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Monetary policy in a data-rich environment

  • Bernanke, Ben S.
  • Boivin, Jean

Most empirical analyses of monetary policy have been confined to frameworks in which the Federal Reserve is implicitly assumed to exploit only a limited amount of information, despite the fact that the Fed actively monitors literally thousands of economic time series. This article explores the feasibility of incorporating richer information sets into the analysis, both positive and normative, of Fed policymaking. We employ a factor-model approach, developed by Stock and Watson (1999a,b), that permits the systematic information in large data sets to be summarized by relatively few estimated factors. With this framework, we reconfirm Stock and Watson's result that the use of large data sets can improve forecast accuracy, and we show that this result does not seem to depend on the use of finally revised (as opposed to 'real-time') data. We estimate policy reaction functions for the Fed that take into account its data-rich environment and provide a test of the hypothesis that Fed actions are explained solely by its forecasts of inflation and real activity. Finally, we explore the possibility of developing an 'expert system' that could aggregate diverse information and provide benchmark policy settings.

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Article provided by Elsevier in its journal Journal of Monetary Economics.

Volume (Year): 50 (2003)
Issue (Month): 3 (April)
Pages: 525-546

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Handle: RePEc:eee:moneco:v:50:y:2003:i:3:p:525-546
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  1. Forni, Mario & Reichlin, Lucrezia, 1996. "Dynamic Common Factors in Large Cross-Sections," Empirical Economics, Springer, vol. 21(1), pages 27-42.
  2. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
  3. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
  4. Sims, Christopher A., 1992. "Interpreting the macroeconomic time series facts : The effects of monetary policy," European Economic Review, Elsevier, vol. 36(5), pages 975-1000, June.
  5. Richard Clarida & Jordi Galí & Mark Gertler, 1997. "The science of monetary policy: A new Keynesian perspective," Economics Working Papers 356, Department of Economics and Business, Universitat Pompeu Fabra, revised Apr 1999.
  6. Clarida, Richard & Galí, Jordi & Gertler, Mark, 1998. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," CEPR Discussion Papers 1908, C.E.P.R. Discussion Papers.
  7. Myles Callan & Eric Ghysels & Norman R. Swanson, 1998. "Monetary Policy Rules with Model and Data Uncertainty," CIRANO Working Papers 98s-40, CIRANO.
  8. Eric M. Leeper & Christopher A. Sims & Tao Zha, 1996. "What Does Monetary Policy Do?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 27(2), pages 1-78.
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  12. Nicoletta Batini & Andrew G Haldane, 1999. "Forward-looking rules for monetary policy," Bank of England working papers 91, Bank of England.
  13. Dean Croushore & Tom Stark, 1999. "A real-time data set for marcoeconomists: does the data vintage matter?," Working Papers 99-21, Federal Reserve Bank of Philadelphia.
  14. Danny Quah & Thomas J. Sargent, 1993. "A Dynamic Index Model for Large Cross Sections," CEP Discussion Papers dp0132, Centre for Economic Performance, LSE.
  15. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
  16. Forni, Mario & Lippi, Marco, 2001. "The Generalized Dynamic Factor Model: Representation Theory," Econometric Theory, Cambridge University Press, vol. 17(06), pages 1113-1141, December.
  17. John B. Taylor, 1999. "Monetary Policy Rules," NBER Books, National Bureau of Economic Research, Inc, number tayl99-1, September.
  18. Thomas J. Sargent & Christopher A. Sims, 1977. "Business cycle modeling without pretending to have too much a priori economic theory," Working Papers 55, Federal Reserve Bank of Minneapolis.
  19. Athanasios Orphanides, 2001. "Monetary Policy Rules Based on Real-Time Data," American Economic Review, American Economic Association, vol. 91(4), pages 964-985, September.
  20. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 1997. "Monetary policy shocks: what have we learned and to what end?," Working Paper Series, Macroeconomic Issues WP-97-18, Federal Reserve Bank of Chicago.
  21. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  22. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
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