Are There Any Reliable Leading Indicators for U.S. Inflation and GDP Growth?

Anindya Banerjee and Massimiliano Marcellino

No 236, Working Papers from IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University

Abstract: In this paper we evaluate the relative merits of three approaches to information extraction from a large data set for forecasting, namely, the use of an automated model selection procedure, the adoption of a factor model, and single-indicator-based forecast pooling. The comparison is conducted using a large set of indicators for forecasting US inflation and GDP growth. We also compare our large set of leading indicators with purely autoregressive models, using an evaluation procedure that is particularly relevant for policy making. The evaluation is conducted both ex-post and in a pseudo real time context, for several forecast horizons, and using both recursive and rolling estimation. The results indicate a preference for simple forecasting tools, with a good relative performance of pure autoregressive models, and substantial instability in the leading characteristics of the indicators.

Date: 2003
New Economics Papers: this item is included in nep-cba, nep-mac and nep-mon
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Related works:
Journal Article: Are there any reliable leading indicators for US inflation and GDP growth? (2006)
Working Paper: Are There Any Reliable Leading Indicators for US Inflation and GDP Growth? (2002)
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