EconPapers    
Economics at your fingertips  
 

Testing for monotonicity under endogeneity

Daniel Gutknecht

Journal of Econometrics, 2016, vol. 190, issue 1, 100-114

Abstract: This paper develops a test for monotonicity of nonparametric regression models under endogeneity, which in its generality is novel in the literature. The test statistic, which is built upon a second order U-process, introduces ‘correction terms’ based on control functions that purge the endogeneity. The test has a non-standard asymptotic distribution from which asymptotic critical values can directly be derived. Furthermore, the test statistic is extended to accommodate multivariate (exogenous) regressors. Consistency against general alternatives is proved and the finite sample properties of the test are examined in a Monte Carlo experiment. The test is used to formally assess the monotonicity of the reservation wage as a declining function of elapsed unemployment duration, which has implications for underlying job search models. This relationship is difficult to measure due to the simultaneity of both variables. Results for UK data indicate that reservation wage functions do in fact not decline monotonically thereby contradicting some partial equilibrium job search models.

Keywords: Control function; Endogeneity; Reservation wages; Test for monotonicity (search for similar items in EconPapers)
JEL-codes: C14 C36 C54 J64 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407615002341
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:190:y:2016:i:1:p:100-114

DOI: 10.1016/j.jeconom.2015.09.002

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 ().

 
Page updated 2025-03-19
Handle: RePEc:eee:econom:v:190:y:2016:i:1:p:100-114