Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-23T06:40:34.773Z Has data issue: false hasContentIssue false

USING FORECASTS TO UNCOVER THE LOSS FUNCTION OF FEDERAL OPEN MARKET COMMITTEE MEMBERS

Published online by Cambridge University Press:  06 January 2016

Christian Pierdzioch
Affiliation:
Helmut-Schmidt-University
Jan-Christoph Rülke*
Affiliation:
EBS—Universität für Wirtschaft und Recht
Peter Tillmann
Affiliation:
Justus-Liebig-University Giessen
*
Address correspondence to: Jan-Christophe Rülke, Department of Management and Economics, EBS—Business School, Rheingaustrasse 1, D-65375 Oestrich-Winkel, Germany; e-mail: [email protected].

Abstract

We revisit the sources of the bias in Federal Reserve forecasts and assess whether a precautionary motive can explain the forecast bias. In contrast to the existing literature, we use forecasts submitted by individual Federal Open Market Committee (FOMC) members to uncover members' implicit loss function. Our key finding is that the loss function of FOMC members is asymmetric: FOMC members incur a higher loss when they underpredict (overpredict) inflation and unemployment (nominal and real growth) as compared to their making an overprediction (underprediction) of similar size. We also find that an asymmetric loss function, in some cases, weakens evidence against forecast rationality, though results depend on the variable being projected and the subgroup of FOMC members being studied. Furthermore, we add to the recent controversy on the relative quality of FOMC forecasts compared to staff forecasts. Our results suggest that differences in predictive ability could indeed stem from differences in preferences.

Type
Articles
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Banternghansa, Chanont and McCracken, Michael W. (2009) Forecast Disagreement among FOMC Members. Working paper 2009-059A, Federal Reserve Bank of St. Louis.CrossRefGoogle Scholar
Belden, Susan (1989) Policy preferences of FOMC members as revealed by dissenting votes. Journal of Money, Credit and Banking 21, 432441.Google Scholar
Besley, Timothy, Meade, Neil, and Surico, Paolo (2008) Insiders versus outsiders in monetary policymaking. American Economic Review: Papers and Proceedings 98, 218223.CrossRefGoogle Scholar
Bhattacharjee, Arnab and Gelain, Paolo (2011) Monetary Policy under Model Uncertainty: A Bayesian Analysis of FOMC Forecasts. Working paper, University of Dundee.Google Scholar
Blinder, Alan S. (2009) Making monetary policy by committee. International Finance 12, 171194.CrossRefGoogle Scholar
Branch, William A. (2013) Nowcasting and the Taylor Rule. Working paper, University of California, Irvine.Google Scholar
Capistrán, Carlos (2008) Bias in Federal Reserve inflation forecasts: Is the Federal Reserve irrational or just cautious? Journal of Monetary Economics 55, 14151427.Google Scholar
Caunedo, Julieta, DiCecio, Riccardo, Komunjer, Ivana, and Owyang, Michael T. (2013) Federal Reserve Forecasts: Asymmetry and State-Dependence. Working paper 2013-012A, Federal Reserve Bank of St. Louis.Google Scholar
Chappell, Henry W., McGregor, Rob R., and Vermilyea, Todd (2005) Committee Decisions in Monetary Policy: Evidence from Historical Records of the Federal Open Market Committee. Cambridge, MA: MIT Press.Google Scholar
Elliott, Graham, Komunjer, Ivana, and Timmermann, Alan (2005) Estimation and testing of forecast rationality under flexible loss. Review of Economic Studies 72, 11071125.Google Scholar
Ellison, Martin and Sargent, Thomas (2012) A defence of the FOMC. International Economic Review 53, 10471065.Google Scholar
Gavin, William T. (2003) FOMC forecasts: Is all the information in the central tendency? Federal Reserve Bank of St. Louis Review May/June 2003, 27–46.Google Scholar
Gavin, William T. and Mandal, Rachel J. (2003) Evaluating FOMC forecasts. International Journal of Forecasting 19, 655667.Google Scholar
Gavin, William T. and Pande, Geetanjali (2008) FOMC consensus forecasts. Federal Reserve Bank of St. Louis Review May/June 2008, 149–163.Google Scholar
Gerlach-Kristen, Petra (2008) The role of the chairman in setting monetary policy: Individualistic vs. autocratically collegial MPCs. International Journal of Central Banking 4, 119143.Google Scholar
Gerlach-Kristen, Petra (2009) Outsiders at the Bank of England's MPC. Journal of Money, Credit and Banking 41, 10991115.Google Scholar
Hansen, Stephen, McMahon, Michael, and Rivera, Carlos Velasco (2012) How Experts Decide: Preferences or Private Assessments on a Monetary Policy Committee? Working paper, Universitat Pompeu Fabra.Google Scholar
Havrilesky, Thomas, and Gildea, John A. (1991) The policy preferences of FOMC members as revealed by dissenting votes–-A comment. Journal of Money, Credit and Banking 23, 130138.Google Scholar
Kilian, Lutz and Manganelli, Simone (2008) The central banker as a risk manager: Estimating the Federal Reserve's preferences under Greenspan. Journal of Money, Credit and Banking 40, 11031129.Google Scholar
McCracken, Michael W. (2010) Using FOMC Forecasts to Forecast the Economy. Economic synopses, no. 5, Federal Reserve Bank of St. Louis.CrossRefGoogle Scholar
Meade, Ellen E. (2005) The FOMC: Preferences, voting, and consensus. Federal Reserve Bank of St. Louis Review 87, 93101.Google Scholar
Meade, Ellen E. and Thornton, Daniel L. (2012) The Phillips curve and US monetary policy: What the FOMC transcripts tell us. Oxford Economic Papers 64, 197216.Google Scholar
Nobay, A. Robert and Peel, David (2003) Optimal discretionary monetary policy in a model of asymmetric central bank preferences. Economic Journal 113, 657665.Google Scholar
Orphanides, Athanasios and Wieland, Volker (2008) Economic projections and rules of thumb for monetary policy. Federal Reserve Bank of St. Louis Review, 307–324.Google Scholar
Patton, Andrew J. and Timmermann, Allan (2007) Testing forecast optimality under unknown loss. Journal of the American Statistical Association 102, 11721184.Google Scholar
Pierdzioch, Christian, Rülke, Jan-Christoph, and Stadtmann, Georg (2012) On the loss function of the Bank of Canada: A note. Economics Letters 115, 155159.Google Scholar
R Development Core Team (2012) R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing. Available at http://www.R-project.org.Google Scholar
Riboni, Alessandro and Ruge-Murcia, Francisco J. (2008) Preference heterogeneity in monetary policy committees. International Journal of Central Banking 4, 213233.Google Scholar
Romer, Christina and Romer, David H. (2008) The FOMC versus the staff: Where can monetary policymakers add value? American Economic Review: Papers and Proceedings 98, 230235.Google Scholar
Romer, David H. (2010) A new data set on monetary policy: The economic forecasts of individual members of the FOMC. Journal of Money, Credit and Banking 42, 951957.Google Scholar
Ruge-Murcia, Francisco J. (2003) Inflation targeting under asymmetric preferences. Journal of Money, Credit and Banking 35, 763785.Google Scholar
Rülke, Jan-Christoph and Tillmann, Peter (2011) Do FOMC members herd? Economics Letters 113, 176179.Google Scholar
Surico, Paolo (2007) The Fed's monetary policy rule and U.S. inflation: The case of asymmetric preferences. Journal of Economic Dynamics and Control 31, 305324.Google Scholar
Tillmann, Peter (2010a) Do FOMC members believe in Okun's Law? Economics Bulletin 30, 23982404.Google Scholar
Tillmann, Peter (2010b) The Fed's perceived Phillips curve: Evidence from individual FOMC forecasts. Journal of Macroeconomics 32, 10081013.Google Scholar
Tillmann, Peter (2011a) Strategic forecasting on the FOMC. European Journal of Political Economy 27, 547553.Google Scholar
Tillmann, Peter (2011b) Parameter uncertainty and non-linear monetary policy rules. Macroeconomics Dynamics 15, 184200.Google Scholar
Wang, Yiyao and Lee, Tae-Hwy (2014) Asymmetric loss in the Greenbook and the Survey of Professional Forecasters. International Journal of Forecasting 30 (2), 235245.Google Scholar
Wieland, Volker and Wolters, Maik H. (2013) Forecasting and policy making. In Elliott, G. and Timmermann, A. (eds.), Handbook of Economic Forecasting, vol. 2, pp. 239325. Amsterdam: Elsevier.Google Scholar
Zhang, Wenlang and Semmler, Willi (2005) Monetary policy rules under uncertainty: Empirical evidence, adaptive learning and robust control. Macroeconomic Dynamics 9 (5), 651681.Google Scholar