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Accepted Paper:

Using Machine Learning and Econometric Methods to Forecast Kyrgyz Republic' Labor Market.  
Saltanat Biibosunova (Arabaev Kyrgyz State University) Kalybek Choroev (Kyrgyz State University named after I. Arabaev)

Paper short abstract:

Co-author: Kalybek Choroev bbolotbek@mail.ru

Paper abstract:

The paper focuses on the process of building a socio-economic system in Kyrgyzstan based on the principles of a modern market economy. The study highlights the deep crisis phenomena that have acquired a systemic character in the country's economy, leading to significant social stratification and poverty. To address these issues, theauthors accomplish economic-mathematical and econometric analysis using new information technologies and methods of machine learning to analyze and forecast the labor market of Kyrgyzstan.

The research uses mathematical models and methods to study the modern labor market of Kyrgyzstan, including its conjuncture, dynamics, and main characteristics. The study proposes mathematical models for labor market analysis that take into account the gender component and sectoral asymmetry in the Kyrgyz Republic’ economy. Additionally, new balance models have been developed to study labor resources, employment, and unemployment, taking into account external and internal labor migration, as well as balance models for the female segment of the labor market.

The paper also examines the features of employment and sectoral segregation, as well as the main factors determining the growth of the level of unemployment, including female unemployment. The study uses machine learning and regression and factor analysis methods to explore the influence of macroeconomic factors on the level of employment and unemployment, constructing probabilistic predictive models for analysis and estimates and forecasts of employment and unemployment, including the gender component.

In conclusion, the research provides a systematic approach based on mathematical modeling, econometric forecasting methods, and new information technologies and methods of machine learning for the analysis and forecast of the labor market of Kyrgyzstan. The study's findings could be of great theoretical and scientific and practical importance to policymakers and stakeholders seeking to develop and implement strategies to improve the country's socio-economic system and labor market.

Panel ECON03
Political Economy of Poverty and Labor Market in Kyrgyzstan
  Session 1 Sunday 22 October, 2023, -