Estimating the binary endogenous effect of insurance on doctor visits by copula‐based regression additive models

Giampiero Marra, Rosalba Radice and David Zimmer

Journal of the Royal Statistical Society Series C, 2020, vol. 69, issue 4, 953-971

Abstract: The paper estimates the causal effect of having health insurance on healthcare utilization, while accounting for potential endogeneity bias. The topic has important policy implications, because health insurance reforms implemented in the USA in recent decades have focused on extending coverage to the previously uninsured. Consequently, understanding the effects of those reforms requires an accurate estimate of the causal effect of insurance on utilization. However, obtaining such an estimate is complicated by the discreteness inherent in common measures of healthcare usage. The paper presents a flexible estimation approach, based on copula functions, that consistently estimates the coefficient of a binary endogenous regressor in count data settings. The relevant numerical computations can be easily carried out by using the freely available GJRM R package. The empirical results find significant evidence of favourable selection into insurance. Ignoring such selection, insurance appears to increase doctor visit usage by 62% but, adjusting for it, the effect increases to 134%.

Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.1111/rssc.12419

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:bla:jorssc:v:69:y:2020:i:4:p:953-971

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().