<?xml version='1.0' encoding='UTF-8'?><xml><records><record><source-app name="HighWire" version="7.x">Drupal-HighWire</source-app><ref-type name="Journal Article">17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kinnan, Cynthia</style></author></authors><secondary-authors></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Distinguishing Barriers to Insurance in Thai Villages</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Human Resources</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2022-01-01 00:00:00</style></date></pub-dates></dates><pages><style  face="normal" font="default" size="100%">44-78</style></pages><doi><style  face="normal" font="default" size="100%">10.3368/jhr.57.1.0219-10067R1</style></doi><volume><style face="normal" font="default" size="100%">57</style></volume><issue><style face="normal" font="default" size="100%">1</style></issue><abstract><style  face="normal" font="default" size="100%">Informal insurance is an important risk-coping mechanism in developing countries, yet this risk sharing is incomplete. Models of limited commitment, moral hazard, and hidden income have been proposed to explain incomplete informal insurance. This work shows that the way history matters in forecasting consumption can be used to distinguish hidden income from limited commitment and moral hazard. The paper also develops a nonparametric test that is robust to nonclassical measurement error and individual–level heterogeneity. In panel data from rural Thailand, limited commitment and moral hazard are rejected. The predictions of the hidden income model are supported by the data.</style></abstract></record></records></xml>