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Tests of Additive Derivative Constraints

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Author Info
Stoker, Thomas M
Abstract

This paper proposes nonparametric tests of additive constraints on the first and second derivatives of a model E(y/x) = g(x), where the true function g is unknown. Such constraints are illustrated by the economic restrictions of homogeneity and symmetry, and the functional form restrictions of additivity and linearity. The proposed tests are based on estimates of regression coefficients that statistically characterize the departures from the constraint exhibited by the data. The coefficients are based on weighted-average derivatives that are reformulated in terms of derivatives of the density of x. Coefficient estimators are proposed that use nonparametric kernel estimators of the density and its derivatives. These statistics are shown to be consistent and asymptotically normal, and, thus, are comparable to estimators based on a (correctly specified) parametric model of g(x). Copyright 1989 by The Review of Economic Studies Limited.

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Publisher Info
Article provided by Blackwell Publishing in its journal Review of Economic Studies.

Volume (Year): 56 (1989)
Issue (Month): 4 (October)
Pages: 535-52
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Handle: RePEc:bla:restud:v:56:y:1989:i:4:p:535-52

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  1. Halbert White & Yongmiao Hong, 1999. "M-Testing Using Finite and Infinite Dimensional Parameter Estimators," University of California at San Diego, Economics Working Paper Series 1993-01R, Department of Economics, UC San Diego. [Downloadable!]
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