[雙語(yǔ)翻譯]汽車保險(xiǎn)外文翻譯--汽車保險(xiǎn)的市場(chǎng)信息不對(duì)稱來(lái)自德國(guó)的證據(jù)（節(jié)選）

1、中文 中文 3285 字， 字，1800 英文單詞， 英文單詞，10800 英文字符 英文字符文獻(xiàn)出處： 文獻(xiàn)出處：Spindler M, Winter J, Hagmayer S. Asymmetric Information in the Market for Automobile Insurance: Evidence From Germany[J]. Journal of Risk & Insurance, 2014,

2、81(4):781-801.Asymmetric Information in the Market for Automobile Insurance: Evidence From GermanyMartin Spindler , Joachim Winter Steffen , HagmayerAbstractAsymmetric information is an important phenomenon in insurance

3、markets, but the empirical evidence on the extent of adverse selection and moral hazard is mixed. Because of its implications for pricing, contract design, and regulation, it is crucial to test for asymmetric information

4、 in specific insurance markets. In this article, we analyze a recent data set on automobile insurance in Germany, the largest such market in Europe. We present and compare a variety of statistical testing procedures. We

5、find that the extent of asymmetric information depends on coverage levels and on the specific risks covered, which enhances the previous literature. Within the framework of Chiappori et al. (2006), we also test whether d

6、rivers have realistic expectations concerning their loss distribution, and we analyze the market structure.IntroductionSince Akerlof (1970), the consequences of asymmetric information, in particular, ad- verse selection

7、and moral hazard, have been explored in a vast body of research. The initial gap between the theoretical developments and empirical studies of asymmetric information has recently become narrower. In particular, insurance

8、 markets have proved a fruitful and productive field for empirical studies, for two reasons. First, the data are well structured: insurance contracts are usually highly standardized, they can be described completely by a

9、 relatively small set of variables, and data on the insured person’s claim history, that is, the occurrence of claims and the associated costs, are stored in the database of an insurance company. Second, insurance compan

10、ies have hundreds of thousands or even millions of clients and therefore the samples are sufficiently large to conduct powerful statistical tests. The markets for automobile insurance, annuities and life insurance, crop

11、insurance, as well as long-term care and health insurance provide large samples of standardized contracts for which performances are recorded and are well suited for testing the theoretical predictions of insurance theor

12、y. Chiappori and Salanie´ (1997) provide a detailed justification for using insurance data to test contract theory. Cohen and Siegelman (2010) present a comprehensive overview of approaches for testing for adverse s

13、election in insurance markets, covering a large number of empirical studies in different insurance branches.In statistical terms, the notion of asymmetric information implies a positive (conditional) correlation between

14、coverage and risk. Several different methods that explain how to test for asymmetric information have been proposed in the literature. In this article, we apply an array of such tests to detailed contract-level data from

15、 the German car insurance market.Our study contributes to the existing literature in several respects. First, we present the first study analyzing the German car insurance market. The German car insurance market is the l

16、argest in Europe and therefore for many insurance companies the most important sales market for their insurance policies. We had unique access to the data set of one of the largest insurance companies in the field of aut

17、omobile insurance in Germany.Second, the empirical literature has reached an almost complete consensus that asymmetric basic model, the insureds have private information about the expected claim, exactly speaking about t

18、he probability that a claim with fixed level occurs, while the insurers do not have this information. Thus, there are two groups with different claim probabilities, the “bad” and “good” risks. The agents have identical p

19、references that are perfectly known to the insurer. Additionally, perfect competition and exclusive contracts are assumed. Exclusive contracts mean that an insured can buy coverage only from one insurance company. This a

20、llows firms to implement nonlinear (especially convex) pricing schemes that are typical under asymmetric information. In this setting, insurance companies offer a menu of contracts in equilibrium: a full insurance that i

21、s chosen by the “bad” risks and a partial coverage that is bought by the “good” risks. In general, contracts with more comprehensive coverage are sold at a higher (unitary) premium.Clearly, one expects a positive correla

22、tion between “risk” and “coverage” (conditional on observables). Since the assumptions in the Rothschild and Stiglitz model are very simplistic and normally not fulfilled in real applications, an important question to ad

23、dress is how robust this coverage–risk correlation is. Chiappori et al. (2006) show that the positive correlation property extends to much more general models under a suitably defined notion. In particular, the notion of

24、 positive correlation is generalized in this context. On competitive markets, this property is also valid in a very general framework entailing heterogeneous preferences, multiple level of losses, multidimensional advers

25、e selection plus possible moral hazard and even nonexpected utility theory.3 In the case of imperfect competition, some form of positive correlation must hold if the agent’s risk aversion becomes public information. In t

26、he case of private information, the property does not necessarily hold (see Jullien, Salanie´, and Salanie´, 2007).While adverse selection concerns “hidden information,” moral hazard deals with “hidden action.”

27、 Moral hazard occurs when the expected loss (accident probability or level of damage) is not exogenous, as assumed in the adverse selection case, but depends on some decision or action made by the insured (e.g., effort s

28、pent to prevent a damage) that is neither observable nor contractible. Higher coverage leads to de- creased effort and therefore to higher expected loss. Thus, moral hazard also predicts a positive correlation between co

29、verage and risk.To summarize, the theory of asymmetric information on insurance markets predicts a positive correlation between (appropriately defined) “risk” and “coverage,” a prediction that is quite robust across diff

30、erent theoretical models. Nevertheless, there is one important difference: under adverse selection, the risk of the potential insured affects the choice of the contract, whereas under moral hazard the chosen contract inf

31、luences behavior and therefore the expected loss. However, there exists reversed causality in both cases. It seems that the empirical insurance literature has concentrated on testing for adverse selection whereas the mor

32、al hazard aspect has received only minor attention (see, inter alia, Cohen and Siegelman, 2010).In order to test for asymmetric information, the researcher needs to have access to the same information that is available t

33、o the insurer (and used for pricing). The theory of adverse selection predicts that the insurance company offers a menu of contracts to indistinguishable individuals. Individuals are indistinguishable for the insurer if

34、they share the same characteristics. Therefore, the positive risk–coverage correlation is valid only conditional on the observed characteristics. In general, different classes of observationally equivalent individuals wi

35、ll be offered different menus of contracts with different prices according to their risk exposure.The mechanisms described above are valid only within each class.Despite the scarcity of data sets in empirical contract th