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In the unidimensional poverty field, a number of axioms capture the distribution sensitivity among the poor. One of them is the monotonicity sensitivity axiom that demands that a poverty measure should be more sensitive to a reduction in the income of a poor person, the poorer that person is. On the other hand, the minimal transfer axiom requires poverty to decrease when a transfer of income is made from a poor person to a poorer one. These axioms turn out to be identical, but they provide different and interesting interpretations. Both of them rely deeply on the income-ranking of the poor.

Some generalizations of the minimal transfer axiom and its variations have been proposed in the multidimensional framework. In none of them the partial ordering of the poor is taken into account. No counterpart of the monotonicity sensitivity axiom exists.

This note introduces multidimensional generalizations of the two mentioned axioms, keeping the crucial assumption that only when the poor involved are unambiguously ranked are the axioms uncontroversial. We show that the two generalizations proposed are also identical in the multidimensional setting although offering different interpretations. Relationships between the new properties and those existing in the literature are analyzed.

The paper is dedicated to the analysis of fuzzy similarity measures in uncertainty analysis in general, and in economic decision-making in particular. The purpose of this paper is to explain how a similarity measure can be chosen to quantify a qualitative description of similarities provided by experts of a given domain, in the case where the objects to compare are described through imprecise or linguistic attribute values represented by fuzzy sets. The case of qualitative dissimilarities is also addressed and the particular case of their representation by distances is presented.

The approach is based on measurement theory, following Tversky’s well-known paradigm.

A list of axioms which may or may not be satisfied by a qualitative comparative similarity between fuzzy objects is proposed, as extensions of axioms satisfied by similarities between crisp objects. They enable to express necessary and sufficient conditions for a numerical similarity measure to represent a comparative similarity between fuzzy objects. The representation of comparative dissimilarities is also addressed by means of specific functions depending on the distance between attribute values.

Examples of functions satisfying certain axioms to represent comparative similarities are given. They are based on the choice of operators to compute intersection, union and difference of fuzzy sets. A simple application of this methodology to economy is given, to show how a measure of similarity can be chosen to represent intuitive similarities expressed by an economist by means of a quantitative measure easily calculable. More detailed and formal results are given in Coletti and Bouchon-Meunier (2020) for similarities and Coletti et al. (2020) for dissimilarities.

Our purpose is to examine the “envy” within the context of income inequality measurement.

We use a simple axiomatic structure that takes into account “envy” in the income distribution. The concept of envy incorporated here concerns the distance of each person's income from his or her immediately richer neighbour.

We derive two classes of inequality indices – absolute and relative. The envy concept is shown to be similar to justice concepts based on income relativities.

This is the first time a complete characterisation has been provided for envy-related inequality.

The purpose of this paper is to solve the problem existing in the forecast of impact disturbance grey system.

Under the axiomatic system of buffer operator in grey system theory, a novel kind of buffer operators with variable weight λ based on the principle of average tempo of time sequence and using new information is proposed. The optimization solution for variable weight λ is obtained by using genetic algorithm. It is proved that the new buffer operators are effective.

The results show that the new buffer operators accord with the buffer operator's three axioms and the monotonicity non‐variable axiom. It is proved theoretically and in practice that the new buffer operators are more useful than other buffer operators in grey modeling for sequence with impact disturbance.

The novel buffer operators can reduce the randomness of grey sequence distorted by impact factors, and the forecast accuracy of a model which is built through the process with a novel buffer operator is significantly increased.

The paper succeeds in constructing two novel buffer operators with variable weight and the properties of novel operators are studied. The method to solve optimization value of weight is proposed. The method widens the scope of grey model application.

The dominant theory of individual decision making under uncertainty is the von Neumann and Morgenstern's expected utility model (EUM). Although, this model has gained its popularity from its ability to explain a wide range of attitudes toward risk, empirical evidence over the last three decades has documented paradoxical behavior that is inconsistent with the EUM model. The present study examines in an experimental setting individuals' inconsistent behavior in choosing between two pairs of lotteries known as the Allais paradox. This study extends previous literature on money gamble situations by conducting a series of experiments to test expected utility behavior on auditing student subjects in pure money and audit settings. Two variants of audit settings are examined: overall audit plan case and audit procedure evaluation of internal control case.

The idea of using stochastic control methods for theoretical studies of portfolio management has long been standard, with maximum expected utility criteria commonly being used. But in recent years a new kind of criterion, the risk sensitive criterion, has emerged from the control theory literature and been applied to portfolio management. This paper studies various economic properties of this criterion for portfolio management, thereby providing justification for its theoretical and practical use. In particular, it is shown that the risk sensitive criterion amounts to maximizing a portfolio's risk adjusted growth rate. In other words, it is essentially the same as what is commonly done in practice: find the best trade‐off between a portfolio's average return and its average volatility.

The purpose of this paper is to expand the peer effect analysis to investments in the stock market, where neither direct competition nor interaction with other investors exists.

A total of 772 subjects dwelling in six countries completed a questionnaire about their satisfaction with the performance of their hypothetical investment in the stock market. They were informed about the performance of the local stock market and the performance of their peer group, referred to in the questionnaire as their “friends.”

Only 5 per cent of subjects are indifferent to their friends’ investment performance, as advocates by expected utility paradigm. Most subjects are happier when their friends earn lower rather than higher returns. On average, subjects are better off losing rather than gaining money as long as their friends lose more money, which violates the univariate monotonicity axiom. A negligible number of subjects exhibit a consistent favorable response, which is a necessary condition for pure economic altruism. Hostility is greater in less-wealthy countries. No link is found with regard to economic inequality.

This paper shows that when a conflict between absolute wealth and relative wealth arises, the latter dominates, even when the comparison is not with an opponent or a colleague but with the subject’s friends. The astonishing result is that subjects prefer having less wealth as long as their friends lose more, despite no direct competition between subjects as in ultimatum games and despite the performance being equal to market performance.

An axiomatic approach is used to propose a measure of extreme poverty which is not only multidimensional in nature, but also recognizes the fact that there are interaction effects between different deprivations, and that the length of time during which deprivations are felt may also have a negative impact on household well-being. The proposed definition of extreme poverty formalizes an approach developed by Joseph Wresinski, the founder of the International Movement ATD Fourth World.

The purpose of this study is to estimate the convergence order of the Aumann–Serrano Riskiness Index.

This study uses the equivalent relation between the Aumann–Serrano Riskiness Index and the moment generating function and aggregately compares between each two statistical moments for statistical significance. Thus, this study enables to find the convergence order of the index to its stable value.

This study finds that the first-best estimation of the Aumann–Serrano Riskiness Index is reached in no less than its seventh statistical moment. However, this study also finds that its second-best approximation could be achieved with its second statistical moment.

The implications of this research support the standard deviation as a statistically sufficient approximation of Aumann–Serrano Riskiness Index, thus strengthening the CAPM methodology for asset pricing in the financial markets.

This research sheds a new light, both in theory and in practice, on understanding of the risk’s structure, as it may improve accuracy of asset pricing.

The purpose of this paper is to increase the accuracy of the efficient portfolios frontier and the capital market line using the Riskiness Index.

This paper will develop the mean-riskiness model for portfolio selection using the Riskiness Index.

This paper’s main result is establishing a mean-riskiness efficient set of portfolios. In addition, the paper presents two applications for the mean-riskiness portfolio management method: one that is based on the multi-normal distribution (which is identical to the MV model optimal portfolio) and one that is based on the multi-normal inverse Gaussian distribution (which increases the portfolio’s accuracy, as it includes the a-symmetry and tail-heaviness features in addition to the scale and diversification features of the MV model).

The Riskiness Index is not a coherent measurement of financial risk, and the mean-riskiness model application is based on a high-order approximation to the portfolio’s rate of return distribution.

The mean-riskiness model increases portfolio management accuracy using the Riskiness Index. As the approximation order increases, the portfolio’s accuracy increases as well. This result can lead to a more efficient asset allocation in the capital markets.