Forecasting Unemployment Rate in the Aftermath of the Covid-19 Pandemic: The Turkish Case
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Tarih
2021
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info:eu-repo/semantics/openAccess
Özet
The coronavirus (Covid-19) pandemic caused the loss of lives, global problems, and the collapse of economies. Especially, the high unemployment rates in developing countries at present makes the unemployment rate predictions important. The aim of this study is to estimate the unemployment rate for the future by ARIMA and Artificial Neural Networks (ANN) models for Turkey. The contribution of the study to the literature is to estimate the unemployment rate in Turkey in the aftermath of the Covid-19 by ARIMA and ANN models. In the study, the Box-Jenkins method was used to find the appropriate ARIMA process. Then, the estimated performance of the results obtained up to 2021M8 unemployment rates in Turkey have been compared in the framework of criteria for success. Our results show that ANN was more successful than the ARIMA model in estimating the unemployment variable. It seemed that the unemployment rate estimated by the model is very close to the actual unemployment rate. According to the model results, in the aftermath of Covid-19, the unemployment rate in Turkey will be occurred over 5% of the natural rate of unemployment.
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Cilt
36
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3
