Knowledge that Transforms

Forward-looking investments determine the resilience of firms’ supply chains. Such investments confer externalities on other firms in the production network. We compare the equilibrium and optimal allocations in a general equilibrium model with an arbitrary number of vertical production tiers. Our model features endogenous investments in protective capabilities, endogenous formation of supply links, and sequential bargaining over quantities and payments between firms in successive tiers. We derive policies that implement the first-best allocation, allowing for subsidies to input purchases, network formation, and investments in protective capabilities. The first-best policies depend only on production function parameters of the pertinent tier. When subsidies to transactions are infeasible, the second-best subsidies for resilience depend on production function parameters throughout the network, and subsidies are larger upstream than downstream whenever the bargaining weights of buyers are nonincreasing along the chain.

For many decisions, we encounter relevant information over the course of days, months, or years. We consume such information in various forms, including stories (qualitative content about individual instances) and statistics (quantitative data about collections of observations). This article proposes that information type—story versus statistic—shapes selective memory. In controlled experiments, we document a pronounced story-statistic gap in memory: the average impact of statistics on beliefs fades by 73% over the course of a day, but the impact of a story fades by only 32%. Guided by a model of selective memory, we disentangle different mechanisms and document that similarity relationships drive this gap. Recall of a story increases when its qualitative content is more similar to a memory prompt. Irrelevant information in memory that is similar to the prompt, on the other hand, competes for retrieval with relevant information, impeding successful recall.

We estimate perceptions about the Federal Reserve’s monetary policy rule from panel data on professional forecasts of interest rates and macroeconomic conditions. The perceived dependence of the federal funds rate on economic conditions varies substantially over time, in particular over the monetary policy cycle. Forecasters update their perceptions about the Fed’s policy rule in response to monetary policy actions, measured by high-frequency interest rate surprises, suggesting that they have imperfect information about the rule. Monetary policy perceptions matter for monetary transmission, as they affect the sensitivity of interest rates to macroeconomic news, term premia in long-term bonds, and the response of the stock market to monetary policy surprises. A simple learning model with forecaster heterogeneity and incomplete information about the policy rule motivates and explains our empirical findings.

We construct measures of industry performance and welfare in the U.S. automobile market from 1980 to 2018. We estimate a demand model using product-level data on market shares, prices, and attributes, and consumer-level data on demographics, purchases, and stated second choices. We estimate marginal costs assuming Nash-Bertrand pricing. We relate trends in consumer welfare and markups to trends in market structure and the composition of products. Although real prices rose, we find that markups decreased substantially, and the fraction of total surplus accruing to consumers increased. Consumer welfare increased over time due to improved product quality and improved production technology.

Anti-scientific attitudes can impose substantial costs on societies. Can schools be an important agent in mitigating the propagation of such attitudes? This article investigates the effect of the content of science education on anti-scientific attitudes, knowledge, and choices. The analysis exploits staggered reforms that reduce or expand the coverage of evolution theory in U.S. state science education standards. I compare adjacent student cohorts in models with state and cohort fixed effects. There are three main results. First, expanded evolution coverage increases students’ knowledge about evolution. Second, the reforms translate into greater evolution belief in adulthood, but do not crowd out religiosity or affect political attitudes. Third, the reforms affect high-stakes life decisions, namely, the probability of working in life sciences.

In 2013, the Dutch government mandated that new conforming mortgages must fully amortize. Within a difference-in-differences design, we estimate that the marginal wealth accumulation from amortization is close to one, even five years later. Households purchasing after the reform primarily cut consumption and leisure over other savings, leading to a rise in wealth. This holds if we use life events to instrument for the timing of home purchase. Estimates are similar for seemingly unconstrained households and movers, suggesting a broad applicability of our results. Consistent with a simple model, we find lower estimates for households that appear less financially sophisticated or willing to adjust short-term consumption. Mortgage amortization schedules are among the largest savings plans in the world, and our results highlight their critical importance for household wealth building and macroprudential policies.

In the early 1900s, telephone operation was among the most common jobs for American women, and telephone operators were ubiquitous. Between 1920 and 1940, AT&T undertook one of the largest automation investments in modern history, replacing operators with mechanical switching technology in over half of the U.S. telephone network. Using variation across U.S. cities in the timing of adoption, we study how this wave of automation affected the labor market for young women. Although automation eliminated most of these jobs, it did not reduce future cohorts’ overall employment: the decline in operators was counteracted by employment growth in middle-skill clerical jobs and lower-skill service jobs, including new categories of work. Using a new genealogy-based census-linking method, we show that incumbent telephone operators were most affected, and a decade later more likely to be in lower-paying occupations or no longer working.

The article develops a model of nonmarket allocation of resources such as the awarding of grants to meritorious projects, honors to outstanding students, or journal slots to quality publications. On the supply side, the available budget of grants is awarded to applicants who are evaluated most favorably according to the noisy information available to reviewers. On the demand side, stronger candidates are more likely to obtain grants and thus self-select into applying, given that applications are costly. We establish that if evaluation is perfect, grading on a curve inefficiently discourages even the very best candidates from applying. More generally, when the budget is insufficient to award grants to all applicants, the equilibrium unravels if information is symmetric enough—the paradox of relative evaluation. Leveraging a technique based on the quantile function pioneered by Lehmann, we characterize a broad set of nonmarket allocation rules under which an increase in evaluation noise in a field (or course) raises equilibrium applications in that field, and reduces applications in all other fields. We empirically confirm these comparative statics by exploiting a change in the rule for apportioning the total budget to applications in different fields at the European Research Council, showing that a 1 standard deviation increase in own evaluation noise leads to a 0.4 standard deviation increase in the number of applications and budget share. Moreover, we derive insights for the design of evaluation institutions, particularly regarding the endogenous choice of noise by fields or courses and the optimal aggregation of fields into panels.

Standard labor market models assume that workers hold accurate beliefs about the external wage distribution, and hence their outside options with other employers. We test this assumption by comparing German workers’ beliefs about outside options with objective benchmarks. First, we find that workers wrongly anchor their beliefs about outside options on their current wage: workers that would experience a 10% wage change if switching to their outside option only expect a 1% change. Second, workers in low-paying firms underestimate wages elsewhere. Third, in response to information about the wages of similar workers, respondents correct their beliefs about their outside options and change their job search and wage negotiation intentions. Finally, we analyze the consequences of anchoring in a simple equilibrium model. In the model, anchored beliefs keep overly pessimistic workers stuck in low-wage jobs, which gives rise to monopsony power and labor market segmentation.

Gun violence is the most pressing public safety problem in U.S. cities. We report results from a randomized controlled trial (N = 2,456) of a community-researcher partnership called the Rapid Employment and Development Initiative (READI) Chicago. The program offered an 18-month job alongside cognitive behavioral therapy and other social support. Both algorithmic and human referral methods identified men with strikingly high scope for gun violence reduction: for every 100 people in the control group, there were 11 shooting and homicide victimizations during the 20-month outcome period. Fifty-five percent of the treatment group started programming, comparable to take-up rates in programs for people facing far lower mortality risk. After 20 months, there is no statistically significant change in an index combining three measures of serious violence, the study’s primary outcome. Yet there are signs that this program model has promise. One of the three measures, shooting and homicide arrests, declined 65% (p = .13 after multiple-testing adjustment). Because shootings are so costly, READI generated estimated social savings between $182,000 and $916,000 per participant (p = .03), implying a benefit-cost ratio between 4:1 and 18:1. Moreover, participants referred by outreach workers—a prespecified subgroup—saw enormous declines in arrests and victimizations for shootings and homicides (79% and 43%, respectively) which remain statistically significant even after multiple-testing adjustments. These declines are concentrated among outreach referrals with higher predicted risk, suggesting that human and algorithmic targeting may work better together.