Analysis of Determinants of Regional Unemployment Rate Using Dynamic Spatial Panel Model

Abstract

Purpose - This study analyzed the determinants of local unemployment rate in Korea using panel data from 16 metropolitan cities and provinces from 2000 to 2018. Design/methodology/approach - We use a dynamic spatial panel model that considers characteristics of the regional unemployment rate such as the common factors effect, spatial dependence, and serial correlations. Findings - The local unemployment rate is affected by the past and present values of the national unemployment rate. And it is significantly affected by the past local unemployment rate and the past neighboring unemployment rate because spatial dependence and serial correlations are clearly present. In addition, when the industrial structure diversity and labor productivity were high, the regional unemployment rate decreased, and when the education level was high, the regional unemployment rate increased. Research implications or Originality - In order to reduce regional unemployment rate, it is necessary to plan and establish regional customized industrial structure policies under the stance of diversification rather than specializing the regional industrial structure and accompany improvement of the quality of education with the number of years of education. In addition, the redistribution of labor from low labor productivity sectors to high labor productivity sectors through technology development will help to reduce the local unemployment rate.