We study identification and inference in first-price auctions with risk-averse bidders and selective entry, building on a flexible framework we call the Affiliated Signal with Risk Aversion (AS-RA) model. Assuming exogenous variation in either the number of potential bidders (N) or a continuous instrument (z) shifting opportunity costs of entry, we provide a sharp characterization of the nonparametric restrictions implied by equilibrium bidding. This characterization implies that risk neutrality is nonparametrically testable. In addition, with sufficient variation in both N and z, the AS-RA model primitives are nonparametrically identified (up to a bounded constant) on their equilibrium domains. Finally, we explore new methods for inference in set-identified auction models based on Chen et al. (2018, Econometrica, vol. 86, 1965–2018), as well as novel and fast computational strategies using Mathematical Programming with Equilibrium Constraints. Simulation studies reveal the good finite-sample performance of our inference methods, which can readily be adapted to other set-identified flexible equilibrium models with parameter-dependent support.
Human capital is central to efforts to promote growth, convergence, and the elimination of poverty. Drawing on seminal macroeconomic frameworks by Nelson-Phelps, Lucas, and subsequent developments, alongside macro and microeconomic evidence, the chapter examines the role of human capital in driving innovation and growth, emphasizing how different types of human capital matter at different stages of development, and discussing obstacles to accumulation and evidence from policy interventions.
During adolescence, peer interactions become increasingly central to children’s development, whereas the direct influence of parents wanes. Nevertheless, parents can continue to exert leverage by shaping their children’s peer groups. We construct and estimate a model of parenting with peer and neighborhood effects where parents intervene in peer formation and show that the model captures empirical patterns of skill accumulation, parenting style, and peer characteristics among US high school students. We find that interventions that move children to better neighborhoods lose impact when they are scaled up, because parents’ equilibrium responses push against successful integration with the new peer group.
This paper provides the first nationwide U.S. evidence on the effects of electric vehicle (EV) adoption on air quality and child health. Using county-level data from 2010–2021, we link EV registrations to air pollution, birth outcomes, and emergency department visits. Endogenous adoption is addressed using two-way fixed effects and an instrumental variables strategy exploiting the rollout of federally designated Alternative Fuel Corridors. Greater EV adoption significantly lowers nitrogen dioxide and improves infant and child health, reducing very low birth weight, prematurity, and asthma-related emergency visits. The largest health gains occur in high-pollution areas and exceed $1.2–$4.0 billion annually.
Many mental health disorders start in adolescence, and appropriate initial treatment may improve trajectories. But what is appropriate treatment? We use a large national database of insurance claims to examine the impact of initial mental health treatment on the outcomes of adolescent children over the next 2 years, where treatment is either consistent with US Food and Drug Administration guidelines, consistent with looser guidelines published by professional societies (gray area prescribing), or inconsistent with any guidelines (red-flag prescribing). We find that red-flag prescribing increases self-harm, use of emergency rooms, and health care costs, suggesting that treatment guidelines effectively scale up good treatment in practice.
This chapter, prepared for the Handbook of Development Economics (Vol. 6), reviews recent microeconomic evidence on the causes of resource misallocation in developing countries. It distinguishes between “technological” and “distortionary” wedges, develops a unified theoretical framework linking market power, taxes, financial frictions, and firm dynamics, and summarizes empirical findings from the “direct approach” to misallocation. The authors emphasize how wedges vary by firm size and discuss policy implications for improving allocative efficiency.
We study two-player constant-sum Bayesian games with type-independent payoffs. Under a “completeness” statistical condition, any “identifiable” equilibrium is an ex-post equilibrium. We apply this result to a Downsian election in which office-motivated candidates possess private information about policy consequences. The ex-post property implies a sharp bound on information aggregation: equilibrium voter welfare is at best equal to the efficient use of a single candidate’s information. In canonical specifications, politicians may “anti-pander” (overreact to their information), whereas some degree of pandering would be socially beneficial. We discuss other applications of the ex-post result.
We study mechanism design for a sophisticated agent with non-expected utility (EU)
preferences. We show that the revelation principle holds if and only if all types are EU
maximizers: if at least one type is a non-EU maximizer, randomizing over dynamic
mechanisms generates a strictly larger set of implementable allocations than using static
mechanisms. Moreover, dynamic stochastic mechanisms can fully extract the private
information of any type who doesn’t have uniformly quasi-concave preferences without
providing that type any rent. Full-surplus extraction is possible in a broad variety of
non-EU environments, but impossible for types with concave preferences.
We develop a methodology for modeling household income processes when subjective probabilistic assessments of future income are available. This allows us to flexibly estimate conditional cdf s directly using elicited individual subjective probabilities, and to obtain empirical measurements of subjective risk and subjective persistence. We then use two longitudinal surveys collected in rural India and rural Colombia to explore the nature of perceived income dynamics in those contexts. Our results suggest linear income processes are rejected in favor of more flexible versions in both cases; subjective income distributions feature heteroskedasticity, conditional skewness and nonlinear persistence.
We study mechanism design in environments where agents have private preferences and private information about a common payoff-relevant state. In such settings with multi-dimensional types, standard mechanisms fail to implement efficient allocations. We address this limitation by proposing data-driven mechanisms that condition transfers on additional post-allocation information, modeled as an estimator of the payoff-relevant state. Our mechanisms extend the classic Vickrey–Clarke–Groves framework. We show they achieve exact implementation in posterior equilibrium when the state is fully revealed or utilities are affine in an unbiased estimator. With a consistent estimator, they achieve approximate implementation that converges to exact implementation as the estimator converges, and we provide bounds on the convergence rate. We demonstrate applications to digital advertising auctions and AI shopping assistants, where user engagement naturally reveals relevant information, and to procurement auctions with consumer spot markets, where additional information arises from a pricing game played by the same agents.
How should a buyer design procurement mechanisms when suppliers’ costs are unknown, and the buyer does not have a prior belief? We demonstrate that notably simple mechanisms—those that share a constant fraction of the buyer utility with the seller—allow the buyer to realize a guaranteed positive fraction of the efficient social surplus across all possible costs. Moreover, a judicious choice of the share based on the known demand maximizes the surplus ratio guarantee that can be attained across all possible (arbitrarily complex and nonlinear) mechanisms and cost functions. Results apply to related nonlinear pricing and optimal regulation problems.
We analyze a nonlinear pricing model where the seller controls both product pricing (screening) and buyer information about their own values (persuasion). We prove that the optimal mechanism always consists of finitely many signals and items, even with a continuum of buyer values. The seller optimally pools buyer values and reduces product variety to minimize informational rents. We show that value pooling is optimal even for finite value distributions if their entropy exceeds a critical threshold. We also provide sufficient conditions under which the optimal menu restricts offering to a single item.
We propose a new formulation of the maximum score estimator that uses compositions of rectified linear unit (ReLU) functions, instead of indicator functions as in Manski (1975, 1985), to encode the sign alignment restrictions. Since the ReLU function is Lipschitz, our new ReLU-based maximum score criterion function is substantially easier to optimize using standard gradient-based optimization pacakges. We also show that our ReLU-based maximum score (RMS) estimator can be generalized to an umbrella framework defined by multi-index single-crossing (MISC) conditions, while the original maximum score estimator cannot be applied. We establish the n −s/(2s+1) convergence rate and asymptotic normality for the RMS estimator under order-s Holder smoothness. In addition, we propose an alternative estimator using a further reformulation of RMS as a special layer in a deep neural network (DNN) architecture, which allows the estimation procedure to be implemented via state-of-the-art software and hardware for DNN.
Does electoral replacement ensure that officeholders eventually act in voters’ interests? We study a reputational model of accountability. Voters observe incumbents’ performance and decide whether to replace them. Politicians may be “good” types who always exert effort or opportunists who may shirk. We find that good long-run outcomes are always attainable, though the mechanism and its robustness depend on economic conditions. In environments conducive to incentive provision, some equilibria feature sustained effort, yet others exhibit some long-run shirking. In the complementary case, opportunists are never fully disciplined, but selection dominates: every equilibrium eventually settles on a good politician, yielding permanent effort.
In sorting literature, comparative statics for multidimensional assignment models with general output functions and input distributions is an important open question. We provide a complete theory of comparative statics for technological change in general multidimensional assignment models. Our main result is that any technological change is uniquely decomposed into two distinct components. The first component (gradient) gives a characterization of changes in marginal earnings through a Poisson equation. The second component (divergence-free) gives a characterization of labor reallocation. For U.S. data, we quantify equilibrium responses in sorting and earnings with respect to cognitive skill-biased technological change
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