The Predictive Utility of Generalized Expected Utility Theories

Many alternative theories have been proposed to explain violations of expected utility (EU) theory observed in experiments. Several recent studies test some of these alternative theories against each other. Formal tests used to judge the theories usually count the number of responses consistent with the theory, ignoring systematic variation in responses that are inconsistent. We develop a maximum-likelihood estimation method which uses all the information in the data, creates test statistics that can be aggregated across studies, and enables one to judge the predictive utility-the fit and parsimony-of utility theories. Analyses of 23 data sets, using several thousand choices, suggest a menu of theories which sacrifice the least parsimony for the biggest improvement in fit. The menu is: mixed fanning, prospect theory, EU, and expected value. Which theories are best is highly sensitive to whether gambles in a pair have the same support (EU fits better) or not (EU fits poorly). Our method may have application to other domains in which various theories predict different subsets of choices (e.g., refinements of Nash equilibrium in noncooperative games)

Revisiting forever gained: income dynamics in the resettlement areas of Zimbabwe

This paper examines income dynamics for a panel of households resettled on former white-owned farms in the aftermath of Zimbabwe's independence. There are four core findings: (i) there has been an impressive accumulation of assets by these households; (ii) while this accumulation has played a role in increases in crop income, increases in returns to these assets have been especially important in generating the dramatic increase in crop incomes observed in these households; (iii) differences in initial conditions across these households, such as previous farming experience, have few persistent effects; and (iv) growth in incomes has been shared across all households, with the largest percentage increases in predicted incomes recorded by households that had the lowest predicted incomes at the beginning of the survey.

A Geneaology of Correspondence Analysis: Part 2 - The Variants

In 2012, a comprehensive historical and genealogical discussion of correspondence analysis was published in Australian and New Zealand Journal of Statistics. That genealogy consisted of more than 270 key books and articles and focused on an historical development of the correspondence analysis,a statistical tool which provides the analyst with a visual inspection of the association between two or more categorical variables. In this new genealogy, we provide a brief overview of over 30 variants of correspondence analysis that now exist outside of the traditional approaches used to analysethe association between two or more categorical variables. It comprises of a bibliography of a more than 300 books and articles that were not included in the 2012 bibliography and highlights the growth in the development ofcorrespondence analysis across all areas of research

Probabilistic performance estimators for computational chemistry methods: Systematic Improvement Probability and Ranking Probability Matrix. I. Theory

The comparison of benchmark error sets is an essential tool for the evaluation of theories in computational chemistry. The standard ranking of methods by their Mean Unsigned Error is unsatisfactory for several reasons linked to the non-normality of the error distributions and the presence of underlying trends. Complementary statistics have recently been proposed to palliate such deficiencies, such as quantiles of the absolute errors distribution or the mean prediction uncertainty. We introduce here a new score, the systematic improvement probability (SIP), based on the direct system-wise comparison of absolute errors. Independently of the chosen scoring rule, the uncertainty of the statistics due to the incompleteness of the benchmark data sets is also generally overlooked. However, this uncertainty is essential to appreciate the robustness of rankings. In the present article, we develop two indicators based on robust statistics to address this problem: P_{inv}, the inversion probability between two values of a statistic, and \mathbf{P}_{r}, the ranking probability matrix. We demonstrate also the essential contribution of the correlations between error sets in these scores comparisons

Cumulative chi-squared statistics for the service quality improvement: new properties and tools for the evaluation

In service quality evaluation, data are often categorical variables with ordered categories and collected in two way contingency table. The Taguchi’s statistic is a measure of the association between these variables as a simple alternative to Pearson’s test. An extension of this statistic for three way contingency tables handled in two way mode is introduced.We highlight its several properties, the approximated distribution, a decomposition according to orthogonal quantities reflecting the main effects and the interaction terms, and an extension of cumulative correspondence analysis based on it