Sugita, Katsuhiro (2002) Testing for cointegration rank using Bayes factors. Working Paper. University of Warwick, Department of Economics, Coventry.

Preview

PDF WRAP_Sugita_twerp654.pdf - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader Download (287Kb)

Abstract

This paper proposes Bayesian methods for estimating the cointegration rank using Bayes factors. We consider natural conjugate priors for computing Bayes factors. First, we estimate the cointegrating vectors for each possible rank. Then, we compute the Bayes factors for each rank against 0 rank. Monte Carlo simulations show that using Bayes factor with conjugate priors produces fairly good results. We apply the method to demand for money in the US.

Item Type:	Working or Discussion Paper (Working Paper)
Subjects:	H Social Sciences > HB Economic Theory
Divisions:	Faculty of Social Sciences > Economics
Library of Congress Subject Headings (LCSH):	Cointegration, Econometrics, Bayesian statistical decision theory, Monte Carlo method
Series Name:	Warwick economic research papers
Publisher:	University of Warwick, Department of Economics
Place of Publication:	Coventry
Date:	July 2002
Number:	No.654
Number of Pages:	17
Status:	Not Peer Reviewed
Access rights to Published version:	Open Access
References:	[1] Bauwens, L., and Giot, P. 1998, A Gibbs Sampling Approach to Cointegration, Computational Statistics, 13, 339-368. [2] Bauwens, L., and Lubrano, M. 1996, Identi�cation Restrictions and Posterior Densities in Cointegrated Gaussian VAR Systems, in T.B. Fomby (ed.), Advances in Econometrics, vol. 11B, JAI press, Greenwich, CT. [3] Bauwens, L., Lubrano, M., and Richard, J-F. 1999, Bayesian Inference in Dynamic Econometric Models, Oxford University Press, Oxford. [4] Chib, S. 1995, Marginal Likelihood From the Gibbs Output, Journal of the American Statistical Association, 90, 1313-1321. [5] Chib, S., and Greenberg, E. 1995, Understanding the Metropolis-Hastings Algorithm, The American Statistician, 49, 327-335. [6] Chen, M-H. 1994, Importance-Weighted Marginal Bayesian Posterior Density Estimation, Journal of the American Statistical Association, 89, 818-824. [7] Chen, M-H., Shao, Q-M., and Ibrahim, J-G. 2000, Monte Carlo Methods in Bayesian Computation, Springer Series in Statistics, Springer. [8] Dickey, J., 1971, The Weighted Likelihood Ratio, Linear Hypothesis on Normal Location Parameters, The Annals of Mathematical Statistics, 42, 204-223. [9] Doornik, J.A. 1998, OX An Object-Oriented Matrix programming Language, Timberlake Consultants Press., London. [10] Evans, M. and Swartz, T. 2000, Approximating Integrals via Monte Carlo and Deterministic Methods, Oxford University Press, Oxford. [11] Geweke, J. 1989, Bayesian inference in Econometric Models Using Monte Carlo Integration, Econometrica, 57, 1317-1340. [12] Geweke, J. 1996, Bayesian Reduced Rank Regression in Econometrics, Journal of Econometrics,75, 127-146. [13] Goldfeld, S., and Sichel, D., 1990, The Demand for Money, Chapter 8 in B. Friedman and F. Hahn (eds.), Handbook of Monetary Economics, Vol I, North-Holland, New York. [14] Johansen, S. 1991, The Power Function for the Likelihood Ratio Test for Cointegration, in J. Gruber, ed., Econometric Decision Models: New Methods of Modeling and Applications, Springer Verlag, New York, NY, 323-335. [15] Johansen, S. 2000, A Small Sample Correction of the Test for Cointegrating Rank in the Vector Autoregressive Model�, EUI Working Paper, ECO No. 2000/15, European University Institute, Italy. [16] Kass, R.E., and Raftery, A. E. 1995, Bayes Factors, Journal of the American Statistical Association, 90, 773-795. [17] Kass, R. E., and Wasserman, L. 1996, The Selection of Prior Distributions by Formal Rules, Journal of the American Statistical Association, 91, 1343-1370.. [18] Kleibergen, F., and van Dijk, H.K. 1994, On the Shape of the Likelihood/Posterior in Cointegration Models, Econometric Theory, 10, 514 - 551. [19] Kleibergen, F., and Paap, R. 1999, Priors, Posteriors and Bayes Factors for a Bayesian Analysis of Cointegration, rewritten version of Econometric Institute Report 9821/A, Erasmus University Rotterdam. [20] Lucas, R., 1988, Money Demand in the United States: A Quantitative Review, Carnegie-Rochester Conference Series on Public Policy. Vol 29, 137-168. [21] Newton, M.A., and Raftery, A. E., 1994, Approximate Bayesian Inference by the Weighted Likelihood Bootstrap, Journal of the Royal Statistical Society, Ser. B, 56, 3-48. [22] Phillips, P. C. B. 1996, Econometric Model Determination, Econometrica, 64, 763-812. [23] Phillips, P. C. B., and Ploberger, W. 1996, An Asymptotic Theory of Bayesian Inference for Time Series, Econometrica, 64, 381-412. [24] Ritter. C., and Tanner, M.A. 1992, Facilitating the Gibbs Sampler: The Gibbs Stopper and the Griddy-Gibbs Sampler, Journal of the American Statistical Association, 87, 861-868. [25] Tierney, L., and Kadane, J.B. 1986, Accurate Approximations for Posterior Moments and Marginal Densities, Journal of the American Statistical Association, 81, 82-86 [26] Tsurumi. H., and Wago, H. 1996, A Bayesian Analysis of Unit Root and Cointegration with an Application to a Yen-Dollar Exchange Rate Model, in T.B. Fomby (ed.), Advances in Econometrics, vol. 11B, JAI press, Greenwich, CT. [27] Verdinelli, I., and Wasserman, L. 1995, Computing Bayes Factors Using a Generalization of the Savage-Dickey Density Ratio, Journal of the American Statistical Association, 90, 614-618. [28] Zellner, A. 1986, On Assessing Prior Distributions and Bayesian Regression Analysis with g-prior Distributions, ed. P.K. Goel and A. Zellner, Bayesian Inference and Decision Techniques: Essays in Honor of Bruno de Finetti, North-Holland, Amsterdam, 233-243.
URI:	http://wrap.warwick.ac.uk/id/eprint/1533

Request changes to a record

Actions (login required)

View Item