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Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence

Katja Heinisch and Rolf Scheufele

German Economic Review, 2019, vol. 20, issue 4, e170-e200

Abstract: In this paper, we investigate whether differences exist among forecasts using real-time or latest-available data to predict gross domestic product (GDP). We employ mixed-frequency models and real-time data to reassess the role of surveys and financial data relative to industrial production and orders in Germany. Although we find evidence that forecast characteristics based on real-time and final data releases differ, we also observe minimal impacts on the relative forecasting performance of indicator models. However, when obtaining the optimal combination of soft and hard data, the use of final release data may understate the role of survey information.

Keywords: Mixed-frequency VAR; real-time data; nowcasting; forecasting (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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Journal Article: Should Forecasters Use Real‐Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence (2019) Downloads
Working Paper: Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? German evidence (2017) Downloads
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DOI: 10.1111/geer.12163

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German Economic Review is currently edited by Peter Egger, Almut Balleer, Jesus Crespo-Cuaresma, Mario Larch, Aderonke Osikominu and Georg Wamser

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