Abstract
This article provides a quantitative assessment of long-term socio-economic dynamics in an emerging economy, using the Republic of Kazakhstan as a case study. The empirical basis is a multidimensional annual vector series of macroeconomic and social indicators for 2001–2024, constructed from official data of the Bureau of National Statistics. The analysis covers demographic indicators, healthcare infrastructure, labor market and income characteristics, pension provision, real sector and trade indicators, as well as government finance and external sector parameters. Using classical time-series and index- number methods, we compute absolute and relative changes, growth rates and increment coefficients, construct linear trend models, and evaluate interrelationships among indicators. To aggregate the multidimensional data, a block-structured system of composite indices is proposed, based on weighted geometric means of normalized indicator levels. The results reveal sustained growth in population size and life expectancy, a marked decline in total, infant, and maternal mortality, a substantial increase in average and minimum pensions, and structural changes in the healthcare and pension systems. The block-level composite indices provide a compact representation of the coordinated dynamics of key socio-economic parameters and can be used for monitoring and medium-term forecasting of Kazakhstan’s development.