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Combining forecasts from nested models

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  • Todd E. Clark
  • Michael W. McCracken

Abstract

Motivated by the common finding that linear autoregressive models forecast better than models that incorporate additional information, this paper presents analytical, Monte Carlo, and empirical evidence on the effectiveness of combining forecasts from nested models. In our analytics, the unrestricted model is true, but as the sample size grows, the data generating process converges to the restricted model. This approach captures the practical reality that the predictive content of variables of interest is often low. We derive MSE-minimizing weights for combining the restricted and unrestricted forecasts. Monte Carlo and empirical analyses verify the practical effectiveness of our combination approach.

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Bibliographic Info

Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series Finance and Economics Discussion Series with number 2007-43.

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Date of creation: 2007
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Handle: RePEc:fip:fedgfe:2007-43

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Keywords: Econometric models ; Economic forecasting;

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Citations

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Cited by:
  1. James H. Stock & Mark W. Watson, 2008. "Phillips Curve Inflation Forecasts," NBER Working Papers 14322, National Bureau of Economic Research, Inc.
  2. Todd E. Clark & Michael W. McCracken, 2007. "Averaging forecasts from VARs with uncertain instabilities," Finance and Economics Discussion Series 2007-42, Board of Governors of the Federal Reserve System (U.S.).
  3. Issler, João Victor & Lima, Luiz Renato Regis de Oliveira, 2007. "A Panel Data Approach to Economic Forecasting: The Bias-Corrected Average Forecast," Economics Working Papers (Ensaios Economicos da EPGE) 642, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
  4. Han Hong & Bruce Preston, 2008. "Bayesian Averaging, Prediction and Nonnested Model Selection," NBER Working Papers 14284, National Bureau of Economic Research, Inc.
  5. Andrea Carriero & Raffaella Giacomini, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Post-Print hal-00844809, HAL.
  6. Andrea Carriero & Raffaella Giacomini, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Post-Print peer-00844809, HAL.
  7. Eric Hillebrand & Tae-Hwy Lee, 2012. "Stein-Rule Estimation and Generalized Shrinkage Methods for Forecasting Using Many Predictors," CREATES Research Papers 2012-18, School of Economics and Management, University of Aarhus.
  8. Carriero, Andrea & Giacomini, Raffaella, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Journal of Econometrics, Elsevier, vol. 164(1), pages 21-34, September.
  9. Todd E. Clark & Michael W. McCracken, 2006. "Forecasting of small macroeconomic VARs in the presence of instabilities," Research Working Paper RWP 06-09, Federal Reserve Bank of Kansas City.
  10. Huiyu Huang & Tae-Hwy Lee, 2006. "To Combine Forecasts or to Combine Information?," Working Papers 200806, University of California at Riverside, Department of Economics, revised Feb 2009.

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