ADVERSE SELECTION AND MORAL HAZARD IN INSURANCE: CAN DYNAMIC DATA HELP TO DISTINGUISH?

被引：65

作者：

Abbring, Jaap H. ^{[1
]}

Heckman, James J. ^{[2
]}

Chiappori, Pierre-Andre ^{[2
]}

Pinquet, Jean ^{[3
]}

机构：

[1] Free Univ, Berlin, Germany

[2] Univ Chicago, Chicago, IL 60637 USA

[3] Univ Paris 10, F-92001 Nanterre, France

来源：

JOURNAL OF THE EUROPEAN ECONOMIC ASSOCIATION | 2003年 / 1卷 / 2-3期

关键词：

D O I：

10.1162/154247603322391152

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

A standard problem of applied contracts theory is to empirically distinguish between adverse selection and moral hazard. We show that dynamic insurance data allow to distinguish moral hazard from dynamic selection on unobservables. In the presence of moral hazard, experience rating implies negative occurrence dependence: individual claim intensities decrease with the number of past claims. We discuss econometric tests for the various types of data that are typically available. Finally, we argue that dynamic data also allow to test for adverse selection, even if it is based on asymmetric learning. (JEL: D82, G22, C41, C14)

引用

页码：512 / 521

页数：10

共 27 条

[21] Panel data discrete choice models with lagged dependent variables [J].