Heterogeneity and the nonparametric analysis of consumer choice: conditions for invertibility

This paper considers structural nonparametric random utility models for continuous choice variables. It provides sufficient conditions on random preferences to yield reduced- form systems of nonparametric stochastic demand functions that allow global invertibility between demands and random utility components. Invertibility is essential for global identifcation of structural consumer demand models, for the existence of well-specified probability models of choice and for the nonparametric analysis of revealed stochastic preference

Contraction Consistent Stochastic Choice Correspondence

We model a general choice environment via probabilistic choice correspondences, with (possibly) incomplete domain and infinite universal set of alternatives. We offer a consistency restriction regarding choice when the feasible set contracts. This condition, 'contraction consistency', subsumes earlier notions such as Chernoff's Condition, Sen's α and β, and regularity. We identify a restriction on the domain of the stochastic choice correspondence, under which contraction consistency is equivalent to the weak axiom of revealed preference in its most general form. When the universal set of alternatives is finite, this restriction is also necessary for such equivalence. Analogous domain restrictions are also identified for the special case where choice is deterministic but possibly multi-valued. Results due to Sen (Rev Econ Stud 38: 307-317, 1971) and Dasgupta and Pattanaik (Econ Theory 31: 35-50, 2007) fall out as corollaries. Thus, conditions are established, under which our notion of consistency, articulated only in reference to contractions of the feasible set, suffices as the axiomatic foundation for a general revealed preference theory of choice behaviour.stochastic choice correspondence, contraction consistency, regularity, Chernoff’s condition, weak axiom of revealed preference, weak axiom of stochastic revealed preference, complete domain, incomplete domain

ENVIRONMENTAL RISK AND AGRI-ENVIRONMENTAL POLICY DESIGN

Agricultural nonpoint pollution is inherently stochastic (e.g., due to weather). In theory, this randomness has implications for the choice and design of policy instruments. However, very few empirical studies have modeled natural variability. This paper investigates the importance of stochastic processes for the choice and design of alternative nonpoint instruments. The findings suggest that not explicitly considering the stochastic processes in the analysis can produce significantly biased results.Agricultural and Food Policy, Environmental Economics and Policy,

STOCHASTIC CHOICE ANALYSIS OF TOURISM DESTINATIONS

The analysis of tourist destination choice, defined by intra-country administrative units and by product types "coastal/inland and village/city", permits the characterisation of tourist flow behaviour, which is fundamental for public planning and business management. In this study, we analyse the determinant factors of tourist destination choice, proposing various research hypotheses relative to the impact of destination attributes and the personal characteristics of tourists. The methodology applied estimates Nested and Random Coefficients Multinomial Logit Models, which allow control over possible correlations among different destinations. The empirical application is realised in Spain on a sample of 3,781 individuals and allows us to conclude that prices, distance to the destination and personal motivations are determinants in destination choice.Tourism Marketing, Intra-country destination, Coastal/inland, Village/city, Nested and Random Coefficients Logit Models.

Maximum principle for a stochastic delayed system involving terminal state constraints

We investigate a stochastic optimal control problem where the controlled system is depicted as a stochastic differential delayed equation; however, at the terminal time, the state is constrained in a convex set. We firstly introduce an equivalent backward delayed system depicted as a time-delayed backward stochastic differential equation. Then a stochastic maximum principle is obtained by virtue of Ekeland's variational principle. Finally, applications to a state constrained stochastic delayed linear-quadratic control model and a production-consumption choice problem are studied to illustrate the main obtained result.Comment: 16 page

Improved Portfolio Choice using Second-Order Stochastic Dominance

We examine the use of second-order stochastic dominance as both a way to measure performance and also as a technique for constructing portfolios. Using in-sample data, we construct portfolios such that their second-order stochastic dominance over a typical pension fund benchmark is most probable. The empirical results based on 21 years of daily data suggest that this portfolio choice technique significantly outperforms the benchmark portfolio out-of-sample. As a preference-free technique it will also suit any risk-averse investor in e.g. a pension fund. Moreover, its out-of-sample performance across eight different measures is superior to widely discussed portfolio choice approaches such as equal weights, mean variance, and minimum-variance methods.second-order stochastic dominance, portfolio choice, portfolio measurement