A Gibbs sampling approach to estimation and prediction of time-varying-parameter models

Computational Statistics and Data Analysis

Volumn 27, Issue 2, 1998, Pages 171-194

  Min, Chung Ki ^a  

^a Hankuk University of Foreign Studies   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

DATA REDUCTION; ESTIMATION; FORECASTING; MATHEMATICAL MODELS; SAMPLING;

GIBBS SAMPLER;

REGRESSION ANALYSIS;

EID: 0032478438     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-9473(97)00054-6     Document Type: Article

References (25)

1. Blattberg, R.C., George, E.I., 1991. Shrinkage estimation of price and promotional elasticities: seemingly unrelated equations. J. Am. Statist. Assoc. 86, 304-315.
2. Campbell, J.Y., Mankiw, N.G., 1987. Are output fluctuations transitory? Quarter. J. Econom. 102, 857-880.
3. Carlin, B.P., Polson, N.G., Stoffer, D.S., 1992. A Monte Carlo approach to nonnormal and nonlinear state space modeling. J. Am. Statist. Assoc. 87, 493-500.
4. Casella, G, George, E.I., 1992. Explaining the gibbs sampler. Am. Stat. 46, 167-174.
5. Chib, S., 1993. Bayes regression with autoregressive errors: a gibbs sampling approach. J. Econom. 58, 275-294.
6. Chib, S., Tiwari, R.C., Jammalamadaka, S.R., 1990. On Bayes smoothing in a time varying regression model. In: Geisser, S., Hodges, J., Press, S.J., Zellner, A. (Eds.), Bayesian Likelihood Methods in Statistics and Econometrics: Essays in Honor of George A. Barnard. North-Holland, Amsterdam.
7. Cooley, T.F., Prescott, E.C., 1973. An adaptive regression model. Int. Econom. Rev. 14, 364-371.
8. Cooley, T.F., Prescott, E.C., 1976. Estimation in the presence of stochastic parameter variation. Econometrica 44, 167-184.
9. DeJong, D.N., Whiteman, C.H., 1991. Reconsidering trends and random walks in macroeconomic time series. J. Monetary Econom. 28, 1991.
10. Doan, T., Litterman, R., Sims, C., 1984. Forecasting and conditional projection using realistic prior distributions. Econom. Rev. 3, 1-144.
11. Franses, P.H., Kleibergen, F., 1996. Unit roots in the Nelson-Plosser data: do they matter for forecasting? Int. J. Forecasting 12, 283-288.
12. Gelfand, A.E., Smith, A.F.M., 1990. Sampling based approaches to calculating marginal densities. J. Am. Statist. Assoc. 85, 398-409.
13. Geman, S., Geman, D., 1984. Stochastic relaxation, Gibbs distributions and the bayesian restoration of images. IEEE Trans.on Pattern Anal. and Machine Intell. 6, 721-741.
14. Geweke, J., 1992. Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments. in: Bernardo, J.M., Berger, J.O., Dawid, A.P., Smith, A.F.M. (Eds.), Bayesian Statistics, Vol. 4, Oxford University Press, Oxford, pp. 169-188.
15. Harvey, A.C., 1978. The estimation of time-varying parameters from panel data (with discussion). Annales de L'Insee 30/31, 203-226.
16. Johnson, V.E., 1992. A technique for estimating marginal posterior densities in hierarchical models using mixtures of conditional densities. J. Am. Statist. Assoc. 87, 852-860.
17. Liu, L.M., Hanssens, D.M., 1981. A bayesian approach to time-varying cross-sectional regression models. J. Econom. 15, 341-356.
18. McCulloch, R.E., Rossi, P.E., 1994. An exact likelihood analysis of the multinomial probit model. J. Econom. 64, 207-240.
19. Nelson, C.R., Plosser, C.I., 1982. Trends and random walks in macroeconomic time series: some evidence and implications. J. Monetary Econom. 10, 139-162.
20. Perron, P., 1989. The great crash, the oil price shock, and the unit root hypothesis. Econometrica 57, 1361-1401.
21. Tanner, M.A., Wong, W.H., 1987. The calculation of posterior distributions by data augmentation (with discussion). J. Am. Statist. Assoc. 82, 528-550.
22. Tierney, L., 1994. Markov chains for exploring posterior distributions (with discussion). Ann. Stat. 22, 1701-1762.
23. Tierney, L., Kadane, J.B., 1986. Accurate approximations for posterior moments and marginal densities. J. Am. Statist. Assoc. 81, 82-86.
24. Zellner, A., Min, C., 1995. Gibbs sampler convergence criteria. J. Am. Statist. Assoc. 90, 921-927.
25. Zellner, A., Rossi, P., 1982. Bayesian analysis of dichotomous quantal response models. J. Econometrics 25, 365-393.