Most research on poverty focuses on the damage caused by persistent unemployment. But what happens when jobs are plentiful and workers are hard to come by? Moving the Needle examines how very low unemployment boosts wages at the bottom, improves benefits, lengthens job ladders, and pulls the unemployed into a booming job market. Drawing on over seventy years of quantitative data, as well as interviews with employers, jobseekers, and longtime residents of poor neighborhoods, Katherine S. Newman and Elisabeth S. Jacobs investigate the most durable positive consequences of tight labor markets. They also consider the downside of overheated economies that can ignite surging rents and spur outmigration. Moving the Needle is an urgent and original call to implement policies that will maintain the current momentum and prepare for potential slowdowns that may lie ahead.

In 1935, the United States passed Social Security Act (SSA) providing financial security to American families. I use the individual census data for 1940 and 1960 to show that women from states that allowed for more social spending under the SSA had substantially more children than women from states that allowed for lower social benefits. I also use a new panel of state-level fertility by parity between 1935 and 1959 to show that family allowances were connected to first, second and third parities, but that there was a differential effect according to the different social programs and race.

Does population aging fuel or hinder support for long-term public investments? Existing theories associate seniors with shorter time horizons but a higher inclination towards borrowing, yielding contradictory predictions of their support for debt-funded investments. I study the effect of aging on approval for real public investments using novel data sets on U.S. state and local bond referendums over six decades. Aging decreases approval for investments because it lowers support for lengthier policies. By contrast, aging does not make communities prefer policies funded by debt rather than taxation. Aging also shifts collective policy preferences, creating tensions between age groups on which policies to fund. Hence, communities with higher age heterogeneity present lower support for investments, especially when aging communities experience an influx of children. Intergenerational contact within families does not alleviate conflicts. These findings suggest that population aging can complicate coalition building around investments, particularly in communities with diverse age distribution.

The instability of fathers’ co-residence with children has become an increasingly prevalent experience for U.S. families. Despite long-standing scholarship examining the relationship between fatherhood and wage advantages, few studies have investigated how variation in fathers’ stable co-residence with a child may produce temporal changes in the wage premium over the life course. Building on prior explanations of the fatherhood wage premium, I test if the wage premium grows with time since the birth of a resident child and if the premium depends on fathers’ co-residence with a child. I use marginal structural models with repeated outcome measures and data from 4060 men in the National Longitudinal Survey of Youth 1979 to assess the cumulative influence of co-residential biological fatherhood on wages. I find that each year of residential fatherhood is associated with a wage gain of 1.2 percent, while the immediate wage benefit to residential fatherhood is minor. Thus, the fatherhood premium is better understood as an unfolding process of cumulative advantage rather than a one-time bonus. Furthermore, the wage premium ceases to accumulate once fathers lose co-residential status with a child, which highlights the contingency of the premium on stable co-residence. Together, these findings shed light on one pathway through which family (in)stability—a phenomenon fundamentally embedded in individual life experiences—stratifies men’s wages across the life course.

BACKGROUND The Rogers-Castro model migration schedule is a key model for migration trends over the life course. It is applied in a wide variety of settings by demographers to examine the relationship between age and migration intensity. This model is nonlinear and it can have up to 13 parameters, which can make estimation difficult. Existing techniques for parameter estimation can lead to issues such as nonconvergence, sensitivity to initial values, or optimization algorithms that do not reach the global optimum. OBJECTIVE We propose a new method of estimating the Rogers-Castro model migration schedule parameters that overcomes most common difficulties. METHODS We apply a Bayesian framework for fitting the Rogers-Castro model. We also provide the R package 'rcbayes' with functions to easily apply our proposed methodology. RESULTS We illustrate how this model and R package can be used in a variety of settings by applying it to data from the American Community Survey. CONTRIBUTION We provide a novel and easy-to-use approach for estimating Rogers-Castro model parameters. Our approach is formalized in an R package which makes parameter estimation and Bayesian methods more accessible for demographers and other researchers.

Why more young people choose to live with their parents instead of becoming independent. Revealing analysis on Millennials and Gen Z from RentCafe.

We investigate the drivers of female labor force participation in the presence of unbalanced sex ratios due to a scarcity of males. To do so, we exploit exogenous variation in sex ratios across cohorts and regions, using instruments based on massive emigration in the 1960s that was fueled by the Portuguese Colonial War. As the sex ratio declined, female labor force participation increased, while the marriage rate was unaffected. Female representation among top occupations increased, and the gender pay gap declined, consistent with the predominance of a demand shock favoring female labor.

Using data from the US Census Bureau's Household Pulse Survey, we analyzed the likelihood of loss of health insurance and enrollment into new health coverage during the early months of the COVID-19 pandemic. Loss of employment was associated with a significant increase in the likelihood of loss of health insurance and, specifically, an increase in the likelihood of employer-sponsored health insurance. However, individuals in Medicaid expansion states experienced a lower likelihood of loss of health insurance compared with individuals in nonexpansion states. At the same time, there was a statistically significant increase in Medicaid enrollment in expansion states, by 3.2 percentage points. Reemployment or acquiring employment was associated with a gain in health insurance coverage. During an economic downturn, eligibility, and coverage gaps leave many without affordable coverage options, and the pandemic will likely bring renewed attention to gaps in Medicaid coverage in nonexpansion states.

Women are underrepresented in construction, accounting for almost half of the entire workforce in 2021 but only 11.0% of the construction workforce. This trend persists among blue-collar workers; only 3.7% of construction workers are women, compared to 16.5% in all industries. The continuing labor shortages in construction highlight the need for a diverse workforce and for understanding growing workforce populations, including women, Hispanics, and workers 55 years or older.

This research report presents a comprehensive analysis of the current socioeconomic status of the Dominican population in Puerto Rico and its changes over time. Using information provided by the U.S., Census for Puerto Rico and the Puerto Rico Community Survey, the study has the following conclusions.

On the eve of World War II, a number of threads converged and resulted in the evacuation and incarceration of Japanese Americans that followed the outbreak of war. They include demographic and economic situation of the West Coast of the United States, particularly the Japanese ancestry community; the information from and characteristics of the federal statistical system and the census at the time; the emerging mobilization for national defense as war loomed; and the political strategies and personalities in the Roosevelt administration who would soon be called upon to protect the nation and prosecute the war. "Regarding the 1940 census. Suggest someone get to work right away to see if they cannot break down at the earliest possible moment the Japanese figures of this census. I suggest this because I find that no one has any really reliable figures and the data are all available in the 1940 census which has already been taken. Each district is working on these figures but it means a terrible lot of work which they should be putting on other things and in the end will only be a duplication of what the census already has. These figures should be broken down to show distribution of all people in the United States of Japanese descent right down to counties…." Presidential Advisor John Franklin Carter to Henry Field, November 14, 1941 (Carter 1941)

I analyze the impact of industrial robots on the employment of natives and immigrants in US local labor markets between 1990 and 2014. The proposed mechanism, through which robot adoption affects the employment of natives and immigrants differentially, is based on two facts: first, robots tend to displace workers based on the task content of occupations, and second, natives and immigrants in the US differ in their task specialization. Therefore, robots should affect their employment unequally. Exploiting plausibly exogenous variation in robot exposure across US local labor markets over time, I test this mechanism and find that the effect on immigrants is roughly 1.76 times greater than that observed for natives. Specifically, I find that one more robot per thousand workers reduces the employment-to-population ratio of natives and immigrants by 0.38 and 0.67 percentage points, respectively. I attribute these results to the fact that immigrants specialize in jobs or tasks at risk of being automated.

This paper presents an analysis of how firing costs impact the wages. The analysis exploits the changes of the employment-at-will introduced in different states from 1977 to 1997 in the United States, to evaluate how these increases in firing costs affected the wages of individuals with varying levels of education. A quasi-experimental approach reveals negative effects of these reforms at both the top and bottom of the wage-education distribution, indicating a polarized impact. The calibration of a standard search and matching highlights the crucial role of the probability of match-specific productivity changes in explaining the strong negative effect of firing costs on wages at both ends of the wage distribution.

We study the labor market effects of information technology (IT) during the onset of the COVID-19 pandemic, using data on IT adoption covering almost three million establishments in the US. We find that in areas where firms had adopted more IT before the pandemic, the unemployment rate rose less in response to social distancing. IT shields all individuals, regardless of gender and race, except those with the lowest educational attainment. Instrumental variable estimates–leveraging historical routine employment share as a booster of IT adoption– confirm IT had a causal impact on fostering labor markets’ resilience. Additional evidence suggests this shielding effect is due to the easiness of working-from-home and to stronger creation of digital jobs in high IT areas.

Home and community-based services (HCBS) are the predominant approach to delivering long-term services and supports in the US, but there are growing numbers of reports of worker shortages in this industry. Medicaid, the primary payer for long-term services and supports, has expanded HCBS coverage, resulting in a shift in the services' provision out of institutions and into homes. Yet it is unknown whether home care workforce growth has kept up with the increased use of these services. Using data from the American Community Survey and the Henry J. Kaiser Family Foundation, we compared trends in the size of the home care workforce with data on Medicaid HCBS participation between 2008 and 2020. The home care workforce grew from approximately 840,000 to 1.22 million workers between 2008 and 2013. After 2013, growth slowed, ultimately reaching 1.42 million workers in 2019. In contrast, the number of Medicaid HCBS participants grew continuously from 2008 to 2020, with accelerated growth between 2013 and 2020. As a consequence, the number of home care workers per 100 HCBS participants declined by 11.6 percent between 2013 and 2019, with preliminary estimates suggesting that further declines occurred in 2020. Improving access to HCBS will require not just expanded insurance coverage but also new workforce investments.

Construction is one of the most dangerous industries in the United States, with 1,034 fatal occupational injuries among all construction workers and 74,520 nonfatal injuries among private wage-and-salary construction workers in 2020. A majority of fatal occupational injuries and a large proportion of nonfatal injuries result from Construction Focus Four hazards, which include falls to a lower level, struck-by, electrocutions, and caught-in/between injuries. This classification was created in 1994 in response to the impact the top four safety hazards have on construction workers.

This dissertation explores several topics in welfare, well-being, and labor economics, with a focus on: (1) health, wealth, and racial and ethnic welfare inequality; (2) the natural environment and well-being; and (3) whether labor markets place a wage premia for jobs that require workers to consume disamenities. To achieve these goals, the study utilizes three distinct datasets and applies a range of machine learning and econometric techniques, including natural language processing algorithms, as well as dynamic panel data estimators, natural experiments, and microsimulations. In Chapter 1, titled “Beyond Income: Health, Wealth, and Racial/Ethnic Welfare Gaps Among Older Americans”, we estimate racial and ethnic disparities in well-being among the older U.S. population using an expected utility framework that incorporates differences in consumption, leisure, health, mortality, and wealth. We use longitudinal data from the Health and Retirement Study (HRS) supplemented with data from the Consumption and Activities Mail Survey (CAMS). Together, these provide a long and rich panel (1992- 2016) for our analysis. Our measure broadly indicates that racial and ethnic inequality is larger than suggested by other welfare metrics such as income or consumption. We also find health, mortality, and wealth gaps are important in explaining the level of racial and ethnic welfare inequality among the older Americans in our sample, with leisure playing a comparatively minor role. Our decomposition exercises show that a majority of the estimated welfare gaps are determined by age sixty initial conditions as opposed to racial and ethnic differences in dynamic processes after age sixty. Our morbidity counterfactuals further suggest that eliminating common heath risk factors such as hypertension or diabetes in late-life only marginally closes overall welfare gaps. These simulations suggest that policies aimed at closing racial and ethnic gaps in late-life may be more successful and efficient if targeted earlier in the life-cycle. In other words, outside of direct wealth transfers, it may largely be too late to target such interventions directly at older populations. In Chapter 2, titled “The Morning Advantage: Differential Returns to Sunlight Exposure on Well-Being”, we estimate the effect of sunlight exposure on well-being by mimicking a natural experiment that utilizes the transition to daylight savings time as an external shock to the reallocation of sunlight between the morning and evening induced by differences in sunrise and sunset times across space, and time. We combine a collection of geolocated and timestamped tweets from Twitter with Natural Language Processing algorithms to create a comprehensive panel dataset of well-being (2014-2022) for the United States. Our findings show that the returns to sunlight on sentiment are stronger in the morning than in the evening. These results contribute significantly to the ongoing debate about whether to continue or abandon the practice of daylight savings. Specifically, the positive turn of sentiment in the morning highlights the underappreciated benefits to human well-being. Therefore, the potential shifting to darker mornings and brighter evenings following the proposed Sunshine Protection Act may do more harm than good. In Chapter 3, titled “The Compensation of Conscience: Evidence from the U.S. Labor Market”, we investigate compensating differentials in the U.S. labor market related to the degree of moral compromise required in different occupations. Specifically, we explore whether jobs that require workers to compromise their moral values offer higher compensation to compensate for the disamenities that contradict their moral beliefs. To conduct our analysis, we utilize data from the National Longitudinal Survey of Youth 1997 (NLSY97) and supplement it with data from the Occupational Information Network (O*NET) job descriptor, which allows us to develop a continuous measure of moral index across occupations. This data provides a rich and extensive panel spanning from 1997 to 2017 for our analysis. Our findings, obtained through the use of two-ways fixed-effects and first-difference models, indicate that jobs that require workers to compromise their moral principles are associated with higher compensation. This suggests that there is indeed a compensating differential for engaging in disamenities that conflict with a worker’s moral values. Additionally, we observed that workers with a college education receive higher pay in jobs that require moral compromise, indicating that individuals with a college degree may have more employment opportunities and greater bargaining power, influencing their compensation preferences. Furthermore, we discovered evidence supporting an asymmetric relationship between changes in the occupational moral index and total hourly compensation. This relationship appears to be responsive to the intensity of moral compromise in the job.

The COVID-19 pandemic has been particularly devastating for those with limited economic resources. Extensive research demonstrates the negative relationship between wealth and mortality at both the individual and area levels. In addition, residential segregation has been linked to poor health and greater mortality. Home equity is the largest asset that many Americans own, but residential segregation devalues homes located in Black neighborhoods. Despite the interlocking relationships between wealth, residential segregation, and mortality, it remains unclear how wealth and residential segregation work to predict COVID-19 deaths. Using U.S. Census data and county-level COVID-19 data from Johns Hopkins University (n = 1164), I deploy median home value as a wealth proxy and negative binomial regression models to interrogate two questions. (1) What is the relationship between home value and COVID-19 deaths? (2) How does the relationship vary by level of residential segregation? Results indicate that COVID-19 mortality is 64 percent greater in the lowest wealth counties than in the wealthiest counties. At average median home value, the most segregated counties with the largest Black populations suffer 28 percent more COVID-19 deaths than similarly situated counties with low levels of residential segregation and small Black populations. This study underscores the importance of accounting for residential segregation in examinations of the well-established relationship between socioeconomic status and health and mortality.

A key reason for the existence of cities are the external-ities created when people cluster together in close proximity. During Covid, such interactions became with health risks and people found other ways to interact. We document how cities changed during Covid and consider how the persistence of these new ways of interacting, particularly remote work, will shape the development of cities in the future. We first summarize evidence showing how residential and commercial prices and activity adjusted at different distances from dense city centers during and since the pandemic. We use a textbook monocentric city model to demonstrate that two adjustments associated with remote work-reduced commuting times and increased housing demand-generate the patterns observed in the data. We then consider how these effects might be magnified by changes in urban amenities and agglomeration forces, and what such forces might mean for the future of cities.

Low-and middle-income countries (LMICs) are vulnerable to climate change and associated extreme temperatures, where the health of pregnant women and fetuses could be particularly affected. However, the extent to which anthropogenic climate change contributes to their health has not been documented. Utilizing 451,252 mother-infant pairs from 31 LMICs during 1990-2014, we show highly robust and spatially-heterogeneous associations between pregnancy extreme temperature exposure and the increased risk of reduced birth weight and low birth weight (LBW). Anthropogenic climate change contributed approximately 68.05%, 86.41%, and 76.79% of extreme heat-related LBWs in Southern Asia, Western Africa, and Eastern Africa, respectively, whereas it reduced extreme cold-related LBWs in Central, Eastern, and Southern Africa. The exposure-response relationship and the contribution from anthropogenic climate change are determined largely by the climate mean states in different regions. Our study provides compelling evidence that anthropogenic climate change disproportionately modulates extreme temperature-related fetal growth in LMICs.