Testing exogeneity of multinomial regressors in count data models: does two stage residual inclusion work?

Geraci, Andrea ; Fabbri, Daniele ; Monfardini, Chiara (2014) Testing exogeneity of multinomial regressors in count data models: does two stage residual inclusion work? Bologna: Dipartimento di Scienze economiche DSE, p. 37. DOI 10.6092/unibo/amsacta/3937. In: Quaderni - Working Paper DSE (921). ISSN 2282-6483.
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Abstract

We study a simple exogeneity test in count data models with possibly endogenous multinomial treatment. The test is based on Two Stage Residual Inclusion (2SRI). Results from a broad Monte Carlo study provide novel evidence on important features of this approach in nonlinear settings. We find differences in the finite sample performance of various likelihood-based tests under correct specification and when the outcome equation is misspecified due to neglected over-dispersion or non-linearity. We compare alternative 2SRI procedures and uncover that standardizing the variance of the first stage residuals leads to higher power of the test and reduces the bias of the treatment coefficients. An original application in health economics corroborates our findings.

Abstract
Document type
Monograph (Working Paper)
Creators
CreatorsAffiliationORCID
Geraci, Andrea
Fabbri, Daniele
Monfardini, Chiara
Keywords
count data, endogenous treatment, exogeneity test, health care utilization
Subjects
ISSN
2282-6483
DOI
Deposit date
24 Jan 2014 10:40
Last modified
10 Feb 2014 11:13
URI

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