Knowledge that Transforms

Alphabetical name order is the norm for joint publications in economics. However, alphabetical order confers greater benefits on the first author. In a two-author model, we introduce and study certified random order: the uniform randomization of names made universally known by a commonly understood symbol. Certified random order (i) distributes the gain from first authorship evenly over the alphabet; (ii) allows either author to signal when contributions are extremely unequal; (iii) will invade an environment where alphabetical order is dominant; (iv) is robust to deviations; (v) may be ex ante more efficient than alphabetical order; and (vi) is no more complex than the existing alphabetical system modified by occasional reversal of name order.

This paper uses a natural experiment to estimate the causal effect of temporary trade protection on long-term economic development. I find that regions in the French Empire which became better protected from trade with the British for exogenous reasons during the Napoleonic Wars (1803–1815) increased capacity in mechanized cotton spinning to a larger extent than regions which remained more exposed to trade. In the long run, regions with exogenously higher spinning capacity had higher activity in mechanized cotton spinning. They also had higher value added per capita in industry up to the second half of the nineteenth century, but not later.

This paper investigates the effects of polling station administrator diversity on elections in India, using a natural experiment: the random assignment of government officials to teams managing stations on election day, together with surveys conducted with voters and election officers. I demonstrate that changes in the religious and caste composition of officer teams impact voting at the polling station level, causing shifts in coalition vote shares large enough to influence election outcomes. Effects are strongest when officers have greater discretion over the voting process. I also provide evidence suggesting own-group favoritism by election personnel as one relevant mechanism.

Richard H. Thaler delivered his Prize Lecture on 8 December 20167 at the Aula Magna, Stockholm University.

In this comment on Callen et al. (2014), I revisit recent evidence uncovering a “preference for certainty” in violation of dominant normative and descriptive theories of decision-making under risk. I show that the empirical findings are potentially confounded by systematic noise. I then develop choice lists that allow me to disentangle these different explanations. Experimental results obtained with these lists reject explanations based on a preference for certainty in favor of explanations based on random choice. From a theoretical point of view, the levels of risk aversion detected in the choice list involving certainty can be accounted for by prospect theory through reference dependence activated by salient outcomes.

How large are the benefits of transportation infrastructure projects, and what explains these benefits? This paper uses archival data from colonial India to investigate the impact of India's vast railroad network. Guided by four results from a general equilibrium trade model, I find that railroads: (1) decreased trade costs and interregional price gaps; (2) increased interregional and international trade; (3) increased real income levels; and (4) that a sufficient statistic for the effect of railroads on welfare in the model accounts well for the observed reduced-form impact of railroads on real income in the data.

Differences in employment-population ratios across US commuting zones have persisted for many decades. We claim these disparities represent real gaps in economic opportunity for individuals of fixed characteristics. These gaps persist despite a strong migratory response, and we attribute this to high persistence in labor demand shocks. These trends generate a “race” between local employment and population: population always lags behind employment, yielding persistent deviations in employment rates. Methodologically, we argue the employment rate can serve as a sufficient statistic for local well-being; and we model population and employment dynamics using an error correction mechanism, which explicitly allows for disequilibrium.

We identify structural vector autoregressions using narrative sign restrictions. Narrative sign restrictions constrain the structural shocks and/or the historical decomposition around key historical events, ensuring that they agree with the established narrative account of these episodes. Using models of the oil market and monetary policy, we show that narrative sign restrictions tend to be highly informative. Even a single narrative sign restriction may dramatically sharpen and even change the inference of SVARs originally identified via traditional sign restrictions. Our approach combines the appeal of narrative methods with the popularized usage of traditional sign restrictions.

To understand the elasticity of employment to local labor demand shocks, we develop a quantitative general equilibrium model that incorporates spatial linkages in goods markets (trade) and factor markets (commuting and migration). We show that local employment elasticities differ substantially across U.S. counties and commuting zones in ways that are not well explained by standard empirical controls but are captured by commuting measures. We provide independent evidence for these predictions from million dollar plants and find that empirically-observed reductions in commuting costs generate welfare gains of around 3.3 percent and employment reallocations from -20 to 30 percent.

We establish the importance of team-specific capital in the typical inventor's career. Using administrative tax and patent data for the population of US patent inventors from 1996 to 2012, we find that an inventor's premature death causes a large and long-lasting decline in their co-inventor's earnings and citation-weighted patents (−4 percent and −15 percent after 8 years, respectively). After ruling out firm disruption, network effects, and top-down spillovers as main channels, we show that the effect is driven by close-knit teams and that team-specific capital largely results from an “experience” component increasing collaboration value over time.