Although gender gaps in parenting time endure for parents of young children, and in physical and developmental care, men’s changing attitudes toward egalitarian gender roles suggest that gender disparities in parenting time may have closed in some contexts: particularly, in other shared activities with children, when children are school aged or older, and among higher educated parents. We investigate these possibilities using weekday time diary data from a nationally-representative survey of parents participating in the American Time Use Survey (2003-2014; n=28,698). In contrast to our expectations, we find that the gender gap in parents’ time with children persists when children are older, and even grows for some activities; extends to several other forms of shared parent-child time; and is often largest for higher-educated parents. At the same time, there are notable contexts in which the gaps disappear, although they encompass the most pleasant activities, at less intensive stages of parenting.

Analyzing relational data typically involves tasks that facilitate gaining familiarity or insights and coming up with findings or conclusions based on the data. This process is usually practiced by data experts, such as data scientists, who share their output with a potentially less expert audience (everyone). Our goal is to enable everyone to participate in analyzing data rather than passively consuming its outputs (analytics democratization). With today’s increasing availability of data (data democratization) on the internet (web) combined with already widespread personal computing capabilities such a goal is becoming more attainable. With the recent increase of public data, i.e., Open Data, users without a technical background are keener than ever to analyze new data sets that are relevant to wide sectors of society. An important example of Open Data is the data released by governments all over the world, i.e., Open Government. This dissertation focuses on two main challenges that would face data exploration scenarios such as exploring open data found over the web. First, the infrastructure necessary for interactive data exploration is costly and hard to manage, especially by users who do not have technical knowledge. Second, the target users need guidance through the data exploration since there are too many starting points.

We develop improved statistical procedures for testing stochastic monotonicity. While existing tests use a fixed critical value to set the limiting rejection rate equal to nominal size at the least favorable case, we use a bootstrap procedure to raise the limiting rejection rate to nominal size over much of the null. This improves power against relevant local alternatives. To show the validity of our approach we draw on recent results on the directional differentiability of the least concave majorant operator, and on bootstrap inference when smoothness conditions sufficient to apply the functional delta method for the bootstrap are not satisfied.

The Supplemental Nutrition Assistance Program (SNAP) provides food assistance to nearly 44 million Americans each year. Empirical estimates of the program’s ability to stimulate food consumption vary widely. Studies of SNAP recipients from the 1960s-1980s find much smaller marginal propensities to consume food (MPCf) out of SNAP than studies using samples of recipients from the late-2000s and 2010s. I provide some of the first evidence on the cause of this increase by investigating whether this difference can be explained by the shift from paper coupons (“food stamps”) to Electronic Benefit Transfer (EBT) cards. I use a linear fixed effects model to exploit plausibly exogenous variation in the introduction of EBT across states and time to identify the effect of EBT introduction on the MPCf out of SNAP. I find that EBT introduction can partially explain the increase in the MPCf out of SNAP between earlier and later studies. Additionally, the transition to EBT caused an economically significant increase in food expenditures by SNAP households. This work documents a significant, though unintended, increase in the ability of SNAP to stimulate food consumption. It has significant implications for estimating the impact of SNAP benefits today as well as understanding the effects of changing how transfer payments are made.

Glendale may house the most visible Armenian diaspora in the world; however, it remains among the most invisible in print. The following begins to shed light on this community by providing a brief background and demographic profile of Armenians in Glendale. The article then attempts to expand discussions of Chinese “ethnoburbs” by situating Glendale Armenians in these discussions. Despite scholars’ expansion of the concept, the ethnoburb has had limited application—largely, to Chinese and a few other Asian immigrant communities. However, is the concept of the ethnoburb generalizable in contexts outside of Chinese immigrant settlements? In this article, I contend that the ethnoburb model is generalizable by situating Glendale's Armenian community within this framework.

The Internet has evolved from Web 1.0, with static web pages and limited interactivity, to Web 2.0, with dynamic content that relies on user engagement. This change increased production costs significantly, but the price charged for Internet content has generally remained the same: zero. Because no transaction records the "purchase" of this content, its value is not reflected in measured growth and productivity. To capture the contribution of the "free" Internet, we model the provision of "free" content as a barter transaction between the content users and the content creators, and we value this transaction at production cost. When we incorporate this implicit transaction into U.S. gross domestic product (GDP), productivity, and household accounts, we find that including "free" content raises estimates of growth, but not nearly enough to reverse the recent slowdown.

We argue theoretically and document empirically that aging leads to greater (industrial) automation, and in particular, to more intensive use and development of robots. Using US data, we document that robots substitute for middle-aged workers (those between the ages of 36 and 55). We then show that demographic change—corresponding to an increasing ratio of senior to middle-aged workers—is associated with pronounced increases in the adoption of robots and other automation technologies across countries and with more robot-related activities in US commuting zones. We provide a directed technological change model that explains not only these main effects of aging, but also predicts that these responses should be more pronounced in industries that rely more on middle-aged workers and those that present greater opportunities for automation. Both of these predictions receive support from country-industry variation in the adoption of robots. Our model also implies that the productivity implications of aging are ambiguous when technology responds to demographic change, but we should expect productivity to increase relatively in industries that are most amenable to automation, and this is indeed the pattern we find in the data.

The United States economy was transformed in the period between American independence and the beginning of the Civil War by rapid population growth, the development of manufacturing, the onset of modern economic growth, increasing urbanization, the rapid spread of se lement into the trans-Appalachian west, and the rise of European immigration. ese years were also characterized by an increasing sectional con ict between free and slave states that culminated in 1861 in Southern secession from the Union and a bloody and destructive Civil War. Labor markets were central to each of these developments, directing the reallocation of labor between sectors and regions, channeling a growing population into productive employment and shaping in important ways the growing North-South division within the country. Put di erently, labor markets in uenced the pace and character of economic development in the antebellum United States. On the one hand, the responsiveness of labor markets to economic shocks was an important factor in promoting economic growth; on the other, imperfections in labor market response to these shocks had signi cant e ects on the character and development of the national economy.

How does place structure the gendered division of household labor? Because people’s living spaces and lifestyles differ dramatically across urban, suburban, and rural areas, it follows that time spent on household chores may vary across places. In cities, for example, many households do not have vehicles or lawns, and housing units tend to be relatively small. Urban men’s and women’s time use therefore provides insight into how partners contribute to household chores when there is less structural demand for the types of tasks they typically do. We examine these dynamics using data on heterosexual married individuals from the American Time Use Survey combined with the Current Population Survey. We find that urban men spend relatively little time on male-typed chores, but they spend the same amount of time on female-typed chores as their suburban and rural counterparts. This pattern suggests that urban men do not “step up” their involvement in female-typed tasks even though they contribute little in the way of other housework. In contrast, urbanicity rarely predicts women’s time use, implying that women spend considerable time on household chores regardless of where they live. Implications for research on gender and housework are discussed.

Skyline query retrieves a set of skyline points which are not dominated by any other point and has attracted wide attention in database community. Recently, an important variant G-Skyline is developed. It aims to return optimal groups of points. However, when data dimensionality is high, G-Skyline result has too many groups, which makes that users cannot determine which groups are satisfactory. To find less but more representative groups of points, in this paper, we propose a novel concept of k-dominant G-Skyline, which first adopts k-dominance to retrieve more representative points and then computes the groups not k-dominated by others. In addition, we present a two-phase algorithm to efficiently compute k-dominant G-Skyline groups. In the first phase, we construct a lkDG structure while pruning the points never included in any k-dominant G-Skyline group as much as possible. In the second phase, using lkDG, we propose two efficient k-dominant G-Skyline searching methods SM-P and SM-G, which generate new candidate groups from single points and ancestor groups, respectively. Our experimental results indicate that our proposed algorithms are more efficient than the baseline methods on real and synthetic data sets.

When consumer choices have inertia, firms have incentives to use dynamic pricing by first reducing the price to build a large market share, and then by increasing prices. This strategy may reduce consumer welfare through increases in the prices for incumbents, while also changing the patterns of entry and exit in the market. Although the presence of inertia in health care markets has been well established, little is known about the welfare implications of dynamic pricing in these markets. In order to assess these implications, in this paper I develop and estimate a dynamic model of supply and demand for Medicare Part D prescription drug insurance plans, where multi-product firms consider consumer inertia in their decisions about premiums, offerings of new plans, and exit of plans. Using the model and the estimated parameters, I conduct counterfactual exercises where I explore the welfare effects of a policy that limits dynamic pricing by imposing fixed markups. I find that this policy, given the actual consumer inertia present in this market, would improve consumer welfare by 3.1%, through a reduction in premiums that is partially offset by a reduction of entry into the market. When the same policy is implemented in a counterfactual scenario without inertia, it has a larger positive effect, increasing consumer welfare by 9.4% relative to the benchmark. This difference indicates that policies that limit dynamic pricing can be more effective in improving consumer welfare in markets with lower levels of consumer inertia, where they are less likely to harm market entry.

We document that the decline in the labor income share since the 1950s has been countered by a rise in the income share of capital goods that embody information and communication technology (ICT). In parallel, there has been substantial reallocation of labor income from occupations relatively substitutable with ICT (routine) to ones relatively complementary (non-routine). These trends are consistent with the view that ICT allows for the mechanization of tasks that traditionally required labor, a process known as automation. Our calibration suggests that automation can account for half of the decline in the labor share, but that it is unlikely to be the sole driver of the decline in the routine labor income share. A representative agent framework suggests welfare gains of 4%.

The Internet has evolved from Web 1.0, with static Web pages and limited interactivity, to Web 2.0, with dynamic content that relies on user engagement. This change increased production costs significantly, but the price charged for Internet content has generally remained the same: zero. Because no transaction records the "purchase" of this content, its value is not reflected in measured growth and productivity. To capture the contribution of the "free" Internet, we model the provision of "free" content as a barter transaction between the content users and the content creators, and we value this transaction at production cost. When we incorporate this implicit transaction into U.S. gross domestic product (GDP), productivity, and household accounts, we find that including "free" content raises estimates of growth, but not nearly enough to reverse the recent slowdown.

The authors examine racial disparities in infants’ exposure to economic disadvantage at the family and local area levels. Using data from the 2008–2014 files of the American Community Survey, the authors provide an up-to-date empirical benchmark of newborns’ exposure to poverty. Large shares of Hispanic (36.5 percent) and black (43.2 percent) infants are born poor, though white infants are also overrepresented among the poor (17.7 percent). The authors then estimate regression models to identify risk factors and perform decompositions to identify compositional factors underlying between-race differences. Although more than half of the black-white poverty gap is explained by differences in family structure and employment, these factors account for less than one quarter of white-Hispanic differences. The results also highlight the unmet need for social protection among babies born to poor families lacking access to assistance programs and the safety net. Hispanic infants are particularly likely to be doubly disadvantaged in this manner. Moreover, large and disproportionate shares of today’s black (48.3 percent) and Hispanic (40.5 percent) babies are born into poor families and places with poverty rates above 20 percent. These results raise important questions about persistent and possibly growing racial inequality as America makes its way to a majority-minority society as early as 2043.

The gender wage gap, the disparity in pay between men and women, has narrowed to 81 cents in 2016 from 57 cents on the dollar in 1975. Nevertheless, the gap persists. Over the course of a career, the gender wage gap results in women earning $1 million less than men do. To close this gap, women have relied primarily on the advantages conferred by education. Today, women are enrolling in college in greater numbers than men, breaking through barriers to pursue degrees in male-dominated majors that offer higher earnings, as well as graduating in greater numbers at all levels of education. In the 1970s, the number of associate’s degrees awarded to women began outnumbering those awarded to men. In the 1980s, the number of bachelor’s degrees and master’s degrees awarded to women overtook the number awarded to men. By the 2000s, more women completed doctoral degrees than men.

This dissertation is comprised of three chapters concerned with public insurance programs in the United States and their impact on households and the macroeconomy. In 2015 the Social Security Administration’s old-age and survivors insurance (OASI), disability Insurance (SSDI), and Medicaid programs benefited 90 million adult individuals and accounted for 23% of all government expenditures. In the first chapter, “Medicaid’s Long-Term Care Programs and the Macroeconomy", I calibrate an overlapping-generations model to the U.S. economy and quantify the fiscal and welfare implications of the eligibility rules that govern access to Medicaid’s care programs. I find that the costs associated with expanding home care benefits among the aged population are partially mitigated by individuals substituting out of institutional care. The substitution is most prevalent among elderly individuals with marginally higher incomes that gain access to Medicaid through a spend-down rule.

Selecting a certain number of data points (or records) from a database which "best" satisfy users' expectations is a very prevalent problem with many applications. One application is a hotel booking website showing a certain number of hotels on a single page. However, this problem is very challenging since the selected points should "collectively" satisfy the expectation of all users. Showing a certain number of data points to a single user could decrease the satisfaction of a user because the user may not be able to see his/her favorite point which could be found in the original database. In this paper, we would like to find a set of k points such that on average, the satisfaction (ratio) of a user is maximized. This problem takes into account the probability distribution of the users and considers the satisfaction (ratio) of all users, which is more reasonable in practice, compared with the existing studies that only consider the worst-case satisfaction (ratio) of the users, which may not reflect the whole population and is not useful in some applications. Motivated by this, in this paper, we propose algorithms for this problem. Finally, we conducted experiments to show the effectiveness and the efficiency of the algorithms.

Exercise capacity (EC) is a critical outcome in chronic obstructive lung disease (chronic obstructive pulmonary disease (COPD)). It measures the impact of the disease and the effect of specific interventions like pulmonary rehabilitation (PR). EC determines COPD prognosis and is associated with health-care utilization and quality of life. Field walking tests and cardiopulmonary exercise test (CPET) are two ways to measure EC. The 6-minute walking test (6MWT) is the commonest and easiest field test. CPET has the advantage of assessing maximal aerobic capacity. Determinants of EC include age, gender, breathlessness, and lung function. Previous research suggests that socioeconomic status (SES), a meaningful factor in COPD, may also be associated with EC. However, those findings have not been replicated. We aimed to determine whether SES is an independent factor associated with EC in COPD. For this analysis, we used the National Emphysema Treatment Trial (NETT) database. NETT was a multicenter clinical trial where severe COPD patients were randomized to lung volume reduction surgery or medical therapy. Measures used were taken at baseline, postrehabilitation. Patients self-reported their income and were divided in two groups whether it was less or above US$30,000. Patients with a lower income had worse results in 6MWT (p < 0.0001). We found an independent association between income and the 6MWT in patients with severe COPD after adjusting for age, gender, lung function, dyspnea, and living conditions (p < 0.0007). One previous publication stated the relationship between income and EC. Our research confirms and extends previous publications associating EC with income by studying a large and well characterized cohort of severe COPD patients, also addressing EC by two different methods (maximal watts and 6MWT). Our results highlight the importance of addressing social determinants of health such as income when assessing COPD patients.

Previous studies have examined the link between land-use regulation and home prices extensively. Yet there are few studies that examine the influence of land-use regulation on housing affordability. Even more uncommon is a focus on the effects of specific types of regulation on individual households, and variations in these effects by racial and ethnic group. Using a cross-sectional regression design analyzing existing Wharton Residential Land Use Regulation Survey data, land use regulation survey data developed by Pendall, Puentes, and Martin (2006), and American Community Survey data, this article estimates the impact of various kinds of exclusionary land use regulation on individual housing affordability by housing tenure and race. We find that mobile home bans have powerful and consistent effects on owner affordability. Affordability for African Americans is especially harmed by multi-family development limits and for Hispanics by restrictions on the pace of housing construction.

We study the effects of state and federal dependent health insurance mandates on marriage rates of young adults, ages 19 to 25. Motivated by low rates of coverage among this age group, state governments began mandating health insurers in the 1970s to allow adult children to stay on their parents’ insurance plans. These state level efforts successfully increased insurance coverage rates, but also came with unintended implications for the marriage decisions of young adults. Almost all state mandates explicitly prohibited marriage as a condition of eligibility, thereby directly discouraging marriage. Additionally, by making access to health insurance through parents easier, the mandates made access through spouses’ employers relatively less attractive. To the extent that young adults were altering their marriage plans to gain access through potential spouses, they no longer needed to do so under the mandates, thereby implicitly discouraging marriage. When the dependent coverage mandate of the Affordable Care Act (ACA) was enacted, it effectively ended the state-based marriage restrictions, thereby encouraging marriage among young adults previously eligible for state mandates. On the other hand, for those who were not eligible for state mandates, the ACA represented an attractive new path to obtain coverage, thereby discouraging marriage for these young adults, just as the state mandates had implicitly done previously for others. Thus, the separate efforts at the state and federal level to address low coverage rates for young adults ended up interacting and influencing incentives for marriage in opposite directions. We study these interaction effects on marriage empirically using a new dataset we compiled on state-level dependent coverage mandates. Consistent with theoretical arguments, we find that, before the implementation of the ACA, state mandates lowered marriage rates by about 2 percentage points, but this pattern reversed upon the passage of the ACA. We also find that state mandates increased the probability of out-of-wedlock births among state-mandate-eligible women as compared to ineligible ones, but the ACA reversed this trend as well. Our study provides an important example where fundamental understanding of the effects of the ACA dependent coverage mandate can only be had with full consideration of the pre-existing state laws.