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Implications of Cointegration for Forecasting: A Review and an Empirical Analysis

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  • Barakchian , Seyed Mahdi

    (Graduate School of Management and Economics, Sharif University of Technology)

Abstract

Cointegration has different theoretical implications for forecasting. Several empirical studies have compared the out of sample forecasting performance of cointegrated VECMs against unrestricted VARs in levels and in differences. The results of these studies have been generally mixed and inconclusive. This paper provides a comprehensive review over the subject, and also examines the effects of cointegration rank restrictions on forecasting performance of VAR models through conducting an empirical exercise in the framework of a new two-country (Canada-US) model. The results show that a VAR/DVAR model forecasts as well as the best cointegrated VAR model (and even better). Therefore, it seems that using cointegration techniques does not pay a dividend.

Suggested Citation

  • Barakchian , Seyed Mahdi, 2012. "Implications of Cointegration for Forecasting: A Review and an Empirical Analysis," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 7(1), pages 87-118, October.
    • Handle: RePEc:mbr:jmonec:v:7:y:2012:i:1:p:87-118
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    Cited by:

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    More about this item

    Keywords

    Cointegration; Forecasting using VECX; Rank restrictions;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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