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Simple versus optimal rules as guides to policy

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  • Brock, William A.
  • Durlauf, Steven N.
  • Nason, James M.
  • Rondina, Giacomo

Abstract

This paper contributes to the policy evaluation literature by developing new strategies to study alternative policy rules. We compare optimal rules to simple rules within canonical monetary policy models. In our context, an optimal rule represents the solution to an intertemporal optimization problem in which a loss function for the policymaker and an explicit model of the macroeconomy are specified. We define a simple rule to be a summary of the intuition policymakers and economists have about how a central bank should react to aggregate disturbances. The policy rules are evaluated under minimax and minimax regret criteria. These criteria force the policymaker to guard against a worst-case scenario, but in different ways. Minimax makes the worst possible model the benchmark for the policymaker, while minimax regret confronts the policymaker with uncertainty about the true model. Our results indicate that the case for a model-specific optimal rule can break down when uncertainty exists about which of several models is true. Further, we show that the assumption that the policymaker’s loss function is known can obscure policy trade-offs that exist in the short, medium, and long run. Thus, policy evaluation is more difficult once it is recognized that model and preference uncertainty can interact.
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  • Brock, William A. & Durlauf, Steven N. & Nason, James M. & Rondina, Giacomo, 2007. "Simple versus optimal rules as guides to policy," Journal of Monetary Economics, Elsevier, vol. 54(5), pages 1372-1396, July.
  • Handle: RePEc:eee:moneco:v:54:y:2007:i:5:p:1372-1396
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    Cited by:

    1. Giorgio Fagiolo & Andrea Roventini, 2017. "Macroeconomic Policy in DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(1), pages 1-1.
    2. Francesca Rondina, 2010. "Policy evaluation and uncertainty about the effects of oil prices on economic activity," UFAE and IAE Working Papers 855.10, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    3. Christian Matthes & Francesca Rondina, 2012. "Two-sided Learning in New Keynesian Models: Dynamics, (Lack of) Convergence and the Value of Information," UFAE and IAE Working Papers 913.12, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    4. Di Bartolomeo, Giovanni & Di Pietro, Marco & Giannini, Bianca, 2016. "Optimal monetary policy in a New Keynesian model with heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 373-387.
    5. Stephen J. Turnovsky, 2011. "Stabilization Theory and Policy: 50 Years after the Phillips Curve," Economica, London School of Economics and Political Science, vol. 78(309), pages 67-88, January.
    6. Giorgio Fagiolo & Andrea Roventini, 2012. "Macroeconomic Policy in DSGE and Agent-Based Models," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 67-116.
    7. Eric Leeper & James Nason, 2014. "Bringing Financial Stability into Monetary Policy," Caepr Working Papers 2014-003, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
    8. Martin Ellison & Thomas J. Sargent, 2012. "A Defense Of The Fomc," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(4), pages 1047-1065, November.
    9. Rondina, Francesca, 2012. "The role of model uncertainty and learning in the US postwar policy response to oil prices," Journal of Economic Dynamics and Control, Elsevier, vol. 36(7), pages 1009-1041.
    10. repec:cup:macdyn:v:22:y:2018:i:01:p:135-152_00 is not listed on IDEAS
    11. Cohen-Cole, Ethan B. & Durlauf, Steven N. & Rondina, Giacomo, 2012. "Nonlinearities in growth: From evidence to policy," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 42-58.
    12. G. Fagiolo & A. Roventini., 2009. "On the Scientific Status of Economic Policy: A Tale of Alternative Paradigms," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 6.
    13. Yu, Xiangrong, 2013. "Measurement error and policy evaluation in the frequency domain," Journal of Macroeconomics, Elsevier, vol. 38(PB), pages 307-329.
    14. repec:inu:caeprp:2014003 is not listed on IDEAS
    15. Pataracchia, Beatrice, 2011. "The spectral representation of Markov switching ARMA models," Economics Letters, Elsevier, vol. 112(1), pages 11-15, July.
    16. Di Bartolomeo, Giovanni & Di Pietro, Marco, 2018. "Optimal Inflation Targeting Rule Under Positive Hazard Functions For Price Changes," Macroeconomic Dynamics, Cambridge University Press, vol. 22(01), pages 135-152, January.
    17. Carson, Richard T & Murray, Jason H., 2012. "Fisheries Management Implications of Intrinsic Under Identification of Growth Equation Parameters," University of California at San Diego, Economics Working Paper Series qt8bw0b76s, Department of Economics, UC San Diego.
    18. William A. Brock & Steven N. Durlauf & Giacomo Rondina, 2008. "Frequency-Specific Effects of Stabilization Policies," American Economic Review, American Economic Association, vol. 98(2), pages 241-245, May.

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