Background: Woman employment has been discussed as a debatable factor against IPV in the literature. This study, however categorizes women employment into four categories (agriculture, blue collar and white-collar jobs) in 18 developing countries and finds whether it is a protective or a risk factors, along with other significantly impacting factors of IPV. Method: The study is based on data extracted from Demographic and Health Survey (DHS) and has been taken from the Integrated Public Use Microdata Series (IPUMS) database. The total number of women interviewed are 961,571 from 18 developing countries of Sub-Saharan Africa and South Asia. Adjusted and unadjusted “Multivariate Logistic Regression Models” are used to determine the impact of women employment on Intimate Partner Violence. In addition, meta-analysis is done to compare results across countries. . .

Using a recent result from the program evaluation literature, the author demonstrates that the interpretation of regression estimates of between-group differences in wages and other economic outcomes depends on the relative sizes of subpopulations under study. When the disadvantaged group is small, regression estimates are similar to the average loss for disadvantaged individuals. When this group is a numerical majority, regression estimates are similar to the average gain for advantaged individuals. The author analyzes racial test score gaps using ECLS-K data and racial wage gaps using CPS, NLSY79, and NSW data, and shows that the interpretation of regression estimates varies substantially across data sets. Methodologically, he develops a new version of the Oaxaca–Blinder decomposition, in which the unexplained component recovers a parameter referred to as the average outcome gap. Under additional assumptions, this estimand is equivalent to the average treatment effect. Finally, the author reinterprets the Reimers, Cotton, and Fortin decompositions in the context of the program evaluation literature, with attention to the limitations of these approaches.

Estimates of the proportion of the U.S. population living close to high-traffic roads range from four to 19%. These proportions are higher for minority and low-income populations. Although the relationships among traffic exposure, race, and socioeconomic status have been consistent and reproducible, they are spatially heterogeneous and there has been limited investigation into the patterns heterogeneity. Using a spatially-explicit global regression and an exploratory geographically weighted regression (GWR), we examined variation in residential exposure to traffic at regional and neighborhood scales. Race/ethnicity, income, and college attainment are our variables of interest. Consistent with prior studies, we found that minority and lower socioeconomic status are systematically linked to higher exposure to traffic. Furthermore, the GWR approach has the potential to uncover patterns of disparities at a more localized level. However, a richer set of land use variables needs to be evaluated within this framework.

This paper studies the human capital responses to a large shock in the returns to education for undocumented youth. We obtain variation in the benefits of schooling from the enactment of the Deferred Action for Childhood Arrivals (DACA) policy in 2012, which provides work authorization and deferral from deportation for high school educated youth. We implement a difference-in-differences design by comparing DACA eligible to non-eligible individuals over time, and we find that DACA had a significant impact on the investment decisions of undocumented youth. High school graduation rates increased by 15 percent while teenage births declined by 45 percent. Further, we find that college attendance increased by 25 percent among women, suggesting that DACA raised aspirations for education above and beyond qualifying for legal status. We find that the same individuals who acquire more schooling also work more (at the same time), counter to the typical intuition that these behaviors are mutually exclusive, indicating that the program generated a large boost in productivity.

This dissertation uses Schneider and Ingram’s Social Construction and Policy Design Theory (SCT) to help understand movements in funding for higher education at the state-level over the past 25 years. SCT argues that social constructions - the symbols, images, and stereotypes used to label social groups as desirable or undesirable - and power - the voting prowess, wealth, and ability to mobilize for action - converge to predict the distribution of benefits and burdens for policy targets. In my first article, I conduct a descriptive analysis of the changes in spending on state-level grant aid for higher education, using SCT to guide expectations on how funding will be distributed. My second article uses SCT to construct and test hypotheses on state-level decisions regarding need and merit- based financial aid, showing that states with more negative social constructions of low-income and minority students allocate fewer dollars to need-based aid. Finally, my third article uses SCT to explain the adoption of state-level merit-aid financial aid policies over the last two decades. Overall, my dissertation is one of the first studies to use SCT for studying state higher education policy, and provides a confirmatory test of SCT within a new policy domain.

The main purpose of the Affordable Care Act (ACA) was to extend health insurance coverage to more individuals. Another potential benefit of the ACA, however, was to free up workers to find jobs that better fit their needs, by ending their dependence on employer-provided health insurance. There is considerable evidence indicating that before the implementation of the ACA, many workers stayed in jobs that they otherwise would have left solely because they needed the health insurance provided by the employer. This was likely to be especially true of workers with children, workers who either have a disability or have a family member with a disability, and older workers. By increasing access to insurance outside of employment, either through Medicaid or the health care exchanges, the ACA made it easier for workers to get jobs that better fit their needs. There was a substantial increase in voluntary part-time employment in the years immediately after the main provisions of the ACA took effect, which is evidence of this effect on the labor market. The rise in voluntary part-time employment was largest among young people and was especially pronounced for young women.

Rail transit and neighborhood compositional changes are becoming clearly linked in the public mind. Examples where rail transit has been associated, at least anecdotally, with neighborhood gentrification abound. In Washington, D.C., the Green and Yellow lines are associated with neighborhood transition north and east of downtown. In Los Angeles, the Gold, Expo, and Red/Purple lines have been associated with gentrification concerns (Zuk & Chapple, 2015a), and similar concerns have been raised regarding the soon-to-open Crenshaw Line. On balance, these same concerns are present in most large metropolitan areas that are building or expanding rail transit. Gentrification is a process of neighborhood change characterized by increasing housing prices and changing demographic and socioeconomic composition of the neighborhood. These components of gentrification are often mutually reinforcing: changing composition can further increase housing prices and vice versa. Prior studies have raised the concern that rail transit expansion catalyzes or exacerbates gentrification (Zuk et al., 2017; Rayle, 2015). This report seeks to shed light on this latter concern. It begins with a brief summary of the evidence from prior studies on both rail-related housing price increases and changing composition. It then introduces a newly available data source, which the authors use to examine the relationship between new rail transit station opening and neighborhood income composition. This report aims to determine whether a rail station opening in Los Angeles County is associated with the share and income composition of residents who move in and out of neighborhoods near that rail station. Specifically, the researchers address the following questions regarding gentrification and its tie to rail transit stations: (1) Who moves into rail-station neighborhoods and when? (2) Are higher income households growing as a share of station area population relative to lower-income households? (3) Do rail stations cause this phenomenon or is this happening regardless of the transit investment?

In January 2018, the Centers for Medicare & Medicaid Services approved Kentucky’s Section 1115 Medicaid demonstration waiver, which allows the state to require some beneficiaries to participate in “community engagement” activities for at least 80 hours a month to retain their Medicaid coverage. Qualifying activities are (among others) working, participating in community service, searching for jobs, attending school or vocational training programs, or receiving treatment for a substance use disorder. This is an unprecedented step for Medicaid, but such requirements may become increasingly common given that other states have also submitted waivers that would make coverage conditional on such activities (Hahn et al. 2017). An analysis of the state’s Medicaid enrollment projections following the waiver’s implementation estimates a 15 percent drop in Medicaid enrollment by its fifth year.

States where teachers are protesting have among the largest pay discrepancies when compared with similarly educated private-sector workers.

Health insurance is a primary driver of rising medical expenditures. I examine insurance's effect on risky sex, a behavior with quick, meaningful negative results. Leveraging mandated zero cost-sharing for contraception and pre-policy insured rates as a measure of treatment intensity, I find this 2012 policy reduced fertility but caused unintended consequences: decreased prevention and increased sexually transmitted infections. I discuss imperfections of controlling for pre-trends using state-trends in difference-indifferences and suggest approaches to control for pre-trends directly. I use the 2010 dependent coverage mandate to examine the overall effect of insurance and find protective net effects of insurance on STIs.

In recent years, more and more historians and historical geographers have begun to focus on applying GIS technology, and conducted extensive explorations in the research and construction of historical GIS databases and information systems. However, most of these researches are technology-dominated applications. The organization of historical information and historical geographic information mostly focuses on specific topics or applications, lacking data model for the historical GIS basic software. From the dual perspectives of geography and history, this paper is based on the four elements of history: time, place, person, and event (from beginning to the end), integrating geography to emphasize the idea of the "man-earth relationship" and abstracting historical information into historical figures, events, features and scenes, as well as the relationships and experiences/processes. This paper proposed and designed a general historical GIS data model, discussed the composition, attribute, storage scheme of space-temporal objects, the relationship between spatial-temporal objects in the data model. In the application system, the validity of the model was verified by taking the storage and visualization of typical historical figures, events, features and scenes as examples.

Adoption of rooftop solar in the United States primarily has been concentrated in higher-income households (Moezzi et al. 2017; Vaishnav et al. 2017). As technology costs decline and markets expand, however, focus is shifting to increasing solar access in underserved market segments— particularly to low-to-moderate income (LMI) households, or those earning 80% or less of the area median income (AMI). A key policy goal is to expand solar access more equitably to ensure the benefits of solar, including reduced energy burden, increased resilience, and hedge against electricity rate changes are available to all ratepayers. To achieve this goal, a deeper understanding of the potential LMI market is needed. Although LMI households represent about 43% of the U.S. population, it is unknown what proportion live in buildings suitable for PV, how this potential is distributed among the buildings they live in, or what fraction of their electricity needs could be met with rooftop solar.

This paper evaluates the incidence of a natural experiment entailed by the 2005 Ohio tax reform. The policy reduced the corporate and personal income taxes over the period 2006-2010. I observe several cross-sections of the Current Population Survey and compare individuals in Ohio to similar individuals in Pennsylvania. Using a triple difference identification approach, I conclude that the reform significantly boosted labor force participation for women, specifically those with 5-year-old children and increased reported self-employment taxable earnings. However, it does not seem to have had a positive impact on corporate wages in the short-run. JEL Classifications: H20, H24, H25

The Federal Open Market Committee (FOMC) in its January meeting decided to leave the federal funds rate unchanged in a range of 125 to 150 basis points. In our FOMC statement after the meeting, the committee explained that it expects “economic conditions will evolve in a manner that will warrant further gradual increases in the federal funds rate.” The purpose of this essay is to briefly discuss my views regarding economic conditions, the implications for monetary policy and address a few of the fundamental challenges facing the U.S. economy.

We ask whether regional attitudes towards gender roles impact the prevalence of women in corporate leadership. Previous studies show that cross-country differences in gender attitudes are highly persistent and have pre-industrial origins. We find that countries with more gender-egalitarian attitudes have more women on corporate boards. These effects persist through immigration. U.S. firms located in counties with greater portions of their populations originating from gender-egalitarian countries have more women on corporate boards, more women in leadership roles on boards, and more female executives. The effects of culture extend beyond corporate leadership, as greater gender-egalitarianism is associated with high female labor participation, lower gender pay gaps, and greater female participation in STEM jobs.

Nonmarket damages are largely missing from aggregate climate impacts, although reduced-form research is beginning to quantify these effects. We propose a general, theoretically consistent method for calculating welfare changes for nonmarket climate damages. This approach has minimal data requirements and provides a bridge between standard valuation techniques and reduced-form climate impact research. We elucidate the theoretical properties of our welfare measure, showing that it tends to produce exact or conservative estimates of surplus changes. We illustrate our approach by estimating impacts of climate change on outdoor recreation using nationally representative timeuse survey data, which reveals substantial net welfare gains by the end of the century.

Geocoding longitudinal and individual-level historical demographic databases enables novel analyses of how micro-level geographic factors affected demographic outcomes over long periods. However, such detailed geocoding involves high costs. Additionally, the high spatial resolution cannot be properly utilized if inappropriate methods are used to quantify the geographic factors. We assess how different geocoding levels and methods used to define geographic variables affects the outcome of detailed spatial and historical demographic analyses. Using a longitudinal and individual-level demographic database geocoded at the property unit level, we analyse the effects of population density and proximity to wetlands on all-cause mortality for individuals who lived in five Swedish parishes, 1850–1914. We compare the results from analyses on three detailed geocoding levels using two common quantification methods for each geographic variable. Together with the method selected for quantifying the geographic factors, even small differences in positional accuracy (20–50 m) between the property units and slightly coarser geographic levels heavily affected the results of the demographic analyses. The results also show the importance of accounting for geographic changes over time. Finally, proximity to wetlands and population density affected the mortality of women and children, respectively. However, all possible determinants of mortality were not evaluated in the analyses. In conclusion, for rural historical areas, geocoding to property units is likely necessary for fine-scale analyses at distances within a few hundred metres. We must also carefully consider the quantification methods that are the most logical for the geographic context and the type of analyses.

Education mobility contributes to income mobility and is an important policy target but has received little attention. This paper documents trends (1982-2004) and geographical differences (across US states) in education mobility. We develop mobility measures that respect the unique properties of education attainment. While standard approaches suggest slightly increasing mobility over the sample period, we find that mobility fluctuated, decreasing over roughly the first decade and increasing in the second. Geographic variation in education mobility is correlated with local community and policy factors-such as the existence of high school exit exams. Finally, the South is excluded from national increases in mobility.

In Enduring Bonds, Philip N. Cohen, renowned sociologist and blogger of the wildly popular and insightful Family Inequality, examines the complex landscape of today's diverse families. Through his interpretive lens and lively discussions, Cohen encourages us to alter our point of view on families, sharing new ideas about the future of marriage, the politics of research, and how data can either guide or mislead us. Deftly balancing personal stories and social science research, and accessibly written for students, Cohen shares essays that tie current events to demographic data. Class-tested in Cohen’s own lectures and courses, Enduring Bonds challenges students to think critically about the role of families, gender, and inequality in our society today.

Labor reallocation from agriculture to other more productive sectors is key to the development process. There is an extensive literature that studies the role of demand-side and supply-side forces in explaining this reallocation. On the supply-side, capital deepening is an important driver of changes in the return to labor and labor reallocation. There are two margins that are relevant to capital deepening, the intensive and the extensive margins of capital accumulation. In this paper, we study the role of shifts in the average quality of the capital stock for the process of structural transformation. The return to labor in a given sector depends on the technology of such a sector through the share of capital in production, and through the pattern of complementarity between capital and labor inputs. Disparities in the patterns of complementarity between capital of different vintages and labor across sectors generate unbalanced growth as newer vintages of higher quality arrive to the economy. Baumol (1967), later formalized by Acemoglu and Guerrieri (2008), first suggested that capital deepening can also induce unbalanced growth across sectors. To date, there are no systematic measures of the impact of capital deepening on structural transformation across countries. Dennis and Iscan (2009) evaluate the role of capital deepening for the reallocation of workers out of agriculture in the last two centuries in the US. The feature that generates unbalanced growth in response to capital deepening in these papers is the disparity in the share of capital across sectors. This paper advances the literature in two dimensions: a) by exploring the role of capital-embodied technology adoption (quality) for structural transformation, and b) by arguing that an additional feature that generates unbalanced cross-sectorial growth as higher quality capital arrives to the economy, is the disparate complementarity between capital and labor across sectors. Formally, we study a multisector vintage capital model where heterogeneous workers are assigned to different sectors and vintages of a machine. Workers are heterogeneous in their efficiency units of labor, their education and their complementarity with vintages of capital. Each worker draw a vector of efficiency units associated with each capital-vintage and sector from a Frechet distribution, in the tradition of McFadden (1974) and Eaton and Kortum (1992). We assume that newer cohorts of workers are more complementary to vintages of capital introduced to the economy when such a cohort hit working age than any other vintage in the economy. Each period, workers assign themselves to different vintages and sectors following their comparative advantage. At the same time, households decide how much to consume of the goods produced in agriculture and non-agriculture, which vintages of capital to purchase and how much capital to accumulate of each available vintage. We characterize the optimal allocation of workers to vintages, as well the price of capital in the economy. We show that, as standard in the literature on capital-embodied technology adoption Greenwood et.al. (1988), the inverse of the relative price of investment to consumption pins down the rate of change in the quality of newer stocks. We also show that the return to labor in each sector depends endogenously on the allocation of workers, as well as on the pattern of capital-labor complementarities of different cohorts of workers. To bring the model to the data, we use data on labor shares and average labor returns (wages) in agriculture and non-agriculture from IPUMS. The identification of the complementarity patterns is key to our exercise. Given our assumptions on the pattern of complementarity and absent any frictions, a worker is assigned to the best vintage of capital available at the time in which his cohort hit the labor market. The allocation of workers of a given educational group to sectors and vintages pins down the average efficiency units in production for each vintage-sector. In addition, for a given vintage, the probability of a worker-education group to be assigned to a sector pins down the efficiency units in production across educational groups. Given the random arrival of the vector of worker efficiency by sector and vintage, the probability of assignment maps one-to-one to the share of workers in that sector vintage. We use data on wages to calibrate the distribution of talent across cohorts and sectors. We present reduced form evidence in line with the predictions of the model. In particular, we measure of rate of capital-embodiment using data from Penn World Tables on the price of consumption relative to the price of investment. We show that, across countries, the share of workers in agriculture is lower in countries with higher education of their labor force and a higher rate of capital-embodied technology adoption. This is consistent with the pattern of complementarity between labor and capital vintages uncovered by our identification and the predictions of the model in terms of capital deepening. In our paper, the main exercise consists of computing the allocation of workers in the agricultural and non-agricultural sectors predicted by the model to match the path of labor allocation observed in the data. Then we use the model to understand what is the role of capital-embodied technology adoption and capital-skill complementarities for the dynamic of wage gaps, labor reallocation and ultimately, labor productivity. The closest paper to ours is Burstein, Morales and Vogel (2017) who characterize a static allocation of workers to different types of capital. Relative to theirs, we study an environment with a non-trivial capital accumulation dynamic with multiple assets. This feature is key to uncovering the role of capital-embodied technology adoption (a form of capital deepening) for labor reallocation and wage gaps across sectors.