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Do Estimated Taylor Rules Suffer from Weak Identification?

Author

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  • Christian Murray

    () (University of Houston)

  • Juan Urquiza

    () (Pontificia Universidad Católica de Chile)

Abstract

Over the last decade, applied researchers have estimated forward looking Taylor rules with interest rate smoothing via Nonlinear Least Squares. A common empirical finding for post-Volcker samples, based on asymptotic theory, is that the Federal Reserve adheres to the Taylor Principle. We explore the possibility of weak identification and spurious inference in estimated Taylor rule regressions with interest rate smoothing. We argue that the presence of smoothing subjects the parameters of interest to the Zero Information Limit Condition analyzed by Nelson and Startz (2007, Journal of Econometrics). We demonstrate that confidence intervals based on standard methods such as the delta method can have severe coverage problems when interest rate smoothing is persistent. We then demonstrate that alternative methodologies such as Fieller (1940, 1954), Krinsky and Robb (1986), and the Anderson-Rubin (1949) test have better finite sample coverage. We reconsider the results of four recent empirical studies and show that the evidence supporting the Taylor Principle can be reversed over half of the time.

Suggested Citation

  • Christian Murray & Juan Urquiza, 2017. "Do Estimated Taylor Rules Suffer from Weak Identification?," Working Papers 2017-274-09, Department of Economics, University of Houston.
  • Handle: RePEc:hou:wpaper:2017-274-09
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    References listed on IDEAS

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    1. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, Oxford University Press, vol. 115(1), pages 147-180.
    2. Olivier Coibion & Yuriy Gorodnichenko, 2011. "Monetary Policy, Trend Inflation, and the Great Moderation: An Alternative Interpretation," American Economic Review, American Economic Association, vol. 101(1), pages 341-370, February.
    3. Jean-Thomas Bernard & Nadhem Idoudi & Lynda Khalaf & Clément Yélou, 2007. "Finite sample inference methods for dynamic energy demand models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(7), pages 1211-1226.
    4. Olivier Coibion & Yuriy Gorodnichenko, 2012. "Why Are Target Interest Rate Changes So Persistent?," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(4), pages 126-162, October.
    5. Orphanides, Athanasios, 2004. "Monetary Policy Rules, Macroeconomic Stability, and Inflation: A View from the Trenches," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(2), pages 151-175, April.
    6. Nelson, Charles R. & Startz, Richard, 2007. "The zero-information-limit condition and spurious inference in weakly identified models," Journal of Econometrics, Elsevier, vol. 138(1), pages 47-62, May.
    7. Hirschberg, J.G. & Lye, J.N. & Slottje, D.J., 2008. "Inferential methods for elasticity estimates," Journal of Econometrics, Elsevier, vol. 147(2), pages 299-315, December.
    8. Bolduc, Denis & Khalaf, Lynda & Yélou, Clément, 2010. "Identification robust confidence set methods for inference on parameter ratios with application to discrete choice models," Journal of Econometrics, Elsevier, vol. 157(2), pages 317-327, August.
    9. Jean-Marie Dufour, 1997. "Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models," Econometrica, Econometric Society, vol. 65(6), pages 1365-1388, November.
    10. Alex Nikolsko‐Rzhevskyy, 2011. "Monetary Policy Estimation in Real Time: Forward‐Looking Taylor Rules without Forward‐Looking Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(5), pages 871-897, August.
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    More about this item

    Keywords

    Spurious Inference; Zero-Information-Limit-Condition; Interest Rate Smoothing; Nonlinear Least Squares.;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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