A simple and effective misspecification test for the double-hurdle model☆
Section snippets
Introduction and motivation
The double-hurdle model is a commonly used model for dealing with double censoring. This model is well suited for analysing situations where a sample selection effect occurs and a corner zero solution is possible in the optimisation process by the individual. As such, it has been used in countless applications, such as labour market studies, in which the dependent variable is the number of hours worked (the classic reference here is Blundell et al. (1987)), migrant remittances (Bettin et al.,
Our proposed test
The test we propose builds on a conditional-moment approach originally proposed by Smith (1987), supplemented with a bootstrap correction to improve its poor finite-sample properties, as suggested by Horowitz (1994). A similar strategy was recently proposed by Lucchetti and Pigini (2013), who focused on testing the bivariate normality assumption in the bivariate probit and sample selection models.
This test uses the fact that, under correct specification, the information matrix equality implies
Monte Carlo study
Before going into the details of our Monte Carlo experiment, a word of warning is necessary. Numerical optimisation of the double-hurdle log-likelihood may be difficult in some cases for two reasons: first, as is well known among practitioners, the log-likelihood may be bimodal, especially in smaller samples2; moreover, the maximal value of may, in finite
Conclusions
Testing for misspecification in the double hurdle model is an important task that can be carried out very effectively by a conditional moment test.
Since the routine estimation technique is maximum likelihood, the relevant moment conditions can be chosen from those stemming from the information matrix equality. However, a bootstrap correction is absolutely indispensable. Moreover, the choice of the actual moment conditions to use in practice may be an issue.
In this article, we propose two
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Cited by (6)
Semiparametric Estimation of a Censored Regression Model Subject to Nonparametric Sample Selection
2022, Journal of Business and Economic StatisticsAdoption of crop insurance in Ghana: an application of the complementary log-log truncated Poisson double-hurdle model
2021, Agricultural Finance ReviewThe role of local leaders in regional development funding: Evidence from an elite survey
2020, Journal of Regional ScienceEvidence on copula-based double-hurdle models with flexible margins
2016, Empirical Economics
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The authors wish to thank, without implicating them for remaining errors, Chiara Gigliarano and an anonymous referee for their useful comments.