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Forecasting the labour force participation rate in Belarus
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DOI：10.1007/s13198-026-03275-z.png)
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Abstract
En 中文
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.
Keywords:
Labour force participation rate
Holt's linear trend
Holt's damped method
ARIMA model
Support vector regression
Time series forecasting
J21
J24
J82
Journal
I
IF:
1.4
Papers:
291
Citations:
3.0K