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<p>This study aims to forecast the labour force participation rate in Belarus from 2024 to 2028 using various time series models. The study explores historical trends using data from the International Labour Organization, which spans from 1993 to 2023. It applies Holt’s linear trend method, Holt’s damped method, support vector regression and the ARIMA (Auto-regressive Integrated Moving Average) model for short-term and long-term forecasting. The analysis indicates that although Holt’s methods display better forecast precision, the ARIMA model offers the best fit. The forecast suggests a slight decline in the labour force participation rate over the next few years, with minor variations among the models. These findings can assist policymakers in comprehending and addressing future labour market dynamics in Belarus.</p>

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Forecasting the labour force participation rate in Belarus

  • 期刊论文

  • 发表日期：

    2026年4月2日

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  • Manya Gupta,
  • Kavita Gupta

摘要

This study aims to forecast the labour force participation rate in Belarus from 2024 to 2028 using various time series models. The study explores historical trends using data from the International Labour Organization, which spans from 1993 to 2023. It applies Holt’s linear trend method, Holt’s damped method, support vector regression and the ARIMA (Auto-regressive Integrated Moving Average) model for short-term and long-term forecasting. The analysis indicates that although Holt’s methods display better forecast precision, the ARIMA model offers the best fit. The forecast suggests a slight decline in the labour force participation rate over the next few years, with minor variations among the models. These findings can assist policymakers in comprehending and addressing future labour market dynamics in Belarus.