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Consider a quasiconcave, upper semicontinuous and homogeneous of degree γ function f. This paper shows that the reciprocal of the degree of homogeneity, 1 / γ , can be interpreted as a measure of the degree of concavity of f. As a direct implication of this result, it is also shown that f is harmonically concave if γ ≤ - 1 or γ ≥ 0 , concave if 0 ≤ γ ≤ 1 and logconcave if γ ≥ 0 . Some relevant applications to economic theory are given. For example, it is shown that a quasiconcave and homogeneous production function is concave if it displays nonincreasing returns to scale and logconcave if it displays increasing returns to scale. [ABSTRACT FROM AUTHOR]

The Houtman–Maks index is a measure of the size of a violation of utility-maximizing (that is, rational) behavior. In this article, we introduce the command hmindex, which calculates the Houtman–Maks index for a dataset of prices and observed choices of a consumer. The command is illustrated with an empirical application. [ABSTRACT FROM AUTHOR]

The revealed preference approach in economics is central to the empirical analysis of consumer behavior. In this article, we introduce the commands checkax, aei, and powerps as a bundle within the package rpaxioms. The first command allows a user to test whether consumer expenditure data satisfy several revealed preference axioms; the second command calculates measures of goodness of fit when the data violate these axioms; and the third command calculates power against uniformly random behavior as well as predictive success for each axiom. We illustrate the commands using individual-level experimental data and household-level aggregate consumption data. [ABSTRACT FROM AUTHOR]

This paper proposes new power indices for revealed preference tests. The indices are based on models of irrational consumption behavior where the consumer randomly allocates a certain fraction of expenditure. The methods allow a researcher to trace out the entire power curve against random expenditure allocation. The power indices are illustrated on altruistic choices in experimental data. [ABSTRACT FROM AUTHOR]

Highlights • Proposes method to recover homothetic preferences from choices with optimization errors. • Allows for a more detailed graphical analysis to reveal subjects' preferences. • Can extend applications of the money metric function. • Can be used to classify choices into different preference types. Abstract We introduce a method to recover homothetic preferences from choice data with minor optimization or measurement errors. Our method allows for a more detailed graphical analysis to reveal subjects' preferences and to choose appropriate functional forms for parametric analysis. It has also various other uses such as improving applications of the money metric function or classifying choice data into different preference types. We illustrate some of those approaches using data from an experiment on social preferences. [ABSTRACT FROM AUTHOR]