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An Estimation of Seasonal GDP Gap in Iran: Application of Adaptive Least Squares Method

Author

Listed:
  • Arash Hadizadeh

    (Ph.D. student of economics at The University of Mazandaran, Babolsar, Iran.)

  • Ahmad Jafari Samimi

    (Professor of economics .The University of Mazandaran, Babolsar, Iran.)

  • Zahra Mila Elmi

    (Associate professor of economics The University of Mazandaran, Babolsar ,Iran)

Abstract

This paper estimates the long-term trend of seasonal real GDP in Iran, using a new econometric technique called Adaptive Least Squares (ALS). ALS is a special case of Kalman Filter that allows a time-varying parameter model to be estimated relatively easy. The estimated trend is used to proxy the output gap. Since the coefficients of the GDP lags are significantly different from zero, the model with intercept and trend and with three lags of the dependent variable has been tested in this article. The comparison of the results of ALS, OLS, HP and Kalman Filter show that the ALS method provides a better estimate. Therefore, it is suggested that the output gap estimation method provided in this paper be used in dealing with the monetary policies.

Suggested Citation

  • Arash Hadizadeh & Ahmad Jafari Samimi & Zahra Mila Elmi, 2013. "An Estimation of Seasonal GDP Gap in Iran: Application of Adaptive Least Squares Method," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 18(1), pages 157-177, winter.
    • Handle: RePEc:eut:journl:v:18:y:2013:i:1:p:157
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    References listed on IDEAS

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    5. Mark Gertler & Jordi Gali & Richard Clarida, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," Journal of Economic Literature, American Economic Association, vol. 37(4), pages 1661-1707, December.
    6. Cogley, Timothy & Nason, James M., 1995. "Effects of the Hodrick-Prescott filter on trend and difference stationary time series Implications for business cycle research," Journal of Economic Dynamics and Control, Elsevier, vol. 19(1-2), pages 253-278.
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