Insurance Intermediation: An Economic Analysis of the by Martina Eckardt

By Martina Eckardt

Assurance intermediaries will help shoppers to save money on info and transaction charges in assurance markets. in spite of the fact that, competing intermediaries offer heterogeneous details providers, that are tricky to evaluate through incompletely trained shoppers. behavior and function available in the market for coverage details companies are analyzed by means of making use of seek theoretical and commercial association techniques. according to a pattern of 927 coverage intermediaries, the criteria that have an effect on the standard of the knowledge companies supplied through them are studied empirically. the implications received aid the most hypotheses derived from commercial association theories as to the bad operating of caliber festival less than incomplete and uneven details at the facet of shoppers. therefore, public coverage may still pay attention to expanding transparency approximately intermediaries' (in-)dependence from insurance firms and increase shoppers' monetary literacy to elevate the general caliber within the details companies marketplace.

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1 Insurance Intermediaries in the Basic Intermediation Model Like in the basic model (Sect. 1) three types of actors are engaged in the market: insurance companies, insurance intermediaries and consumers. Insurance companies offer a variety of differentiated insurance products. They are assumed to behave passively in all other respects. There is only one insurance intermediary in the market, who maximizes his profits. It is further assumed that consumers seek to maximize their utility by deciding either on personal or intermediated search activities.

In this case the expected net reward from a further observation is G ( X m ) 0 . If X m  x * a further search step would still increase the expected net reward, while if X m ! x * an additional search step would reduce the expected net reward. Therefore, G ( X m ) 0 signals the optimal stopping rule for the consumer’s search activities. This result can be transformed to obtain the consumer’s maximum utility by introducing the utility function U j X i . It represents the valuation of the jth searcher for a certain attribute value Xi of the random variable X (Rose 1999, 89–90).

E O˜ X ! 0 I wc 1 F X > @ Second Order Partial Derivative w2 wc 2 C I . 18) I I w c˜ f X I w2 C I . c ˜ O ˜ e O˜X ! 0 C I . c ˜ O2 ˜ e O ˜ X ! 1. ) First Order Partial Derivative Density of High Quality Information Ȝ · w I w §¨ c ¸ C . wO wO ¨© 1  F X I ¸¹ > @ Second Order Partial Derivative w2 wO2 C I . c ˜ X I 2 I ˜ e O˜ X ! 0 ¨c ˜ e ¸ c˜ X ˜e ¹ wO © Source: Following Rose (1999, 101). The total search costs are the higher, the higher the costs of a single observation c, the higher the optimal reservation value X I or the lower the density Ȝ of high quality objects in the distribution are (Fig.

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