OBJECTIVE: In this paper, we describe the methods underlying the econometric model developed by the Office of the Actuary in the Centers for Medicare & Medicaid Services, to explain differences in per capita total personal health care spending by state, as described in Cuckler, et al. (2011). Additionally, we discuss many alternative model specifications to provide additional insights for valid interpretation of the model. DATA SOURCE: We study per capita personal health care spending as measured by the State Health Expenditures, by State of Residence for 1991-2009, produced by the Centers for Medicare & Medicaid Services' Office of the Actuary. State-level demographic, health status, economic, and health economy characteristics were gathered from a variety of U.S. government sources, such as the Census Bureau, Bureau of Economic Analysis, the Centers for Disease Control, the American Hospital Association, and HealthLeaders-InterStudy. PRINCIPAL FINDINGS: State-specific factors, such as income, health care capacity, and the share of elderly residents, are important factors in explaining the level of per capita personal health care spending variation among states over time. However, the slow-moving nature of health spending per capita and close relationships among state-level factors create inefficiencies in modeling this variation, likely resulting in incorrectly estimated standard errors. In addition, we find that both pooled and fixed effects models primarily capture cross-sectional variation rather than period-specific variation.

Many American families whose incomes are not low enough to officially place them in poverty live in economically precarious situations. This struggling lower-middle class consists of the 30 percent of working-age families with children who have incomes between 100 and 250 percent of the federal poverty level (FPL), or between roughly $15,000 and $60,000, depending on family composition. Though not officially poor, these individuals and families experience limited economic security. One major setback could thrust them into economic chaos. The struggling lower-middle class encompasses low- and middle-skilled workers whose wages have stagnated in recent decades (Autor, Katz, and Kearney 2008). More than half of these families are headed by married couples, and of these families, roughly half rely on two earners to make ends meet. While lower-middleclass families face many challenges, this policy paper focuses . . .

Extensive research documents the relevance of families and socioeconomic resources to health. This article extends that research to sexual minorities, using 12 years of the National Health Interview Survey (N = 460,459) to examine self-evaluations of health among male and female adults living in same-sex and different-sex relationships. Adjusting for socioeconomic status eliminates differences between same- and different-sex cohabitors so that they have similarly higher odds of poor health relative to married persons. Results by gender reveal that the cohabitation disadvantage for health is more pronounced for different-sex cohabiting women than for men, but little difference exists between same-sex cohabiting men and women. Finally, the presence of children in the home is more protective for womens than mens health, but those protections are specific to married women. In all, the results elucidate the importance of relationship type, gender, and the presence of children when evaluating health.

Explanations for gender difference often focus on relative differences in time and money connected to employment within couples and cultural (e.g. doing gender) arguments to pinpoint the mechanisms that lead to gender-based inequality. However, previous research indicates clear differences in how heterosexual couples allocate time to childcare, housework, and leisure, suggesting that time/money tradeoffs and cultural pressures may operate in different ways across different areas of time use. Further, research points to couples with atypical work/family allocations, like those with a stay-at-home father or breadwinner mother, as drivers of gender similarity or difference in some areas, finding that families with a breadwinner mother and at-home father are the most equal when it comes to childcare time, but the least equal when it comes to housework allocations. However, a rigorous examination of time use in these atypical families has not been conducted drawing on a population sample. We use integrated American Time Use Survey (ATUS) data and seemingly unrelated regression (SUR) analyses to extend previous research focused on pinpointing the mechanisms that underlie gender difference and investigate whether time in childcare, housework, leisure, exercise, and sleep differ among a nationally representative sample of at-home and breadwinner parents to better understand how very unequal employment and care obligations (primary parenting vs. breadwinning) and gender shape these time allocations. Overall, we find that mothers and fathers are more alike than different, suggesting that gender, not jobs, has a stronger influence on time use, even in couples with very unequal paid work commitments.

Using the 1995–2011 March Current Population Survey and 1970–2000 Census data, we find that the fertility, education, and labor supply of second-generation women (US-born women with at least one foreign-born parent) are significantly positively affected by the immigrant generation’s levels of these variables, with the effect of the fertility and labor supply of women from the mother’s source country generally larger than that of women from the father’s source country and the effect of the education of men from the father’s source country larger than that of women from the mother’s source country. We present some evidence that suggests our findings for fertility and labor supply are due at least in part to intergenerational transmission of gender roles. Transmission rates for immigrant fertility and labor supply between generations are higher than for education, but there is considerable intergenerational assimilation toward native levels for all three of these outcomes.

We believe there are state-level policy solutions to this wage gap that can appropriately value womens work and help Oregon women be more economically secure.

We construct longitudinal data from the U.S. Census records to study migration patterns of those affects by the Dust Bowl of the 1930s. We document three principal results. First, inter-county migration rates were much higher in the Dust Bowl than elsewhere in the U.S. This "excessive migration" is due to the fact that individuals who were otherwise unlikely to move (e.g., those who were married, those with young children), were equally likely to move from the Dust Bowl. Second, relative to the other occupational groups, farmers were the least likely to move from the Dust Bowl; this relationship between mobility and occupation was unique to that region. Third, the westward push from the Dust Bowl to California was unexceptional; migrants from the Dust Bowl were no more likely to move to California than migrants from other parts of the U.S.

Attribute-Oriented Induction of High-level Emerging Pattern(AOI-HEP) is a combination of Attribute Oriented Induction (AOI) and Emerging Patterns (EP). AOI is a summarisation algorithm that compact a given dataset into small conceptual descriptions, where each attribute has a defined concept hierarchy. This presents patterns are easily readable and understandable.Emerging patterns are patterns discovered between two datasets and between two time periods such that patterns found in the first dataset have either grown (or reduced) in size, totally disappeared or new ones have emerged. AOI-HEP is not influenced by border-based algorithm like in EP mining algorithms. It is desirable therefore that we obtain summarised emerging patterns between two datasets. We propose High-level Emerging Pattern (HEP) algorithm. The main purpose of combining AOI and EP is to use the typical strength of AOI and EP to extract important high-level emerging patterns from data. The AOI characteristic rule algorithm was run twice with two input datasets,to create two rulesets which are then processed with the HEP algorithm. Firstly, the HEP algorithm starts with cartesian product between two rulesets which eliminates rules in rulesets by computing similarity metric (a categorization of attribute comparisons). Secondly, the output rules between two rulesets from the metric similarity are discriminated by computing a growth rate value to find ratio of supports between rules from two rulesets. The categorization of attribute comparisons is based on similarity hierarchy level. The categorisation of attributes was found to be with three options in how they subsume each other. These were Total Subsumption HEP (TSHEP), Subsumption Overlapping HEP (SOHEP) and Total Overlapping HEP (TOHEP) patterns. Meanwhile, from certain similarity hierarchy level and values, we can mine frequent and similar patterns that create discriminant rules. We used four large real datasets from UCI machine learning repository and discovered valuable HEP patterns including strong discriminant rules, frequent and similar patterns. Moreover, the experiments showed that most datasets have SOHEP but not TSHEP and TOHEP and the most rarely found were TOHEP. Since AOI- iii HEP can strongly discriminate high-level data, assuredly AOI-HEP can be implemented to discriminate datasets such as finding bad and good customers for banking loan systems or credit card applicants etc. Moreover, AOI-HEP can be implemented to mine similar patterns, for instance, mining similar customer loan patterns etc.

Recent media attention highlights American womens exceptionalism in the realm of intensive parenting and raises questions about the implications for mothers well-being. In this paper we: 1) assess the multidimensional nature of subjective well-being among women with and without children in the home across a range of activities; and 2) compare mothers subjective well-being while engaged in intensive versus routine childcare. We use new data from the 2010 American Time Use Survey that includes respondent reports of momentary well-being in three randomly selected activities. We leverage within-person variation in reports of meaning, happiness, stress, tiredness, and sadness to assess how the presence of children and other characteristics of activities (whether others present, timing, duration, location) contribute to well-being. We look further at variation in subjective well-being while parenting in the context of time in activities throughout the day, union status, child and parent age, education, employment, and typical sleep duration.

The increase in high-skilled immigrants to the United States coincided with the expansion of the high-technology sector, and now a large share of Asian immigrants concentrate in high-tech industries. Despite much research on the relationship between ethnic concentration and labor market outcomes, the association between ethnic niche employment and earnings within the high-technology sector of the labor market has yet to be examined. This study compares the relationship between employment in ethnic niches and earnings within high- and low-tech industries among Asian immigrants. In low-technology industries, ethnic niches are generally associated with lower earnings compared with non-niches, but in high-technology industries, employment in an ethnic niche is associated with higher earnings. These patterns vary by gender and ethnic group. This association is partly explained by the industries that comprise ethnic niches, as non-Hispanic white immigrants also experience some of the same advantages and disadvantages.

Casual estimates of the benefits of increasing schooling using U.S. state schooling laws as instruments typically rely on specifications which assume common trends across states in the factors affecting different birth cohorts. Differential changes across states during this period, such as relative school quality improvements, suggest that this assumption may fail to hold. Across a number of outcomes including wages, unemployment, and divorce, we find that statistically significant causal estimates become insignificant and, in many instances, wrong-signed when allowing year of birth effects to vary across regions

The research that follows ties together three topics of interest. These are gentrification, second/vacation-home impact on tourism destinations, and resident livability issues in a tourism dominated community. The study location is South of Broad, Charleston, SC, a historic corner of the city that has transitioned over the years from a traditional, upper-middle class neighborhood to what is today the most upscale part of town; but one heavily influenced by the second/vacation-home part-time residents that constitute a significant share of the area's homeowners. The paper considers, via a mixed-method research approach, how this tourism-oriented transition has affected the neighborhood and how it has been viewed by its residents. Describing the neighborhood's transition, the new term aristophication is proposed.

We exploit exogenous variation in college completion induced by draft-avoidance behavior during the Vietnam War to examine the impact of college completion on adult mortality. Our preferred estimates imply that increasing college completion rates from the level of the state with the lowest induced rate to the highest would decrease cumulative mortality by 28 percent relative to the mean. Most of the reduction in mortality is from deaths due to cancer and heart disease. We also explore potential mechanisms, including differential earnings, health insurance, and health behaviors, using data from the Census, ACS, and NHIS.

This paper studies cross-country differences in female employment and market hours over time in the multi-sector general equilibrium model. The focus is two-fold: (1) to quantify the effect on the consumption of services and service sector employment from women entering the labor force, and (2) to compute the difference of hours worked between Europe and the United States from taxes, structural change and female employment. Increases in female employment, due to a closing gender wage gap and structural change, account for a sizeable portion of the rise in service consumption/employment. Cross-country tax differences are able to explain large sectoral differences across countries, which are reinforces by a lack of female employment. The key driver is the substitution of market-services for home production. Women, being less productive in sectors requiring brawn, have a comparative advantage in working at home or in the service sector compared to industry. High taxes disincetivize women from working in the market and service production remains at home, reducing demand for market-services, which feeds back into a smaller service sector and lower female market hours. Subsidies to female employment can circumvent the high tax effect, but lead to considerable welfare losses.

Research suggests that merit scholarship programs increase college enrollment in states that adopt them but post-college migration may limit the effect these programs have on the stock of college-educated labor in those states. In this paper we consider the effect of Georgia's HOPE Scholarship program on post-college retention, estimating the effect in two ways. First, we use administrative data on student and employment records to examine the effects of the HOPE Scholarship on post-college retention rates in the Georgia workforce for students enrolled in the University System of Georgia (USG). Second, we use data from the census and ACS and a difference-in-difference model following the approach of Hickman (2009).

On March 23, 2010, President Obama signed the Patient Protection and A↵ordable Care Act (ACA) into law. The ACA includes a wide-reaching set of reforms to ensure more universal and comprehensive health insurance benefits. The bill has the potential to impact U.S. firms across all industries through regulations on employer-sponsored insurance (ESI), which resemble mandated benefits, and general equilibrium e↵ects. We aim to identify how much shareholders across industries and firms will bear the burden of the ACA based on an event study of asset prices. We focus on two key legislative dates: (1) when the ACA was passed by the U.S. House of Representatives and (2) when the U.S. Supreme Court ruled on the constitutionality of the ACA. This unexpected change in asset prices captures the long-run expected impact of the reform for a given firm, including general equilibrium e↵ects. Using a dataset of 321 publicly traded firms from 19 sectors (defined by the 2-digit North American Industry Classification System code), we find that 56% of firms experienced a negative impact on their asset prices when ACA was passed, and that the impact on asset prices was heterogeneous across firms. We find that this heterogeneity in asset price e↵ects is consistent with partial equilibrium e↵ects predicted by theory. In particular, shareholders of firms in sectors with a higher proportion of employees who are uninsured or who have ESI prior to the reform experience a negative impact on their asset prices from the ACA. In contrast, shareholders of firms in sectors with a higher proportion of employees who would qualify for the Medicaid expansion or who would qualify for premium subsidies on the health insurance exchanges experience a positive impact on their asset prices. Collectively, our results suggest that the incidence of the ACA lies partly on shareholders, but that the expansion of coverage through public insurance or publicly-supported insurance markets is incident on taxpayers or possibly employees of the a↵ected firms.

In this paper we provide an overview of the patterns of intergenerational proximity and coresidence of adult children and their mothers in the U.S., using data from the National Survey of Families and Households (NSFH) and the U.S. Census. We highlight the importance of three specification and sample choices in the analysis. First, most previous studies consider coresidence to be the limiting case of proximity, using Tobit, ordered logit, or ordered probit specifications. We argue that proximity and coresidence are qualitatively different, and show that the multinomial logit provides a better representation of the patterns in the data. Second, we argue that substantial differences in the correlates of proximity by gender and marital status indicate the importance of modeling these categories separately. Third, the NSFH allows us to consider the proximity of couples to both his mother and her mother. This information is rarely available in survey data but is important for complete analyses. Our results show that education and age are the most robust predictors of proximity: college graduates are less likely to live near their mothers and older children live further from their mothers. Other demographic variables such as race, ethnicity and only child status also affect the probability of close proximity and coresidence. However, characteristics indicating adult childrens current need for transfers (e.g. grandchildren) are not correlated with either close proximity or coresidence, while characteristics indicating mothers current needs for transfers (e.g., disability) are correlated with coresidence but not close proximity.

Although weights are widely used in survey sampling their ultimate justification from the design perspective is often problematical. Here we will argue for a stepwise Bayes justification for weights that does not depend explicitly on the sampling design. This approach will make use of the standard kind of information present in auxiliary variables however it will not assume a model relating the auxiliary variables to the characteristic of interest. The resulting weight for a unit in the sample can be given the usual interpretation as the number of units in the population which it represents.

Manhattan's Chinatown is the oldest and used to be the largest Chinese community in the East Coast of the United States. Since the repeal of the Chinese Exclusion Acts in 1940s, it experienced great expansion, tremendous population influx and significant real estate development. As a community located next door to the world class financial district, Chinatown has been under the pressure of gentrification for decades, people keep on moving to outer-bound communities. However, Chinatown is still a low income community and persists highly mix- used land use patter, comparing with other downtown Manhattan communities. Why Chinatown has gentrifed later than other communities in downtown Manhattan? To answer the question, this planning history study examined four cases in the second half of the 20 century, which are Chinatown Street Revitalization Study of 1976, Special Manhattan Bridge District of 1982, East Village/Lower East Side Rezoning of 2008, and Establishment of Chinatown Business Improvement District of 2011.