Comparing the Performance of ARIMA and MS-AR Models to Forecast Business Cycles in Iran

Subject Areas : Labor and Demographic Economics

Mehdi Fazel ¹ , Akbar Tavakoli ² , Mostafa Rajabi ³

1 - کارشناس ارشد توسعه اقتصادی و برنامه ریزی
2 - دانشیار اقتصاد دانشگاه صنعتی اصفهان
3 - استادیار دانشگاه آزاد اسلامی واحد خمینی شهر

Received: 2015-04-12 Accepted : 2015-04-12 Published : 2013-04-01

Keywords: E32, C24, E37,

Abstract :

It is clear that business cycles are inevitable in economy. On the other hand, the economists are always looking for how to form business cycles and so under the effect of economic policies, since the economic situation is depended to these policies. Therefore, the access to more precise business cycles forecasting methods would direct and manage the economic situation and policies powerfully. Hence, the main objective of this study is to construct a new model based on Markov-Switching Autoregressive (MS-AR) model to forecast the business cycles in Iran. In addition, the model constructed is compared to ARIMA to represent its power. GDP data seasonally covers the period 1989: I – 2009: IV collected from Central Bank of Iran. MS-AR and ARIMA models are applied to forecast the behavior of business cycles. By using MAPE, RMSE and Theil criteria (TIC), the results indicate that MS-AR model will work better than ARIMA to forecast GDP business cycles.

References:

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