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SPECIFICATION TESTING WHEN THE NULL IS NONPARAMETRIC OR SEMIPARAMETRIC

Published online by Cambridge University Press:  18 September 2014

Juan M. Rodríguez-Póo ,
Stefan Sperlich  and
Philippe Vieu
Juan M. Rodríguez-Póo*
Affiliation:
Universidad de Cantabria
Stefan Sperlich
Affiliation:
Université de Genève
Philippe Vieu
Affiliation:
Université Paul Sabatier
*
*Address correspondence to Juan Manuel Rodriguez-Poo, Departamento de Economía, Universidad de Cantabria, Avda. de los Castros s/n, 39005, Santander, Spain; e-mail: rodrigjm@unican.es
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Abstract

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This paper discusses the problem of testing misspecifications in semiparametric regression models for a large family of econometric models under rather general conditions. We focus on two main issues that typically arise in econometrics. First, many econometric models are estimated through maximum likelihood or pseudo-ML methods like, for example, limited dependent variable or gravity models. Second, often one might not want to fully specify the null hypothesis. Instead, one would rather impose some structure like separability or monotonicity. In order to address these points we introduce an adaptive omnibus test. Special emphasis is given to practical issues like adaptive bandwidth choice, general but simple requirements on the estimates, and finite sample performance, including the resampling approximations.

Information

Type
ARTICLES
Information
Econometric Theory , Volume 31 , Issue 6 , December 2015 , pp. 1281 - 1309
Copyright
Copyright © Cambridge University Press 2014 

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