Two years prior to elections, two-thirds of Delhi municipal councillors learned they had been randomly chosen for a preelection newspaper report card. Treated councillors in high-slum areas increased pro-poor spending, relative both to control counterparts and treated counterparts from low-slum areas. Treated incumbents ineligible to rerun in home wards because of randomly assigned gender quotas were substantially likelier to run elsewhere only if their report card showed a strong pro-poor spending record. Parties also benefited electorally from councillors' high pro-poor spending. In contrast, in a cross-cut experiment, councillors did not react to actionable information that was not publicly disclosed.
We derive a small open economy (SOE) as the limit of an economy as the number or size of its trading partners goes to infinity and trade costs also go to infinity. We obtain this limit in the Armington, Eaton–Kortum, Krugman, and Melitz models. In all cases, the trade of the SOE with the foreign countries approaches a finite limit, and the domestic expenditure share for the SOE approaches a limit that is not zero or unity. The foreign countries can be either infinitely many SOEs, or alternatively, one or many large countries with domestic expenditure shares that approach unity. We illustrate the usefulness of this framework by obtaining a formula for the optimal tariff in the SOE – depending on the elasticity of domestic wages with respect to the tariff – that is consistent with all models.
We study personalized pricing in a general oligopoly model. The impact of personalized pricing relative to uniform pricing hinges on the degree of market coverage. If market conditions are such that coverage is high (e.g., the production cost is low or the number of firms is high), personalized pricing harms firms and benefits consumers, whereas the opposite is true if coverage is low. When only some firms have data to personalize prices, consumers can be worse off compared to when either all or no firms personalize prices.
This paper studies the social value of closing price differentials in financial markets. We show that arbitrage gaps exactly correspond to the marginal social value of executing an arbitrage trade. Moreover, arbitrage gaps and price impact measures are sufficient to compute the total social value from closing an arbitrage gap, which may emerge for different reasons, including nonpecuniary benefits of holding particular assets. Theoretically, we show that, for a given arbitrage gap, the total social value of arbitrage is higher in more liquid markets. We compute the welfare gains from closing arbitrage gaps for covered interest parity violations.
We study robust welfare comparisons of learning biases (misspecified Bayesian and some forms of non-Bayesian updating). Given a true signal distribution, we deem one bias more harmful than another if it yields lower objective expected payoffs in all decision problems. We characterize this ranking in static and dynamic settings. While the static characterization compares posteriors signal by signal, the dynamic characterization employs an "efficiency index" measuring how fast beliefs converge. We quantify and compare the severity of several well-documented biases. We also highlight disagreements between the static and dynamic rankings, and that some "large" biases dynamically outperform other "vanishingly small" biases.
The US-China trade war created net export opportunities rather than simply shifting trade across destinations. Many "bystander" countries grew their exports of taxed products into the rest of the world (excluding the United States and China). Country-specific components of tariff elasticities, rather than specialization patterns, drove large cross-country variation in export growth of tariff-exposed products. The elasticities of exports to US-Chinese tariffs identify whether a country's exports complement or substitute the United States or China and its supply curve's slope. Countries that operate along downward-sloping supplies whose exports substitute (complement) the United States and China are among the larger (smaller) beneficiaries of the trade war.
Building on Pomatto, Strack, and Tamuz (2020), we identify a tight condition for when background risk can induce first-order stochastic dominance. Using this condition, we show that under plausible levels of background risk, no theory of choice under risk can simultaneously satisfy the following three economic postulates: (i) decision-makers are risk averse over small gambles, (ii) their preferences respect stochastic dominance, and (iii) they account for background risk. This impossibility result applies to expected utility theory, prospect theory, rank-dependent utility, and many other models.
There is a large gender wage gap among college graduates. This gender gap could be partially driven by differences in college major and prior skills. We use Swedish register data to study how much of the gender gap can be explained by differences in majors, skills, and skill prices. College majors explain 60 percent of the gender wage gap, but large gaps remain within majors. We find that within-major wage gaps are driven by neither differences in multidimensional skills nor returns to these skills. In fact, women are positively selected in terms of college preparation and skills in almost every major.
Low- and middle-income nations host 76 percent of the world's refugees. This study uses original data to explore within-country spatial variability in refugee-hosting responsibilities. We find that hosting responsibilities for the displaced Rohingya people in Bangladesh are allocated in similarly unequal fashion when analyzed at the national, regional, and microregional levels. Refugee camps are placed in socioeconomically disadvantaged communities relative to both Bangladesh as a whole and surrounding areas. Our findings underscore the importance of considering host communities in the coordination of humanitarian responses to refugee crises to prevent economic hardship and political backlash.
Firms facing complex objectives often decompose the problems they face, delegating different parts of the decision to distinct subunits. Using comprehensive data and internal models from a large U.S. airline, we establish that airline pricing is not well approximated by a model of the firm as a unitary decision maker. We show that observed prices, however, can be rationalized by accounting for organizational structure and for the decisions by departments that are tasked with supplying inputs to the observed pricing heuristic. Simulating the prices the firm would charge if it were a rational, unitary decision maker results in lower welfare than we estimate under observed practices. Finally, we discuss why counterfactual estimates of welfare and market power may be biased if prices are set through decomposition, but we instead assume that they are set by unitary decision makers.