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An empirical analysis of nonstationarity in a panel of interest rates with factors

  • Benoit Perron

    (Département de sciences économiques, CIREQ and CIRANO, Université de Montréal, Montreal, Quebec, Canada)

  • Hyungsik Roger Moon

    (Department of Economics, University of Southern California, Los Angeles, CA, USA)

This paper studies nonstationarities in a panel of Canadian and US interest rates of different maturities and risk. We focus on methods which model the cross-sectional dependence within the panel as a linear dynamic factor model, and decompose our data into common and idiosyncratic components that we analyze in turn. Our results suggest the presence of a single nonstationary factor in our panel. Since some of the idiosyncratic components are stationary, we conclude that these series are cointegrated. Finally, the dominant factors can be interpreted as level and slope factors as in the term structure literature. Copyright © 2007 John Wiley & Sons, Ltd.

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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 22 (2007)
Issue (Month): 2 ()
Pages: 383-400

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Handle: RePEc:jae:japmet:v:22:y:2007:i:2:p:383-400
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  1. Moon, H.R.Hyungsik Roger & Perron, Benoit, 2004. "Testing for a unit root in panels with dynamic factors," Journal of Econometrics, Elsevier, vol. 122(1), pages 81-126, September.
  2. Jushan Bai & Serena Ng, 2001. "A Panic Attack on Unit Roots and Cointegration," Economics Working Paper Archive 469, The Johns Hopkins University,Department of Economics.
  3. Campbell, John Y & Shiller, Robert J, 1987. "Cointegration and Tests of Present Value Models," Journal of Political Economy, University of Chicago Press, vol. 95(5), pages 1062-88, October.
  4. Timothy K. Chue & In Choi, 2007. "Subsampling hypothesis tests for nonstationary panels with applications to exchange rates and stock prices," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 233-264.
  5. Bai, Jushan, 2004. "Estimating cross-section common stochastic trends in nonstationary panel data," Journal of Econometrics, Elsevier, vol. 122(1), pages 137-183, September.
  6. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
  7. Luciano Gutierrez, 2006. "Panel Unit-root Tests for Cross-sectionally Correlated Panels: A Monte Carlo Comparison," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(4), pages 519-540, 08.
  8. Peter C.B. Phillips & Hyungsik Roger Moon & Benoit Perron, 2004. "Incidental Trends and the Power of Panel Unit Root Tests," Yale School of Management Working Papers ysm414, Yale School of Management.
  9. Sargan, John Denis & Bhargava, Alok, 1983. "Testing Residuals from Least Squares Regression for Being Generated by the Gaussian Random Walk," Econometrica, Econometric Society, vol. 51(1), pages 153-74, January.
  10. Yoosoon Chang, 2000. "Nonlinear IV Unit Root Tests in Panels with Cross-Sectional Dependency," CIRJE F-Series CIRJE-F-85, CIRJE, Faculty of Economics, University of Tokyo.
  11. Francis X. Diebold & Glenn D. Rudebusch & S. Boragan Aruoba, 2004. "The Macroeconomy and the Yield Curve: A Dynamic Latent Factor Approach," NBER Working Papers 10616, National Bureau of Economic Research, Inc.
  12. Im, Kyung So & Pesaran, M. Hashem & Shin, Yongcheol, 2003. "Testing for unit roots in heterogeneous panels," Journal of Econometrics, Elsevier, vol. 115(1), pages 53-74, July.
  13. Martin D. Evans & Karen K. Lewis, 1992. "Do Stationary Risk Premia Explain It All? Evidence from the Term Structure," Working Papers 92-11, New York University, Leonard N. Stern School of Business, Department of Economics.
  14. Sarno, Lucio & Taylor, Mark P, 1997. "The Behaviour of Real Exchange Rates During the Post-Bretton Woods Period," CEPR Discussion Papers 1730, C.E.P.R. Discussion Papers.
  15. Jörg Breitung & Samarjit Das, 2005. "Panel unit root tests under cross-sectional dependence," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 59(4), pages 414-433.
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