Cities exist because of the productivity gains that arise from clustering production and workers, a process called agglomeration. How important is agglomeration for aggregate growth? This paper constructs a dynamic stochastic general equilibrium model of cities and uses it to estimate the effect of local agglomeration on aggregate growth. We combine aggregate timeseries and citylevel panel data to estimate the model's parameters via generalized method of moments. The estimates imply a statistically and economically significant impact of local agglomeration on the growth rate of per capita consumption, raising it by about 10%.

This research project builds on a half-century of demographic studies about turn-of-the-twentieth-century U.S. race differences in fertility. As background, mid-twentieth century demographers began to study historical fertility differentials when a newly released U.S. 1940 Census Bureau report allowed comparisons of aggregate fertility rates by age, race, region and other characteristics for decennial census years 1910 and 1940. They were surprised to find, in back-casting fertility rates, that at some point prior to 1910 the fertility of African American women had dropped, much more precipitously than that of white women. This was surprising because the fertility of very early nineteenth century white and black women stood at biological maximums, although white women had the highest birth rates of all women in North America and perhaps in the world. It was assumed that white women of the time, like most preindustrial women, had high rates because they had not yet elected to practice voluntary fertility control. In contrast, nineteenth century African and African American women experienced high fertility rates under a system of slavery, until the early 1860s, with vastly different constraints regarding fertility control at that point. Were white women first to control their fertility? If so, why did African American fertility rates fall far more quickly, once declines began?

We document that age pro files of labor earnings for college- and high-school-educated workers are flatter for recent cohorts than for older cohorts. Workers who were 20-year old in 1940 saw their annual earnings increase four-fold over the course of their working lives. For workers who were 20-year old in 1970 the increase was 2-fold. We propose a parsimonious model of schooling and human capital accumulation on the job to account for this phenomenon. In our model a workers' ability is key for the accumulation of human capital in school and on the job. Workers with higher ability are more likely to attend college, and have steeper earning profi les. In this model the flattening results from the changing composition of workers: when the fraction of college-educated workersincreases for a particular generation, the average ability of both college- and high-school-educated workers decreases. Thus, average earnings profi les flatten. We calibrate the model to t some moments characterizing the earnings of the 1940 generation at diff erent age. There is only one exogenous variable: the rental rate of human capital that increases through time. Our model accounts for 40% of the observed flattening of high-school earnings, and 73% for college earnings.

Theories of the demographic transition often center on the rising price of children. A model of fertility derived from household production in the antebellum United States contains both own children and slaves as inputs. Changes in slaveholdings beget changes in the marginal product of the slaveowners' own children and, hence, their price. I use panel data on slaveowning households between 1850 and 1870 to measure the slaveowners' own fertility responses to exogenous changes in slaveholdings. Results indicate a strong, negative correlation between own child prices and fertility.

Employment to population ratios differ markedly across Organization for Economic Cooperation and Development (OECD) countries, especially for people aged over 55 years. In addition, social security features differ markedly across the OECD, particularly with respect to features such as generosity, entitlement ages, and implicit taxes on social security benefits. This study postulates that differences in social security features explain many differences in employment to population ratios at older ages. This conjecture is assessed quantitatively with a life cycle general equilibrium model of retirement. At ages 60–64 years, the correlation between the simulations of this study׳s model and observed data is 0.67. Generosity and implicit taxes are key features to explain the cross-country variation, whereas entitlement age is not.

Public administrators have always been interested in identifying cost-effective strategies for managing their programs. As government agencies invest in data warehouses and business intelligence capabilities, it becomes feasible to employ analytic techniques used more-commonly in the private sector. Predictive analytics and rapid-cycle evaluation are analytical approaches that are used to do more than describe the current status of programs: in both the public and private sectors, these approaches provide decision makers with guidance on what to do next. Predictive analytics refers to a broad range of methods used to anticipate an outcome. For many types of government programs, predictive analytics can be used to anticipate how individuals will respond to interventions, including new services, targeted prompts to participants, and even automated actions by transactional systems. With information from predictive analytics, administrators can identify who is likely to benefit from an intervention and find . . .

Demographic changes, such as increases in cohabitation, divorce, and single parenthood as well as the delay in marriage entry and decrease in remarriage, continue to shape American families and households (Cherlin, 2010). The effects of these changes over time, however, differ across race/ethnicity and educational levels (Kennedy & Bumpass, 2008; Manning, 2013; Teachman, et al. 2000). This profile presents changes in the proportion of U.S. single, cohabiting couple, and married couple households across race/ethnicity between 1995 and 2012.

In this data brief, we describe changes in the Cincinnati MSA labor market the recession and recovery period of 2006-2011. We see an increase in the share of younger workers with at least a Bachelor’s degree and a higher share of workers employed in Education and Business & Financial jobs. The education level of workers in Healthcare Support is on the rise, and employment in this field grew while real wages remained stable during our study period. Other occupations accessible to lower-skilled workers, including Food Preparation & Services, experienced gains in employment but losses in full-time workers.

Studies that report an association between Parkinson's disease (PD) and occupational pesticide exposure often use self-reported exposure and none adjust for concomitant ambient pesticide exposure. For a population-based case-control study of PD conducted in California's heavily agricultural region, the authors developed a comprehensive job exposure matrix (JEM) to assess occupational exposure to pesticides. Relying on 357 incident cases and 750 population controls enrolled between 2001 and 2011, the authors estimated more than a 2-fold risk increase for PD among men classified as highly occupationally exposed. The authors also observed an exposure-response pattern and farming tasks with direct and intense pesticide exposures such as spraying and handling of pesticides resulted in greater risks than indirect bystander exposures. Results did not change after adjustment for ambient pesticide exposure. The authors provide further evidence that occupational pesticide exposure increases the risk of PD.

Nearly 294,000 Mexicans who have obtained a Bachelor's degree have migrated to the United States. Most are employed in occupations for which a lower level of qualification is required. This research discusses the factors associated with this condition. It is argued that their employment status is part of a process that began in their home country where family, school and work experiences are combined. To analyze this process a mixed methodology is followed: Qualitative and quantitative. The first was to conduct interviews with Mexican graduates who emigrated and work in the United States; analysis showed distinct processes: first, an association was observed between skilled and unskilled migrants: unskilled migrants motivate and guide at the skilled migrants in their mobilization strategies and job search; Moreover there are another flow of migrants who is oriented by professional development opportunities. The quantitative analysis was based on descriptive statistics and logistic regression models applied to data for the period 2000-2011; the results show that migrants used rarely mechanisms designed to offer professional services in the American labor market, such as TN and H-1B visas, in addition, a negative association was observed in the probability of being employed in a skilled occupation and belonging to unskilled migrant networks. From these results, it is argued that a considerable part of the mobility of skilled Mexicans to the United States do not follow the logic and dynamics that characterize the phenomenon of skilled migration and this affects their employment type.

In this paper, we present a spatial equilibrium model where search frictions hinder the immediate reallocation of workers both within and across local labor markets. Because of the frictions, firms and workers find themselves in bilateral monopoly positions when determining wages. Although workers are not at each instant perfectly mobile across cities, in the baseline model we assume that workers flows are sufficient to equate expected utility across markets. We use the model to explore the joint determination of wages, unemployment, house prices and city size (or migration). A key role of the model is to clarify conditions under which this type of spatial equilibrium setup can be estimated. We then use U.S. data over the period 19702007 to explore the fit and quantitative properties of the model. Our main goal is to highlight forces that influence spatial equilibria at 10-year intervals.

We specify a new model of homeowner mortgage default. In our model, homeowners do not know the current price of their home until they sell; rather, they maintain an unbiased guess of the price and optimally update this guess as new information, such as the sale price of similar homes, is observed. Compared to the predictions of a model where homeowners know the current price with certainty, uncertainty about the price considerably reduces the probability homeowners default even when the current price is likely substantially less than the mortgage balance. We estimate model parameters using data on self-assessed house prices, house-price indexes and mortgage defaults. We find uncertainty about the current level of house prices reduced defaults for a cohort of prime mortgages issued in 2006 by 25 percent in 2010 and 2011.

The rapid increase in immigration has left many states and localities scrambling to employ strategies to successfully integrate immigrants into their local communities. While the federal government sets immigration policy (dealing with the admission, entry, legal status and deportation of immigrants), it naturally falls to states and localities (the communities where immigrants reside) to develop immigrant policy that is, policy that assists or hampers immigrants in their ability to adapt to living in the United States. The integration of immigrants has many facets. According to the Washington new americans Policy Council, integration requires more than just citizenship and a voter registration card, it must also include: training and employment at ones highest potential; the ability to communicate in English; the opportunity to increase personal wealth through greater access to mainstream financial services; and the ability to meaningfully engage ones government.

Low income bill subsidy and energy efficiency programs for low income households in California are provided by the investor owned electric and gas utilities of California. IPUMS provides assistance in annual estimates of eligibility, in combination with a number of other data sources including the American Community Survey (PUMS and Summary), monthly CPS data, California CPI estimates, California Employment Development Department small area reports, and others.

Organizations share data about individuals to drive business and comply with law and regulation. However, an adversary may expose confidential information by tracking an individual across disparate data publications using quasi-identifying attributes (e.g., age, geocode and sex) associated with the records. Various studies have shown that well-established privacy protection models (e.g., k -anonymity and its extensions) fail to protect an individuals privacy against this composition attack. This type of attack can be thwarted when organizations coordinate prior to data publication, but such a practice is not always feasible. In this paper, we introduce a probabilistic model called (d,a)(d,a)-linkable, which mitigates composition attack without coordination. The model ensures that d confidential values are associated with a quasi-identifying group with a likelihood of aa. We realize this model through an efficient extension to k-anonymization and use extensive experiments to show our strategy significantly reduces the likelihood of a successful composition attack and can preserve more utility than alternative privacy models, such as differential privacy.

Financial literacy and cognitive capabilities are convincingly linked to the quality of financial decision-making. Yet, there is little evidence that education intended to improve financial decision-making is successful. Using plausibly exogenous variation in exposure to state-mandated personal finance and mathematics high school courses, affecting millions of students, this paperanswers the question "Can good financial behavior be taughtin high school?" It can, though not via traditional personal finance courses, which we find have no effect on financial outcomes. Instead, we find additional mathematics training leads to greater financial market participation, investment income, and better credit management, including fewer foreclosures.

Richard Floridas theory of the creative class has led cities to offer amenities as a way to attract the knowledge workers that he argues drive the economy. At present, scant evidence exists concerning the leisure activities different worker classes choose to engage in. Using logit analysis on data from the American Time Use Survey, I analyze the leisure preferences of the creative class and find limited support for Floridas assertions about their amenity use. Cities and policymakers should consider the evidence here before trying to create unique amenities to attract the creative class, because they may not require distinctive activities to choose a location.

The collection and analysis of observational and experimental data represent the main tools for assessing the presence, the extent, the nature, and the trend of discrimination phenomena. Data analysis techniques have been proposed in the last 50 years in the economic, legal, statistical, and, recently, in the data mining literature. This is not surprising, since discrimination analysis is a multidisciplinary problem, involving sociological causes, legal argumentations, economic models, statistical techniques, and computational issues. The objective of this survey is to provide a guidance and a glue for researchers and anti-discrimination data analysts on concepts, problems, application areas, datasets, methods, and approaches from a multidisciplinary perspective. We organize the approaches according to their method of data collection as observational, quasi-experimental, and experimental studies. A fourth line of recently blooming research on knowledge discovery based methods is also covered. Observational methods are further categorized on the basis of their application context: labor economics, social profiling, consumer markets, and others.