Experimental data on social preferences present a number of features that need to be incorporated in econometric modelling. We explore a variety of econometric modelling approaches to the analysis of such data. The approaches under consideration are: the Random Utility approach ; the Random Behavioural approach ; and the Random Preference approach. These approaches are applied in various ways to an experiment on fairness conducted by Cappelen et al. :818–827, 2007). Various models that we estimate succeed in capturing the key (...) features of the dataset. Conclusions concerning fairness-related behaviour depend crucially on the choice of econometric model. (shrink)

Abstract.The starting point of deontic logic is the distinction between non‐normative necessity and normative necessity. The first part of the paper shows that the distinction between normative necessity and non‐normative necessity occurs already in Aristotle's Orgunon. The second part of the paper makes a further distinction within normative deon itself: The distinction between deontic deon and anankastic deon. Anankastic deon behaves differently from deontic deon in a very important respect: Deontic indifference has no anankastic counterpart.

This essay deals with the concept of negation in Deontics. In relation with this concept, the polish logician Jerzy Sztykgold seems to put forward these two thesis: a) a norm may have a negation; b) a norm may be a negation. Sztykgold studies the concept of Inegation of a norm through the analysis of other two concepts of a right or of a duty and the concept of opposition of behaviour), and, as early as 1936, he puts hirnself in a (...) clear position in relation to the problem of the possibility of a logic of norms: There is a deontic analogonof truth, which is the słuszność consequently, for the norms, entities of which the słuszność is predicated, are valid the thesis of the propositional logic that are valid for the apophantic sentences. (shrink)

Spousal correlation in risk attitude is estimated using data from the German Socio-Economic Panel over the period 2004–2009. We apply the bivariate panel ordered probit model to the analysis of the simultaneous determination of the male’s and the female’s risk attitude, using the survey question about general willingness to take risk, provided on a 0–10 Likert-scale. The correlations between both the individual-specific effects of the two partners and the two within-individual errors are separately estimated, and found to be +0.285 and (...) +0.310, respectively. We consider the former to be a key parameter, since its positive sign may be interpreted in terms of positive assortative mating on risk attitude: individuals tend to form partnerships with others having a similar risk attitude. We also find evidence that this correlation increases with years of marriage, suggesting either a form of spousal socialization or a selection process in which marriage breakdown is more likely in poorly matched couples. (shrink)

Panel data from the German SOEP is used to test for risk vulnerability in the wider population. Two different survey responses are analysed: the response to the question about willingness-to-take risk in general and the chosen investment in a hypothetical lottery. A convenient indicator of background risk is the VDAX index, an established measure of volatility in the German stock market. This is used as an explanatory variable in conjunction with HDAX, the stock market index, which proxies wealth. The impacts (...) of these measures on risk attitude are identifiable by exploiting the time dimension of the panel and matching survey months with corresponding observations from these time-varying factors. Both of the survey responses allow us to test for decreasing absolute risk aversion ; in one case, we find strong evidence of DARA, while in the other, we do not. Both survey responses also allow us to test for RV, and in both cases we find strong evidence. In the case of the hypothetical lottery response, we are also able to estimate a “coefficient of risk vulnerability”. This is defined as the absolute amount by which absolute risk aversion rises in response to a doubling of background risk. We estimate CRV to be between 1.03 and 1.27. (shrink)