Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-30T15:40:59.795Z Has data issue: false hasContentIssue false

PRECAUTIONARY LEARNING AND INFLATIONARY BIASES

Published online by Cambridge University Press:  14 November 2018

Chetan Dave*
Affiliation:
University of Alberta
James Feigenbaum
Affiliation:
Utah State University
*
Address correspondence to: Chetan Dave, Department of Economics, University of Alberta, 8-14 HM Tory Building, Edmonton, Alberta, Canada T6G 2H4. e-mail: [email protected].

Abstract

In a canonical monetary policy model in which the central bank learns about underlying fundamentals by estimating the parameters of a Phillips curve, we show that the bank’s loss function is asymmetric such that parameter overestimates may be more or less costly than underestimates, creating a precautionary motive in estimation. This motive suggests the use of a more efficient variance-adjusted least-squares estimator for learning about fundamentals. Informed by this “precautionary learning” the central bank sets low inflation targets, and the economy can settle near a Ramsey equilibrium.

Type
Articles
Copyright
© Cambridge University Press 2018

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.)

Footnotes

We thank Jess Benhabib, John Duffy, John Leahy, Tom Sargent, and colleagues and seminar participants at New York University (Abu Dhabi), the Southern Economics Association Conference, Society for Nonlinear Dynamics and Econometrics Conference, the Federal Reserve Banks of Dallas and Richmond, and the Computational Economics and Finance Conference for insightful comments and support. The usual disclaimer applies.

References

Barro, R. J. and Gordon, D. B. (1983) Rules, discretion and reputation in a model of monetary policy. Journal of Monetary Economics 12, 101121.CrossRefGoogle Scholar
Benhabib, J. and Dave, C. (2014) Learning, large deviations and rare events. Review of Economic Dynamics 17, 367382.CrossRefGoogle Scholar
Berger, J. O. (1985) Statistical Decision Theory and Bayesian Analysis, 2nd ed. New York: Springer.CrossRefGoogle Scholar
Brainard, W. C. (1967) Uncertainty and the effectiveness of policy. American Economic Review 57, 411425.Google Scholar
Bullard, J. (2006) The learnability criterion and monetary policy. Federal Reserve Bank of St. Louis Review 88, 203217.Google Scholar
Carceles-Poveda, E. and Giannitsarou, C. (2008) Asset pricing with adaptive learning. Review of Economic Dynamics 11, 629651.CrossRefGoogle Scholar
Carrillo, J. D. and Mariotti, T. (2000) Strategic ignorance as a self-disciplining device. The Review of Economic Studies 67, 529544.CrossRefGoogle Scholar
Cho, I.-K. and Kasa, K. (2015) Learning and model validation. Review of Economic Studies 82, 4582.CrossRefGoogle Scholar
Cho, I.-K., Sargent, T. J. and Williams, N. (2002) Escaping Nash inflation. The Review of Economic Studies 69, 140.CrossRefGoogle Scholar
Cone, T. E. and Shea, P. (2017) Learning, hedging, and the natural rate hypothesis. Macroeconomic Dynamics, 126. doi: http://dx.doi.org/10.1017/S1365100517000578.Google Scholar
Cukierman, A. (2002) Are contemporary central banks transparent about economic models and objectives and what difference does it make? Federal Reserve Bank of St. Louis Review 84, 1535.Google Scholar
Evans, G. W. and Honkapohja, S. (1999) Learning dynamics. In: Taylor, J. B. and Woodford, M. (eds.), Handbook of Macroeconomics, pp. 449-452. Amsterdam: Elsevier.CrossRefGoogle Scholar
Evans, G. W. and Honkapohja, S. (2001) Learning and Expectations in Macroeconomics. Princeton: Princeton University Press.CrossRefGoogle Scholar
Evans, G. W. and Honkapohja, S. (2003) Adaptive learning and monetary policy design. Journal of Money, Credit and Banking 35, 10451072.CrossRefGoogle Scholar
Evans, G. W., Honkapohja, S. and Mitra, K. (2009) Anticipated fiscal policy and adaptive learning. Journal of Monetary Economics 56, 930953.CrossRefGoogle Scholar
Evans, G. W., Honkapohja, S. and Williams, N. (2010) Generalized stochastic gradient learning. International Economic Review 51, 237262.CrossRefGoogle Scholar
Kolyuzhnov, D., Bogomolova, A. and Slobodyan, S. (2014) Escape dynamics: A continuous-time approximation. Journal of Economic Dynamics and Control 38, 161183.CrossRefGoogle Scholar
Kydland, F. and Prescott, E. C. (1977) Rules rather than discretion: The inconsistency of optimal plans. Journal of Political Economy 85, 473491.CrossRefGoogle Scholar
Leland, H. E. (1968) Saving and uncertainty: The precautionary demand for saving. The Quarterly Journal of Economics 82, 465473.CrossRefGoogle Scholar
McGough, B. (2006) Shocking escapes. Economic Journal 116, 507528.CrossRefGoogle Scholar
Mitra, K., Evans, G. W. and Honkapohja, S. (2017) Fiscal policy multipliers in an RBC model with learning. Macroeconomic Dynamics, 144. doi: http://dx.doi.org/10.1017/S1365100516001176.Google Scholar
Ruge-Murcia, F. J. (2003) Inflation targeting under asymmetric preferences. Journal of Money, Credit and Banking 35, 763785.CrossRefGoogle Scholar
Sandmo, A. (1970) The effect of uncertainty on saving decisions. Review of Economic Studies 37, 353360.CrossRefGoogle Scholar
Sargent, T. J. (1999) The Conquest of American Inflation. Princeton: Princeton University Press.CrossRefGoogle Scholar
Sargent, T. J. and Wallace, N. (1973) The stability of models of money and growth with perfect foresight. Econometrica 41, 10431048.CrossRefGoogle Scholar
Sargent, T. J. and Williams, N. (2005) Impacts of priors on convergence and escapes from Nash inflation. Review of Economic Dynamics 8, 360391.CrossRefGoogle Scholar
Sinclair-Desgagne, B. and Spaeter, S. (2011) The Prudent Principal. SSRN Working Paper: No. 1953548.CrossRefGoogle Scholar
Sims, C. A. (1988) Projecting policy effects with statistical models. Revista de Analisis Economico 3, 320.Google Scholar
Slobodyan, S., Bogomolova, A. and Kolyuzhnov, D. (2016) Stochastic gradient learning and instability: An example. Macroeconomic Dynamics 20, 777790.CrossRefGoogle Scholar
Tetlow, R. and von zur Muehlen, P. (2004) Avoiding Nash inflation: Bayesian and robust responses to model uncertainty. Review of Economic Dynamics 7, 869899.CrossRefGoogle Scholar
Varian, H. R. (1975) A Bayesian approach to real estate assessment. In: Fienberg, S. E. and Zellner, A. (eds.), Studies in Bayesian Econometrics and Statistics in Honor of Leonard J. Savage. Amsterdam: North-Holland.Google Scholar
Zellner, A. (1986) Bayesian estimation and prediction using asymmetric loss functions. Journal of the American Statistical Association 81, 446451.CrossRefGoogle Scholar
Supplementary material: PDF

Dave and Feigenbaum supplementary material

Online Appendix

Download Dave and Feigenbaum supplementary material(PDF)
PDF 317.3 KB