Panel Data Regression Model on Determinant Factors of Open Unemployment Rate in West Java Post-Covid-19
DOI:
https://doi.org/10.59141/jiss.v6i8.1803Keywords:
Economic Growth, Minimum Wage, Open Unemployment Rate, Panel Data Regression, Post-COVID-19 Labor Market.Abstract
The COVID-19 pandemic significantly impacted West Java's economy, leading to a drastic rise in the open unemployment rate (TPT), which reached 6.75% by 2024. The aim of this study is to provide an overview of the determining factors influencing the open unemployment rate in West Java Province after COVID-19 using a panel data regression model. The sample consists of 27 regencies/cities in West Java Province. The independent variables in this study are Minimum Wage, Labor Force Participation Rate, Economic Growth, and Infrastructure, while the dependent variable is the open unemployment rate. The method used is quantitative, with analysis conducted through panel data regression analysis. The research data was obtained from documents provided by Statistics Indonesia (BPS). The results of the study using the Fixed Effect Model approach indicate that factors such as Minimum Wage, Labor Force Participation Rate, and Gross Regional Domestic Product significantly affect the open unemployment rate, whereas Infrastructure does not have a significant effect. Therefore, to control the open unemployment rate in West Java, the government can regulate minimum wage policies, promote economic growth, and implement training programs to increase labor force participation.
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