We introduce a new solution concept for models of coalition formation, called the myopic stable set (MSS). The MSS is defined for a general class of social environments and allows for an infinite ...state space. An MSS exists and, under minor continuity assumptions, it is also unique. The MSS generalizes and unifies various results from more specific applications. It coincides with the coalition structure core in coalition function form games when this set is nonempty; with the set of stable matchings in the Gale-Shapley matching model; with the set of pairwise stable networks and closed cycles in models of network formation; and with the set of pure strategy Nash equilibria in pseudo-potential games and finite supermodular games. We also characterize the MSS for the class of proper simple games.
This paper presents Markov-Chain-Monte-Carlo (MCMC) procedures to sample uniformly from the collection of datasets that satisfy some revealed preference test. The MCMC for the GARP test combines a ...Gibbs-sampler with a simple hit and run step. It is shown that the MCMC has the uniform distribution as its unique invariant distribution and that it converges to this distribution at an exponential rate.
We show how to obtain bounds on the mean treatment effects by solving a simple linear programming problem. The use of a linear programme is convenient from a practical point of view because it avoids ...the need to derive closed form solutions. Imposing or omitting monotonicity or concavity restrictions is done by simply adding or removing sets of linear restrictions to the linear programme.
•We bound mean treatment effects by solving a simple linear programming problem.•Additional conditions on mean treatments can be imposed by adding linear restrictions.•We illustrate the method by using the US National Longitudinal Survey of Youth.•Implementation codes are provided.
This paper develops mixed integer linear programming (MILP) formulations to compute various revealed preference goodness-of-fit measures. We provide MILP formulations to compute the Houtman–Maks ...index, the average Varian index, and the minimum cost index when there are linear budgets. Next, we provide MILPs to compute minimal “measurement error” in expenditures, prices, and quantities. Finally, we extend our results to non-linear budgets. As a proof of concept, we compute various goodness-of-fit measures for experimental choice data sets from the literature. The maximal computation time is less than 3 s for all measures examined on these datasets.
This paper combines revealed preference and nonparametric estimation techniques to obtain nonparametric bounds on the distribution of the money metric utility and demand functions over a population ...of heterogeneous households. Our approach is independent of any functional specification on the household utility functions. Our method applies the weak axiom of revealed preference to a population of heterogeneous households. Although this does not produce the sharpest bounds, we show that it is computationally attractive and provides narrow bounds. We demonstrate the usefulness of our results by applying it to the Consumer Expenditure Survey, a U.S. cross–sectional consumption data set.
Transferable utility (TU) is a widely used assumption in economics. In this paper, we weaken the TU property to a setting where distinct Pareto frontiers have empty intersections. We call this the ...no-intersection property (NIP). We show that the NIP is strictly weaker than TU, but still allows to derive several desirable properties. We discuss the NIP in relation to several models where TU has turned out to be a key assumption: models of assortative matching, principal-agent models with asymmetric information, the Coase Independence Property and Becker's Rotten Kid Theorem.
We develop a test for the hypothesis that every agent from a population of heterogeneous consumers has the same marginal utility of income function. This homogeneous marginal utility of income (HMUI) ...assumption is often (implicitly) used in applied demand studies because it has nice aggregation properties and facilitates welfare analysis. If the HMUI assumption holds, we can also identify the common marginal utility of income function. We apply our results using a U.S. cross sectional dataset on food consumption.
We develop a novel framework to analyze the structural implications of the marriage market for household consumption. We define a revealed preference characterization of efficient household ...consumption when the marriage is stable. We characterize stable marriage with intrahousehold (consumption) transfers but without assuming transferable utility. Our revealed preference characterization generates testable conditions even with a single observation per household and heterogeneous individual preferences across households. The characterization also allows for identifying the intrahousehold decision structure (including the sharing rule) under the same minimalistic assumptions. An application to Dutch household data illustrates the usefulness of our theoretical results.
We provide statistical inference for measures of predictive success. These measures are frequently used to evaluate and compare the performance of different models of individual and group decision ...making in experimental and revealed preference studies. We provide a brief illustration of our findings by comparing the predictive success of different revealed preference tests for models of intertemporal decision making. This demonstrates that it is possible to compare the predictive success of different models in a statistically meaningful way.
We derive revealed preference tests for models where individuals use consideration sets to simplify their consumption problem. Our basic test provides necessary and sufficient conditions for ...consistency of observed choices with the existence of consideration set restrictions. The same conditions can also be derived from a model in which the consideration set formation is endogenous and based on subjective prices. By imposing restrictions on these subjective prices, we obtain additional refined revealed preference tests. We illustrate and compare the performance of our tests by means of a dataset on household consumption choices.
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