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A Shadow Rate or a Quadratic Policy Rule? The Best Way to Enforce the Zero Lower Bound in the United States

Published online by Cambridge University Press:  18 December 2018

Martin M. Andreasen  and
Andrew Meldrum
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Abstract

We study whether it is better to enforce the zero lower bound (ZLB) in models of U.S. Treasury yields using a shadow rate model or a quadratic term structure model. We show that the models achieve a similar in-sample fit and perform comparably in matching conditional expectations of future yields. However, when the recent ZLB period is included in the sample, the models’ ability to match conditional expectations away from the ZLB deteriorates because the time-series dynamics of the pricing factors change. In addition, neither model provides a reasonable description of conditional volatilities when yields are away from the ZLB.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 54 , Issue 5 , October 2019 , pp. 2261 - 2292
Creative Commons
This is a work of the U.S. Government and is not subject to copyright protection in the United States.
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2018

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Footnotes

1

We give special thanks to Hendrik Bessembinder (the editor) and Jean-Sébastien Fontaine (the referee) for many helpful suggestions. We thank Jens Christensen, Michiel De Pooter, Hans Dewachter, Gregory R. Duffee, Tom Engsted, Peter Hördahl, Scott Joslin, Don Kim, Donna Lormand, Thomas Pedersen, Jean-Paul Renne, Glenn Rudebusch, Oreste Tristani, and Chris Young for helpful comments, as well as seminar participants at the 2015 SoFie Conference, the Federal Reserve Bank of San Francisco, the European Central Bank, and the Bank of England. Andreasen acknowledges financial support from the Danish e-Infrastructure Cooperation (DeIC) and financial support from CREATES (Center for Research in Econometric Analysis of Time Series; DNRF78) from the Danish National Research Foundation. Meldrum acknowledges the Bank of England, where he worked during the preparation of an early draft of this article (Bank of England Staff Working Paper No. 550, Sept. 2015). The analysis and conclusions are those of the authors and do not indicate concurrence by the Bank of England, the Board of Governors of the Federal Reserve System, or other members of the research staff of the Board.

References

Adrian, T.; Crump, R. K.; and Moench, E.. “Pricing the Term Structure with Linear Regressions.” Journal of Financial Economics, 110 (2013), 110–138.Google Scholar
Ahn, D.-H.; Dittmar, R. F.; and Gallant, A. R.. “Quadratic Term Structure Models: Theory and Evidence.” Review of Financial Studies, 15 (2002), 243–288.Google Scholar
Andersen, T. G.; Fusari, N.; and Todorov, V.. “Parametric Inference and Dynamic State Recovery from Option Panels.” Econometrica, 83 (2015), 1081–1145.Google Scholar
Andreasen, M. M., and Christensen, B. J.. “The SR Approach: A New Estimation Procedure for Non-Linear and Non-Gaussian Dynamic Term Structure Models.” Journal of Econometrics, 184 (2015), 420–451.Google Scholar
Bauer, M. D., and Rudebusch, G. D.. “Monetary Policy Expectations at the Zero Lower Bound.” Journal of Money, Credit and Banking, 48 (2016), 1440–1465.Google Scholar
Bauer, M. D.; Rudebusch, G. D.; and Wu, J. C.. “Correcting Estimation Bias in Dynamic Term Structure Models.” Journal of Business and Economic Statistics, 30 (2012), 454–467.Google Scholar
Black, F.“Interest Rates as Options.” Journal of Finance, 50 (1995), 1371–1376.Google Scholar
Bollerslev, T.“Generalized Autoregressive Conditional Heteroskedasticity.” Journal of Econometrics, 31 (1986), 307–327.Google Scholar
Campbell, J. Y., and Shiller, R. J.. “Yield Spread and Interest Rate Movements: A Bird’s Eye View.” Review of Economic Studies, 58 (1991), 495–514.Google Scholar
Christensen, J. H. E.; Diebold, F. X.; and Rudebusch, G. D.. “The Affine Arbitrage-Free Class of Nelson–Siegel Term Structure Models.” Journal of Econometrics, 164 (2011), 4–20.Google Scholar
Christensen, J. H. E., and Rudebusch, G. D.. “Estimating Shadow-Rate Term Structure Models with Near-Zero Yields.” Journal of Financial Econometrics, 13 (2015), 226–259.Google Scholar
Cochrane, J. H., and Piazzesi, M.. “Decomposing the Yield Curve.” Working Paper, University of Chicago (2008).Google Scholar
Cox, J. C.; Ingersoll, J. E.; and Ross, S. A.. “A Theory of the Term Structure of Interest Rates.” Econometrica, 53 (1985), 385–407.Google Scholar
Dai, Q., and Singleton, K. J.. “Specification Analysis of Affine Term Structure Models.” Journal of Finance, 55 (2000), 1946–1978.Google Scholar
Dai, Q., and Singleton, K. J.. “Expectation Puzzles, Time-Varying Risk Premia and Affine Models of the Term Structure.” Journal of Financial Economics, 63 (2002), 415–441.Google Scholar
Diebold, F. X., and Li, C.. “Forecasting the Term Structure of Government Bond Yields.” Journal of Econometrics, 130 (2006), 337–364.Google Scholar
Duffee, G. R.“Term Premia and Interest Rate Forecasts in Affine Models.” Journal of Finance, 57 (2002), 405–443.Google Scholar
Duffee, G. R.“Sharpe Ratios in Term Structure Models.” Working Paper, Johns Hopkins University (2010).Google Scholar
Duffee, G. R.“Forecasting with the Term Structure: The Role of No-Arbitrage Restrictions.” Working Paper, Johns Hopkins University (2011a).Google Scholar
Duffee, G. R.“Information in (and not in) the Term Structure.” Review of Financial Studies, 24 (2011b), 2895–2934.Google Scholar
Fama, E. F., and Bliss, R. R.. “The Information in Long-Maturity Forward Rates.” American Economic Review, 77 (1987), 680–692.Google Scholar
Feunou, B.; Fontaine, J.-S.; Le, A.; and Lundblad, C.. “Tractable Term-Structure Models and the Zero Lower Bound.” Working Paper, Bank of Canada (2015).Google Scholar
Filipovic, D.; Larsson, M.; and Trolle, A. B.. “Linear-Rational Term Structure Models.” Journal of Finance, 72 (2017), 655–704.Google Scholar
Joslin, S.; Singleton, K. J.; and Zhu, H.. “A New Perspective on Gaussian Dynamic Term Structure Models.” Review of Financial Studies, 24 (2011), 926–970.Google Scholar
Kim, D. H.“Spanned Stochastic Volatility in Bond Markets: A Reexamination of the Relative Pricing between Bonds and Bond Options.” Working Paper, Bank for International Settlements (2007).Google Scholar
Kim, D. H., and Singleton, K. J.. “Term Structure Models and the Zero Bound: An Empirical Investigation of Japanese Yields.” Journal of Econometrics, 170 (2012), 32–49.Google Scholar
Leippold, M., and Wu, L.. “Asset Pricing under the Quadratic Class.” Journal of Financial and Quantitative Analysis, 37 (2002), 271–295.Google Scholar
Mincer, J. A., and Zarnowitz, V.. “The Evaluation of Economic Forecasts.” In Economic Forecasts and Expectations: Analyses of Forecasting Behavior and Performance, Mincer, J., ed. New York, NY: National Bureau of Economic Research (1969), 3–46.Google Scholar
Monfort, A.; Pegoraro, F.; Renne, J.-P.; and Roussellet, G.. “Staying at Zero with Affine Processes: A New Dynamic Term Structure Model.” Journal of Econometrics, 201 (2017), 348–366.Google Scholar
Priebsch, M. A.“Computing Arbitrage-Free Yields in Multi-Factor Gaussian Shadow-Rate Term Structure Models.” Finance and Economics Discussion Series. Working Paper, Federal Reserve Board (2013).Google Scholar
Realdon, M.“Quadratic Term Structure Models in Discrete Time.” Finance Research Letters, 3 (2006), 277–289.Google Scholar
Realdon, M.“Gaussian Models for Euro High Grade Government Yields.” European Journal of Finance, 23 (2016), 1–44.Google Scholar
Rudebusch, G. D., and Wu, T.. “Accounting for a Shift in Term Structure Behavior with No-Arbitrage and Macro-Finance Models.” Journal of Money, Credit and Banking, 39 (2007), 395–422.Google Scholar
Wu, J. C., and Xia, F. D.. “Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound.” Journal of Money Credit and Banking, 48 (2016), 253–291.Google Scholar
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