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The changing role of expectations in US monetary policy: A new look using the Livingston Survey

Author

Listed:
  • Banerjee, A.
  • Malik, S.
Abstract
Using a Bayesian structural vector autoregression (TVP-SVAR) with time-varying parameters and volatility we investigate monetary policy in the United States, in particular its interaction with the formation of inflation expectations and the linkages between monetary policy, inflation expectations and the behaviour of CPI inflation. We use Livingston Survey data for expected inflation, measured at a bi-annual frequency, actual inflation, unemployment and a nominal interest rate to estimate the VAR and show the significant changes that have occurred in the responses of these variables to monetary policy shocks or to shocks to expected and actual inflation. In so doing, we generalize the analysis undertaken by Leduc, Sill and Stark (2007) to allow for a more nuanced and detailed look at questions such as the impact of different chairmanship regimes at the Federal Reserve Board, the role of good policy versus good luck, and second round inflation effects. While some of the questions asked have a relatively long history, the methods used to undertake our investigations are very new, and the time-varying structure allows us to offer a more detailed picture. In using these methods we also undertake a substantial technical discussion to unearth the appropriateness of the TVP-SVAR models hitherto estimated in the literature, in particular the role of the choice of priors in determining the outcome of the estimations. As we discuss in the paper, this is an important issue which has remained rather hidden in the discussions surrounding the estimation of TVP-SVARs, yet may have a substantially important role to play in determining the results obtained.

Suggested Citation

  • Banerjee, A. & Malik, S., 2012. "The changing role of expectations in US monetary policy: A new look using the Livingston Survey," Working papers 376, Banque de France.
  • Handle: RePEc:bfr:banfra:376
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    References listed on IDEAS

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    1. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    2. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    3. Leduc, Sylvain & Sill, Keith & Stark, Tom, 2007. "Self-fulfilling expectations and the inflation of the 1970s: Evidence from the Livingston Survey," Journal of Monetary Economics, Elsevier, vol. 54(2), pages 433-459, March.
    4. Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 361-393.
    5. N. Gregory Mankiw, 2001. "U.S. Monetary Policy During the 1990s," NBER Working Papers 8471, National Bureau of Economic Research, Inc.
    6. Nakajima, Jouchi & Kasuya, Munehisa & Watanabe, Toshiaki, 2011. "Bayesian analysis of time-varying parameter vector autoregressive model for the Japanese economy and monetary policy," Journal of the Japanese and International Economies, Elsevier, vol. 25(3), pages 225-245, September.
    7. Markus Kirchner & Jacopo Cimadomo & Sebastian Hauptmeier, 2010. "Transmission of Government Spending Shocks in the Euro Area: Time Variation and Driving Forces," Tinbergen Institute Discussion Papers 10-021/2, Tinbergen Institute.
    8. Fabio Canova & Matteo Ciccarelli, 2009. "Estimating Multicountry Var Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(3), pages 929-959, August.
    9. N. G. Shephard & A. C. Harvey, 1990. "On The Probability Of Estimating A Deterministic Component In The Local Level Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 11(4), pages 339-347, July.
    10. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 69-87, January.
    11. Benjamin M. Friedman, 2006. "The Greenspan Era: Discretion, Rather than Rules," American Economic Review, American Economic Association, vol. 96(2), pages 174-177, May.
    12. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models: Comments: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 413-417, October.
    13. Benati, Luca & Mumtaz, Haroon, 2007. "U.S. evolving macroeconomic dynamics: a structural investigation," Working Paper Series 746, European Central Bank.
    14. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    15. Christina D. Romer & David H. Romer, 2004. "Choosing the Federal Reserve Chair: Lessons from History," Journal of Economic Perspectives, American Economic Association, vol. 18(1), pages 129-162, Winter.
    16. Benjamin M. Friedman, 2006. "The Greenspan Era: Discretion, Rather Than Rules," NBER Working Papers 12118, National Bureau of Economic Research, Inc.
    17. Watanabe, Toshiaki, 2000. "Bayesian Analysis of Dynamic Bivariate Mixture Models: Can They Explain the Behavior of Returns and Trading Volume?," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(2), pages 199-210, April.
    18. Ireland, Peter N, 1996. "The Role of Countercyclical Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 104(4), pages 704-723, August.
    19. Jouchi Nakajima, 2011. "Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 29, pages 107-142, November.
    20. J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.
    21. Toshiaki Watanabe, 2004. "A multi-move sampler for estimating non-Gaussian time series models: Comments on Shephard & Pitt (1997)," Biometrika, Biometrika Trust, vol. 91(1), pages 246-248, March.
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    Cited by:

    1. Emmanuel Owusu-Sekyere, 2016. "The impact of monetary policy on household consumption in South Africa. Evidence from Vector Autoregressive Techniques," Working Papers 598, Economic Research Southern Africa.
    2. Chance Ngamanya Mwabutwa & Nicola Viegi & Manoel Bittencourt, 2016. "Evolution Of Monetary Policy Transmission Mechanism In Malawi: A Tvp-Var Approach," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 41(1), pages 33-55, March.

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    More about this item

    Keywords

    monetary policy; expectations; inflation; time variation; VARs; impulse responses.;
    All these keywords.

    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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