This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Bayesian analysis of ARMA models using noninformative priors

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Kleibergen, F.
Hoek, H. (Tilburg University, Center for Economic Research)

Additional information is available for the following registered author(s):

Abstract

Parameters in ARMA models are only locally identified. It is shown that the use of diffuse priors in these models leads to a preference for locally nonidentified parameter values. We therefore suggest to use likelihood based priors like the Jeffreys' priors which overcome these problems. An algorithm involving Importance Sampling for calculating the posteriors of ARMA parameters using Jeffreys' priors is constructed. This algorithm is based on the implied AR specification of ARMA models and shows good performance in our applications. As a byproduct the algorithm allows for the computation of the posteriors of diagnostic parameters which show the identifiability of the MA parameters. As a general to specific modeling approach to ARMA models suffers heavily from the previous mentioned identification problems, we derive posterior odds ratios which are suited for comparing (nonnested) parsimonious (low order) ARMA models. These procedures are applied to two datasets, the (extended) Nelson-Plosser data and monthly observations of US 3-month and 10 year interest rates. For approximately 50% of the series in these two datasets an ARMA model is favored above an AR model which has important consequences for especially the long run parameters

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://arno.uvt.nl/show.cgi?fid=3242
File Format: application/pdf
File Function:
Download Restriction: no
File URL: http://arno.uvt.nl/show.cgi?fid=3243
File Format: application/postscript
File Function:
Download Restriction: no

Publisher Info
Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 116.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: 1995
Date of revision:
Handle: RePEc:dgr:kubcen:1995116

Contact details of provider:
Web page: http://center.uvt.nl

For technical questions regarding this item, or to correct its listing, contact: (Corry Stuyts).

Related research
Keywords:

Other versions of this item:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Monahan, John F., 1983. "Fully Bayesian analysis of ARMA time series models," Journal of Econometrics, Elsevier, vol. 21(3), pages 307-331, April. [Downloadable!] (restricted)
  2. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-39, November. [Downloadable!] (restricted)
  3. Chib, Siddhartha & Greenberg, Edward, 1994. "Bayes inference in regression models with ARMA (p, q) errors," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 183-206. [Downloadable!] (restricted)
  4. DeJong, David N & Whiteman, Charles H, 1993. "Estimating Moving Average Parameters: Classical Pileups and Bayesian Posteriors," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(3), pages 311-17, July.
  5. Kloek, Tuen & van Dijk, Herman K, 1978. "Bayesian Estimates of Equation System Parameters: An Application of Integration by Monte Carlo," Econometrica, Econometric Society, vol. 46(1), pages 1-19, January. [Downloadable!] (restricted)
  6. Peter C.B. Phillips, 1987. "Partially Identified Econometric Models," Cowles Foundation Discussion Papers 845R, Cowles Foundation, Yale University, revised Aug 1988. [Downloadable!]
  7. Kleibergen, F.R. & Van Dijk, H.K., 1993. "On the Shape of the Likelyhood/Posterior in Cointegration Models," Papers 9315-a, Erasmus University of Rotterdam - Econometric Institute.
    Other versions:
  8. Phillips, P C B, 1991. "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 333-64, Oct.-Dec.. [Downloadable!] (restricted)
    Other versions:
  9. Geweke, John, 1989. "Exact predictive densities for linear models with arch disturbances," Journal of Econometrics, Elsevier, vol. 40(1), pages 63-86, January. [Downloadable!] (restricted)
  10. Sargan, J D & Bhargava, Alok, 1983. "Maximum Likelihood Estimation of Regression Models with First Order Moving Average Errors When the Root Lies on the Unit Circle," Econometrica, Econometric Society, vol. 51(3), pages 799-820, May. [Downloadable!] (restricted)
  11. Uhlig, Harald, 1994. "On Jeffreys Prior when Using the Exact Likelihood Function," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 633-644, August. [Downloadable!]
  12. Schotman, Peter C & van Dijk, Herman K, 1991. "On Bayesian Routes to Unit Roots," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 387-401, Oct.-Dec.. [Downloadable!] (restricted)
    Other versions:
  13. Franses, Philip Hans & Kleibergen, Frank, 1996. "Unit roots in the Nelson-Plosser data: Do they matter for forecasting?," International Journal of Forecasting, Elsevier, vol. 12(2), pages 283-288, June. [Downloadable!] (restricted)
  14. Kleibergen, Frank & van Dijk, Herman K., 1994. "Direct cointegration testing in error correction models," Journal of Econometrics, Elsevier, vol. 63(1), pages 61-103, July. [Downloadable!] (restricted)
    Other versions:
Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. P. Saikkonen & H. Lütkepohl, . "Testing for a Unit Root in a Time Series with a Level Shift at Unknown Time," Sonderforschungsbereich 373 1999-72, Humboldt Universitaet Berlin.
    Other versions:
  2. M. Lanne & H. Lütkepohl & P. Saikkonen, . "Test Procedures for Unit Roots in Time Series with Level Shifts at Unknown Time," Sonderforschungsbereich 373 2001-39, Humboldt Universitaet Berlin.
    Other versions:
  3. Kleibergen, Frank & Dijk, Herman K. van, 1996. "Bayesian simultaneous equations analysis using reduced rank structures," Econometric Institute Report 47, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
    Other versions:
  4. Kleibergen, Frank & Paap, Richard, 1996. "Priors, posterior odds and Lagrange multiplier statistics in Bayesian analyses of cointegration," Econometric Institute Report 37, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
    Other versions:
Statistics
Access and download statistics

Did you know? The RePEc project started in 1997. Its precursor, NetEc, dates back to 1993.

This page was last updated on 2009-11-25.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.