Various fields and commercial sectors have witnessed a transformation with the advent of the internet. In the last decade, the retail sector in particular has witnessed the massive growth of e-commerce. This has also significantly altered our shopping experiences, influencing a range of decisions, from where, how, and how much to shop. With the consistent growth of e-commerce transactions, more trucks than ever before are entering cities today, bringing with them the negative externalities of increased congestion and pollution. This study first unravels underlying shopping behaviors–both in-store and online–using the 2016 American Time Use Survey (ATUS) data. The authors also develop an econometric behavioral model to understand the factors that affect shopping decisions. At a macro level, the disaggregate individual shopping behaviors are studied by implementing the model to synthetic populations to estimate potential vehicle miles traveled and environmental emissions in two metropolitan areas, Dallas and San Francisco (SF). Finally, the study estimates the impacts of rush deliveries, basket size, and consolidation levels by developing a breakeven analysis between in-store and online shopping. These results confirm the importance of managing the urban freight system, including delivery services and operations, to foster a more sustainable urban environment.

There is a transformation now underway in economics that is thoroughly upending the conventional wisdom about how our nation can deliver strong, stable, and broadly shared economic growth. A new generation of scholars, informed by new data and sources of empirical evidence, is challenging long-held assumptions about how the economy works and the extent to which those workings can be understood in isolation from the larger dynamics of the rest of society. Real-world observations are undermining the claim that markets left to their own devices reliably deliver socially beneficial outcomes. All this is paving the way for a major shift. The new framework starts from the understanding—grounded in the evidence—of the ways that inequality obstructs, subverts, and distorts economic growth. While Adam Smith’s famous invisible hand pushes the economy toward broadly beneficial outcomes, economic inequality acts as bind, thwarting the idealized market processes as it transforms into social and political power. A rising tide cannot lift all boats when some cannot even get launched and others pushed off course and deprived of navigation tools, founder on the rocks. Inequality constricts economic growth. This framework exposes dynamics more complex than the conventional economic wisdom of the past can explain. While it is tempting to embrace the simple tale that a rising tide lifts all boats, we need to make sense of a large body of research literature, much of which has focused not directly on the question of how inequality affects economic growth but rather on how inequality affects mechanisms that in turn drive investment and productivity. The reasons that economic benefits are not flowing to families may be disparate, but there are many common themes—which, once fully traced, can reveal new patterns to guide better economic thinking and policymaking.

In the United States, the COVID-19 pandemic struck a uniquely precarious workforce: No other high-income country has experienced such deep job losses. The shock has exposed and widened rifts in our two-tiered labor market—between workers with stable jobs and the newly unemployed, between those who can work from home and those who can’t, and between high-income workers and those struggling to make ends meet.

The proliferation of dams since 1950 promoted sediment deposition in reservoirs, which is thought to be starving the coast of sediment and decreasing the resilience of communities to storms and sea-level rise. Diminished river loads measured upstream from the coast, however, should not be assumed to propagate seaward. Here, we show that century-long records of sediment mass accumulation rates (g cm−2 yr−1) and sediment accumulation rates (cm yr−1) more than doubled after 1950 in coastal depocenters around North America. Sediment sources downstream of dams compensate for the river-sediment lost to impoundments. Sediment is accumulating in coastal depocenters at a rate that matches or exceeds relative sea-level rise, apart from rapidly subsiding Texas and Louisiana where water depths are increasing and intertidal areas are disappearing. Assuming no feedbacks, accelerating global sea-level rise will eventually surpass current sediment accumulation rates, underscoring the need for including coastal-sediment management in habitat-restoration projects.

This paper focuses on the implications of marital status on homeownership trends. Using data from the Integrated Public Use Microdata Series (IPUMS-USA), over years 2006-2017, I use a linear regression model to first examine factors that contribute to declining marriage rates. Factors that affect marriage rates include race, gender, personal income, employment. Next, I analyze the impact of marital status on homeownership trends. Our results show that those who have never been married have a negative relationship with homeownership. This holds true for both females and males. Overall, women showed stronger correlation towards decisions of homeownership over men across all variables. Certain variables like employment, race, education, and age affects one's decision to own over rent while personal income showed little to no influence.

Ethnoracial diversification is a necessary if insufficient step toward integration. It expands access to the advantages that decades of segregationist policies concentrated in white neighborhoods. Policy makers have long experimented with strategies to encourage and anchor neighborhood diversification, with limited success. Most diversification, however, has happened without policy interventions in cities across the United States. There is today more diverse neighborhoods than ever, but do they fulfill the promises of integration? If so, where? The first chapter examines the potential of white neighborhoods that gradually diversified to lead to integration in Los Angeles County. Gradual diversification balances the reproduction of neighborhood advantage with expanding access to lower income residents. Neighborhoods that . . .

In geographical literature, numerous studies have demonstrated the differences that arise if spatial autocorrelation (SAC) is incorporated into a conventional nonspatial modeling procedure, but little is known about when these differences might be magnified. This study addressed this query by conducting two sets of regression modeling for 561 variables representing housing prices, metropolitan industry, health, crime, education, and (un)employment across various parts of the United States: (1) nonspatial ordinary least squares (OLS) using a set of selected independent variables and (2) spatial regression incorporating spatial filters into the nonspatial OLS as additional independent variables. This incorporation generally improved the model outcomes through decreases in residual autocorrelation and Akaike’s information criterion (AIC). The degree of improvement correlated positively with the level of SAC inherent in the dependent variables. That is, strongly autocorrelated socioeconomic variables underwent greater decreases in residual autocorrelation and AIC than those variables with weaker SAC. The results imply that spatial modeling outcomes are sensitive to and potentially predictable by the level of SAC possessed by dependent variables. Therefore, the degree of SAC present in a socioeconomic variable can serve as a direct indicator of how much improvement a nonspatial OLS will experience if that SAC is properly accounted for.

Combining narrative history with data-rich social and economic analysis, this new institutional economics study examines the failure of frontier farms in the antebellum Northwest Territory, where legislatively-created imperfect markets and poor surveying resulted in massive investment losses for both individual farmers and the national economy. The history of farming and spatial settlement patterns in the Great Lakes region is described, with specific focus on the State of Michigan viewed through a case study of Midland County. Inter and intra-state differences in soil endowments, public and private promoters of site-specific investment opportunities, time trends in settled populations and the experiences of individual investors are covered in detail.

This paper extends previous measurements of the children’s income-health gradient through 2015. We first replicate findings about the steepness of the gradient from 1986 to 2005. We then find that since 2005, the health gradient between children in low-income families and high-income families has flattened, but it still steepens with age. We also show that overall children’s health has improved since 2005.

Knowledge of the determinants of self-employment income is critical to entrepreneurial development strategies ifthe development goal is to increase incomes not just employment.Using American Community Survey data, unconditional quantile regression is used to investigate differences in the relationship between entrepreneurial income and an array of individual, industry, and regional characteristics across the self-employment income distribution. Personal attributes, such as education, race,age, and gender, both explaindifferences in self-employment income and vary in importance across the income distribution.Regional agglomerative effects are significantly positive and stronger at the upper end of the self-employed income distribution.

The race between education and technology provides a canonical framework that does an excellent job of explaining U.S. wage structure changes across the twentieth century. The framework involves secular increases in the demand for more-educated workers from skill-biased technological change, combined with variations in the supply of skills from changes in educational access. We expand the analysis backwards and forwards. The framework helps explain rising skill differentials in the nineteenth and twenty-first centuries, but needs to be augmented to illuminate the recent convexification of education returns and implied slowdown in the growth of the relative demand for college workers. Increased educational wage differentials explain 75 percent of the rise of U.S. wage inequality from 1980 to 2000 as compared to 38 percent for 2000 to 2017.

Many U.S. cities have recently increased their minimum wages, especially in California. We report results from carrying out analyses of the impacts of these city minimum wages, as specified in a pre-analysis plan (PAP) that was registered on Open Science Framework prior to the release of data covering two years of minimum wage increases. In this working paper, we report results updating the data through 2018; our final paper will add another year of evidence on minimum wages. For employment effects, in our analysis of California cities we find a hint of negative employment effects, but the estimates are neither robust nor statistically strong. The analysis of local minimum wages nationally also provides some evidence of disemployment effects, although it is not statistically significant. For distributional effects, our city-specific analyses do not provide clear evidence one way or the other, except for evidence of increases in the shares poor or low-income in Santa Clara. In our panel data analyses of all California or national local minimum wages, there is evidence pointing to declines in the shares poor or low-income, although at least for California the data indicate that the shares poor or low-income were declining before local minimum wages took effect (or were increased). More definitive results await our next update.

In this study, we explore the dimensions of local gender norms across U.S. commuting zones. Applying hierarchical cluster analysis with four established indicators of gender norms, we find that these local cultural environments are best conceptualized with a multilevel framework. Commuting zones can be differentiated between those that are egalitarian and those that are traditional. Within these general categories, however, exist more complex dimensions. Gender-traditional areas may be distinguished between traditional-breadwinning and traditional-essentialist, while egalitarian areas are separated into those that are liberal-egalitarian and egalitarian-essentialist. Examining the factors sustaining this spatial variation, we test the role of compositional and contextual effects. We find limited support for compositional effects because commuting zone demographic makeup explains little variation in gender norm indicators. Instead, we find evidence that local gender norms are sustained through contextual effects where the experience of living in a particular environment shapes residents’ attitudes and behaviors. Contextual effects are exceptionally strong in areas with traditional gender norms, where residents who would otherwise hold gender-egalitarian perspectives (e.g., the highly educated) have more traditional outlooks than those who share the same characteristics but reside in places with egalitarian gender norms.

Background: In Los Angeles County, the tuberculosis (TB) disease incidence rate is seven times higher among non-U.S.-born persons than U.S.-born persons and varies by country of birth. But translating these findings into public health action requires more granular information, especially considering that Los Angeles County is more than 4000 mile2. Local public health authorities may benefit from data on which areas of the county are most affected, yet these data remain largely unreported in part because of limitations of sparse data. We aimed to describe the spatial distribution of TB disease incidence in Los Angeles County while addressing challenges arising from sparse data and accounting for known cofactors. Methods: Data on 5447 TB cases from Los Angeles County were combined with stratified population estimates available from the 2005-2011 Public Use Microdata Survey. TB disease incidence rates stratified by country of birth and Public Use Microdata Area were calculated and spatial smoothing was applied using a conditional autoregressive model. We used Bayesian Poisson models to investigate spatial patterns adjusting for age, sex, country of birth and years since initial arrival in the U.S. Results: There were notable differences in the crude and spatially-smoothed maps of TB disease rates for high-risk subgroups, namely persons born in Mexico, Vietnam or the Philippines. Spatially-smoothed maps showed areas of high incidence in downtown Los Angeles and surrounding areas for persons born in the Philippines or Vietnam. Areas of high incidence were more dispersed for persons born in Mexico. Adjusted models suggested that the spatial distribution of TB disease could not be fully explained using age, sex, country of birth and years since initial arrival. Conclusions: This study highlights areas of high TB incidence within Los Angeles County both for U.S.-born cases and for cases born in Mexico, Vietnam or the Philippines. It also highlights areas that had high incidence rates even when accounting for non-spatial error and country of birth, age, sex, and years since initial arrival in the U.S. Information on spatial distribution provided here complements other descriptions of local disease burden and may help focus ongoing efforts to scale up testing for TB infection and treatment among high-risk subgroups.

This dissertation contains three chapters in the field of family and development economics. The first two chapters study the effects of traditional gender roles on economic outcomes. The last chapter discusses the effects of a spatial development policy in India. Chapter 1 examines the dynamics of intra-household time allocation in response to economic incentives, and the role of traditional gender norms. Using unique longitudinal data on Japanese households, it finds that spouses in dual-income households adjust their market hours but not home hours as own wages change. In addition, per earthquake-induced changes in market hours, wives make little or no change in home hours while husbands show significant, yet small in magnitude, responses. The responses are driven by individuals with less traditional gender role attitudes. Traditional gender roles exacerbate not only the asymmetry but also the rigidity of gendered division of intrafamily labor. Chapter 2 studies whether the effects of traditional gender roles on female labor supply are greater in endogamous marriage by examining the labor supply pattern of immigrant women in the United States. The endogenous formation of marriage is addressed by incorporating local marriage market conditions. Using survey responses on gender roles in source countries as cultural proxies, it finds that the negative effects of traditional gender roles on female labor supply are amplified in endogamous marriage at the extensive and intensive margins of labor market. Differential patterns of immigrant assimilation by marriage type fail to fully explain the asymmetry, supporting the hypothesis that culture is more relevant within endogamous marriage. Chapter 3 (with Shree Ravi) analyzes the aggregate and distributional effects of Special Economic Zones (SEZs) in India. It investigates the influence of Indian SEZs by exploiting spatial variations in the timing of zonal operations. Using satellite and survey data, it establishes that SEZs boosted economic activity within areas several times the size of the zones. The zones also drove a structural change in the local economy with resources shifting away from the informal sector and the formal sector growing in size and productivity. This growth, however, differently benefits workers across income and skill distributions.

Objective: This study examines the association between psychological distress and Alzheimer’s disease mortality among US adults aged ≥45. Methods: We analyzed the Kessler 6-item psychological distress scale as a risk factor for Alzheimer’s mortality using the pooled 1997–2014 National Health Interview Survey (NHIS)- National Death Index (NDI) database (N = 265,089). Cox regression was used to model mortality as a function of psychological distress and sociodemographic and behavioral covariates. Results: The Alzheimer’s mortality risk was 97% higher (HR = 1.97; 95% confidence interval [CI] = 1.37, 2.84) in adults with serious psychological distress compared with those without psychological distress, controlling for sociodemographic covariates. The relative mortality risk remained statistically significant (HR = 1.49; 95% CI = 1.04, 2.13) after additional adjustment for smoking, alcohol consumption, health status, activity limitation, and body mass index. Discussion: US adults had significantly higher risks of Alzheimer’s disease mortality at higher psychological distress levels. These findings underscore the significance of addressing psychological well-being as a strategy for reducing Alzheimer’s disease mortality.

This research investigates vulnerability to mortality from a pandemic by creating a novel spatiotemporal epidemiological model that will simulate a pandemic and subsequent attempts by the population to access health care throughout the course of the simulated pandemic. Despite extensive and on-going research on pandemic influenza preparedness planning, there is a surprising dearth of literature regarding who is most at risk to dying from influenza, where this risk is concentrated, and why. The results of this study suggest that should a pandemic comparable to the 1918 Spanish Flu happen today, when the differentiating effects of receiving health care are considered, the mortality impacts of such a pandemic would be worse than what would be expected based on historical rates alone. This research provides evidence of the potential deadly impacts of a pandemic when the health care system is unable to provide care at the magnitude demanded.

This paper develops a random matching model with unobserved worker heterogeneity and learning about worker types from unemployment duration. The model features negative duration dependence that stems from unobserved heterogeneity as well as statistical discrimination and skill depreciation. We estimate our model using micro-level data from Current Population Survey (CPS) and we decompose the contribution of each channel to job finding rates by duration. We find that shutting down statistical discrimination substantially increases the job finding rates of the long-term unemployed while skill depreciation mainly affects the medium-term unemployed.

This paper investigates youth migration in Russia at the sub-regional level of administrative division. The aim of the research is to assess the volume of internal youth migration in cohort perspective. The task is only doable with the use of census data, which not only makes it possible to conduct research at the sub-regional level, but also provides much more accurate information on youth migration than the current migration record. I utilize cohort-component analysis to study sub-regional population dynamics. As mortality is quite insignificant at young ages, most of the change in cohort size is caused by migration. My estimates show that during the last intercensal period, 2003–2010, up to 70% of youth cohorts have left the regional periphery after graduating from school, and there was no substantial return to the demographically depleted periphery in the young working ages.

The prevalence of food insecurity in the United States is a persisting issue and poses several implications to public health. In this study, we use data from the Current Population Survey and its Food Security Supplement to explore food insecurity dynamics in the United States over the period of 2005-2017. During and after the Great Recession, we find food insecurity rates worsening drastically between 2005-2009, plateauing in 2009-2013, before slowly declining again between 2013-2017, yet still not meeting pre-recession levels. We examine several characteristics that may influence U.S. households’ food security status, including education, race, marital status, family size, age, metropolitan proximity, and state. Our results suggest that particularly individuals with lower educational attainment are severely affected by increasing rates of food insecurity and are at persistent risk of entering into food insecurity almost a decade after the recession.