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AbstractThe effects of climate change on human migration have received widespread attention, driven in part by concerns about potential large‐scale population displacements. Recent studies demonstrate that climate‐migration linkages are often complex, and climatic variability may increase, decrease, or have null effects on migration. However, the use of noncomparable analytic strategies across studies makes it difficult to disentangle substantive variation in climate effects across populations and places from methodological artifacts. We address this gap by using harmonized census and survey microdata from six Asian countries (n = 54,987,838) to measure climate effects on interprovincial migration, overall and among subpopulations defined by age, sex, education, and country of residence. We also evaluate whether climate effects differ according to the distance and type of move. Exposure to precipitation deficits leads to substantively large reductions in out‐migration, and, surprisingly, these overall effects do not vary meaningfully by age, sex, or educational attainment. However, there are significant differences in the strength and direction of temperature and precipitation effects by country and within countries. Multinomial models show that precipitation deficits reduce internal migration to both adjacent and nonadjacent provinces. Finally, consistent with expectations that climate effects operate through economic mechanisms, spells of low precipitation reduce the probability of work‐related moves in the countries where the reason for migration is measured. Our findings provide further evidence that adverse environmental conditions can reduce migration, underlining the need for policymakers to consider how to support both displaced and trapped populations.

AbstractThe literature on climate exposures and human migration has focused largely on assessing short‐term responses to temperature and precipitation shocks. In this paper, we suggest that this common coping strategies model can be extended to account for mechanisms that link environmental conditions to migration behavior over longer periods of time. We argue that early‐life climate exposures may affect the likelihood of migration from childhood through early adulthood by influencing parental migration, community migration networks, human capital development, and decisions about household resource allocation, all of which are correlates of geographic mobility. After developing this conceptual framework, we evaluate the corresponding hypotheses using a big data approach, analyzing 20 million individual georeferenced records from 81 censuses implemented across 31 countries in tropical Africa, Latin America, and Southeast Asia. For each world region, we estimate regression models that predict lifetime migration (a change in residence between birth and ages 30–39) as a function of temperature and precipitation anomalies in early life, defined as the year prior to birth to age four. Results suggest that early‐life climate is systematically associated with changes in the probability of lifetime migration in most regions of the tropics, with the largest effects observed in sub‐Saharan Africa. In East and Southern Africa, the effects of temperature shocks vary by sex and educational attainment and in a manner that suggests women and those of lower socioeconomic status are most vulnerable. Finally, we compare our main results with models using alternative measures of climate exposures. This comparison suggests climate exposures during the prenatal period and first few years of life are particularly (but not exclusively) salient for lifetime migration, which is most consistent with the hypothesized human capital mechanism.

AbstractHigh underemployment has been a chronic structural feature of the rural United States for decades. In this paper, we assess whether and how inequalities in underemployment between metropolitan (metro) and nonmetropolitan (nonmetro) areas have changed over the course of the last five decades. Drawing on data from the March Current Population Survey from 1968 to 2017, we analyze inequality in the prevalence of underemployment between metro and nonmetro areas of the United States, paying special attention to differences between white, black, and Hispanic workers. Our results show that the underlying risk of underemployment has increased in both metro and nonmetro areas over the last 50 years. Nonmetro workers have consistently faced greater employment hardship compared to their metro counterparts, and these differences cannot be fully explained by differences in population characteristics. Nonmetro ethnoracial minorities have experienced particularly poor labor market outcomes. The disadvantage of ethnoracial minority status and rural residence is especially pronounced for nonmetro black workers, among whom underemployment has remained persistently high with only modest convergence with other workers. Hispanic workers also face an elevated risk of underemployment, but we observe a unique convergence between metro and nonmetro workers within this population.

This article explores recent racial and ethnic inequalities in poverty, estimating the share of racial poverty differentials that can be explained by variation in family structure and workforce participation. The authors use logistic regression to estimate the association between poverty and race, family structure, and workforce participation. They then decompose between‐race differences in poverty risk to quantify how racial disparities in marriage and work explain observed inequalities in the log odds of poverty. They estimate that 47.7% to 48.9% of Black–White differences in poverty risk can be explained by between‐group variance in these two factors, while only 4.3% to 4.5% of the Hispanic–White differential in poverty risk can be explained by these variables. The findings underscore the continued but varied association between racial disparities in poverty and labor and marriage markets. Clear racial differences in the origin of poverty suggest that policy interventions will not have uniformly effective impacts on poverty reduction.

AbstractThe current natural gas and oil boom in North America requires new pipelines, which pose environmental risks from wellheads to their destinations. The environmental justice literature suggests that ethno‐racial minorities, populations with low socioeconomic status, and rural communities are disproportionally exposed to risks associated with potentially harmful land uses. Using data from the American Community Survey's 2015 five‐year estimates and data on the route of proposed pipelines compiled by The FracTracker Alliance, this study tests whether the above assumptions are true for proposed FERC‐permitted natural gas transmission pipelines in the United States for which planned routes have been made available. The results of logistic regression models provide only limited, and in some cases contradictory, support for these hypotheses. Although an increased share of highly educated residents significantly decreases the likelihood of a pipeline proposal in a census tract, a higher poverty rate also significantly lowers this probability. Likewise, the share of Black and Hispanic residents is significantly and negatively associated with pipeline proposals. However, reliable routing data are needed to test whether this holds true for built pipelines, but these data are considered confidential and thus inaccessible in the United States.