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A common model approach to macroeconomics: using panel data to reduce sampling error

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  • William T. Gavin

    (Federal Reserve Bank of St. Louis, USA)

  • Athena T. Theodorou

    (Federal Reserve Bank of St. Louis, USA)

Abstract

Is there a common model inherent in macroeconomic data? Macroeconomic theory suggests that market economies of various nations should share many similar dynamic patterns; as a result, individual country empirical models, for a wide variety of countries, often include the same variables. Yet, empirical studies often find important roles for idiosyncratic shocks in the differing macroeconomic performance of countries. We use forecasting criteria to examine the macrodynamic behaviour of 15 OECD countries in terms of a small set of familiar, widely used core economic variables, omitting country-specific shocks. We find this small set of variables and a simple VAR 'common model' strongly support the hypothesis that many industrialized nations have similar macroeconomic dynamics. Copyright © 2005 John Wiley & Sons, Ltd.

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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 24 (2005)
Issue (Month): 3 ()
Pages: 203-219

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Handle: RePEc:jof:jforec:v:24:y:2005:i:3:p:203-219

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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  1. James H. Stock & Mark W. Watson, 2001. "Forecasting Output and Inflation: The Role of Asset Prices," NBER Working Papers 8180, National Bureau of Economic Research, Inc.
  2. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1986. "Forecasting and conditional projection using realistic prior distribution," Staff Report 93, Federal Reserve Bank of Minneapolis.
  3. Fabio Canova & Matteo Ciccarelli, 2000. "Forecasting And Turning Point Predictions In A Bayesian Panel Var Model," Working Papers. Serie AD 2000-05, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  4. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  5. Canova, Fabio, 2002. "G-7 Inflation forecasts," Working Paper Series 0151, European Central Bank.
  6. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 1998. "Monetary Policy Shocks: What Have We Learned and to What End?," NBER Working Papers 6400, National Bureau of Economic Research, Inc.
  7. Fiorito, Riccardo & Kollintzas, Tryphon, 1992. "Stylized Facts of Business Cycles in the G7 from a Real Business Cycles Perspective," CEPR Discussion Papers 681, C.E.P.R. Discussion Papers.
  8. David K. Backus & Patrick J. Kehoe, 1991. "International evidence on the historical properties of business cycles," Staff Report 145, Federal Reserve Bank of Minneapolis.
  9. Michael D. Bordo & John Landon Lane & Angela Redish, 2004. "Good versus Bad Deflation: Lessons from the Gold Standard Era," NBER Working Papers 10329, National Bureau of Economic Research, Inc.
  10. Thursby, Jerry G., 1987. "OLS or GLS in the presence of specification error? : An expected loss approach," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 359-374, July.
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Cited by:
  1. Nikolay Hristov & Oliver Hülsewig & Timo Wollmershäuser, 2011. "Loan Supply Shocks during the Financial Crisis: Evidence for the Euro Area," CESifo Working Paper Series 3395, CESifo Group Munich.
  2. Leonardo Gambacorta & Boris Hofmann & Gert Peersman, 2012. "The Effectiveness of Unconventional Monetary Policy at the Zero Lower Bound: A Cross-Country Analysis," BIS Working Papers 384, Bank for International Settlements.
  3. Gert Peersman, 2012. "Effectiveness of Unconventional Monetary Policy at the Zero Lower Bound," 2012 Meeting Papers 400, Society for Economic Dynamics.
  4. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
  5. William T. Gavin & David M. Kemme, 2007. "Using extraneous information to analyze monetary policy in transition economies," Working Papers 2004-034, Federal Reserve Bank of St. Louis.
  6. Tuomas A. Peltonen & Ricardo M. Sousa & Isabel S. Vansteenkiste, 2009. "Fundamentals, Financial Factors and The Dynamics of Investment in Emerging Markets," NIPE Working Papers 19/2009, NIPE - Universidade do Minho.
  7. Galvao Jr., Antonio F., 2011. "Quantile regression for dynamic panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 164(1), pages 142-157, September.
  8. Luca Agnello & Ricardo M. Sousa, 2013. "Fiscal Policy And Asset Prices," Bulletin of Economic Research, Wiley Blackwell, vol. 65(2), pages 154-177, 04.

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