Knowledge that Transforms

We use natural experiments embedded in state-run lotteries and a new nationally representative survey to provide reduced-form and structural estimates of risk preferences and behavioural biases in lottery demand, and to explore the implications for optimal lottery design. We find that sales respond more to the expected value of the jackpot than to price but are unresponsive to variation in the second prize—a pattern that is consistent with probability weighting but is inconsistent with standard parameterizations. In the survey, we find that lottery spending decreases modestly with income and is strongly associated with measures of innumeracy, poor statistical reasoning, and other proxies for behavioural bias, which also decline with income. Regression predictions suggest that Americans would spend 43% less on lotteries if they were unbiased, while the remaining lottery demand is due to other factors such as anticipatory utility or entertainment value. We use these empirical moments to estimate a model of socially optimal lottery design. In the model, current multi-state lottery designs increase welfare but may harm heavy spenders.

This article studies how firms’ screening incentives in the labour market affect the optimal design of social insurance programs and quantitatively assesses the U.S. disability policies accounting for firms’ screening of the disabled. We develop an equilibrium search model where workers with different productivities have heterogeneous preferences over non-wage benefits and firms cannot offer an employment contract that explicitly depends on worker types. In this environment, firms may use contracts to screen out a certain type of workers, distorting employment rates and contracts in equilibrium. Therefore, the optimal structure of social insurance policies depends on firms’ screening incentives. We extend and structurally estimate this framework to quantitatively understand the inefficiencies arising from firms’ incentives to screen out disabled workers and examine the optimal joint design of disability insurance (DI) and various forms of firm subsidies. We find that hiring subsidies mitigate screening distortions; at the same time, they interact with DI by reducing the labour supply disincentives it generates. The optimal policy structure leads to a considerable welfare gain by simultaneously making firm subsidies and DI benefits more generous.

We document five novel facts about the role of search effort in forming trading relationships among firms by combining a variety of micro and macro datasets. These facts strongly suggest the presence of search complementarities. To study the implications of these facts for aggregate fluctuations, we build a dynamic general equilibrium model, disciplined by our new firm-level evidence on search effort. The model matches key aspects of the macro and micro data that have remained unaccounted for by standard models, including the time-varying bimodal distribution of output and the strong, nonlinear propagation of shocks. Also, changes to the volatility of shocks have nonlinear effects on macroeconomic fluctuations that advance a novel interpretation of the Great Moderation. Finally, we provide a new account of the state-dependent effects of fiscal policy.

We propose a new sequential Efficient Pseudo-Likelihood (k-EPL) estimator for dynamic discrete choice games of incomplete information. k-EPL considers the joint behaviour of multiple players simultaneously, as opposed to individual responses to other agents’ equilibrium play. This, in addition to reframing the problem from conditional choice probability (CCP) space to value function space, yields a computationally tractable, stable, and efficient estimator. We show that each iteration in the k-EPL sequence is consistent and asymptotically efficient, so the first-order asymptotic properties do not vary across iterations. Furthermore, we show the sequence achieves higher-order equivalence to the finite-sample maximum-likelihood estimator with iteration and that the sequence of estimators converges almost surely to the maximum-likelihood estimator at a nearly superlinear rate when the data are generated by any regular Markov perfect equilibrium, including equilibria that lead to inconsistency of other sequential estimators. When utility is linear in parameters, k-EPL iterations are computationally simple, only requiring that the researcher solve linear systems of equations to generate pseudo-regressors which are used in a static logit/probit regression. Monte Carlo simulations demonstrate the theoretical results and show k-EPL’s good performance in finite samples in both small- and large-scale games, even when the game admits spurious equilibria in addition to one that generated the data. We apply the estimator to analyse competition in the U.S. wholesale club industry.

We consider the effects of climate change on seasonally migrant populations that herd livestock—i.e. transhumant pastoralists—in Africa. Traditionally, transhumant pastoralists benefit from a cooperative relationship with sedentary agriculturalists whereby arable land is used for crop farming in the wet season and animal grazing in the dry season. Rainfall scarcity can disrupt this arrangement by inducing pastoral groups to migrate to agricultural lands before the harvest, causing conflict to emerge. We examine this hypothesis by combining ethnographic information on the traditional locations of transhumant pastoralists and sedentary agriculturalists with high-resolution data on the location and timing of rainfall and violent conflict events in Africa from 1989 to 2018. We find that reduced rainfall in the territory of transhumant pastoralists leads to conflict in neighbouring areas. Consistent with the proposed mechanism, the conflicts are concentrated in agricultural areas; they occur during the wet season and not the dry season; and they are due to rainfall’s impact on plant biomass growth. Since pastoralists tend to be Muslim and agriculturalists Christian, this mechanism accounts for a sizable proportion of the rapid rise in religious conflict observed in recent decades. Regarding policy responses, we find that development aid projects tend not to mitigate the effects that we document. By contrast, the effects are reduced when transhumant pastoralists have greater power in national government, suggesting that more equal political representation is conducive to peace.

We study partially linear models when the outcome of interest and some of the covariates are observed in two different datasets that cannot be linked. This type of data combination problem arises very frequently in empirical microeconomics. Using recent tools from optimal transport theory, we derive a constructive characterization of the sharp identified set. We then build on this result and develop a novel inference method that exploits the specific geometric properties of the identified set. Our method exhibits good performances in finite samples, while remaining very tractable. We apply our approach to study intergenerational income mobility over the period 1850–1930 in the U.S. Our method allows us to relax the exclusion restrictions used in earlier work, while delivering confidence regions that are informative.

We study mislearning from equilibrium prices, and contrast this with mislearning from exogenous fundamentals. We micro-found mislearning from prices with a psychologically founded theory of “Partial Equilibrium Thinking” (PET), where traders learn fundamental information from prices, but fail to realize others do so too. PET leads to over-reaction, and upward sloping demand curves, thus contributing to more inelastic markets. The degree of individual-level over-reaction and the extent of inelasticity vary with the composition of traders, and with the informativeness of new information. More generally, unlike mislearning from fundamentals, mislearning from prices (i) generates a two-way feedback between prices and beliefs that can provide an arbitrarily large amount of amplification and (ii) can rationalize both over-reaction and more inelastic markets. The two classes of biases are not mutually exclusive. Instead, they interact in very natural ways, and mislearning from prices can vastly amplify mislearning from fundamentals.

This paper builds a world atlas of child penalties in employment based on microdata from 134 countries. The estimation of child penalties is based on pseudo-event studies of first child birth using cross-sectional data. The pseudo-event studies are validated against true event studies using panel data for a subset of countries. Most countries display clear and sizable child penalties: men and women follow parallel trends before parenthood, but diverge sharply and persistently after parenthood. While this pattern is pervasive, there is enormous variation in the magnitude of the effects across different regions of the world. The fraction of gender inequality explained by child penalties varies systematically with economic development and proxies for structural transformation. At low levels of development, child penalties represent a minuscule fraction of gender inequality. But as economies develop—incomes rise and the labour market transitions from subsistence agriculture to salaried work in industry and services—child penalties take over as the dominant driver of gender inequality. The relationship between child penalties and development is validated using historical data from current high-income countries, back to the 1700s for some countries. Finally, because parenthood is often tied to marriage, we also investigate the existence of marriage penalties in female employment. In general, women experience both marriage and child penalties, but their relative importance depends on the level of development. The development process is associated with a substitution from marriage penalties to child penalties, with the former gradually converging to zero.

How do social networks influence the decision to migrate? Prior work suggests two distinct mechanisms that have historically been difficult to differentiate: as a conduit of information, and as a source of social and economic support. We disentangle these mechanisms using a massive “digital trace” dataset that allows us to observe the migration decisions made by millions of individuals over several years, as well as the complete social network of each person in the months before and after migration. These data allow us to establish a new set of stylized facts about the relationship between social networks and migration. Our main analysis indicates that the average migrant derives more social capital from “interconnected” networks that provide social support than from “extensive” networks that efficiently transmit information.

We measure desired labour supply at the extensive (employment) margin in two representative surveys of the U.S. and German populations. We elicit reservation raises: the percent wage change that renders a given individual indifferent between employment and nonemployment. It is equal to her reservation wage divided by her actual, or potential, wage. The reservation raise distribution is the nonparametric aggregate labour supply curve. Locally, the curve exhibits large short-run elasticities above 3, consistent with business cycle evidence. For larger upward shifts, arc elasticities shrink towards 0.5, consistent with quasi-experimental evidence from tax holidays. Existing models fail to match this nonconstant, asymmetric curve.