We study mechanism design when agents hold private information about both their preferences and a common payoff-relevant state. We show that standard message-driven mechanisms cannot implement socially efficient allocations when agents have multidimensional types, even under favorable conditions.
To overcome this limitation, we propose data-driven mechanisms that leverage additional post-allocation information, modeled as an estimator of the pay-off relevant state. Our data-driven mechanisms extend the classic Vickrey-Clarke-Groves class. We show that they achieve exact implementation in posterior equilibrium when the state is either fully revealed or the utility is linear in an unbiased estimator. We also show that they achieve approximate implementation with a consistent estimator, converging to exact implementation as the estimator converges, and present bounds on the convergence rate. We demonstrate applications to digital advertising auctions and large language model (llm) - based mechanisms, where user engagement naturally reveals relevant information.
This research examines the determinants of entrepreneurship in China’s transition from agriculture to domestic production in the 1990’s and the subsequent transition to exporting in the 2000’s. The model that we develop and test to describe these transitions incorporates a productivity enhancing role for community (birth county) networks, which emerge in response to market imperfections at early stages of economic development. Using administrative data covering the universe of registered firms over the 1994-2012 period and the universe of exporters over the 2002-2012 period, we provide causal evidence that these networks of firms were active and were effective at increasing the revenues of their members, both in domestic production and exporting. While this substantially increased the number of domestic producers in the first stage, the incumbent domestic networks created a disincentive to enter exporting in the second stage that dominated the positive effect of the export networks. Our analysis provides a novel characterization of the development process in which community-based networks emerge at each stage to facilitate the occupational mobility of their members, and pre-existing networks slow down the growth of the networks that follow.
This research provides a status-based explanation for the high rates of female labor force non-participation (FLFNP) and the sustained increase in these rates over time that have been documented in many developing economies. This explanation is based on the idea that households or ethnic groups can signal their wealth, and thereby increase their social status, by withdrawing women from the labor force. If the value of social status or the willingness to bear the signaling cost is increasing with economic development, then this would explain the persistent increase in FLFNP. To provide empirical support for this argument, we utilize two independent sources of exogenous variation – across Indian districts in the cross-section and within districts over time – to establish that status considerations determine rural FLFNP. Our status-based model, which is used to derive the preceding tests, is able to match the high levels and the increase in rural Indian FLFNP that motivate our analysis. Counterfactual simulations of the estimated model indicate that conventional development policies, such as a reduction in the cost of female education, could raise FLFNP by increasing potential household incomes and, hence, the willingness to compete for social status. The steep increase in female education in recent decades could paradoxically have increased FLFNP in India even further.
We study agents who are more likely to remember some experiences than others but update beliefs as if the experiences they remember are the only ones that occurred. To understand the long-run effects of selective memory, we propose selective-memory equilibrium. We show that if the agent’s behavior converges, their limit strategy is a selective-memory equilibrium, and we provide a sufficient condition for behavior to converge. We use this equilibrium concept to explore the consequences of several well-documented biases. We also show that there is a close connection between selective-memory equilibria and the outcomes of misspecified learning.
We develop a state-space model with a transition equation that takes the form of a functional vector autoregression (VAR) and stacks macroeconomic aggregates and a cross-sectional density. The measurement equation captures the error in estimating log densities from repeated cross-sectional samples. The log densities and their transition kernels are approximated by sieves, which leads to a finite-dimensional VAR for macroeconomic aggregates and sieve coefficients. With this model, we study the dynamics of technology shocks, GDP (gross domestic product), employment, and the earnings distribution. We find that spillovers between aggregate and distributional dynamics are generally small, that a positive technology shock tends to decrease inequality, and that a shock that raises earnings inequality leads to a small and insignificant GDP response.
A common tactic to estimate willingness-to-travel exploits variation in the relative proximity of consumers to supplier locations. The validity of these estimates relies on the exogeneity of that consumer-supplier distance. We argue that distance to suppliers is endogenous because suppliers strategically choose locations to target consumers; we introduce a novel instrument to address this form of endogeneity. Using geolocation data from millions of smartphones, we estimate consumer preferences for specific retail chains across income groups and regions. We show that accounting for distance endogeneity significantly alters willingness-to-travel measures. Contrary to the prevailing “retail apocalypse” narrative, we find that consumer surplus per trip to general merchandise stores did not significantly decline from 2010 to 2019. For the lowest-income consumers, the expansion of national chains, particularly dollar stores, nearly compensates for the closure of traditional department stores and regional chains. Notably, failing to account for distance endogeneity leads to the erroneous conclusion that lower-income households experienced statistically significant consumer surplus declines.
Climate policy by a coalition of countries can shift activities—extraction, production, and consumption—to regions outside the coalition. We build a stylized general-equilibrium model of trade and carbon externalities to derive a coalition’s optimal Pareto-improving policy in such an environment. It can be implemented through: (i) a tax on fossil-fuel extraction at a rate equal to the global marginal harm from carbon emissions, (ii) a tax on imports of energy and goods, and a rebate of the tax on exports of energy but not goods, all at a lower rate per unit of carbon than the extraction tax rate, and (iii) a goods-specific export subsidy. This combination of taxes and subsidies exploits international trade to expand the policy’s reach. It promotes energy efficient production and eliminates leakage by taxing the carbon content of goods imports and by encouraging goods exports. It controls the energy price in the non-taxing region by balancing supply-side and demand-side taxes. We use a quantitative version of the model to illustrate the gains achieved by the optimal policy and simpler variants of it. Combining supply-side and demand-side taxes generates first-order welfare improvements over current and proposed climate policies.
Positive assortative matching refers to the tendency of individuals with similar char-acteristics to form partnerships. Measuring the extent to which assortative matching differs between two economies is challenging when the marginal distributions of the characteristic along which sorting takes place (e.g., education) change for either or both sexes. We show how the use of different measures can generate different conclusions. We provide axiomatic characterization for measures such as the odds ratio, normalized trace, and likelihood ratio, and provide a structural economic interpretation of the odds ratio. We then use our approach to consider how marital sorting by education changed between the 1950s and the 1970s cohort, for which both educational attainment and returns in the labor market changed substantially.
We propose a new adaptive hypothesis test for inequality (e.g., monotonicity, convexity) and equality (e.g., parametric, semiparametric) restrictions on a structural function in a nonparametric instrumental variables (NPIV) model. Our test statistic is based on a modified leave-one-out sample analog of a quadratic distance between the restricted and unrestricted sieve two-stage least squares estimators. We provide computationally simple, data-driven choices of sieve tuning parameters and Bonferroni adjusted chi-squared critical values. Our test adapts to the unknown smoothness of alternative functions in the presence of unknown degree of endogeneity and unknown strength of the instruments. It attains the adaptive minimax rate of testing in L2. That is, the sum of the supremum of type I error over the composite null and the supremum of type II error over nonparametric alternative models cannot be minimized by any other tests for NPIV models of unknown regularities. Confidence sets in L2 are obtained by inverting the adaptive test. Simulations confirm that, across different strength of instruments and sample sizes, our adaptive test controls size and its finite-sample power greatly exceeds existing non-adaptive tests for monotonicity and parametric restrictions in NPIV models. Empirical applications to test for shape restrictions of differentiated products demand and of Engel curves are presented.
A signal is privacy‐preserving with respect to a collection of privacy sets if the posterior probability assigned to every privacy set remains unchanged conditional on any signal realization. We characterize the privacy‐preserving signals for arbitrary state space and arbitrary privacy sets. A signal is privacy‐preserving if and only if it is a garbling of a reordered quantile signal. Furthermore, distributions of posterior means induced by privacy‐preserving signals are exactly mean‐preserving contractions of that induced by the quantile signal. We discuss the economic implications of our characterization for statistical discrimination, the revelation of sensitive information in auctions and price discrimination.