Knowledge that Transforms

We propose a positive model of empirical science in which an analyst makes a report to an audience after observing some data. Agents in the audience may differ in their beliefs or objectives, and may therefore update or act differently following a given report. We contrast the proposed model with a classical model of statistics in which the report directly determines the payoff. We identify settings in which the predictions of the proposed model differ from those of the classical model, and seem to better match practice.

We develop a tractable general equilibrium framework in which firms are large and have market power with respect to both products and labor, and in which a firm's decisions are affected by its ownership structure. We characterize the Cournot–Walras equilibrium of an economy where each firm maximizes a share‐weighted average of shareholder utilities—rendering the equilibrium independent of price normalization. In a one‐sector economy, if returns to scale are non‐increasing, then an increase in “effective” market concentration (which accounts for common ownership) leads to declines in employment, real wages, and the labor share. Yet when there are multiple sectors, due to an intersectoral pecuniary externality, an increase in common ownership could stimulate the economy when the elasticity of labor supply is high relative to the elasticity of substitution in product markets. We characterize for which ownership structures the monopolistically competitive limit or an oligopolistic one is attained as the number of sectors in the economy increases. When firms have heterogeneous constant returns to scale technologies, we find that an increase in common ownership leads to markets that are more concentrated.

What incentives do governments have to negotiate trade agreements that constrain their domestic regulatory policies? We study a model in which firms design products to appeal to local consumer tastes, but their fixed costs increase with the difference between versions of their product destined for different markets. In this setting, firms' profit‐maximizing choices of product attributes are globally optimal in the absence of consumption externalities, but national governments have unilateral incentives to invoke regulatory protectionism to induce firm delocation. An efficient trade agreement requires commitments not to engage in such opportunistic behavior. A rule requiring mutual recognition of standards can be used to achieve efficiency, but one that requires only national treatment falls short. When product attributes confer local consumption externalities, an efficient trade agreement must coordinate the fine details of countries' regulatory policies.

This paper develops inference methods for the iterated overidentified Generalized Method of Moments (GMM) estimator. We provide conditions for the existence of the iterated estimator and an asymptotic distribution theory, which allows for mild misspecification. Moment misspecification causes bias in conventional GMM variance estimators, which can lead to severely oversized hypothesis tests. We show how to consistently estimate the correct asymptotic variance matrix. Our simulation results show that our methods are properly sized under both correct specification and mild to moderate misspecification. We illustrate the method with an application to the model of Acemoglu, Johnson, Robinson, and Yared (2008).

This paper shows that the products and prices offered in markets are correlated with local income‐specific tastes. To quantify the welfare impact of this variation, I calculate local price indexes micro‐founded by a model of non‐homothetic demand over thousands of grocery products. These indexes reveal large differences in how wealthy and poor households perceive the choice sets available in wealthy and poor cities. Relative to low‐income households, high‐income households enjoy 40 percent higher utility per dollar expenditure in wealthy cities, relative to poor cities. Similar patterns are observed across stores in different neighborhoods. Most of this variation is explained by differences in the product assortment offered, rather than the relative prices charged, by chains that operate in different markets.

This paper presents a continuous‐time model of sovereign debt. In it, a relatively impatient sovereign government's hidden type switches back and forth between a commitment type, which cannot default, and an opportunistic type, which can, and where we assume outside lenders have particular beliefs regarding how a commitment type should borrow for any given level of debt and bond price. In any Markov equilibrium, the opportunistic type mimics the commitment type when borrowing, revealing its type only by defaulting on its debt at random times. The equilibrium features a “graduation date”: a finite amount of time since the last default, after which time reputation reaches its highest level and is unaffected by not defaulting. Before such date, not defaulting always increases the country's reputation. For countries that have recently defaulted, bond prices and the total amount of debt are increasing functions of the amount of time since the country's last default. For countries that have not recently defaulted (i.e., those that have graduated), bond prices are constant.

This paper studies asset pricing and labor market dynamics when idiosyncratic risk to human capital is not fully insurable. Firms use long‐term contracts to provide insurance to workers, but neither side can fully commit; furthermore, owing to costly and unobservable retention effort, worker‐firm relationships have endogenous durations. Uninsured tail risk in labor earnings arises as a part of an optimal risk‐sharing scheme. In equilibrium, exposure to the tail risk generates higher aggregate risk premia and higher return volatility. Consistent with data, firm‐level labor share predicts both future returns and pass‐throughs of firm‐level shocks to labor compensation.

This paper develops methods for detecting discrimination by individual employers using correspondence experiments that send fictitious resumes to real job openings. We establish identification of higher moments of the distribution of job‐level callback rates as a function of the number of resumes sent to each job and propose shape‐constrained estimators of these moments. Applying our methods to three experimental data sets, we find striking job‐level heterogeneity in the extent to which callback probabilities differ by race or sex. Estimates of higher moments reveal that while most jobs barely discriminate, a few discriminate heavily. These moment estimates are then used to bound the share of jobs that discriminate and the posterior probability that each individual job is engaged in discrimination. In a recent experiment manipulating racially distinctive names, we find that at least 85% of jobs that contact both of two white applications and neither of two black applications are engaged in discrimination. To assess the potential value of our methods for regulators, we consider the accuracy of decision rules for investigating suspicious callback behavior in various experimental designs under a simple two‐type model that rationalizes the experimental data. Though we estimate that only 17% of employers discriminate on the basis of race, we find that an experiment sending 10 applications to each job would enable detection of 7–10% of discriminatory jobs while yielding Type I error rates below 0.2%. A minimax decision rule acknowledging partial identification of the distribution of callback rates yields only slightly fewer investigations than a Bayes decision rule based on the two‐type model. These findings suggest illegal labor market discrimination can be reliably monitored with relatively small modifications to existing correspondence designs.

This paper draws parallels between the principal components analysis of factorless high‐dimensional nonstationary data and the classical spurious regression. We show that a few of the principal components of such data absorb nearly all the data variation. The corresponding scree plot suggests that the data contain a few factors, which is corroborated by the standard panel information criteria. Furthermore, the Dickey–Fuller tests of the unit root hypothesis applied to the estimated “idiosyncratic terms” often reject, creating an impression that a few factors are responsible for most of the nonstationarity in the data. We warn empirical researchers of these peculiar effects and suggest to always compare the analysis in levels with that in differences.

Waitlists are often used to ration scarce resources, but the trade-offs in designing these mechanisms depend on agents' preferences. We study equilibrium allocations under alternative designs for the deceased donor kidney waitlist. We model the decision to accept an organ or wait for a preferable one as an optimal stopping problem and estimate preferences using administrative data from the New York City area. Our estimates show that while some kidney types are desirable for all patients, there is substantial match-specific heterogeneity in values. We then develop methods to evaluate alternative mechanisms, comparing their effects on patient welfare to an equivalent change in donor supply. Past reforms to the kidney waitlist primarily resulted in redistribution, with similar welfare and organ discard rates to the benchmark first come first served mechanism. These mechanisms and other commonly studied theoretical benchmarks remain far from optimal. We design a mechanism that increases patient welfare by the equivalent of an 18.2 percent increase in donor supply.