A consistent nonparametric bootstrap test of exogeneity

This paper proposes a novel way of testing exogeneity of an explanatory variable without any parametric assumptions in the presence of a "conditional" instrumental variable. A testable implication is derived that if an explanatory variable is endogenous, the conditional distribution of the outcome given the endogenous variable is not independent of its instrumental variable(s). The test rejects the null hypothesis with probability one if the explanatory variable is endogenous and it detects alternatives converging to the null at a rate n^{-1/2}. We propose a consistent nonparametric bootstrap test to implement this testable implication. We show that the proposed bootstrap test can be asymptotically justified in the sense that it produces asymptotically correct size under the null of exogeneity, and it has unit power asymptotically. Our nonparametric test can be applied to the cases in which the outcome is generated by an additively non-separable structural relation or in which the outcome is discrete, which has not been studied in the literature.Postprin

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

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

GMM for panel count data models

This paper gives an account of the recent literature on estimating models for panel count data. Specifically, the treatment of unobserved individual heterogeneity that is correlated with the explanatory variables and the presence of explanatory variables that are not strictly exogenous are central. Moment conditions are discussed for these type of problems that enable estimation of the parameters by GMM. As standard Wald tests based on efficient two-step GMM estimation results are known to have poor finite sample behaviour, alternative test procedures that have recently been proposed in the literature are evaluated by means of a Monte Carlo study.GMM, exponential models, hypothesis testing

GMM for panel count data models

This chapter gives an account of the recent literature on estimating models for panel count data. Specifically, the treatment of unobserved individual heterogeneity that is correlated with the explanatory variables and the presence of explanatory variables that are not strictly exogenous are central. Moment conditions are discussed for these type of problems that enable estimation of the parameters by GMM. As standard Wald tests based on efficient two-step GMM estimation results are known to have poor finite sample behaviour, alternative test procedures that have recently been proposed in the literature are evaluated by means of a Monte Carlo study.GMM, Exponential Models, Hypothesis Testing

On the Empirical Finding of a Higher Risk of Poverty in Rural Areas: Is Rural Residence Endogenous to Poverty?

Includes: On the Empirical Finding of a Higher Risk of Poverty in Rural Areas: Is Rural Residence Endogenous to Poverty?:COMMENT, by Thomas A. Hirschl; On the Empirical Finding of a Higher Risk of Poverty in Rural Areas: Is Rural Residence Endogenous to Poverty?: REPLY, by Monica Fisher. Research shows people are more likely to be poor in rural versus urban America. Does this phenomenon partly reflect that people who choose rural residence have unmeasured attributes related to human impoverishment? To address this question, two models are estimated using Panel Study of Income Dynamics data. A single equation Probit model of individual poverty replicates the well-documented finding of higher poverty risk in rural places. However, an instrumental variables approach, accounting for correlation between rural residence and the poverty equation error term, finds no measured effect of rural location on poverty. Results suggest failure to correct for endogeneity or omitted variable bias may overestimate the "rural effect."endogeneity, instrumental variables, omitted variable bias, poverty, rural, Food Security and Poverty,

De-mystifying the Inconvenient Truth : Does Ex Post Moral Hazard Indeed Exist in Korean Private Health Insurance Market?

There have been heated debates on whether private health insurance creates moral hazard effects. Despite its importance, however, the moral hazard problem of private health insurance is still controversial and understudied. To empirically examine whether or not moral hazard exists in the Korean private health insurance market, we employed two-stage regression for endogeneity control and the Heckman two-step procedure for sample selection bias control, which are expected to produce consistent estimates. All estimation results do not allow us to detect the presence of the moral hazard effects and imply that people hold private health insurance simply as “safety net”.Private Health Insurance, Moral Hazard, Endogeneity, Sample Selection Bias

A global analysis of third generation mobile telecommunications market entry

National regulatory authorities (NRAs) attempt to encourage participation in spectrum assignments by enhancing entrants' likelihood of success. The question this study addresses is: Can NRA policy tools really affect the probability an entrant wins a 3G spectrum licence? In particular, the econometric analysis allows consideration of whether licence concession or mode of assignment encourages entry. The study finds that auction assignment processes only slightly increase the probability of entry, whilst price and quantity concessions have no impact. --Market entry,global mobile telephone markets,3G spectrum assignment