A Multinomial Logit Based Evaluation of the Behavior of the Life Insureds in Romania
ABSTRACT The Romanian life insurance market is in full expansion. There exists competition between insurance companies as well as between different products of the same company. In this article we describe a study using data that we collected from clients of a Romanian insurance company. We have observed two types of variables: attributes of the insurance products (e.g., profitability, risk), as well as characteristics of the individuals (e.g., sex, age, income). Using elements of economic theory and a multinomial logit model we explain the behavior of the life insureds. We estimate the variations in the market shares of life insurance products using marginal effects. The variations are due to possible changes in the values of some attributes or characteristics.
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ABSTRACT: This article considers the problem of "supply-and-demand" analysis on a cross section of oligopoly markets with differentiated products. The primary methodology is to assume that demand can be described by a discrete-choice model and that prices are endogenously determined by price-setting firms. In contrast to some previous empirical work, the techniques explicitly allow for the possibility that prices are correlated with unobserved demand factors in the cross section of markets. The article proposes estimation by "inverting" the market-share equation to find the implied mean levels of utility for each good. This method allows for estimation by traditional instrumental variables techniques.The RAND Journal of Economics 01/1994; 25(2):242-262. · 1.49 Impact Factor
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ABSTRACT: The numerical certainty scale (NCS) and polychotomous choice (PC) methods are two widely used techniques for measuring preference uncertainty in contingent valuation (CV) studies. The NCS follows a numerical scale and the PC is based on a verbal scale. This paper presents results of two experiments that use these preference uncertainty measurement techniques. The first experiment was designed to compare and contrast the uncertainty scores obtained from the NCS and the PC method. The second experiment was conducted to test a preference uncertainty measurement scale which combines verbal expressions with numerical and graphical interpretations: a composite certainty scale (CCS). The construct validity of the certainty scores obtained from these three techniques was tested by estimating three separate ordered probit regression models. The results of the study can be summarized in three key findings. First, the PC method generates a higher proportion of ‘Yes’ responses than the conventional dichotomous choice elicitation format. Second, the CCS method generates a significantly higher proportion of certain responses than the NCS and the PC methods. Finally, the NCS method performs poorly in terms of construct validity. We conclude that, overall, the verbal measures perform better than the numerical measure. Furthermore, the CCS method is promising in measuring preference uncertainty in CV studies. However, further empirical applications are required to develop a better understanding of its strengths and the weaknesses.The Journal of Business. 01/1980; 53(3):13-29.