (r=0.35, r2≈0.12) and Income (r=0.19, r2≈0.04) are also positive, though weaker.
Removing 5 regions with extreme TFR values (like Tyva and Chechnya with very high rates) strengthened the correlation between TFR and Wages (r=0.43, r2≈0.18).
The connection between TFR and IME (r=−0.08) or LE (r=−0.10) is minimal at the regional level.
What the Researchers Say:
The paper suggest several reasons for these findings:
The weak link between migration and direct economic factors might be because people are still moving away from harsh northern regions, even if wages are high there. They might be seeking better climates and living conditions elsewhere, especially retirees. They also point out that official migration data since 2010 might not fully capture the true picture, potentially hiding stronger economic influences.
The surprising negative link between life expectancy and high incomes in some areas is likely due to the severe climate, low population density, poor road and social infrastructure, and specific lifestyles of indigenous populations in those northern territories. High wages there might be compensation for these difficult conditions rather than reflecting a high quality of life that supports longevity.
The positive link between fertility and economic factors is more in line with general expectations, suggesting that higher incomes provide families with greater resources and stability, which can support having children.
Methodologically, the study highlights the importance of preparing data correctly (like using logarithms for skewed economic data) and carefully looking at scatter plots. This helps identify and understand the impact of unusual regions that might otherwise distort the overall findings. They also argue against combining different economic factors into a single measure, as it makes it harder to see how each specific factor influences population trends.
The Bottom Line:
Economic factors do play a role in shaping Russia's regional demographics, but the connections are complex, often unexpected, and heavily influenced by geography, climate, and data limitations. Simple correlations don't tell the whole story. This research emphasizes the need for detailed, region-by-region analysis and potentially tailored demographic and economic policies that consider the unique circumstances of different parts of Russia.