Economists have developed an extensive literature examining the relationships between inequality of outcomes and growth, but few research papers have investigated the relationship between inequality of opportunity and growth. That extensive literature finds both positive and negative effects of inequality on growth, as theory predicts. By contrast, inequality of opportunity should be a drag on growth, as it represents less than full utilization of potential resources. Using recently released data on intergenerational mobility in commuting zones within the United States, this paper investigates the relationship between intergenerational mobility measures (as indicators of inequality of opportunity) and economic growth and finds that local areas with higher intergenerational mobility display faster economic growth over the 2000-2013 and 2007-2013 periods. This is true when intergenerational mobility is measured in both relative and, especially, absolute terms. In the reverse direction, the paper provides suggestive evidence that faster growth enhances economic opportunity.

Mortality from unintentional injuries, or accidents, represents major and understudied causes of death in the United States. Epidemiological studies show social factors, such as socioeconomic and marital status, relate with accidental death. But social theories posit a central role for social statuses on mortality risk, stipulating greater relevance for causes of death that have been medically determined to be more preventable than others. These bodies of work are merged to examine deaths from unintentional injuries using 20 years of nationally representative survey data, linked to prospective mortality. Results indicate that socially disadvantaged persons were significantly more likely to die from the most preventable and equally likely to die from the least preventable accidental deaths over the follow-up, compared to their more advantaged counterparts. This study extends our knowledge of the social contributors to a leading cause of death that may have substantial implications on overall disparities in length of life.

This study examines the impact of hospitals on local labor markets in rural and urban counties. We measure the ability of hospitals, particularly in rural communities, to attract non-health related employment and provide higher wage jobs to residents based on their education level. Results find hospital employees with an associates degree can expect a 21.4% wage premium, when compared to alternative opportunities, and those with a bachelors degree can earn 12.2% more working in a hospital. Hospitals are shown to be positively related to overall employment as well as exhibit positive employment spill-over. For rural counties, a short-term general hospital is associated with 599 jobs in the county; 60 of which are hospital based and 499 are non-healthcare related. With the positive benefits on wages and non-healthcare job growth, hospitals have measurable positive labor market outcomes above their primary objective of providing health care access, particularly in rural counties.

The US labor market has changed in recent decades, both in the medium-term and in the short-term. This paper examines computers as a theoretical explanation for these changes. When computers become cheap and competitive compared to workers, they diffuse more rapidly and become more important in the conventional mechanism of capital-labor substitution. The model can account for recent structural changes with this trend of automation: employment has shifted away from routine occupations and the labor share of income has declined. The model also predicts that recessions accelerate the decline in routine occupationsfirms prefer to destroy routine jobs during a downturn, when the opportunity cost of restructuring is low. This acceleration can account for recent cyclical changes of the labor market: routine job losses are concentrated in recessions and the ensuing recoveries are jobless.

This volume brings together new scholarship on the cultural history of consumption, immigration, and ethnic marketing, focusing on the case of an ethnic group whose material culture and lifestyles has profoundly fascinated, disturbed, and influenced American culture: Italian Americans. The purpose of this introduction and the fourteen essays in the volume is to reread Italian American history in the light of consumer culture, in the process producing an analytical framework to reflect on the ways ethnic and racial groups have shaped their collective identities and negotiated their place in the consumers' emporium and marketplace of difference that is the global United States.

Throughout their history, Jews around the world have spoken distinctly from their non-Jewish neighbors (Peltz, 2010). In some cases, this distinction has come in the form of an entirely different language, such as Yiddish and Ladino (Benor, 2009), and in other cases these differences have manifested themselves in less marked ways. Jews have therefore spoken Jewish languages as part of a larger multilingual repertoire (Fishman, 1981a), and these languages have served diverse functions in intragroup communication (Peltz, 2010). Though Fishman (1985) traditionally focused on the phonological, morphosyntactic, lexical, and orthographic features that distinguish Jewish languages from those used in non-Jewish sociocultural networks, more recently Benor (2008) has considered a Jewish language as “a distinctively Jewish repertoire rather than a separate system” (p. 1062). Some traditional examples of Jewish languages include Yiddish, Hebrew, Ladino (Kushner Bishop, 2004), Judeo-Arabic, and Judeo-Provencal. More recently, scholars have broadened this list to include Yeshivish (Weiser, 1985), Hasidic English (Fader, 2009), Hasidic Yiddish (Fader, 2009), Jewish English (Benor, 2009), and English (Fishman, 1985; Levitt, n.d.). As Peltz (2010) maintains, Although modernity generally ushered in a period of decline for the use of Jewish languages in the world, there was no way that one hundred years ago anyone could have predicted the fate of Jewish languages and their speakers [. . .] the story of Jewish languages is far from over.

Shelved: How Wages and Working Conditions for Californias Food Retail Workers Have Declined as the Industry has Thrived is based on worker surveys, in-depth interviews with workers and employers, analysis of industry and government data, and reviews of existing academic literature. It represents the most comprehensive analysis ever conducted of Californias food retail industry. The report shows that while Californias food retail industry has enjoyed consistent growth over the past two decades, the expansion of a low-price, low-cost business model and the choices that traditional, unionized grocers have made in the face of it have produced a dramatic wage decline, with high rates of poverty and hunger among workers in a sector that once enjoyed relatively high wages and unionization rates. The report calls for a two-pronged strategy to arrest and reverse these trends: support for unionization, and public policies that support livable wages and benefits. This strategy would promote the creation of good jobs in the food retail sector and help build long-term prosperity for Californias families and communities.

This dissertation examines the relevance of technology in explaining structural and cyclical changes in the labor and product markets. The first chapter focuses on computers and the labor market, the second chapter on electricity and the labor market, and the third chapter focuses on computers and the goods market. The three chapters rely on a General Purpose Technology and on the distinction between routine and nonroutine jobs. A General Purpose Technology has three characteristics: it has pervasive use in all industries, it improves over time, and it is able to foster other innovations. This dissertation considers the technology of computers in the second half of the 20th century and electricity in the first half.

あらまし 多くのユーザによって計測された環境データを収集してマイニングする試みが行われて いる.プライバシに配慮するため，ユーザが手元の端末で計測データを一定の確率で他のデータ に置き換え，置き換えたデータをサーバへ通知する，Randomized Reponse (RR) という手法が広 く研究されている.データを収集したサーバは，統計的手法を用いることで計測データの分布を 推測することができるが，その精度が低いという問題がある.本研究ではユーザが手元の端末で データの集合を作成し，その集合を通知する手法を提案する.差分プライバシの指標の下で，RR と比較してプライバシと推測誤差のトレードオフをより高いレベルで取れることを示す

This dissertation contains three essays that aim to provide insight into the way housing policies affect both interstate and intra-county mobility in the United States. In particular, it endeavors to provide policymakers with new information on how the rights granted by landlord-tenant laws impact one aspect of renter’s lives (mobility) and, through the compilation of a state-law database, sets the stage for future research on the effects of landlord-tenant laws on other renter outcomes. The first essay, “Scope and Variation of Landlord-Tenant Laws in the United States,” creates and analyzes a state-level database of landlord-tenant laws and their enactment years. Ranking states as having low, average, and high levels of regulation along four dimensions of landlord-tenant policy as well as classifying these laws as pro-renter or pro-landlord aids in understanding the different policy environments experienced by renters in the U.S. and what makes a state “good” or “bad” for renters.

Rising immigration growth in the Midwest creates Multi-racial communities and segregation such as social class segregation, economic segregation, education segregation, and also housing segregation. In urban America, there are three major sets of explanatory causal factors that have been hypothesized to explain ethnic residential segregation. They are: housing discrimination, socioeconomic status (SES) and ethnic group preferences (French 2008, 1). Lincoln, as a metro city in Nebraska, shows signs of segregation phenomena as well as other metro cities in Midwest. The analysis tool used for this study is Geographic Information System (GIS) spatial analysis. This tool enables us to examine the segregation clustering in Lincoln by using Weighted Overlay Spatial Analysis. Multivariable that will use to overlay are including segregation variables (economic segregation, social segregation, education segregation) and housing quality variables (median housing value and year structure built). We know that houses with structures older than 30 years may be the locations for problems such as injuries, and sometimes death caused by falls, fire and burns, also suffocation and strangulation, elevated lead levels, mental health, structural deficiencies and accessibility. Segregated neighborhoods, which are dominated by middle to low income communities, will have difficulties to solve those. Combining all segregation topics and housing quality special characteristics to analyze, the variables will be united for this study. The analysis of residential housing segregation, will take time series data to see cluster pattern evolution. Census bureau data every ten years since 1990, 2000, and 2010 will be used for the segregation time series analysis. The change of pattern every ten years expected to give some hint of the change in residential housing segregation direction. Expected results are segregated neighborhoods clustering is still exist but reducing. In the future, conducting the segregation clustering research by examine the power of cluster is a bright idea.

Job polarizationthe rise in employment shares of high and low skill jobs at the expense of middle skill jobsoccurred in the US not just recently, but also in the late nineteenth and early twentieth centuries. We argue that in each case polarization resulted from increased automation, and provide a theoretical explanation. In our model, firms deciding whether to employ machines or workers in a given task weigh the cost of using machines, which is increasing in the complexity (in an engineering sense) of the task, against the cost of employing workers, which is increasing in training time required by the task. Insights from artificial intelligence and robotics suggest that some tasks do not require training regardless of complexity, while in other tasks training is required and increases in complexity. In equilibrium, firms are more likely to automate a task that requires training, holding complexity constant. We assume that more-skilled workers learn faster, and thus it is middle skill workers who have a comparative advantage in tasks that are most likely to be automated when machine design costs fall. In addition to explaining job polarization, our model makes sense of observed patterns of automation and accounts for a set of novel stylized facts about occupational training requirements.

Background: Thyroid cancer incidence is increasing worldwide. Incorporating 22 years of incidence data through 2009, we extend examination of these trends among a wide array of subgroups defined by patient (age, sex, race/ethnicity, and nativity), tumor (tumor size and stage), and neighborhood (socioeconomic status and residence in ethnic enclaves) characteristics, to identify possible reasons for this increase. Methods: Thyroid cancer incidence data on 10,940 men and 35,147 women were obtained from the California Cancer Registry for 19882009. Population data were obtained from the 1990 and 2000 U.S. Census. Incidence rates and 95% confidence intervals (CI) were calculated and incidence trends were evaluated using Joinpoint regression to evaluate the timing and magnitude of change [annual percentage change (APC) and rate ratios]. Results: The incidence of papillary thyroid cancer continues to increase in both men (APC, 5.4; 95% CI, 4.56.3 for 19982009) and women (APC, 3.8; 95% CI, 3.44.2 for 19982001 and APC, 6.3; 95% CI, 5.76.9 for 20012009). Increasing incidence was observed in all subgroups examined. Conclusions: Although some variation in the magnitude or temporality of the increase in thyroid cancer incidence exists across subgroups, the patterns (i) suggest that changes in diagnostic technology alone do not account for the observed trends and (ii) point to the importance of modifiable behavioral, lifestyle, or environmental factors in understanding this epidemic. Impact: Given the dramatic and continued increase in thyroid cancer incidence rates, studies addressing the causes of these trends are critical

Grandparents over the age of 65 who are raising grandchildren are a small but extremely vulnerable population in California. These older adults usually become the primary caregivers of their grandchildren after an unexpected event. They are further faced with the financial challenge of having an additional dependent without additional income. This policy brief documents that the actual income needed to support a basic standard of living for older adults with grandchildren in California is about twice the Federal Poverty Level (FPL), depending on the county. Using 200% FPL as an approximate measure, about two-fifths of older grandparents who are responsible for their grandchildren in the state do not have enough income to make ends meet. The Elder Economic Security Standard Index (Elder Index) for California calculates that the costs of housing, food, and the older adults health care account for more than two-thirds of total household expenses for grandparents and the grandchildren they are raising. Despite the high cost of basic needs, public assistance for low-income older adults and children continues to be squeezed. If they are to efficiently serve members of this fragile population, the existing programs that serve them need to maximize and streamline their impact through better coordination and collaboration.

Historical GIS is now a vibrant area of research that applies mapping and spatial methods (both quantitative and qualitative) to study the geographies of the past or the influence of geography on history. A quick search on Google Scholar with keywords “historical GIS” returned over 35,000 results1 . While historians consider time as the key to organize information, GIS methods use space as the first-order principle for representation, inquiries and understanding.

This paper proposes a method for estimating distribution functions that are associated with the nested errors in linear mixed models. The estimator incorporates Empirical Bayes prediction while making minimal assumptions about the shape of the error distributions. The application presented in this paper is the small area estimation of poverty and inequality, although this denotes by no means the only application. Monte-Carlo simulations show that estimates of poverty and inequality can severely biased when the non-normality of the errors is ignored. The bias can be as high as 2 to 3 percent on poverty rate of 20 to 30 percent. Most of this bias is resolved when using the proposed estimator. The approach is applicable to both survey-to-census and survey-to-survey prediction.