Forecasting Turkish Real GDP Growth in a Data Rich Environment

Bahar Sen Dogan and Murat Midilic

Working Papers from Research and Monetary Policy Department, Central Bank of the Republic of Turkey

Abstract: This study generates nowcasts and forecasts for the growth rate of the Gross Domestic Product (GDP) in Turkey using 204 daily financial series with Mixed Data Sampling (MIDAS) framework over the period 2010Q2-2015Q1. Our findings suggest that MIDAS regression models and forecast combinations provide advantage in exploiting information from daily financial data compared to the models using simple aggregation schemes. In addition, incorporating daily financial data into the analysis improves our forecasts substantially. These results indicate that both the information content of the financial data and the flexible data-driven weighting scheme of MIDAS regressions play an essential role in forecasting the future state of the Turkish economy.

Keywords: Real GDP Growth; Forecasting; MIDAS (search for similar items in EconPapers)
JEL-codes: C22 C53 G10 (search for similar items in EconPapers)
Date: 2016
New Economics Papers: this item is included in nep-ara, nep-cwa and nep-for
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Persistent link: https://EconPapers.repec.org/RePEc:tcb:wpaper:1611

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