Ellsberg's famous paradox challenged Savage's subjective expected utility theory (EUT) – which reduces uncertainty to risk – by suggesting an aversion toward ambiguity. We provide a revealed preference test of the full set of axioms underpinning subjective EUT under uncertainty and compare it to an analogous test of objective EUT under risk. We find that individual choices are as consistent with utility maximization and expected utility maximization under uncertainty as they are under risk. Nevertheless, there is greater empirical scope for non-EUT models under uncertainty than under risk, and the absolute and relative consistency of EUT and non-EUT models vary considerably across subjects.

The Allais critique of expected utility theory (EUT) has led to the development of theories of choice under risk that relax the independence axiom but adhere to the fundamental/conventional axioms of ordering (completeness and transitivity) and monotonicity (with respect to first-order stochastic dominance). Unlike experimental work designed to test independence, our experiment is comprehensive, testing the entire set of axioms on which EUT is based. Our econometric analysis is also nonparametric and performed at the level of each individual subject. For the vast majority of subjects, departures from independence are small relative to departures from ordering and/or monotonicity.

The standard criterion of rationality in economics is the maximization of a utility function that is stable across multiple observations of an agent's choice behavior. In this paper, we discuss two notions of the money pump that characterize two corresponding notions of utility-maximization. We explain the senses in which the amount of money that can be pumped from a consumer is a useful measure of the consumer's departure from utility-maximization.

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.

This note explains the equivalence between approximate rationalizability and approximate cost-rationalizability within the context of consumer demand. In connection with these results, we interpret Afriat's (1973) critical cost-efficiency index (CCEI) as a measure of approximate rationalizability through cost inefficiency, in the sense that an agent is spending more money than is required to achieve her utility targets.

We develop a nonparametric method, called Generalized Restriction of Infinite Domains (GRID), for testing the consistency of budgetary choice data with models of choice under risk and under uncertainty. Our test can allow for risk-loving and elation-seeking attitudes, or it can require risk aversion. It can also be used to calculate, via Afriat’s efficiency index, the magnitude of violations from a particular model. We evaluate the performance of various models under risk (expected utility, disappointment aversion, rank-dependent utility, and stochastically monotone utility) using data collected from several recent portfolio choice experiments. (JEL C14, D11, D12, D81)

The package contains three commands. checkax allows the user to test whether consumer demand data satisfy certain revealed preference axioms at a given efficiency level. The command aei calculates measures of goodness-of-fit when the data violates the axioms. The command powerps calculates the power against uniform random behaviour and predictive success for the axioms at any given efficiency level.

The package contains three commands. checkax allows the user to test whether consumer demand data satisfy certain revealed preference axioms at a given efficiency level. The command aei calculates measures of goodness-of-fit when the data violates the axioms. The command powerps calculates the power against uniform random behaviour and predictive success for the axioms at any given efficiency level.

This paper provides a revealed preference characterisation of quasi-hyperbolic discounting which is designed to be applied to readily-available expenditure surveys. We describe necessary and sufficient conditions for the leading forms of the model and also study the consequences of the restrictions on preferences popularly used in empirical lifecycle consumption models. Using data from a household consumption panel dataset we explore the prevalence of time-inconsistent behaviour. The quasi-hyperbolic model provides a significantly more successful account of behaviour than the alternatives considered. We estimate the joint distribution of time preferences and the distribution of discount functions at various time horizons.

Suppose that we have access to a finite set of expenditure data drawn from an individual consumer, i.e., how much of each good has been purchased and at what prices. Afriat (1967) was the first to establish necessary and sufficient conditions on such a data set for rationalizability by utility maximization. In this note, we provide a new and simple proof of Afriat's Theorem, the explicit steps of which help to more deeply understand the driving force behind one of the more curious features of the result itself, namely that a concave rationalization is without loss of generality in a classical finite data setting. Our proof stresses the importance of the non-uniqueness of a utility representation along with the finiteness of the data set in ensuring the existence of a concave utility function that rationalizes the data.

In empirical demand, industrial organization, and labor economics, prices are often unobserved or unobservable since they may only be recorded when an agent transacts. In the absence of any additional information, this partial observability of prices is known to lead to a number of identification problems. However, in this paper, we show that theory-consistent demand analysis remains feasible in the presence of partially observed prices, and hence partially observed implied budget sets, even if we are agnostic about the nature of the missing prices. Our revealed preference approach is empirically meaningful and easy to implement. We illustrate using simple examples.

This paper presents a nonparametric analysis of a common class of intertemporal models of consumer choice that relax consumption independence. Within this class and in the absence of any functional form restrictions on instantaneous preferences, we compare the revealed preference conditions for rational habit formation and rational anticipation. We show that these models are observationally equivalent in the presence of finite data sets composed of prices, interest rates, and consumption choices.

This paper presents a nonparametric analysis of a common class of intertemporal models of consumer choice that relax consumption independence. Within this class and in the absence of any functional form restrictions on instantaneous preferences, we compare the revealed preference conditions for rational habit formation and rational anticipation. We show that these models are nonparametrically equivalent in the presence of finite data sets composed of prices, interest rates, and consumption choices. JEL Classifications: D11, D12, D91.

We show that an agent maximizing some utility function on a discrete (as opposed to continuous) consumption space will obey the generalized axiom of revealed preference (GARP), so long as the agent obeys cost efficiency. Cost efficiency will hold if there is some good, outside the set of goods being studied by the modeler, that can be consumed by the agent in continuous quantities. An application of Afriat's Theorem then guarantees that there is a strictly increasing utility function on the discrete consumption space that rationalizes price and demand observations. (JEL D11)

We derive necessary and sufficient conditions for data sets composed of state-contingent prices and consumption to be consistent with two prominent models of decision making under ambiguity: variational preferences and smooth ambiguity. The revealed preference conditions for the maxmin expected utility and subjective expected utility models are characterized as special cases.