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! ]

Consistency in Nonlinear Econometric Models: A Generic Uniform Law of Large Numbers

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Donald W.K. Andrews () (Cowles Foundation, Yale University)

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

Abstract

A basic tool of modern econometrics is a uniform law of large numbers (LLN). It is a primary ingredient used in proving consistency and asymptotic normality of parametric and nonparametric estimators in nonlinear econometric models. Thus, in a well-known review article, Burguete, Gallant, and Sousa [8, p. 162] introduce a uniform LLN with the statement: "The following theorem is the result upon which the asymptotic theory of nonlinear econometrics rests. "So pervasive is the use of uniform LLNs, that numerous authors appeal to an unspecified generic uniform LLN. Others appeal to some specific result. The purpose of this paper is to provide a generic uniform LLN that is sufficiently general to incorporate most applications of uniform LLNs in the nonlinear econometrics literature. In summary, the paper presents a result that can be used to turn state of the art pointwise LLNs into uniform LLNs over compact sets, with the addition of a single smoothness condition -- either a Lipschitz condition or a derivative condition. The latter is particularly easy to verify, and is implied by common assumptions used to prove asymptotic normality of estimators. Thus, the additional condition is not particularly restrictive. In contrast to other uniform LLNs that appear in the literature, the one given here allows the full range of heterogeneity of summands (i.e., non-identical distributions), and temporal dependence, that is available with pointwise LLNs.

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://cowles.econ.yale.edu/P/cp/p06b/p0693.pdf
File Format: application/pdf
File Function:
Download Restriction: no
File URL: http://cowles.econ.yale.edu/P/cd/d07b/d0790.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by Cowles Foundation, Yale University in its series Cowles Foundation Discussion Papers with number 790.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 26 pages
Date of creation: Apr 1986
Date of revision:
Publication status: Published in Econometrica (November 1987), 55(6): 1465-1471
Handle: RePEc:cwl:cwldpp:790

Note: CFP 693.
Contact details of provider:
Postal: Yale University, Box 208281, New Haven, CT 06520-8281 USA
Phone: (203) 432-3702
Fax: (203) 432-6167
Web page: http://cowles.econ.yale.edu/
More information through EDIRC

Order Information:
Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA

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

Related research
Keywords: Uniform law of large Numbers; consistency; nonlinear econometric models;

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. Amemiya, Takeshi, 1974. "The nonlinear two-stage least-squares estimator," Journal of Econometrics, Elsevier, vol. 2(2), pages 105-110, July. [Downloadable!] (restricted)
  2. Jose Burguete & A. Ronald Gallant & Geraldo Souza, 1982. "On unification of the asymptotic theory of nonlinear econometric models," Econometric Reviews, Taylor and Francis Journals, vol. 1(2), pages 151-190. [Downloadable!] (restricted)
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. Tiemen Woutersen & Robert M. de Jong, 2004. "Dynamic time series binary choice," Econometric Society 2004 North American Summer Meetings 365, Econometric Society. [Downloadable!]
    Other versions:
  2. Altissimo, Filippo & Violante, Giovanni L, 2000. "The Nonlinear Dynamics of Output and Unemployment in the US," CEPR Discussion Papers 2475, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  3. Rosa L. Matzkin, 1989. "A Nonparametric Maximum Rank Correlation Estimator," Cowles Foundation Discussion Papers 918, Cowles Foundation, Yale University. [Downloadable!]
  4. Benedikt M. Potscher & Ingmar R. Prucha, 1994. "On the Formulation of Uniform Laws of Large Numbers: A Truncation Approach," NBER Technical Working Papers 0085, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  5. Donald W.K. Andrews & Werner Ploberger, 1993. "Admissibility of the Likelihood Ratio Test When a Nuisance Parameter Is Present OnlyUnder the Alternative," Cowles Foundation Discussion Papers 1058, Cowles Foundation, Yale University. [Downloadable!]
  6. P. Cizek, . "Robust Estimation in Nonlinear Regression and Limited Dependent Variable Models," Sonderforschungsbereich 373 2001-100, Humboldt Universitaet Berlin.
    Other versions:
  7. P. Cizek, . "Robust Estimation in Nonlinear Regression Models," Sonderforschungsbereich 373 2001-25, Humboldt Universitaet Berlin.
  8. 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:
  9. Benedikt M. Pötscher & Ingmar R. Prucha, 1999. "Basic Elements of Asymptotic Theory," Electronic Working Papers 99-001, University of Maryland, Department of Economics. [Downloadable!]
  10. Darrell Duffie & Kenneth J. Singleton, 1990. "Simulated Moments Estimation of Markov Models of Asset Prices," NBER Technical Working Papers 0087, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  11. M. Hashem Pesaran & Yongcheol Shin, 2002. "Long-Run Structural Modelling," Econometric Reviews, Taylor and Francis Journals, vol. 21(1), pages 49-87. [Downloadable!] (restricted)
    Other versions:
  12. Yoon-Jae Whang & Donald W.K. Andrews, 1991. "Tests of Specification for Parametric and Semiparametric Models," Cowles Foundation Discussion Papers 968, Cowles Foundation, Yale University. [Downloadable!]
    Other versions:
  13. Joris Pinkse, 2000. "Feasible Multivariate Nonparametric Estimation Using Weak Separability," Econometric Society World Congress 2000 Contributed Papers 1241, Econometric Society. [Downloadable!]
Statistics
Access and download statistics

Did you know? IDEAS also indexes books.

This page was last updated on 2009-11-12.


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.