顶刊方法追踪

Abstract We propose a tractable model in which risk, at both the micro and macro levels, is endogenous and driven by incentives. In the model, each firm chooses the mean and the variance of its productivity process, as well as how it covaries with the productivity of other firms. Aggregate risk arises when firms select productivity processes that are correlated with one another. The theory predicts that larger firms and those with lower markups are less volatile and less correlated with aggregate productivity. We find support for these predictions in the data. Through their impact on risk-taking decisions, distortions such as taxes and markups can make GDP more volatile in equilibrium. In a calibrated version of the model, removing distortions significantly reduces GDP volatility.

Abstract School assignment policies are a key lever for expanding access to high-performing schools and promoting racial and socioeconomic integration. For over 50 years, the Metropolitan Council for Educational Opportunity (METCO) has bussed students of color from Boston, Massachusetts, to relatively wealthier and predominantly white suburbs. I estimate the effects of attending a high-performing suburban school by comparing applicants who receive enrollment offers with applicants who do not. A two-stage least squares approach exploits waitlist assignment priorities and controls for a rich set of characteristics from birth records and application data. Attending a suburban school boosts math and English test scores, reduces dropout, and increases on-time high school graduation. Four-year college aspirations, enrollment, and graduation increase along with earnings in adulthood. Students whose parents did not attend college and boys experience the largest effects. The evidence points to several mechanisms, including access to higher value-added schools, higher-achieving peers, and schools with stronger college-going norms. Participants are more likely to be tracked into lower-performing classes, implying that effects could be larger with access to more advanced coursework. District value-added estimates suggest that students’ educational trajectories shift at least as much as they would from growing up in the suburban districts.

Abstract This paper provides evidence on how wage inequality among workers affects the labor movement using three complementary research designs: a vignette experiment with union organizers, a natural policy experiment that increased wage inequality among Wisconsin school teachers, and an information intervention during the 2023 Writers Guild of America strike. Across all studies, we find that inequality undermines union strength through multiple channels. First, workers with high individual bargaining power are more likely to withdraw support in unequal environments, preferring individual over collective bargaining. Second, union organizers facing hypothetical choices strategically respond to inequality in ways that may preserve membership but limit redistribution, such as shifting their campaign away from wages and choosing smaller, more homogeneous bargaining units.

Abstract There is a large latent workforce in developing countries that consists of hundreds of millions of women who prefer to have paid work and yet are out of the labor force. Often, available job opportunities are incompatible with traditional gender roles that encourage women to stay at home. In a randomized experiment with 1,670 households, we partner with a jobs platform to offer short-term data work to women who are out of the labor force. We find three main results. First, flexible work-from-home jobs are highly effective at bringing women into paid work. Job flexibility more than triples take-up from 15% for an office job to 48% for a job that women can do from home while multitasking with childcare. Second, these jobs can act as a stepping stone to less flexible work. Trying paid work from home increases take-up of less flexible jobs two to three months later among women without previous work experience. “Gateway jobs” are especially important for women from more traditional households: their labor supply is more likely to be marginal to flexibility, and in turn, work experience shifts their attitudes to become less traditional. Third, from the labor demand side, remote work comes with trade-offs in worker performance. Working from the office increases accuracy by 3% and speed by 18%. However, these performance drawbacks of work-from-home arrangements may be outweighed by the increase in available workers.

Abstract We measure which economic topics are top of mind using quarterly German household and firm panels from 2020 to 2024, a period that spans the post-pandemic inflation surge and the subsequent disinflation. With these data, we study potential determinants and consequences of having inflation top of mind. In line with goal-directed attention, the likelihood that inflation is top of mind rises with proxies for its true payoff relevance. At the same time, prior experiences predict whether respondents have inflation and energy prices top of mind conditional on a large set of controls for payoff relevance, and this relationship strengthens when the environment becomes more inflationary. Having inflation top of mind predicts stronger increases in information acquisition and inflation expectations over the shock period. At odds with goal-optimality, having inflation top of mind is associated with expectations further away from multiple ex-ante benchmarks. Finally, both key determinants of having inflation top of mind—payoff relevance and prior experiences—are associated with stronger shifts of expectations away from these benchmarks over the shock period.

Abstract This article provides the first comprehensive global evidence on people’s fairness and efficiency preferences, beliefs about the sources of inequality and the efficiency cost of redistribution, and policy attitudes toward redistribution. Using a globally harmonized consequential experiment with more than 65,000 individuals across 60 countries, we show that the source of inequality plays a substantially larger role for inequality acceptance than the efficiency cost of redistribution. At the global level, implemented inequality increases by 85% when inequality is caused by merit rather than luck, compared with a 14% increase when redistribution entails a 50% efficiency cost. We document substantial heterogeneity in fairness views and beliefs within and across societies. The meritocratic fairness view is most prominent in many richer Western societies, while libertarian and egalitarian fairness views are widespread in many other parts of the world. Globally, people are more likely to believe that inequality reflects luck rather than merit, while beliefs in large efficiency costs of redistribution are relatively weak. Fairness preferences and beliefs are strongly associated with redistribution attitudes and actual redistribution through taxes and transfers across countries. Our findings illustrate how the interaction between fairness views and beliefs may shape redistribution across societies, highlighting the importance of jointly understanding preferences and beliefs in the political economy of redistribution.

Abstract We study the history and geography of wealth accumulation in the United States using newly collected historical property tax records from the early 1800s onward. These records come from the administration of the General Property Tax—a tax that aspired to cover all types of property. We construct wealth series at the state, county, and national levels. At the state level, we use annual assessed values of wealth from state-level reports drawn from multiple sources. Because assessed values may differ from market values, we also require assessment ratios, defined as the ratio of assessed to market wealth. We obtain state-level assessment ratios from decadal U.S. Census wealth data (drawn from various census reports, including those on “Wealth, Debt, and Taxation”), in which the census carried out detailed valuation work, complemented with information on changes in assessment practices from the state reports, to build higher-frequency series of assessment ratios. The result is long-run annual wealth series for states from 1850 (or earlier, depending on the state) to 1935. We obtain national wealth series by aggregating these state series. At the county level, we use assessed values (or market values where available) from the U.S. Census wealth data for each decade and apply either state-level or county-level assessment ratios, where available, to obtain market values of wealth for each decade from 1850 to 1930. We use these data to show, first, that the United States experienced extraordinary wealth accumulation after the Civil War and until the Great Depression. Second, spatial inequality in the United States has been large and highly persistent since the mid-1800s. We also examine the determinants of long-term wealth growth and find, among other results, that counties with a higher share of enslaved property before the Civil War or with higher wealth inequality experienced lower subsequent long-run wealth growth.

An increasing number of decisions are guided by machine learning algorithms. But when consequential decisions are encoded in algorithms, individuals may strategically alter their behavior to achieve desired outcomes. This paper develops an empirical approach that adjusts decision algorithms to anticipate manipulation. By explicitly modeling incentives to manipulate, our approach produces decision rules that are stable under manipulation, even when the rules are fully transparent. We stress-test this approach through a large field experiment in Kenya. When implemented, linear strategy-robust decision rules outperform standard linear models such as LASSO. (JEL C45, C93, D12, D91, G51, O12, O16)