预测者应该使用实时数据来评估GDP预测的领先指标模型吗?德国的证据

IF 1.2 4区经济学 Q3 ECONOMICS

German Economic Review Pub Date : 2019-11-01 DOI:10.1111/geer.12163

Katja Heinisch, Rolf Scheufele

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引用次数: 13

摘要

摘要本文研究了实时数据和最新数据在预测国内生产总值(GDP)时是否存在差异。我们采用混合频率模型和实时数据来重新评估与德国工业生产和订单相关的调查和财务数据的作用。虽然我们发现了基于实时和最终数据发布的预测特征不同的证据，但我们也观察到指标模型对相对预测性能的影响很小。然而，在获得软硬数据的最佳组合时，使用最终发布的数据可能会低估调查信息的作用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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.

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来源期刊

German Economic Review ECONOMICS-

CiteScore

2.30

自引率

9.10%

发文量

期刊介绍： German Economic Review, the official publication of the German Economic Association (Verein für Socialpolitik), is an international journal publishing original and rigorous research of general interest in a broad range of economic disciplines, including: - macro- and microeconomics - economic policy - international economics - public economics - finance - business administration The scope of research approaches includes theoretical, empirical and experimental work. Innovative and thought-provoking contributions, in particular from younger authors, are especially welcome.