Knowledge that Transforms

Most empirical work in economics has considered only a narrow set of measures as meaningful and useful to characterize individual behavior, a restriction justified by the difficulties in collecting a wider set. However, this approach often forces the use of strong assumptions to estimate the parameters that inform individual behavior and identify causal links. In this paper, we argue that a more flexible and broader approach to measurement could be extremely useful and allow the estimation of richer and more realistic models that rest on weaker identifying assumptions. We argue that the design of measurement tools should interact with, and depend on, the models economists use. Measurement is not a substitute for rigorous theory, it is an important complement to it, and should be developed in parallel to it. We illustrate these arguments with a model of parental behavior estimated on pilot data that combines conventional measures with novel ones.

We consider social learning in a changing world. With changing states, societies can be responsive only if agents regularly act upon fresh information, which significantly limits the value of observational learning. When the state is close to persistent, a consensus whereby most agents choose the same action typically emerges. However, the consensus action is not perfectly correlated with the state, because societies exhibit inertia following state changes. When signals are precise enough, learning is incomplete, even if agents draw large samples of past actions, as actions then become too correlated within samples, thereby reducing informativeness and welfare.

We propose a theory of how market power affects wage inequality. We ask how goods and labor market power jointly determine the level of wages, the skill premium, and wage inequality. We then use detailed microdata from the U.S. Census Bureau between 1997 and 2016 to estimate the parameters of labor supply, technology, and the market structure. We find that a less competitive market structure lowers the average wage of high‐skilled workers by 11.3%, and of low‐skilled workers by 12.2%, contributes 8.1% to the rise in the skill premium, and accounts for 54.8% of the increase in between‐establishment wage variance.

This paper theoretically and empirically studies the interaction of search and application approval in credit markets. Risky borrowers internalize the probability that their application is rejected and behave as if they had high search costs. Thus, “overpayment” may be a poor proxy for consumer sophistication since it partly represents rational search in response to rejections. Contrary to standard search models, our model implies (1) endogenous adverse selection through the search and application approval process, (2) a possibly non‐monotone or non‐decreasing relationship between search and realized interest, default, and application approval rates, and (3) search costs estimated from transaction prices alone are biased. We find support for the model's predictions using a unique data set detailing search behavior of mortgage borrowers. Estimating the model, we find that screening is informative and search is costly. Counterfactual analyses reveal that tightening lending standards and discrimination through application rejection both increase equilibrium interest rates. This increase in realized interest rates is in part due to strategic complementarity in bank rate setting.

To what extent is a worker's human capital growth affected by the quality of his coworkers? To answer this question, we develop and estimate a model in which the productivity and the human capital growth of an individual depend on the average human capital of his coworkers. The measured production function is supermodular: The marginal product of a more knowledgeable individual is increasing in the human capital of his coworkers. The measured human capital accumulation function is convex: An individual's human capital growth is increasing in coworkers' human capital only when paired with more knowledgeable coworkers, but independent of coworkers' human capital when paired with less knowledgeable coworkers. Learning from coworkers accounts for two thirds of the stock of human capital accumulated on the job. Technological changes that increase production supermodularity lead to labor market segregation and, by reducing the opportunities for low human capital workers to learn from better coworkers, lead to a decline in aggregate human capital and output.

This paper develops a model of private bilateral contracting, in which an exogenous network determines the pairs of players who can communicate and contract with each other. After contracting, the players interact in an underlying game with globally verifiable productive actions and externally enforced transfers. The paper investigates whether such decentralized contracting can internalize externalities that arise due to parties being unable to contract directly with others whose productive actions affect their payoffs. The contract‐formation protocol, called the “contracting institution,” is treated as a design element. The main result is positive: There is a contracting institution that supports efficient equilibria for any underlying game and connected network. A critical property is that the institution allows for sequential contract formation or revision. The equilibrium construction features assurance contracts and cancellation penalties .

An agent selectively samples attributes of a complex project so as to influence the decision of a principal. The players disagree about the weighting, or relevance, of attributes. The correlation across attributes is modeled through a Gaussian process, the covariance function of which captures pairwise attribute similarity. The key trade‐off in sampling is between the alignment of the players' posterior values for the project and the variability of the principal's decision. Under a natural property of the attribute correlation—the nearest‐attribute property (NAP)—each optimal attribute is relevant for some player and at most two optimal attributes are relevant for only one player. We derive comparative statics in the strength of attribute correlation and examine the robustness of our findings to violations of NAP for a tractable class of distance‐based covariances. The findings carry testable implications for attribute‐based product evaluation and strategic selection of pilot sites.

What outcomes can be implemented by the choice of an information structure in binary‐action supermodular games? An outcome is partially implementable if it satisfies obedience (Bergemann and Morris (2016)). We characterize when an outcome is smallest equilibrium implementable (induced by the smallest equilibrium). Smallest equilibrium implementation requires a stronger sequential obedience condition: there is a stochastic ordering of players under which players are prepared to switch to the high action even if they think only those before them will switch. We then characterize the optimal outcome induced by an information designer who prefers the high action to be played, but anticipates that the worst (hence smallest) equilibrium will be played. In a potential game, under convexity assumptions on the potential and the designer's objective, it is optimal to choose an outcome where actions are perfectly coordinated (all players choose the same action), with the high action profile played on the largest event where that action profile maximizes the average potential.