Knowledge that Transforms

We study the relationship between corporate income taxation and carbon dioxide (CO 2 ) emissions in the United States. We show CO 2 -intensive firms benefit more from the tax advantage of debt and pay lower income taxes on their capital income. Building on these new facts, we provide evidence that a cut in the corporate income tax rate leads to a larger expansion of clean firms. We develop a multisector general equilibrium model that accounts for our evidence and quantify the impact of corporate tax reforms on aggregate emissions. A policy that eliminates the tax advantage of debt could reduce aggregate emissions without affecting GDP.

We study cultural integration as an equilibrium outcome of marital matching along cultural and education lines and intrahousehold investment decisions regarding fertility and cultural socialization. Our model allows us to identify cultural-ethnic-group-specific investment parameters and spousal preferences for marital matching. Structural estimates reveal a strong demand to preserve cultural identity on the part of immigrants and limited acceptance of the immigrants' cultural diversity on the part of natives. Furthermore, these estimates reveal a substantial heterogeneity of the parental value of children's education across cultures. Nonetheless, our estimates simulate substantial—though heterogeneous—cultural integration rates across immigrant groups.

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.

We provide experimental evidence on the intergenerational impacts of secondary education subsidies in a low-income context, leveraging a randomized controlled trial and 15-year longitudinal follow-up. Secondary school scholarships delay fertility, reduce unwanted pregnancies, and change partner selection. Under-one mortality is reduced by half. We also document cognitive development gains of 0.24 standard deviations of test scores by age five among children of female scholarship recipients. Means-tested secondary school scholarships are a high-return investment, with a conservatively estimated US$4.1 in benefits for each US$1 the policy would cost the government in the long run.

Digital platforms reduce geographic frictions, enabling better matching between service providers and users. I quantify reallocation gains in Swedish online health care, using nationwide time-conditional random assignment between patients and physicians. Matching high-risk patients with doctors effective at reducing Emergency Room visits lowers such visits by 4.4 percent (SE 1.3); reallocations also reduce Counter-Guideline antibiotics by 3.1 percent (1.4). I find limited trade-offs in matching; horizontal differentiation among doctors and varied patient needs allow improvement in multiple outcomes simultaneously. Efficiency-enhancing reallocations also affect equity. The findings highlight the potential for care reorganization aligning provider heterogeneity with patient needs when geographic constraints are lifted.

We document how deepening resource scarcity results in rationing on the basis of race in a high-stakes setting: health care. Using detailed, time stamped data on 107,000 inpatient admissions to a large health system, we find that in-hospital mortality increases for Black but not White patients as hospitals reach capacity. These findings are not explained by differential patient selection. We identify rationing by wait times as a mechanism, documenting that sicker Black patients wait longer for care than healthier White patients at almost all capacity levels. Text analysis of unstructured clinical notes reveals rationing of provider effort as another mechanism.

Efficient risk sharing implies a simple factor structure for marginal utilities of expenditure (MUEs): Pareto weights divided by a common price. The standard approach infers MUEs from total expenditures, implicitly assuming homothetic preferences, unitary income elasticities, and identical price elasticities. Risk-sharing tests using total expenditures work for idiosyncratic shocks (budgets change, but not prices), but not “covariate” shocks (prices change). I describe all preferences that permit one to infer MUEs from expenditures and estimate nonhomothetic MUEs to test whether covariate shocks are shared efficiently in Uganda. This delivers sensible results; the standard approach suggests that droughts, floods, and pests are beneficial.

A designer employs a dynamic protocol to elicit private information. Protocols produce a set of contextual privacy violations—information learned that may be superfluous given the context. A protocol is maximally contextually private if there is no protocol that produces a proper subset of the violations it produces, while implementing the choice rule. Contextual privacy violations arise when a choice rule makes some agents collectively, but not individually, pivotal. In auctions, designing for contextual privacy requires choosing an initial question posed to each agent and the order for querying agents. Ascending-join protocols are maximally contextually private for k-item Vickrey auctions.

We study the effects of the largest corporate income tax cut in U.S. history on firms and workers. To identify causal effects, we use employer-employee matched tax records and event studies comparing similarly sized firms in the same industry that faced divergent tax changes due to their pre-existing legal status. Tax cuts cause increases in firms' investment, sales, profits, employment, and payrolls, with earnings gains concentrated among highly paid workers. In the short-run, 87% of private income gains flow to the top 10% of the income distribution.

Designing public transport networks involves trade-offs between coverage, service frequency, and direct service. We use the expansion of the bus system in Jakarta, Indonesia, to study these trade-offs. We analyze how new direct connections, changes in bus travel time, and wait-time reductions affect bus ridership and aggregate flows and estimate a transit network demand model by matching the route launch events. Commuters in Jakarta are 2–3 times more sensitive to wait time than bus time and inattentive to long routes. We develop a flexible framework to characterize optimal networks. A less concentrated network would increase ridership and commuter welfare.