Open Unemployment Rate Modeling In Indonesia Using Spatial Bayes Regression Analysis

Abstrak

Unemployment is defined as people over the age of 15 who are looking for or do not have a job. The imbalance between the number of jobs and the number of labor force leads to the potential for spatial labor mobility between villages and cities. Therefore, data on the open unemployment rate (TPT) in Indonesia may have spatial effects. The spatial regression analysis method is a commonly used method to estimate the parameters of spatial econometrics models. However, this method is not good enough to estimate the model parameters when there are many spatial units. To overcome this problem, an alternative Bayesian method can be used. This study uses the Bayesian method approach to the Spatial Autoregressive (SAR) model applied to modeling the open unemployment rate in Indonesia in 2022. The data used is secondary data obtained from the Indonesian Central Bureau of Statistics (BPS) in 2022. The results that have been obtained show that the variable labor force participation rate is significant to the open unemployment rate in Indonesia with an acceptance rate of 0.55.