Academic journal article Journal of Risk and Insurance

Dynamic Moral Hazard: A Longitudinal Examination of Automobile Insurance in Canada

Academic journal article Journal of Risk and Insurance

Dynamic Moral Hazard: A Longitudinal Examination of Automobile Insurance in Canada

Article excerpt

INTRODUCTION

There is a vast literature in contract theory that addresses information asymmetry where one party possesses more information than the counterparty in an economic transaction. Historically, insurance has been a particularly promising field for studying contract design and for investigating asymmetric information both theoretically and empirically (see Dionne, Fombaron, and Doherty, 2013, for a recent review). Two distinct forms are adverse selection and moral hazard. The former predicts the positive relation between policyholders' risk and demand for insurance, and the latter concerns policyholders' behavior change due to the incentives provided in an insurance contract.

In this study, we aim to investigate information asymmetry in the context of dynamic contracting in automobile insurance, especially the effect of moral hazard on policyholders' driving behavior. After decades-long predominance of theoretical work in contract theory, empirical studies on contracts are attracting more attention recently, with a fair amount of work focusing on testing for the existence of private information in automobile insurance markets. Grounded on the theoretical prediction set forth by Rothschild and Stiglitz (1976), Stiglitz (1977), and Wilson (1977), the majority of the existing literature has resorted to the conditional correlation test for the identification of residual asymmetric information by examining the risk--coverage relationship within a risk class (see Cohen and Siegelman, 2010). The evidence is mixed. Using cross-sectional data in a static context, some studies find positive residual correlation, including Puelz and Snow (1994), Cohen (2005), Kim et al. (2009), Shi and Valdez (2011), and Shi, Zhang, and Valdez (2012), while others do not, for example, Chiappori and Salanie (2000) and Dionne, Gourieroux, and Vanasse (2001).

The conditional correlation approach is easy to implement; however, it is subject to the criticism of not being able to disentangle the effects of adverse selection and moral hazard. Addressing this issue, some recent studies have devoted attention to the identification of moral hazard from adverse selection using dynamic insurance data. The first efforts are due to Abbring et al. (2003) and Abbring, Chiappori, and Pinquet (2003), where the authors show that moral hazard can be distinguished from selection on unobservables from the dynamics in claims. Specifically, experience rating implies negative dependence in claim intensity under moral hazard. This prediction was then tested using data in the French market and little evidence of moral hazard was found. More recently, Abbring, Chiappori, and Zavadil (2008) extend the test by differentiating the ex ante and ex post moral hazard, and with additional structural assumptions, they detect moral hazard in the Netherlands. Instead of looking into dynamics of claims, Dionne et al. (2011) examine the demerit points in the public automobile insurance market in the Quebec and also find evidence of moral hazard. Using a unique longitudinal survey data where both reported and unreported accidents are observed, Dionne, Michaud, and Dahchour (2013) are able to distinguish dynamic moral hazard from asymmetric learning in the French automobile insurance market. Recent evidence of asymmetric learning in automobile insurance markets also includes Cohen (2012) and Shi and Zhang (2014). Note that the learning problem in Dionne, Michaud, and Dahchour (2013) is between the insured and the insurer where the insured learns on his risk by observing accidents, while in Cohen (2012) and Shi and Zhang (2014) the learning problem is between insurance companies about the insured.

The current study is more in line with Abbring, Chiappori, and Pinquet (2003) in that we test the existence of moral hazard by investigating the state dependence of driving behavior using dynamic insurance data. To emphasize our departure from the literature, we conduct our investigation in an insurance system that features a very different merit rating system. …

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