Rapid family change has occurred in the United States, but it has not been accurately charted at the local level. Our capacity to understand spatial variation in marriage is hindered by the deterioration and defunding of the U.S. marriage and divorce vital statistics system. While there is easily accessible state-level data, there is no central depository of county-level administrative marriage data preventing researchers from addressing questions about the geographic concentration as well as variation in marriage rates. We compiled 2010 county-level administrative marriage data from over 3000 counties in 49 states. We find there is wide variation in marriage rates within states with marriage rates varying more within states than across states. While the American Community Survey (ACS) is often used to study marriage rates in the U.S., we find that ACS data can only be used to assess local marriage rates for less than one in ten counties. Our findings demonstrate the high level of spatial variation in marriage and the significance of relying on county- rather than state-level marriage rates.

The kinds of errors that children and adolescents make on phonological processing tasks were studied with a large sample between ages 4 and 19 (N = 3,842) who were tested on the Kaufman Test of Educational AchievementThird Edition (KTEA-3). Principal component analysis identified two phonological processing factors: Basic Phonological Awareness and Advanced Phonological Processing. Canonical analysis and correlation analysis were conducted to determine how each factor related to reading, writing, and oral language across the wide age range. Results of canonical correlation analysis indicated that the advanced error factor was more responsible for reading, writing, and oral language skills than the basic error factor. However, in the correlation analysis, both the basic and advanced factors related about equally to different aspects of achievementincluding reading fluency and rapid namingand there were few age differences.

By reviewing US state-level panel data on infrastructure spending and on per capita income inequality over a 60-year period from 1950 to 2010, this paper sets out to test whether there is an empirical link between infrastructure and inequality. Our main results, obtained from panel regressions with both state and time fixed effects, show that highways and higher education spending growth in a given decade correlates negatively with Gini indices at the end of the decade, suggesting a causal effect from growth in infrastructure spending to a reduction in inequality. More importantly, this relationship is stronger with inequality at the bottom 40 per cent of the income distribution. In addition, infrastructure expenditures on highways are shown to be more effective at reducing inequality. A counterfactual experiment reveals which US states ended up with a significantly higher bottom Gini coefficient in 2010 due to underinvestment in infrastructure over the first decade of the 21st century. A second related goal of this paper, from a policy making perspective, is to highlight innovations in finance for infrastructure investments, for the US, other industrially advanced countries and also for developing economies

This paper deals with the quantification of the well-being loss/gain of a demographic group associated with its occupational segregation, an issue that has not been formally tackled in the literature. For this purpose, this paper proposes several properties to take into account when measuring this phenomenon. Building on standard assumptions of social welfare functions, it also defines and characterizes a parameterized family of indices that satisfy those properties. In particular, the indices are equal to zero when either the group has no segregation or all occupations have the same wage, and the indices increase when individuals of the group move into occupations that have higher wages than those left behind. In addition, ceteris paribus, the indices increase more the lower the wage is of the occupation left behind, and consider small improvements for many people to be more important than large improvements for a few.

The changes in technology that took place in the US during the last three decades, mainly due to the introduction of computerization and automation, have been characterized as “routine-substituting.” They have reduced the demand for routine tasks, but have increased the demand for analytical tasks. Indirectly they have also increased the demand for manual tasks and service oriented occupations. Little is known about how these changes have impacted immigration, or task specialization between immigrants and natives. In this paper we show that such technological progress has attracted skilled and unskilled immigrants, with the latter group increasingly specialized in manual-service occupations. We also show that the immigration response has helped to reduce the polarization of employment for natives. We explain these facts with a model of technological progress and endogenous immigration. Simulations show that immigration in the presence of technological change attenuates the drop in routine employment and the increase in service employment for natives.

This thesis comprises two components. The first is an analysis of the relationship between hospital "retail" price lists as described in charge master lists, normalized to Medicare payments, and socioeconomic and demographic covariates of the counties in which facilities are located. This analysis finds that little of the variation in how much hospitals charge the uninsured for services is due to the proportion of the population in a facility’s surrounding county that is uninsured. The second component of the thesis is a description of a data visualization toolkit, the MapSuite package written for R. This code base is designed to facilitate the representation of spatio-temporal data sets. The design philosophy and implementation are described, along with illustrative examples.

The JPMorgan Chase Institute set out to better understand out-of-pocket healthcare spending among US households. Building off a sample of 2.3 million de-identified core Chase customers aged 18 to 64 between 2013 and 2016, we assembled the JPMorgan Chase Institute Healthcare Out-of-pocket Spending Panel (JPMCI HOSP) data asset in order to explore the levels, concentration, and growth of out-of-pocket healthcare spending and the implications for household financial health. The JPMCI HOSP provides a first-ever look into out-of-pocket healthcare spending for households on a month-to-month basis, at the state, metro, and county level, and as recent as 2016. In this report, we describe the creation of, and initial insights gleaned from, this new data asset. We highlight six key findings. First, out-of-pocket healthcare spending grew between 2013 and 2016, but remained a relatively constant share of take-home income. Second, the financial burden of out-of-pocket healthcare spending was highest for older, lower-income, and female account holders and increased in 2016 for low-income account holders. Third, doctor, dental, and hospital payments accounted for more than half of observed healthcare spending; dental and hospital payments were less common but larger in magnitude. Fourth, out-of-pocket healthcare spending was highly concentrated among a few families—often the same families year over year. The top 10 percent of families spent roughly 9 percent of their take-home income on healthcare expenses. Fifth, families made larger healthcare payments in the months and the years when they had a higher ability to pay. Elevated dental and hospital payments primarily contributed to high healthcare spending. Finally, there was dramatic variation in out-of-pocket healthcare spending between and within the 23 states where Chase has a retail footprint. Families in Colorado spent the most on healthcare, while families in Louisiana spent the highest fraction of their gross income on healthcare.

Many cities in developing economies, particularly in Africa, are experiencing ‘urbanisation without industrialisation’. This paper conceptualises this in a framework in which a city can produce non-tradable goods and – if it is sufficiently competitive – also internationally tradable goods, potentially subject to increasing returns to scale. A city is unlikely to produce tradables if it faces high urban and hinterland demand for non-tradables, or high costs of urban infrastructure and construction. The paper shows that, if there are increasing returns in tradable production, there may be multiple equilibria. The same initial conditions can support dichotomous outcomes, with cities either in a low-level (non-tradable only) equilibrium, or diversified in both tradable and non-tradable production. We demonstrate the importance of history and of expectations in determining outcomes. Essentially, a city can be built in a manner which makes it difficult to attract tradable production. This might be a consequence of low (and self-fulfilling expectations) or of history. Predictions of the model are consistent with a number of observed features of African cities.

Previous studies argue that homosexuals can affect house prices through two mechanisms: an esthetic–amenity premium and a tolerance (or open culture) premium. We find that this relationship varies with respect to areas with different compositions of educational attainment and race. While we find evidence of a premium in areas with higher share of college-educated individuals, we find no premium in low-educated areas. Based on the mechanisms above, these results suggest either that low-educated individuals and homosexuals diverge in their preferences for types of amenities, or that the open culture preference from buyers could be biased toward highly educated areas. Interestingly, the magnitude of the premium (or discount for areas with low shares of educated residents) is lower when the number of black residents increases. This suggests that the presence of blacks may help the ‘openness’ perception for areas with low levels of educational attainment, but also highlights differences in preferences for amenities between African-Americans and homosexuals.

What are the distributional impacts of immigration on native workers? To answer this question, we develop a model of worker-establishment matching with a log-supermodular production function and study the impact of low-skilled immigration on native workers where immigration is defined as a matching between immigrant workers and establishments. Immigration will increase the relative supply of workers, intensifying competition among workers within establishment, and thereby reducing wages paid to native workers (matching ratio channel). However, native workers are now pushed up to be matched with establishment with higher productivity, which leads to an increase in wages for native workers (matching quality channel). The model predicts that inequality among native workers widens as more skilled native workers benefit more from this re-matching. Using Census and IPUMS American Community Survey over the period 1980-2010, we test the models predictions by exploiting the variation of stock of immigration across commuting zone-year. We demonstrate that the immigration increases inequality among native workers in the local labor markets as predicted by the model. Next, to test the matching quality channel, we decompose workers wage into components related to observable worker characteristics, establishment heterogeneity, other unobservable fixed effects, and residual variation. Using the estimated establishment heterogeneity as a proxy for native workers matching counterparts, we find that immigration induces native workers to match with more productive establishment.

In this paper, I show that political opposition to immigration can arise even when immigrants bring signiÖcant economic prosperity to receiving areas. I exploit exogenous variation in European immigration to US cities between 1910 and 1930 induced by World War I and the Immigration Acts of the 1920s, and instrument immigrants' location decision relying on pre-existing settlement patterns. Immigration increased natives' employment and occupational standing, and fostered industrial production and capital utilization. However, it lowered tax rates, public spending, and the proimmigration party's (i.e., Democrats) vote share. The ináow of immigrants was also associated with the election of more conservative representatives, and with rising support for anti-immigration legislation. I provide evidence that political backlash was increasing in the cultural distance between immigrants and natives, suggesting that diversity might be economically beneficial but politically hard to manage.

This dissertation is composed of three essays that study the macroeconomic and financial causes of the Great Recession. The first chapter focuses on understanding some of the business cycle dynamics of different regions in the United States. In particular, I seek to understand what shocks and frictions are the drivers of consumption and employment differences across subnational economies, particularly states. I find that the shocks and frictions that drive the aggregate business cycle are not enough to understand regional business cycle dynamics. In this chapter I develop methodological contributions that can help researchers guide the construction of models whose goal is to understand regional business cycle dynamics and how it relates to aggregate business cycle dynamics. The second chapter focuses on understanding the link between regional and aggregate business cycles. We find that that the shocks that we can identify using cross-sectional variation are insufficient to understand the joint dynamics of prices, wages and employment at business cycle frequencies. In particular, demand shocks identified using cross-region variation are insufficient to explain the persistent decline in aggregate employment. This chapter develops methodological contributions to identify shocks in macroeconomic models and to construct regional indexes for prices and wages. The third chapter is an empirical analysis of the non-agency mortgage backed securities market, which has been at the core of the explanations of the causes of the Great Recession. By carefully studying the cash flows, returns, and how they relate to the credit ratings, we find that contrary to the conventional narrative of the crisis, AAA-rated subprime mortgage backed securities performed remarkably well. This calls into question some key aspects of the explanations that have been given as triggers of the crisis of 2008, and points at the need to better understand the forces behind this event in order to have a more accurate understanding and be able to prescribe appropriate policies.

This paper investigates the existence of speculative bubbles in the US national and 21 regional housing markets over three decades (1978–2015). A new method for real-time monitoring exuberance in housing markets is proposed. By taking changes in the macroeconomic conditions (such as interest rate, per-capita income, employment, and population growth) into consideration, the new method provides better control for housing market fundamentals and thereby it is expected to significantly reduce the chance of false positive identification. Compared with the method of Phillips et al. (2015a, 2015b), the new approach finds a dramatic reduction in the number of speculative housing markets and shorter bubble episodes in the US. It locates only one bubble episode in the early-to-mid 2000s over the whole sample period in the national housing market. At the regional level, it identifies two periods of speculation: late 1980s and early-to-mid 2000s. The early-to-mid 2000s bubble episode lasts longer and involves 16 metropolitan statistical areas.

We develop a parametrization of the multinomial probit model that yields greater insight into the underlying decision-making process, by decomposing the error terms of the utilities into latent factors and noise. The latent factors are identified without a measurement system, and they can be meaningfully linked to an economic model. We provide sufficient conditions that make this structure identified and interpretable. For inference, we design a Markov chain Monte Carlo sampler based on marginal data augmentation. A simulation exercise shows the good numerical performance of our sampler and reveals the practical importance of alternative identification restrictions. Our approach can generally be applied to any setting where researchers can specify an a priori structure on a few drivers of unobserved heterogeneity. One such example is the choice of combinations of two options, which we explore with real data on education and occupation pairs.

The US financial sector has become a magnet for the brightest graduates in the science, technology, engineering and mathematical fields (STEM). We provide quantitative bases for this well-known fact and illustrate its consequences for the productivity growth in other sectors over the period 1980-2014. First, we find that the share of STEM talents grew significantly faster in finance than in other key STEM sectors such as high-tech, and this divergent pattern has been more evident for STEM than for general skills and more pronounced for investment banking. Second, this trend did not reverse after the Great Recession, and a persistent wage premium is found for STEM graduates working in finance and especially in typical financial jobs at the top of the wage distribution. Third, the brain drain of STEM talents into finance has been associated with a cumulative loss of labor productivity growth of 6.6% in the manufacturing sectors. Our results suggest that increasing the number of STEM graduates may not be enough to reignite sluggish economic growth without making their employment in finance more costly.

Black and Hispanic men with college degrees earn only 80 cents to the dollar of what White men earn in private industry. Therefore, education somewhat mitigates the minority pay gap, although it is still substantial. One might expect that institutions of higher education would be more equitable as employers, as they are viewed as more progressive. The data in this brief support that hypothesis. Across higher ed administrative positions, there exists no pay gap between minority and White administrators. This is great news; however, there still exists a substantial gap in the representation of minorities in higher ed administrative positions when compared to their representation in the population. This brief provides a summary of how higher education has represented and paid racial/ethnic minorities in administrative positions from 2001-16. For the purposes of this brief, we grouped non-White (minority) statuses collectively, given that until 2012 CUPA-HR collected and reported data for minority/non-minority status alone. In addition, each minority status on its own makes for an extremely small comparison group (Figure 1).The data in Figure 1 foretell one of the main messages of this brief: The clear majority (86%) of higher ed administrators are White. The underrepresentation of minorities in higher ed administrative positions mirrors that of private industry, where 87% of senior-level executives are White. Despite decades of diversity initiatives, the gap in minority representation for leadership positions remains persistent. There are many factors that may explain the large and growing gap between the U.S. minority and higher education administrator populations. One is that the labor pool for these positions is constrained to those individuals who possess at least an undergraduate degree and often a graduate degree in their field. The proportion of minorities who have the college degree needed for administrative positions is much lower than the percentage of non-minorities (Whites). For example, in 2015, the percentage of non-minorities who had a college degree was 33%, whereas the percentage of minorities with a college degree was 21%. For this reason, when we examine minority representation in this brief, we draw comparisons with the percentage of minorities who have a college degree, which represents the potential labor pool for these positions.

ducational Attainment in America is an interactive dot-density map of the US population aged 25 and over by educational attainment. Data are summarized into five categories, which represent the highest education attained: less than high school; high school or equivalent; some college or associate's degree; bachelor's degree; and graduate degree. Data are from the 2011-2015 American Community Survey Table B15003, distributed by NHGIS. Dot locations are approximate and do not represent the locations of individuals. Also, as the ACS is a survey of the US population, its estimates are subject to a margin of error.

Small family firms dominated the American economy in the nineteenth century, and still dominate in many developing economies today. A long-conjectured cause of this phenomenon, represented by Chandler (1977), is that a lack of technological capability to move goods and people precludes the emergence of modern firms. This paper provides the first causal evidence in support of this hypothesis, exploiting the natural experiment that Boston quickly electrified its previous horse-drawn streetcar system between 1889 and 1896 while keeping the preexisting transit routes almost unchanged. The inference comes from comparing changes in firm size in rail-connected locations to changes in neighboring unconnected locations. Analyzing new data transcribed from Boston business records from 1885 to 1905, I find that rail-connected locations experienced a 5.3-percentage point relative drop in the share of sole proprietorship establishments after the streetcar electrification.

We study a novel dataset compiled from archival records, which includes information on men’s wages, union status, educational attainment, work history, and other background variables for several cities circa 1950. Such data are extremely rare for the early post-war period when U.S. unions were at their peak. After describing patterns of selection into unions, we measure the union wage premium using unconditional quantile methods. The wage premium was larger at the bottom of the income distribution than at the middle or higher, larger for African Americans than for whites, and larger for those with low levels of education. Counterfactuals are consistent with the view that unions substantially narrowed urban wage inequality at mid-century.

With increasing numbers of immigrant and refugee families settling outside the handful of states that have traditionally been home to the majority of newcomers, the children of immigrants now make up more than 10 percent of the young child population (ages 0 to 5) in 37 states plus the District of Columbia. Across the United States, about one-third (32 percent) of young children live in homes where a language other than English is spoken. Access to quality early childhood education and care (ECEC) is particularly important for these Dual Language Learners (DLLs) and for children from immigrant families, as such programs can help build language and literacy skills and expose the children and their families to American culture and norms.