Fan Wang

The frequency and intensity of heat waves are increasing, but how these trends translate to changes in the ambient heat to which children are potentially exposed (hereafter, exposures) is not well established. One complicating factor is that it is not only extreme temperatures that change over time, but also the geospatial distribution of children. Another limitation in our understanding is that existing studies often summarize exposure as person-time accumulated above a temperature cutoff, a quantity that confounds the choice of cutoff, the duration of individual exposure, and the share of the population affected. Our study addresses these gaps by developing a double-dual-distributional framework that jointly considers two types of geospatial and temporal distributions (ambient temperatures and child populations) and two types of heat exposure thresholds, namely intensity (heat levels) and duration (hourly exceedance). To illustrate, we assessed potential exposures—the ambient heat conditions experienced—among 250 million children in China, comparing the 1989–1991 and 2019–2021 periods. We found that children’s average annual exposure to moderate or stronger heat increased by 385 h, and the share exposed to strong heat for at least 12% of hours rose from 8.1% (24.9 million) to 23.7% (59.1 million). Both rising temperatures and shifts in child population distributions contribute materially to increased heat exposures in China, a finding that suggests the need for forecasts of children’s potential heat exposures to consider shifting child population distributions.

Global demographic changes in recent decades have sharply altered the contexts in which governments provide education. Focusing on primary education, we demonstrate, first, that recent demographic trends have been highly polarizing for education systems worldwide. Persistent expansionary pressures burden some of the least‐resourced educational systems, whereas these pressures are reversing in wealthier countries with higher educational expenditures. Second, we document that global educational systems have adapted to narrow gaps in student‐ or child‐teacher ratios, despite polarizing demographic trends. Third, we show that system responses vary where school‐age cohorts are declining, although little is known about the impacts of system responses. And, finally, examining Korea, a case at the leading edge of the transition to population scarcity, we demonstrate that educational system consolidation can introduce new salience to geospatial hierarchies and the political economy of allocative decisions. Policy decentralization and popular resistance stymied a trend in which nonmetropolitan areas bore the brunt of primary school closures and teacher losses, while metropolitan areas saw increases in schools and teachers despite student declines. Research is sorely needed to understand how national educational systems are impacted by and adapting to the disparate forces of population growth and scarcity.

This paper derives a closed-form solution for optimally allocating resources among heterogeneous individuals subject to individual-specific allocation constraints assuming the planner has CES-preferences and returns to allocations are non-increasing. We derive the optimal allocation of stimulus checks when the government's objective is to i) minimize inequality in consumption, ii) maximize stimulus, and iii) trade off these goals. The inputs for this analysis are obtained from a life-cycle model with heterogeneous households, which predicts household-type-specific consumption responses to different stimulus check amounts. Compared to the actual 2021-policy, optimal policies under all levels of inequality-aversion allocate more to low-income families with children.

Who should be targeted to receive a job training opportunity, some lump-sum transfer, or nutritional aid? What is the welfare gain from targeting? In this paper, I provide solutions to discrete and bounded--continuous individual allocation problems under a spectrum of planners from the Rawlsian to the Utilitarian. Optimal allocations are determined by resource availability, planner preferences, marginal effects, and expected outcomes without allocations. Optimal targeting queues determine who should receive allocations first and help characterize the optimal allocation functions. The welfare distance between observed and optimal allocations is measured in percentage resource loss as resource equivalent variations.

I develop and estimate a dynamic equilibrium model of risky entrepreneurs’ borrowing and savings decisions incorporating both formal and local-informal credit markets. Households have access to an exogenous formal credit market and to an informal credit market in which the interest rate is endogenously determined by the local demand and supply of credit. I estimate the model via Simulated Maximum Likelihood using Thai village data during an episode of formal credit market expansion. My estimates suggest that a 49 percent reduction in fixed costs increased the proportion of households borrowing formally by 36 percent, and that a doubling of the collateralized borrowing limits lowered informal interest rates by 24 percent. I find that more productive households benefited from the policies that expanded borrowing access, but less productive households lost in terms of welfare due to diminished savings opportunities. Gains are overall smaller than would be predicted by models that do not consider the informal credit market.

Recent estimates are that about 170 million children under five years of age are stunted, with significant long-run negative consequences on their schooling, cognitive skills, health and economic productivity. Understanding what determines such growth retardation, therefore, is very important. We build a structural model for nutritional choices and height growth with reference -- dependent preferences. Parents care about the relative height of their child compared to some reference population. In our empirical model, reference height is an equilibrium object determined by the parental nutritional choices for earlier cohorts in the same village. Taking advantage of a protein-supplementation experiment in Guatemala, we use exogenous variations in differential height growth paths between treated and control villages to estimate the model. We conduct a number of counterfactual policy simulations. First, we find that reference point changes account for up to 60% of the 1.7cm in height difference between experimental and control villages at 24 months of age. Second, focusing on one-period effects, to obtain the same mean effects as an 1 cm increase in reference points would require a protein-price discount of 37 percent or an income increase of 60 percent. Third, endogenous reference points changes lead to significant policy spillovers: under poor-targeted subsidy policies, richer households over time gain up to 50 percent of the height gains of poorer households; under an universal subsidy policy, poorer households' height gains increase from an initially low level by up to 4.8 times across periods as richer households, who also receive subsidies, help push up height reference points.