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Empirical process methods in econometrics

In: Handbook of Econometrics

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Author Info
Andrews, Donald W.K.

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Abstract

This paper provides an introduction to the use of empirical process methods in econometrics. These methods can be used to establish the large sample properties of econometric estimators and test statistics. In the first part of the paper, key terminology and results are introduced and discussed heuristically. Applications in the econometrics literature are briefly reviewed. A select set of three classes of applications is discussed in more detail.The second part of the paper shows how one can verify a key property called stochastic equicontinuity. The paper takes several stochastic equicontinuity results from the probability literature, which rely on entropy conditions of one sort or another, and provides primitive sufficient conditions under which the entropy conditions hold. This yields stochastic equicontinuity results that are readily applicable in a variety of contexts. Examples are provided.

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This chapter was published in: R. F. Engle & D. McFadden (ed.) Handbook of Econometrics, , chapter 37, pages 2247-2294, 1986.

This item is provided by Elsevier in its series Handbook of Econometrics with number 4-37.

Handle: RePEc:eee:ecochp:4-37

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Related research
This chapter was published in the following book, which is listed on IDEAS:
R. F. Engle & D. McFadden (ed.), 1986. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 4, number 4, September. [Downloadable!] (restricted)
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C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other

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  3. Ramdan Dridi & Eric Renault, 2000. "Semi-Parametric Indirect Inference," STICERD - Econometrics Paper Series /2000/392, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE. [Downloadable!]
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  5. F Bravo, 2008. "Effcient M-estimators with auxiliary information," Discussion Papers 08/26, Department of Economics, University of York. [Downloadable!]
  6. 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!]
  7. Saraswata Chaudhuri & Eric Zivot, 2008. "A new method of projection-based inference in GMM with weakly identified nuisance parameters," Working Papers UWEC-2008-26, University of Washington, Department of Economics. [Downloadable!]
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  9. Ramdan Dridi, 2000. "Simulated Asymptotic Least Squares Theory," STICERD - Econometrics Paper Series /2000/396, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE. [Downloadable!]
  10. Woocheol Kim & Oliver Linton, 2003. "A Local Instrumental Variable Estimation Method for Generalized Additive Volatility Models," STICERD - Econometrics Paper Series /2003/456, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE. [Downloadable!]
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