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Bayesian Inference in Cointegrated I (2) Systems: a Generalisation of the Triangular Model

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  • Rodney W. Strachan

Abstract

This paper generalises the cointegrating model of Phillips (1991) to allow for I (0) , I (1) and I (2) processes. The model has a simple form that permits a wider range of I (2) processes than are usually considered, including a more flexible form of polynomial cointegration. Further, the specification relaxes restrictions identified by Phillips (1991) on the I (1) and I (2) cointegrating vectors and restrictions on how the stochastic trends enter the system. To date there has been little work on Bayesian I (2) analysis and so this paper attempts to address this gap in the literature. A method of Bayesian inference in potentially I (2) processes is presented with application to Australian money demand using a Jeffreys prior and a shrinkage prior.

Suggested Citation

  • Rodney W. Strachan, 2005. "Bayesian Inference in Cointegrated I (2) Systems: a Generalisation of the Triangular Model," Discussion Papers in Economics 05/14, Division of Economics, School of Business, University of Leicester.
    • Handle: RePEc:lec:leecon:05/14
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    References listed on IDEAS

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    1. Carmen Fernandez & Eduardo Ley & Mark F. J. Steel, 2001. "Model uncertainty in cross-country growth regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(5), pages 563-576.
    2. Gali, Jordi, 1990. "Finite horizons, life-cycle savings, and time-series evidence on consumption," Journal of Monetary Economics, Elsevier, vol. 26(3), pages 433-452, December.
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    Cited by:

    1. Tsay, Ruey S. & Ando, Tomohiro, 2012. "Bayesian panel data analysis for exploring the impact of subprime financial crisis on the US stock market," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3345-3365.
    2. Justyna Wróblewska, 2009. "Bayesian Model Selection in the Analysis of Cointegration," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 1(1), pages 57-69, March.

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