Learning About Models and Their Fit to Data
The paper asks what is the most informative way of assessing the fit of a model to data. often an answer comes from the context. In particular, from a consideration of how the model is to be used. Such information often leads one to seek transformations of the data that deliver the requisite information. Even in those instances in which we are sure of the best way of looking at fit, e.g. by the mean of the sample scores of an alternative model, it is often useful to augment the information provided by these tests through a decomposition of them. In time series such decolpositions have often involved recursive analyses. In this paper we propose that he moments underlying tests be re-written as an integrated conditional moment, where the conditioning variable is chosen to elicit useful information. The idea is potentially useful in assessing non-linear models. To implement the approach non-parametric methods generally need to be applied to simulated data in order to perform the decomposition. A range of applications of the idea, drawn from published articles, is used to illustrate the advantages of the method. [C10]
If you experience problems downloading a file, check if you have the proper application to view it first. 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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 16 (2002)
Issue (Month): 2 ()
|Contact details of provider:|| Web page: http://www.tandfonline.com/RIEJ20|
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/RIEJ20|
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.:
- Pagan, A.R. & Schwert, G.W., 1989.
"Alternative Models For Conditional Stock Volatility,"
89-02, Rochester, Business - General.
- Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
- Adrian R. Pagan & G. William Schwert, 1989. "Alternative Models For Conditional Stock Volatility," NBER Working Papers 2955, National Bureau of Economic Research, Inc.
- Yacine Ait-Sahalia, 1995.
"Testing Continuous-Time Models of the Spot Interest Rate,"
NBER Working Papers
5346, National Bureau of Economic Research, Inc.
- Ait-Sahalia, Yacine, 1996. "Testing Continuous-Time Models of the Spot Interest Rate," Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 385-426.
- Henry, Olan T & Olekalns, Nilss & Summers, Peter M, 2001. "Exchange Rate Instability: A Threshold Autoregressive Approach," The Economic Record, The Economic Society of Australia, vol. 77(237), pages 160-66, June.
- Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002.
"Bayesian Analysis of Stochastic Volatility Models,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 20(1), pages 69-87, January.
- Hausman, Jerry, 2015.
"Specification tests in econometrics,"
Publishing House "SINERGIA PRESS", vol. 38(2), pages 112-134.
- Horowitz, Joel L., 1993. "Semiparametric estimation of a work-trip mode choice model," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 49-70, July.
- Bodman, Philip M, 1998. "Asymmetry and Duration Dependence in Australian GDP and Unemployment," The Economic Record, The Economic Society of Australia, vol. 74(227), pages 399-411, December.
- Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
When requesting a correction, please mention this item's handle: RePEc:taf:intecj:v:16:y:2002:i:2:p:1-18. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.