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! ]

On unification of the asymptotic theory of nonlinear econometric models

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Jose Burguete
A. Ronald Gallant
Geraldo Souza
Abstract

After reading a few articles in the nonlinear econonetric literature one begins to notice that each discussion follows roughly the same lines as the classical treatment of maximum likelihood estimation. There are some technical problems having to do with simultaneously conditioning on the exogenous variables and subjecting the true parameter to a Pittman drift which prevent the use of the classical methods of proof but the basic impression of similarity is correct . An estimator - be it nonlinear least squares, three - stage nonlinear least squares, or whatever - is the solution of an optimization problem. And the objective function of the optimization problem can be treated as if it were the likelihood to derive the Wald test statistic, the likelihood ratio test statistic , and Rao's efficient score statistic. Their asymptotic null and non - null distributions can be found using arguments fairly similar to the classical maximum likelihood arguments. In this article we exploit these observations and unify much of the nonlinear econometric literature. That which escapes this unificationis that which has an objective function which is not twice continuously differentiable with respect to the parameters - minimum absolute deviations regression for example. The model which generates the data need not bethe same as the model which was presumed to define the optimization problem. Thus, these results can be used to obtain the asymptotic behavior of inference procedures under specification error We think that this will prove to be the nost useful feature of the paper. For example, it i s not necessary toresortto Monte Carlo simulat ionto determine i f a Translog estimate of an elasticity of sub stitution obtained by nonlinear three-stage least squares is robust against a CES truestate of nature. The asymptotic approximations we give here w ill provide an analytic answer to the question, sufficiently accurate for most purposes.

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://www.informaworld.com/openurl?genre=article&doi=10.1080/07311768208800012&magic=repec&7C&7C8674ECAB8BB840C6AD35DC6213A474B5
File Format: text/html
File Function:
Download Restriction: Access to full text is restricted to subscribers.

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.

Publisher Info
Article provided by Taylor and Francis Journals in its journal Econometric Reviews.

Volume (Year): 1 (1982)
Issue (Month): 2 ()
Pages: 151-190
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:taf:emetrv:v:1:y:1982:i:2:p:151-190

Contact details of provider:
Web page: http://taylorandfrancis.metapress.com/link.asp?target=journal&id=107830

Order Information:
Web: http://www.tandf.co.uk/journals/subscription.html

For technical questions regarding this item, or to correct its listing, contact: (Christopher F. Baum).

Related research
Keywords: Nonlinear Models; Asymptotic Theory;

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. Anthony W. Lynch & Jessica A. Wachter, 2008. "Using Samples of Unequal Length in Generalized Method of Moments Estimation," NBER Working Papers 14411, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  2. J. Dufour, . "Some Impossibility Theorems in Econometrics with Applications to Instrumental Variables, Dynamic Models and Cointegration," Sonderforschungsbereich 373 1995-27, Humboldt Universitaet Berlin.
    Other versions:
  3. Donald W.K. Andrews, 1986. "Power in Econometric Applications," Cowles Foundation Discussion Papers 800, Cowles Foundation, Yale University. [Downloadable!]
    Other versions:
  4. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," MPRA Paper 8413, University Library of Munich, Germany. [Downloadable!]
    Other versions:
  5. Albert Satorra, 1989. "Alternative test criteria in covariance structure analysis: A unified approach," Psychometrika, Springer, vol. 54(1), pages 131-151, March. [Downloadable!] (restricted)
  6. P. Bentler, 1986. "Structural modeling and psychometrika: An historical perspective on growth and achievements," Psychometrika, Springer, vol. 51(1), pages 35-51, March. [Downloadable!] (restricted)
  7. Jean-Marie Dufour & Alain Trognon, 2000. "Invariant Tests Based on M-Estimators, Estimating Functions and the Generalized Method of Moments," Econometric Society World Congress 2000 Contributed Papers 1420, Econometric Society. [Downloadable!]
  8. Donald W.K. Andrews, 1986. "Consistency in Nonlinear Econometric Models: A Generic Uniform Law of Large Numbers," Cowles Foundation Discussion Papers 790, Cowles Foundation, Yale University. [Downloadable!]
  9. Donald W.K. Andrews & Ray C. Fair, 1987. "Inference in Econometric Models with Structural Change," Cowles Foundation Discussion Papers 832, Cowles Foundation, Yale University. [Downloadable!]
    Other versions:
Statistics
Access and download statistics

Did you know? IDEAS also covers the most complete directory of Economics departments and institutes, EDIRC.

This page was last updated on 2009-12-10.


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.