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A Decision Theoretic Analysis of the Unit Root Hypothesis Using Mixtures of Elliptical Models

  • Koop, G.
  • Steel, M.F.J.

This paper develops a formal decision theoretic approach to testing for a unit root in economic time series. The approach is empirically implemented by specifying a loss function based on predictive variances; models are chosen so as to minimize expected loss. In addition, the paper broadens the class of likelihood functions traditionally considered in the Bayesian unit root literature by: i) Allowing for departures from normality via the specification of a likelihood based on general elliptical densities; ii) allowing for structural breaks to occur; iii) allowing for moving average errors; and iv) using mixtures of various submodels to create a very flexible overall likelihood. Empirical results indicate that, while the posterior probability of trend-stationarity is quite high for most of the series considered, the unit root model is often selected in the decision theoretic analysis.

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Paper provided by Tilburg - Center for Economic Research in its series Papers with number 9150.

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Length: 28 pages
Date of creation: 1991
Date of revision:
Handle: RePEc:fth:tilbur:9150
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  1. Peter C.B. Phillips & Werner Ploberger, 1991. "Time Series Modelling with a Bayesian Frame of Reference: 1. Concepts and Illustrations," Cowles Foundation Discussion Papers 980, Cowles Foundation for Research in Economics, Yale University.
  2. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
  3. DeJong, David N. & Whiteman, Charles H., 1991. "Reconsidering 'trends and random walks in macroeconomic time series'," Journal of Monetary Economics, Elsevier, vol. 28(2), pages 221-254, October.
  4. Osiewalski, J. & Steel, M.F.J., 1990. "Robust Bayesian inference in elliptical regression models," Discussion Paper 1990-32, Tilburg University, Center for Economic Research.
  5. Sampson, Michael, 1991. "The Effect of Parameter Uncertainty on Forecast Variances and Confidence Intervals for Unit Root and Trend Stationary Time-Series Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(1), pages 67-76, Jan.-Marc.
  6. Banerjee, Anindya & Lumsdaine, Robin L & Stock, James H, 1992. "Recursive and Sequential Tests of the Unit-Root and Trend-Break Hypotheses: Theory and International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 271-87, July.
  7. Sims, Christopher A., 1988. "Bayesian skepticism on unit root econometrics," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 463-474.
  8. Chow, Gregory C, 1973. "Multiperiod Predictions from Stochastic Difference Equations by Bayesian Methods," Econometrica, Econometric Society, vol. 41(1), pages 109-18, January.
  9. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1995. "Bayesian long-run prediction in time series models," Journal of Econometrics, Elsevier, vol. 69(1), pages 61-80, September.
  10. Koop, Gary, 1991. "Intertemporal Properties of Real Output: A Bayesian Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 253-65, July.
  11. Peter C.B. Phillips, 1990. "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends," Cowles Foundation Discussion Papers 950, Cowles Foundation for Research in Economics, Yale University.
  12. Schotman, Peter & van Dijk, Herman K., 1991. "A Bayesian analysis of the unit root in real exchange rates," Journal of Econometrics, Elsevier, vol. 49(1-2), pages 195-238.
  13. Dreze, Jacques H., 1977. "Bayesian regression analysis using poly-t densities," Journal of Econometrics, Elsevier, vol. 6(3), pages 329-354, November.
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