Forecasting unemployment and employment: A system dynamics approach

Abstract

Unemployment is an important factor in forecasting successful employment in the future. This study establishes the unemployment stock-flow model using a system dynamics (SD) approach to forecast unemployment and employment rates with the exogenous parameters of GDP growth rate, inflation rate, and the number of vacant jobs. The unemployment SD model matches the trend of unemployment and employment populations from 1990 to 2020 in South Korea and predicts unemployment and employment from 2021 to 2030. We use the SD model to examine how key variables: re-employment, layoff and job quit rates, affect the sensitivity of unemployment under several policy scenarios. Our results show that increasing reemployment and decreasing voluntary unemployment can lower the unemployment rate and increase the employment rate more effectively than policies that increase newly created jobs.