Analysis of the Phillips Curve for Turkiye: A Comparison of the Johansen Cointegration and Artificial Neural Network Models
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https://doi.org/10.5281/zenodo.14176475摘要
In this study, the validity of the Phillips curve hypothesis is examined using the Johansen cointegration and artificial intelligence methods for the period of 2010-2022 in Türkiye, and the forecasting performance of the Phillips curve of these two models is compared. According to the Johansen cointegration model results a 1% increase in unemployment in the long run leads to a 0.854% decrease in consumer prices. This result supports the Phillips Curve hypothesis for the long run. Beside, the increase in oil prices in the long term was also determined as another factor that increased consumer prices. On the other hand, the error correction model shows that Phillips curve hypothesis is not valid in the short run. The modelling performance of the ANN regression is shown to be better than that of the Johansen modeling. The coefficient of determination values (R2), and other performance metrics namely mean absolute error, root mean square error and the mean absolute percentage error also verify the better forecasting performance of the artificial neural network model. In this context, the findings that can be obtained as a result of artificial intelligence modeling in the management of unemployment are considered to be important.
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