A Simple Benchmark for Forecasts of Growth and Inflation
AbstractA theoretical model for growth or inflation should be able to reproduce the empirical features of these variables better than competing alternatives. Therefore, it is common practice in the literature, whenever a new model is suggested, to compare its performance with that of a benchmark model. However, while the theoretical models become more and more sophisticated, the benchmark typically remains a simple linear time series model. Recent examples are provided, e.g., by articles in the real business cycle literature or by new-keynesian studies on inflation persistence. While a time series model can provide a reasonable benchmark to evaluate the value added of economic theory relative to the pure explanatory power of the past behavior of the variable, recent developments in time series analysis suggest that more sophisticated time series models could provide more serious benchmarks for economic models. In this paper we evaluate whether these complicated time series models can really outperform standard linear models for GDP growth and inflation, and should therefore substitute them as benchmarks for economic theory based models. Since a complicated model specification can over-fit in sample, i.e. the model can spuriously perform very well compared to simpler alternatives, we conduct the model comparison based on the out of sample forecasting performance. We consider a large variety of models and evaluation criteria, using real time data and a sophisticated bootstrap algorithm to evaluate the statistical significance of our results. Our main conclusion is that in general linear time series models can be hardly beaten if they are carefully specified, and therefore still provide a good benchmark for theoretical models of growth and inflation. However, we also identify some important cases where the adoption of a more complicated benchmark can alter the conclusions of economic analyses about the driving forces of GDP growth and inflation. Therefore, comparing theoretical models also with more sophisticated time series benchmarks can guarantee more robust conclusions.
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Bibliographic InfoPaper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 6012.
Date of creation: Dec 2006
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Find related papers by JEL classification:
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-01-02 (All new papers)
- NEP-CBA-2007-01-02 (Central Banking)
- NEP-ECM-2007-01-02 (Econometrics)
- NEP-ETS-2007-01-02 (Econometric Time Series)
- NEP-FOR-2007-01-02 (Forecasting)
- NEP-MAC-2007-01-02 (Macroeconomics)
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- Clements, Michael P. & Hendry, David F., 1996.
"Multi-Step Estimation for Forecasting,"
The Warwick Economics Research Paper Series (TWERPS)
447, University of Warwick, Department of Economics.
- Favero, Carlo A & Marcellino, Massimiliano, 2005.
"Modelling and Forecasting Fiscal Variables for the euro Area,"
CEPR Discussion Papers
5294, C.E.P.R. Discussion Papers.
- Carlo A. Favero & Massimiliano Marcellino, 2005. "Modelling and Forecasting Fiscal Variables for the Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 755-783, December.
- Carlo Favero & Massimiliano Marcellino, 2005. "Modelling and Forecasting Fiscal Variables for the Euro Area," Working Papers 298, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Croushore, Dean, 2006. "Forecasting with Real-Time Macroeconomic Data," Handbook of Economic Forecasting, Elsevier.
- Andrew Atkeson & Lee E. Ohanian., 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-11.
- Timothy Cogley & Thomas Sargent, .
"Evolving Post-World War II U.S. Inflation Dynamics,"
2132872, Department of Economics, W. P. Carey School of Business, Arizona State University.
- Timothy Cogley & Thomas J. Sargent, 2002. "Evolving Post-World War II U.S. Inflation Dynamics," NBER Chapters, in: NBER Macroeconomics Annual 2001, Volume 16, pages 331-388 National Bureau of Economic Research, Inc.
- Chong, Yock Y & Hendry, David F, 1986. "Econometric Evaluation of Linear Macro-Economic Models," Review of Economic Studies, Wiley Blackwell, vol. 53(4), pages 671-90, August.
- Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2008.
"Forecasting Macroeconomic Variables Using Diffusion Indexes in Short Samples with Structural Change,"
334, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Banerjee, Anindya & Marcellino, Massimiliano & Masten, Igor, 2008. "Forecasting Macroeconomic Variables Using Diffusion Indexes in Short Samples with Structural Change," CEPR Discussion Papers 6706, C.E.P.R. Discussion Papers.
- Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2008. "Forecasting Macroeconomic Variables Using Diffusion Indexes in Short Samples with Structural Change," Economics Working Papers ECO2008/17, European University Institute.
- Groen, Jan J.J. & Kapetanios, George & Price, Simon, 2009. "A real time evaluation of Bank of England forecasts of inflation and growth," International Journal of Forecasting, Elsevier, vol. 25(1), pages 74-80.
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