Knowledge that Transforms

Abstract When a Bayesian learns new information and changes her beliefs, she must on average become concomitantly more certain about the state of the world. Consequently, it is rare for a Bayesian to frequently shift beliefs substantially while remaining relatively uncertain, or, conversely, become very confident with relatively little belief movement. We formalize this intuition by developing specific measures of movement and uncertainty reduction given a Bayesian’s changing beliefs over time, showing that these measures are equal in expectation and creating consequent statistical tests for Bayesianess. We then show connections between these two core concepts and four common psychological biases, suggesting that the test might be particularly good at detecting these biases. We provide support for this conclusion by simulating the performance of our test and other martingale tests. Finally, we apply our test to data sets of individual, algorithmic, and market beliefs.

Abstract We propose a theory of indebted demand, capturing the idea that large debt burdens lower aggregate demand, and thus the natural rate of interest. At the core of the theory is the simple yet underappreciated observation that borrowers and savers differ in their marginal propensities to save out of permanent income. Embedding this insight in a two-agent perpetual-youth model, we find that recent trends in income inequality and financial deregulation lead to indebted household demand, pushing down the natural rate of interest. Moreover, popular expansionary policies—such as accommodative monetary policy—generate a debt-financed short-run boom at the expense of indebted demand in the future. When demand is sufficiently indebted, the economy gets stuck in a debt-driven liquidity trap, or debt trap. Escaping a debt trap requires consideration of less conventional macroeconomic policies, such as those focused on redistribution or those reducing the structural sources of high inequality.

Abstract How does unemployment insurance (UI) affect unemployed workers’ search behavior? Search models predict that until benefit exhaustion, UI depresses job search effort and increases reservation wages. Over an unemployment spell, search effort should increase up to benefit exhaustion and stay high thereafter. Meanwhile, reservation wages should decrease up to benefit exhaustion and stay low thereafter. To test these predictions, we link administrative registers to data on job search behavior from a major online job search platform in France. We follow over 400,000 workers, as long as they remain unemployed. We analyze the changes in search behavior around benefits exhaustion and take two steps to isolate the individual response to unemployment benefits. First, our longitudinal data allows us to correct for changes in sample composition over the spell. Second, we exploit data on workers eligible for 12–24 months of UI as well as workers ineligible for UI, to control for behavior changes over the unemployment spell that are independent of UI. Our results confirm the predictions of search models. We find that search effort (the number of job applications) increases by at least 50% during the year preceding benefits exhaustion and remains high thereafter. The target monthly wage decreases by at least 2.4% during the year preceding benefits exhaustion and remains low thereafter. In addition, we provide evidence for duration dependence: workers decrease the wage they target by 1.5% over each year of unemployment, irrespective of their UI status.

Abstract We explore the interplay between trade-invoicing patterns and the pricing of safe assets in different currencies. Our theory highlights the following points: (i) a currency’s role as a unit of account for invoicing decisions is complementary to its role as a safe store of value; (ii) this complementarity can lead to the emergence of a single dominant currency in trade invoicing and global banking, even when multiple large candidate countries share similar economic fundamentals; (iii) firms in emerging-market countries endogenously take on currency mismatches by borrowing in the dominant currency; and (iv) the expected return on dominant-currency safe assets is lower than that on similarly safe assets denominated in other currencies, thereby bestowing an “exorbitant privilege” on the dominant currency. The theory thus provides a unified explanation for why a dominant currency is so heavily used in both trade invoicing and in global finance.

Abstract Information is central to designing effective policy, and policy makers often rely on competing interests to separate useful from biased information. We show how this logic of virtuous competition can break down, using a new and comprehensive data set on U.S. federal regulatory rulemaking for 2003–2016. For-profit corporations and nonprofit entities are active in the rulemaking process and are arguably expected to provide independent viewpoints. Policy makers, however, may not be fully aware of the financial ties between some firms and nonprofits—grants that are legal and tax-exempt but hard to trace. We document three patterns that suggest that these grants may distort policy. First, we show that shortly after a firm donates to a nonprofit, the nonprofit is more likely to comment on rules on which the firm has also commented. Second, when a firm comments on a rule, the comments by nonprofits that recently received grants from the firm’s foundation are systematically closer in content to the firm’s own comments, relative to comments submitted by other nonprofits. Third, the final rule’s discussion by a regulator is more similar to the firm’s comments on that rule when the firm’s recent grantees also commented on it.

Abstract During traffic stops, police search black and Hispanic motorists more than twice as often as white motorists, yet those searches are no more likely to yield contraband. We ask whether equalizing search rates by motorist race would reduce contraband yield. We use unique administrative data from Texas to isolate variation in search behavior across and within highway patrol troopers and find that search rates are unrelated to the proportion of searches that yield contraband. We find that troopers can equalize search rates across racial groups, maintain the status quo search rate, and increase contraband yield. Troopers appear to be limited in their ability to discern between motorists who are more or less likely to carry contraband.

Abstract The labor share in U.S. manufacturing declined from 61% in 1967 to 41% in 2012. The labor share of the typical U.S. manufacturing establishment, in contrast, rose by over 3 percentage points during the same period. Using micro-level data, we document five salient facts: (i) since the 1980s, there has been a dramatic reallocation of value added toward the lower end of the labor share distribution; (ii) this aggregate reallocation is not due to entry/exit, to “superstars” growing faster, or to large establishments lowering their labor shares, but is instead due to units whose labor share fell as they grew in size; (iii) low labor share (LL) establishments benefit from high revenue labor productivity, not low wages; (iv) they also enjoy a product price premium relative to their peers; and (v) they have only temporarily lower labor shares that rebound after five to eight years. This transient pattern has become more pronounced over time, and the dynamics of value added and employment are increasingly disconnected. Taken together, we interpret these facts as pointing to a significant role for demand-side forces.

Abstract We argue that the network of investment production and purchases across sectors is an important propagation mechanism for understanding business cycles. Empirically, we show that the majority of investment goods are produced by a few “investment hubs,” which are more cyclical than other sectors. We embed this investment network into a multisector business cycle model and show that sector-specific shocks to the investment hubs and their key suppliers have large effects on aggregate employment and drive down labor productivity. Quantitatively, we find that sector-specific shocks to hubs and their suppliers account for an increasing share of aggregate fluctuations over time, generating the declining cyclicality of labor productivity and other changes in business cycle patterns since the 1980s.

Abstract Most convicted offenders serve their sentences under “community supervision” at home instead of in prison. Under supervision, however, a technical rule violation, such as not paying fees, can result in incarceration. Rule violations account for 25% of prison admissions nationally and are significantly more common among black offenders. I test whether technical rules are effective tools for identifying likely reoffenders and deterring crime and examine their disparate racial impacts using administrative data from North Carolina. Analysis of a 2011 reform reducing prison punishments for technical violations on probation reveals that 40% of rule breakers would go on to commit crimes if spared harsh punishment. The same reform also closed a 33% black-white gap in incarceration rates without substantially increasing the black-white reoffending gap. These effects combined imply that technical rules target riskier probationers overall but disproportionately affect low-risk black offenders. To justify black probationers’ higher violation rate on efficiency grounds, their crimes must be roughly twice as socially costly as that of white probationers. Exploiting the repeat spell nature of the North Carolina data, I estimate a semiparametric competing risks model that allows me to distinguish the effects of particular types of technical rules from unobserved probationer heterogeneity. Rules related to the payment of fees and fines, which are common in many states, are ineffective in tagging likely reoffenders and drive differential effects by race. These findings illustrate the potentially large influence of ostensibly race-neutral policies on racial disparities in the justice system.

Abstract I study how people understand, reason, and learn about two major tax policies: income taxation and estate taxation. Using large-scale social economics surveys issued to representative U.S. samples and associated experiments, I elicit respondents’ factual knowledge about tax policy and the income or wealth distributions. Most important, I study their understanding of the mechanisms of tax policy and the reasoning that underlies their policy views. In decomposing policy views, I find that support for income and estate taxes is most strongly correlated with social preferences, that is, the perceived benefits of redistribution and concerns around the fairness of inequality and taxation, as well as with broader views of the government. Efficiency concerns play a more minor role. These correlational patterns are confirmed by the experimental approach, which shows people instructional videos that explain the workings and consequences of one of the aspects of tax policy (the Redistribution and the Efficiency treatments) or that bring the two together and focus on the trade-off (the Economist treatment). The Redistribution and Economist treatments significantly increase support for more progressive income or estate taxes, while the Efficiency treatment has no effect. There are large partisan gaps in both the final policy views and at every step of the reasoning about the underlying mechanisms of taxes. Democrats’ and Republicans’ divergences in tax policy views can ultimately be traced back to different normative criteria (social preferences) and views of the government, rather than to different perceptions of the efficiency implications of taxation.