Testing single-index restrictions with a focus on average derivatives

Juan Carlos Escanciano and Kyungchul Song

Journal of Econometrics, 2010, vol. 156, issue 2, 377-391

Abstract: This paper considers a situation where the violation of a single-index restriction is a concern only to the extent that it causes bias to the estimates of the average derivatives. We propose a method to construct tests that concentrate their asymptotic powers upon only such interesting alternatives. The test has a limiting distribution under the null hypothesis, and even accommodates the case where the parameter estimates have a convergence rate slower than as in the case of maximum score estimation. The testing procedure can be easily modified when the main interest lies in average increment effects of binary covariates, multivariate average derivatives or linear restrictions other than those of average derivatives. Results from Monte Carlo experiments show that the asymptotic theory is a reasonable approximation of the finite-sample distributions and an application of our methods to female labor market participation illustrates the importance of this non-omnibus approach.

Keywords: Single-index; restrictions; Average; derivatives; Omnibus; tests; Directional; tests; Series; estimation (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304-4076(09)00296-6
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:156:y:2010:i:2:p:377-391

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu (repec@elsevier.com).