Data and Code for: Long-Term Care Insurance: Information Frictions and Selection

Principal Investigator(s): View help for Principal Investigator(s) Martin Boyer, HEC Montreal; Philippe De Donder, Toulouse School of Economics; Claude Denys Fluet, Université Laval; Marie-Louise Leroux, UQAM; Pierre-Carl Michaud, HEC Montreal

Version: View help for Version V1

Name	File Type	Size	Last Modified
__pycache__			11/05/2019 02:16:PM
old			11/05/2019 02:16:PM
__init__.py	text/x-python		11/05/2019 09:15:AM
asym.py	text/x-python	8.3 KB	11/05/2019 09:15:AM
costs.py	text/x-python	3.3 KB	11/05/2019 09:15:AM
demand.py	text/x-python	1.4 KB	11/05/2019 09:15:AM

Project Description

Summary:

This paper conducts a stated-choice experiment where respondents are asked to rate various insurance products aimed to protect against financial risks associated with long-term care needs. Using exogenous variation in prices from the survey design and individual cost estimates, these stated-choice probabilities are used to predict market equilibrium for long-term care insurance. Our results are twofold. First, information frictions are pervasive. Second, measuring the welfare losses associated with frictions in a framework that also allows for selection, it is found that information frictions reduce equilibrium take-up and lead to large welfare losses while selection plays little role.

Scope of Project

JEL Classification:
      D82 Asymmetric and Private Information; Mechanism Design
      I13 Health Insurance, Public and Private
      J14 Economics of the Elderly; Economics of the Handicapped; Non-labor Market Discrimination

Geographic Coverage: Canada

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Published Versions

V1 [2020-07-23]

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