Impact of GRP Per Capita on the Quality of Life of the Population in Russian Regions
DOI:
https://doi.org/10.17059/ekon.reg.2024-1-12Keywords:
подушевой валовой региональный продукт, качество жизни населения, среднедушевые расходы населения, эконометрическое моделирование, пространственные фиксированные эффекты, региональная политикаAbstract
Most countries consider dynamics of gross domestic product (GDP) as an indicator of economic policy success. Despite its importance and usefulness, GDP has limitations when it comes to assessing the situation in society and some economic development characteristics. The paper examines the relationship between gross regional product (GRP) per capita and the quality of life of the population in Russian regions. The impact of GRP on the quality of life was modelled on panel data using spatial fixed effects. As a result, well-specified models explaining differences in the dependent variable were identified. The study confirmed the presence of a constant elasticity of the integral index of the quality of life of the population in Russian regions for GRP per capita (0.588). Regional fixed effects were analysed in dynamics to assess their potential for ensuring the quality of life of the population. Additionally, opportunities resulting from GRP distribution and the effectiveness of regional policies in creating conditions for maintaining the quality of life were examined. Positive fixed effects increase in regions with high integral indices during the observation period, while the opposite is observed in lagging regions. Therefore, the inequality of regions is growing. The research demonstrated that previously created capacities for ensuring the quality of life of the population, not related to current GRP per capita, are a key factor. Consequently, the integral index of the quality of life in Russian regions is mainly determined not by current GRP per capita but by regional specificity and long-term regional policies of GRP distribution and ensuring the quality of life. In this regard, it is advisable to identify best practices of leading regions and disseminate them in order to support lagging regions.
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