Predicting unemployment rates in Indonesia
The main purpose of this study is to predict the unemployment rate in Indonesia by using time series data from 1986 to 2015 using autoregressive integrated moving average (ARIMA). A differencing process is required due to the actual time series of the unemployment rates in Indonesia is non-stationary. The results show that the best model for forecasting the unemployment rate in Indonesia by using the ARIMA (0,2,1) model. The forecasting results reveal that the unemployment rate in Indonesia tends to decrease continuously. The average of the residuals is close to zero which informs a good result of the forecasting analysis.
Floros, C. (2005). Forecasting the UK unemployment rate: Model comparisons. International Journal of Applied Econometrics and Quantitative Studies, 2(4), 57-72.
Gil-Alana, L.A. (2001). A fractionally integrated exponential model for UK unemployment. Journal of Fore-casting, 20(5), 329-340.
Johnes, G. (1999). Forecasting unemployment. Applied Financial Economics, 6(9), 605-607.
Kurita, T. (2010). A forecasting model for Japan’s unemployment rate. Eurasian Journal of Business and Economics, 3(5), 127-134.
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Economic Journal of Emerging Markets (EJEM)
ISSN 2086-3128 (print), ISSN 2502-180X (online)
Center for Economic Studies, Department of Economics,
Universitas Islam Indonesia, Indonesia.
EJEM by http://journal.uii.ac.id/index.php/JEP/ is licensed under a Creative Commons Attribution 4.0 International License.