MIGRATION PROCESSES IN KYRGYZSTAN AND THEIR MATHEMATICAL FORECASTING

Abstract

The article analyzes migration processes in Kyrgyzstan as a factor of socio-economic development. Particular attention is paid to the study of the dual nature of external labor migration's impact on macroeconomic and social indicators. On the one hand, remittances (migrants' money transfers) act as a powerful tool for reducing poverty and stimulating domestic consumer demand. On the other hand, this process provokes a large-scale outflow of qualified personnel, exacerbates demographic imbalance, and reinforces regional disparities in territorial development. Therefore, forecasting in various fields of science and technology is a highly relevant issue. Using an econometric model, it is possible to analyze and forecast based on statistical data. Brown's double exponential smoothing method is quite frequently applied to forecast migration flows, population size factoring in migration, and related indicators (e.g., remittance volume), especially when the data represents time series with a linear trend and random fluctuations, but without a pronounced seasonality. It yields good results for short- and medium-term migration forecasts when complex models of system dynamics or agent-based modeling are redundant or when data is scarce.