Monetary Policy in a Data-Rich Environment

37 Pages Posted: 22 Jul 2001 Last revised: 16 Sep 2001

Ben S. Bernanke

Board of Governors of the Federal Reserve System

Jean Boivin

HEC Montreal; Columbia Business School; National Bureau of Economic Research (NBER)

Multiple version iconThere are 2 versions of this paper

Date Written: July 2001

Abstract

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.

Suggested Citation

Bernanke, Ben S. and Boivin, Jean, Monetary Policy in a Data-Rich Environment (July 2001). NBER Working Paper No. w8379. Available at SSRN: https://ssrn.com/abstract=277398

Ben S. Bernanke (Contact Author)

Board of Governors of the Federal Reserve System

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Jean Boivin

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