Knowledge that Transforms

We develop a framework to study the dynamics of vote trading over multiple binary issues. We prove that there always exists a stable allocation of votes that is reachable in a finite number of trades, for any number of voters and issues, any separable preference profile, and any restrictions on the coalitions that may form. If at every step all blocking trades are chosen with positive probability, convergence to a stable allocation occurs in finite time with probability 1. If coalitions are unrestricted, the outcome of vote trading must be Pareto optimal, but unless there are three voters or two issues, it need not correspond to the Condorcet winner.

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.

We show that even in the absence of data on individual decisions, the distribution of individual attitudes towards risk can be identified from the aggregate conditions that characterize equilibrium on markets for risky assets. Taking parimutuel horse races as a textbook model of contingent markets, we allow for heterogeneous bettors with very general risk preferences, including non-expected utility. Under a standard single-crossing condition on preferences, we identify the distribution of preferences among the population of bettors and we derive testable implications. We estimate the model on data from U.S. races. Specifications based on expected utility fit the data very poorly. Our results stress the crucial importance of nonlinear probability weighting. They also suggest that several dimensions of heterogeneity may be at work.

We propose a new solution for discrete exchange economies and resource‐allocation problems, the exclusion core. The exclusion core rests upon a foundational idea in the legal understanding of property, the right to exclude others. By reinterpreting endowments as a distribution of exclusion rights, rather than as bundles of goods, our analysis extends to economies with qualified property rights, joint ownership, and social hierarchies. The exclusion core is characterized by a generalized top trading cycle algorithm in a large class of economies, including those featuring private, public, and mixed ownership. It is neither weaker nor stronger than the strong core.

We propose a bootstrap‐based calibrated projection procedure to build confidence intervals for single components and for smooth functions of a partially identified parameter vector in moment (in)equality models. The method controls asymptotic coverage uniformly over a large class of data generating processes. The extreme points of the calibrated projection confidence interval are obtained by extremizing the value of the function of interest subject to a proper relaxation of studentized sample analogs of the moment (in)equality conditions. The degree of relaxation, or critical level, is calibrated so that the function of θ , not θ itself, is uniformly asymptotically covered with prespecified probability. This calibration is based on repeatedly checking feasibility of linear programming problems, rendering it computationally attractive. Nonetheless, the program defining an extreme point of the confidence interval is generally nonlinear and potentially intricate. We provide an algorithm, based on the response surface method for global optimization, that approximates the solution rapidly and accurately, and we establish its rate of convergence. The algorithm is of independent interest for optimization problems with simple objectives and complicated constraints. An empirical application estimating an entry game illustrates the usefulness of the method. Monte Carlo simulations confirm the accuracy of the solution algorithm, the good statistical as well as computational performance of calibrated projection (including in comparison to other methods), and the algorithm's potential to greatly accelerate computation of other confidence intervals.

Fan, Liao, and Yao (2015) recently introduced a remarkable method for increasing the asymptotic power of tests in high‐dimensional testing problems. If applicable to a given test, their power enhancement principle leads to an improved test that has the same asymptotic size, has uniformly non‐inferior asymptotic power, and is consistent against a strictly broader range of alternatives than the initially given test. We study under which conditions this method can be applied and show the following: In asymptotic regimes where the dimensionality of the parameter space is fixed as sample size increases, there often exist tests that cannot be further improved with the power enhancement principle. However, when the dimensionality of the parameter space increases sufficiently slowly with sample size and a marginal local asymptotic normality (LAN) condition is satisfied, every test with asymptotic size smaller than 1 can be improved with the power enhancement principle. While the marginal LAN condition alone does not allow one to extend the latter statement to all rates at which the dimensionality increases with sample size, we give sufficient conditions under which this is the case.

Twelve percent of the Malawian population is HIV infected. Eighteen percent of sexual encounters are casual. A condom is used a third of the time. To analyze the Malawian epidemic, a choice‐theoretic general equilibrium search model is constructed. In the developed framework, people select between different sexual practices while knowing the inherent risk. The calibrated model is used to study several policy interventions, namely, ART, circumcision, better condoms, and the treatment of other STDs. The efficacy of public policy depends upon the induced behavioral changes and equilibrium effects. The framework complements the insights from epidemiological studies and small‐scale field experiments.

We consider a general social choice environment that has multiple agents, a finite set of alternatives, independent types, and atomless type distribution. We show that for any Bayesian incentive compatible mechanism, there exists an equivalent deterministic mechanism that (1) is Bayesian incentive compatible; (2) delivers the same interim expected allocation probabilities and the same interim expected utilities for all agents; and (3) delivers the same ex ante expected social surplus. This result holds in settings with a rich class of utility functions, multidimensional types, interdependent valuations, and in settings without monetary transfers. To prove our result, we develop a novel methodology of mutual purification, and establish its link with the mechanism design literature.

Households face large income uncertainty that varies substantially over the business cycle. We examine the macroeconomic consequences of these variations in a model with incomplete markets, liquid and illiquid assets, and a nominal rigidity. Heightened uncertainty depresses aggregate demand as households respond by hoarding liquid “paper” assets for precautionary motives, thereby reducing both illiquid physical investment and consumption demand. We document the empirical response of portfolio liquidity and aggregate activity to surprise changes in idiosyncratic income uncertainty and find both to be quantitatively in line with our model. The welfare consequences of uncertainty shocks and of the policy response thereto depend crucially on a household's asset position

Comparing the 1935 and 1975 U.S. birth cohorts, wages of married women grew twice as fast as for married men, and the wage gap between married and single women turned from negative to positive. The employment rate of married women also increased sharply, while that of other groups remained quite stable. To better understand these diverse patterns, we develop a life-cycle model incorporating individual and household decisions about education, employment, marriage/divorce, and fertility. The model provides an excellent fit to wage and employment patterns, along with changes in education, marriage/divorce rates, and fertility. We assume fixed preferences, but allow for four exogenously changing factors: (i) mother's education, health, and taxes/transfers; (ii) marriage market opportunities and divorce costs; (iii) the wage structure and job offers; (iv) contraception technology. We quantify how each factor contributed to changes across cohorts. We find that factor (iii) was the most important force driving the increase in relative wages of married women, but that all four factors are important for explaining the many socio-economic changes that occurred in the past 50 years. Finally, we use the model to simulate a shift from joint to individual taxation. In a revenue-neutral simulation, we predict this would increase employment of married women by 9% and the marriage rate by 8.1%.