A Reexamination of the Relationship between Organizational Forms and Distribution Channels in the U.S. Property Liability Insurance Industry
-
Vincent Y. Chang
How do property liability insurance companies choose their organizational forms and distribution channels? Prior studies have not yet provided a consistent conclusion. In this paper, we propose a reduced form approach to reexamine the relationship between organizational forms and distribution channels in the insurance industry, using cross-sectional data pertaining to U.S. property liability insurance companies in 2004. We adopt a conditional dependence test, which can overcome the sensitivity problem of the structural form setting. The results show that after we control for all explanatory variables, the relationship between organizational forms and distribution channels is conditionally uncorrelated. The result is consistent with Regan and Tzeng (1999), but contradicts the findings of Baranoff and Sager (2003) and Kim et al. (1996).
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
Artikel in diesem Heft
- Featured Article
- A Reexamination of the Relationship between Organizational Forms and Distribution Channels in the U.S. Property Liability Insurance Industry
- An Equilibrium Analysis of the Insurance Market with Horizontal Differentiation
- On Modeling Diversification Benefits in Insurance Portfolios--An Australian Perspective
- Asymptotic Tail Probability of Randomly Weighted Sum of Dependent Heavy-Tailed Random Variables
- Survival Mixture Model for Credit Risk Analysis
- A Simple Metric for Gauging Risk Aversion
Artikel in diesem Heft
- Featured Article
- A Reexamination of the Relationship between Organizational Forms and Distribution Channels in the U.S. Property Liability Insurance Industry
- An Equilibrium Analysis of the Insurance Market with Horizontal Differentiation
- On Modeling Diversification Benefits in Insurance Portfolios--An Australian Perspective
- Asymptotic Tail Probability of Randomly Weighted Sum of Dependent Heavy-Tailed Random Variables
- Survival Mixture Model for Credit Risk Analysis
- A Simple Metric for Gauging Risk Aversion
