Knowledge that Transforms

This paper provides empirical evidence of the importance of firm attention to macroeconomic dynamics. We construct a text-based measure of attention to macroeconomic news and document that attention is polarized across firms and countercyclical. Differences in attention lead to asymmetric responses to monetary policy: expansionary monetary shocks raise the market values of attentive firms more than those of inattentive firms, and contractionary shocks lower the values of attentive firms by less. Attention also mitigates the effects of macroeconomic uncertainty on firm performance. In a quantitative rational inattention model that is calibrated with this new text-based measure, inattention drives monetary non-neutrality. As average attention varies over the business cycle, so does the efficacy of monetary policy.

We present a model of digital advertising with three key features: (1) advertisers can reach consumers on and off a platform, (2) additional data enhances the value of advertiser–consumer matches, and (3) the allocation of advertisements follows an auction-like mechanism. We contrast data-augmented auctions, which leverage the platform’s data advantage to improve match quality, with managed-campaign mechanisms that automate match formation and price-setting. The platform-optimal mechanism is a managed campaign that conditions the on-platform prices for sponsored products on the off-platform prices set by all advertisers. This mechanism yields the efficient on-platform allocation but inefficiently high off-platform product prices. It attains the vertical integration profit for the platform and the advertisers, and it increases off-platform product prices while decreasing consumer surplus, relative to data-augmented auctions.

In this paper, we study the effects of economic integration with democratic partners on democracy. We assemble a large country-level panel dataset from 1960 to 2015, and exploit improvements in air, relative to sea, transportation to derive a time-varying instrument for economic integration. We find that economic integration with democracies increases countries’ democracy scores, whereas the impact of economic integration with non-democracies is muted. Results are stronger when democratic partners have a longer history of democracy, grow faster, spend more on public goods, are culturally closer, and export higher quality goods. The effects we document are driven by imports, rather than exports, and by integration with democratic partners that account for a larger share of a country’s trade in institutionally intensive, cultural, and consumer goods, as well as in goods that involve more face-to-face interactions and entail higher levels of bilateral trust. These patterns are consistent with economic integration favouring the transmission of democracy by signalling the (actual or perceived) desirability of democratic institutions. Alternative mechanisms—including human capital accumulation and economic growth—cannot, alone, explain our findings.

Job applications have risen over time, yet job-finding rates remain unchanged. Meanwhile, separations have declined. We argue that increased applications raise the probability of a good match rather than the probability of job-finding. Using a search model with multiple applications and costly information, we show that when applications increase, firms invest in identifying good matches, reducing separations. Concurrently, increased congestion and selectivity over which offer to accept temper increases in job-finding rates. Our framework contains testable implications for changes in offers, acceptances, reservation wages, applicants per vacancy, and tenure, objects that enable it to generate the trends in unemployment flows.

We introduce two data-driven procedures for optimal estimation and inference in nonparametric models using instrumental variables. The first is a data-driven choice of sieve dimension for a popular class of sieve two-stage least-squares estimators. When implemented with this choice, estimators of both the structural function h0 and its derivatives (such as elasticities) converge at the fastest possible (i.e. minimax) rates in sup-norm. The second is for constructing uniform confidence bands (UCBs) for h0 and its derivatives. Our UCBs guarantee coverage over a generic class of data-generating processes and contract at the minimax rate, possibly up to a logarithmic factor. As such, our UCBs are asymptotically more efficient than UCBs based on the usual approach of undersmoothing. As an application, we estimate the elasticity of the intensive margin of firm exports in a monopolistic competition model of international trade. Simulations illustrate the good performance of our procedures in empirically calibrated designs. Our results provide evidence against common parameterizations of the distribution of unobserved firm heterogeneity.

Interviewing is a decisive stage of most processes that match candidates to firms and organizations. This article studies how and why a candidate’s interview outcome depends on the other candidates interviewed by the same evaluator. We use large-scale data from high-stakes admission and hiring processes, where candidates are quasi-randomly assigned to evaluators and time slots. We find that the individual assessment decreases as the quality of other candidates assigned to the same evaluator increases. The influence of the previous candidate stands out, leading to a negative autocorrelation in evaluators’ votes of up to 40% and distorting final admission and hiring decisions. Our findings are in line with a contrast effect model where evaluators form a benchmark through associative recall. We assess potential changes in the design of interview processes to mitigate contrasting against the previous candidate.

For an incompatible patient–donor pair, kidney exchanges often forbid receipt-before-donation (the patient receives a kidney before the donor donates) and donation-before-receipt, causing a double-coincidence-of-wants problem. We study an algorithm, the Unpaired kidney exchange algorithm, which eliminates this problem. In a dynamic matching model, we show that the waiting time of patients under Unpaired is close to optimal and substantially shorter than under widely used algorithms. Using a rich administrative dataset from France, we show that Unpaired achieves a match rate of 63% and an average waiting time of 176 days for transplanted patients. The (infeasible) optimal algorithm is only slightly better (64% and 144 days); widely used algorithms deliver less than 40% match rate and at least 232 days waiting times. We discuss a range of solutions that can address the potential practical incentive challenges of Unpaired. In particular, we extend our analysis to an environment where a deceased donor waitlist can be integrated to improve the performance of algorithms. We show that our theoretical and empirical comparisons continue to hold. Finally, based on these analyses, we propose a practical version of the Unpaired algorithm.

We construct a novel panel dataset for interwar Soviet Union to study the causes of Ukrainian famine mortality (Holodomor) during 1932–3 and document several facts: (1) Ukraine produced enough food in 1932 to avoid famine in Ukraine; (2) 1933 mortality in the Soviet Union was increasing in the pre-famine ethnic Ukrainian population share and (3) was unrelated to food productivity across regions; (4) this pattern exists even outside of Ukraine; (5) migration restrictions exacerbated mortality; (6) actual and planned grain procurement were increasing and actual and planned grain retention (production minus procurement) were decreasing in the ethnic Ukrainian population share across regions. The results imply that anti-Ukrainian bias in Soviet policy contributed to high Ukrainian famine mortality, and that this bias systematically targeted ethnic Ukrainians across the Soviet Union.

Inflation expectations are key determinants of economic activity and are central to the current policy debate about whether inflation expectations will remain anchored in the face of recent pandemic-related increases in inflation. This article explores evidence of inattention by constructing two novel and direct measures of consumers’ inattention, and documents greater attention when inflation is high. This relationship can explain a substantial portion of the flattening of the Phillips curve and also suggests the possibility of upward attention-price spirals.

This paper investigates the construction of moment conditions in discrete choice panel data with individual-specific fixed effects. We describe how to systematically explore the existence of moment conditions that do not depend on the fixed effects, and we demonstrate how to construct them when they exist. Our approach is closely related to the numerical “functional differencing” construction introduced in a seminal paper by Bonhomme, but our emphasis is to find explicit analytic expressions for the moment functions. We first explain the construction and give examples of such moment conditions in various models. Then, we focus on the dynamic binary choice logit model and explore the implications of the moment conditions for the identification and estimation of the model parameters that are common to all individuals.