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"I Just Ran Four Million Regressions" for Backcasting Turkish GDP Growth

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  • Mahmut Gunay

Abstract

In this paper we backcast Turkish GDP growth with bridge equations. In the backcasting models, we consider indicators from production, international trade, consumer and firm surveys, employment, inflation and real exchange rate. We use a systematic search process for finding the combination of variables in the bridge equations that make the least backcast error in the period under investigation. We find that using information from different blocks of data in a bridge equation improves backcasting performance. Our results points out to the importance of using timeliness advantage of soft indicators, such as PMI, effectively. Similar to other studies in the literature, average of backcasts of models makes less backcast error than individual models.

Suggested Citation

  • Mahmut Gunay, 2015. ""I Just Ran Four Million Regressions" for Backcasting Turkish GDP Growth," Working Papers 1533, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    • Handle: RePEc:tcb:wpaper:1533
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    File URL: https://www.tcmb.gov.tr/wps/wcm/connect/EN/TCMB+EN/Main+Menu/Publications/Research/Working+Paperss/2015/15-33
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    More about this item

    Keywords

    GDP Forecasting; Bridge Equations; Forecast Combination;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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