Within-group estimators for unbalanced-panel data regression model of the open unemployment rate data in east kalimantan province
Penulis/Author
DESI YUNIARTI (1); Prof. Dr.rer.nat. Dedi Rosadi, S.Si.,, M.Sc. (2); Prof. Dr. Abdurakhman, S.Si., M.Si. (3)
Tanggal/Date
23 2023
Kata Kunci/Keyword
Abstrak/Abstract
The COVID-19 pandemic has hit hard the In-
donesian economy. Many businesses had to close because they
could not cover operational costs, and many workers were
laid off creating an unemployment crisis. Unemployment causes
people’s productivity and income to decrease, leading to poverty
and other social problems, making it a crucial problem and
great concern for the nation. Economic conditions during this
pandemic have also provided an unusual pattern in economic
data, in which outliers may occur, leading to biased parameter
estimation results. For that reason, it is necessary to deal
with outliers in research data appropriately. This study aims
to find within-group estimators for unbalanced panel data
regression model of the Open Unemployment Rate (OUR) in
East Kalimantan Province and the factors that influence it. The
method used is the within transformation with mean centering
and median centering processing methods. The results of this
study may provide advice on factors that can increase and
decrease the OUR of East Kalimantan Province. The results
show that the best model for estimating OUR data in East
Kalimantan Province is the within-transformation estimation
method using median centering. According to the best model,
the Human Development Index (HDI) and Gross Regional
Domestic Product (GRDP) are two factors that influence the
OUR of East Kalimantan Province (GRDP)
