Following Donald Trump’s unexpected victory in the 2016 US presidential election, the American Association for Public Opinion Research announced that “the polls clearly got it wrong” and noted that talk of a “crisis in polling” was already emerging. Although the national polls ended up being accurate, surveys just weeks before the election substantially over-stated Clinton’s lead and state polls showed systematic bias in favor of Clinton. Different explanations have been offered for these results, including non-response bias and late deciders. We argue, however, that these explanations cannot fully account for Trump’s underperformance in October surveys. Utilizing data from two national polls that we conducted in October of 2016 (n>2100 total) as well as 14 state-level polls from October, we find consistent evidence for the existence of “hidden” Trump supporters who were included in the surveys but did not openly express their intention to vote for Trump. Most notably, when we account for these hidden Trump supporters in our October survey data, both national and state-level analyses foreshadow Trump’s Election Day support. These results suggest that late-breaking campaign events may have had less influence than previously thought and the findings hold important implications for how scholars, media, and campaigns analyze future election surveys.

Word embeddings use vectors to represent words such that the geometry between vectors captures semantic relationship between the words. In this paper, we develop a framework to demonstrate how the temporal dynamics of the embedding can be leveraged to quantify changes in stereotypes and attitudes toward women and ethnic minorities in the 20th and 21st centuries in the United States. We integrate word embeddings trained on 100 years of text data with the U.S. Census to show that changes in the embedding track closely with demographic and occupation shifts over time. The embedding captures global social shifts – e.g., the women’s movement in the 1960s and Asian immigration into the U.S – and also illuminates how specific adjectives and occupations became more closely associated with certain populations over time. Our framework for temporal analysis of word embedding opens up a powerful new intersection between machine learning and quantitative social science.

This paper studies the impact of immigration on wages, internal migration and welfare. Using U.S. Census data, I estimate a spatial equilibrium model where labor differs by skill level, gender and nativity. Workers are heterogeneous in city preferences. Cities vary in productivity levels, housing prices and amenities. I use the estimated model to assess the distributional consequences of several immigration policies. The results show that a skill selective immigration policy leads to welfare gains for low skill workers, but welfare losses for high skill workers. The negative impacts are more substantial among the incumbent high skill immigrants. Internal migration mitigates the initial negative impacts, particularity in cities where high skill workers are relatively mobile. However, the negative impacts on some workers intensify. This is because an out-migration of workers of a given type may raise the local wages for workers of that type, while reducing the local wages of workers with complementary characteristics. Overall, there are substantial variations in the welfare effects of immigration across and within cities. Further, I also use the model to assess a non-selective immigration policy and deportation of unauthorized immigrants in specific areas. as well as many seminar participants for helpful comments.

Informal institutions are defined as socially shared rules that guide individuals' behaviors outside of officially sanctioned channels. This paper investigates the link between individual educational attainment and education-related informal institutions by examining second-generation immigrants in the USA. I measure the education-related informal institutions by average educational attainment among the adult population conditional on per capita GDP in the second generation's country of ancestry. Empirical analysis shows that given similar family background, market, and institutions, higher average educational attainment in the origin country predicts more years of individual schooling; this relationship is stronger among those with less educated parents. These findings are robust to various methods of controlling for unobserved human capital, alternative sample criteria, and alternative measures of informal institutions (JEL I20, J15, Z10).

Americans are increasingly favoring walking and biking as a means of getting around. However, because American suburbs, towns, and cities lack infrastructure that support walking and biking, many Americans still rely on automobiles. Within the last few years, multi-use trails have emerged as a solution to retrofit the suburbs for greater walkability and bikeability, and make towns and cities more connected to the outdoors for both recreation and commuting. Saratoga County is a good reflection of this national trend with over 1,000 miles of trails and very active trail planning. We sought to evaluate the Saratoga County trail system based on several conditions previously studied throughout the United States such as connectivity, safety, presence of adequate maps and signage, trails supporting multiple uses, and the level of public input into the planning process. Our research addressed the following questions: How are people using trails in Saratoga County? What is the planning process for trails? What is the level of communication between the public and the trail planners? and How can the Saratoga County trail system be improved? To conduct our research, we sent out a public online survey, conducted semi-structured interviews with municipal planners and community influentials, attended community trail planning meetings, and conducted a spatial-analysis of connectivity using GIS. Our public survey indicated a desire for greater trail connectivity, better maps and signage, and a consolidated trail map. Semi-structured interviews and participant observation revealed strong communication between the public and trail planners during the planning process and challenges trail planners face during the planning and development process.

This study uses a vector autoregression approach to examine the link between jobless recoveries and the fast employment expansion in finance, health and education (FHE) sectors. Both reduced-form estimates and impulse responses indicate a negative effect of the expansion on aggregate employment. While the expansion Granger causes aggregate employment fluctuations, up to 40 per cent of the error variance of those fluctuations can be explained by innovations in the expansion. Moreover, movements in aggregate employment are reduced by 25 per cent when the expansion is accounted for. Therefore, the fast expansion of the FHE sectors is shown to have notably contributed to the onset of jobless recoveries.

THINK Again is about IBM, its leaders, its employees, its shareholders, its customers, its supportive societies, and one-hundred years of their unique interactions. IBM has had its great, good, and bad moments; and, in this century, some of its ugliest. But there is still hope.

This study examines whether the cost of living is related to the probability of living alone among unmarried persons age 65 years and older in the United States. Cost of living is measured at the metropolitan area level by the Elder Economic Security Standard Index, which takes into account geographic variability in cost of housing, food, transportation, and medical care. Using multilevel modeling, we find that higher cost of living is related to a lower likelihood of living alone net of personal resources. Results also show that the gap in the likelihood of living alone between high- and low-income older adults is slightly lessened in low-cost metropolitan areas. We conclude that the price of purchasing privacy is substantially higher in some metropolitan areas than in others. These findings inform policies designed to help older adults age in place.

It is well documented that the housing boom of the early 2000s fueled credit expansion among homeowners. Less attention has been paid to the effects of the housing boom on renters, who make up over 30% of US households. In this paper, I use detailed credit information from a sample of almost 500,000 US consumers to show that house price growth reduced renter credit access during the last housing boom. In particular, banks reduced non-mortgage credit supply when they expanded mortgage lending to homeowners. As a consequence, renters living in locations where banks had more (national) geographic exposure to the housing boom ended up borrowing less but defaulting more. The results are especially pronounced in locations with stronger credit market frictions, as measured by local banks mortgage retention probability and balance sheet liquidity, or bank competition in the local market. The effects of the housing boom on the borrowing and default behavior of renters persisted during the subsequent recession. This research suggests that policies affecting house prices and mortgage financing have broader implications for less well-off households that do not own a home.

In this accessible, engaging, and up-to-date course book, Susan L. Brown employs ethnographic vignettes and demographic data to introduce students to twenty-first century perspectives of contemporary families. Conceived of as a primary or secondary text in classes on family and marriage, this book probes momentous shifts in the definition of family, such as the legalization of same-sex marriage and policy debates on welfare reform and work-familly issues. Brown also chronicles the rise in non-marital childbearing and single mother families and the decline of "traditional" marriage. The book delves into the historical roots of family change, current trends of family formation and dissolution, and the implications of family change for the well-being of adults and children. With a lens towards socioeconomic inequality and racial-ethnic variation in family patterns, Families in America illustrates how family diversity is now the norm.

implementation of the United Nation’s (UN) MillenniumDevelopment Goals. To further reduce under-five child mortality,the UN’s Sustainable Development Goals (SDGs) will focus oninterventions to address neonatal mortality, a major contributor ofunder-five mortality. The African region has the highest neonatalmortality rate (28.0 per 1000 live births), followed by that of theEastern Mediterranean (26.6) and South-East Asia (24.3). This study used the Demographic and Health Survey Birth Recode data(http://dhsprogram.com/data/File-Types-and-Names..cfm) to identify high-risk countries and districts for neo-natal mortality for two sub-districts of Africa--East Africa and West Africa. ed to capture the spatially varying relationships between neonatal mortality and dimensions of potential need 1) care around the time of delivery iii) maternal education, and iii) women's empowerment.

Analiza la evidencia de importantes reducciones en la mortalidad infantil en Colombia, el desarrollo de la población por sexos y edades, la esperanza de vida y el cambio social de algunas regiones.

Virtual reality (VR) is an increasingly hot tech topic. Because VR may be the ultimate virtual project as defined by this column, replacing the real world with a simulated one, it is worthwhile to pause and reflect on its potential and practicality for health sciences libraries. Virtual reality is a computer technology that uses headsets to create an immersive, computer-generated simulation that allows end users to experience, move about in, and interact with this virtual world, shutting out the real world. Other tightly related technologies that are growing in popularity are augmented reality (AR), which overlays a three-dimensional (3D) environment with supplemental data such as graphics or sound, enabling end users to interact with both physical and virtual objects, and mixed reality (MR), which aims to combine both VR and AR, allowing the digital or VR world to interact in real world surroundings. These new “realities” can create unique experiences that expand learning opportunities and engagement for end users. While the most prevalent uses of these technologies thus far have been in the consumer sector, tools for creating these applications are becoming easier to use and more affordable in the education and health care . . .

Using data from the US Census’s American Community Survey and Bureau of Labor Statistics’ Current Population Survey, I estimate the impact of low-skilled immigrants on the employment of low-skilled native born workers in the non-tradable sector in the US. Specifically, I look at industries such as mining, construction, transportation, farming, fishing and forestry, maintenance, and extraction. These industries are the least vulnerable with respect to outsourcing (i.e. “shipping jobs overseas”). Therefore, a change in employment in these sectors should result from a change in the domestic labor supply rather than from labor being outsourced. The data are separated into foreign born and native born, and they are further separated by country of origin, educational attainment, and age of worker. I use a difference-indifferences model to determine the effects that immigrants have on the low-skilled American workers. The control group consists of Texas and South Dakota while the treatment group consists of Arizona and Georgia. These states are non-contiguous and have similar characteristics in terms of industries and labor composition, but the treatment group recently passed immigration reform, while the control group did not. The immigration reforms decreased the number of immigrants in the treatment states relative to the control states. Despite this, the empirical results from this paper find no evidence that low-skilled native workers in the treatment states benefitted from immigration reform.

U.S.-China competition, including economic competition, has come to define U.S. foreign policy since 2017. The two economies are the first- and second-largest national economies in the world, and they are deeply intertwined in all aspects of international exchange. Any changes to the relationship, however necessary, could be costly. To respond to this challenge, RAND researchers conducted economic and institutional analyses of U.S.-China competition, engaged in a participatory foresight exercise to understand the long-term path for ensuring U.S. economic health, and created two economic competition games exploring the dynamics of multiple countries trying to ensure their economic health while interacting with each other and the private sector. This report, the first of a four-part series, includes the economic and institutional analyses of U.S.-China economic competition. The second report presents the results of a participatory foresight exercise designed to under- stand the path for ensuring long-term U.S. economic health. The third and fourth reports describe two economic competition games that explore the dynamics of multiple countries trying to ensure their economic health while interacting with each other and the private sector.

This paper analyzes the dynamic effects of immigration on worker outcomes by estimating an equilibrium model of local labor markets in the United States. The model includes firms in multiple cities and multiple industries which combine capital, skilled and unskilled labor in production, and forward-looking workers who choose their optimal industry and location each period as a dynamic discrete choice. Immigrant inflows change wages by changing factor ratios, but worker sector and migration choices can mitigate the effect of immigration on wages over time. I estimate the model via simulated method of moments by leveraging differences in wages and labor supply quantities across local labor markets to identify how wages and worker choices respond to immigrant inflows. Counterfactual simulations yield the following main results: (1) a sudden unskilled immigration inflow leads to an initial wage drop for unskilled workers which decreases by over half over 20 years; (2) both workers sector-switching and migration across local labor markets play important roles in mitigating the effects of immigration on wages; (3) a gradual immigration inflow leads to significantly smaller effects on native wages than a sudden inflow of the same magnitude.

Background: The use of acupuncture has gained popularity in the USA. The number of acupuncture users and licensed acupuncturists increased by 50% and 100%, respectively, between 2002 and 2012, coinciding with increasing acknowledgement of the importance and efficacy of acupuncture over this time period. Methods: This paper presents new findings from the complementary health approaches section of the 2012 National Health Interview Survey (n=33,373 respondents). In particular, data on the use of acupuncture and user characteristics were compared against data collected from an earlier survey in 2002. Statistical analyses included weighted distribution, logistical regression and Pearson's X2 tests. Results: The profile of the most common acupuncture users comprised the following sociodemographics age 41-65years (47.4%); female gender (69.6%); and non-Hispanic (85.3%) and/or white (78.1%) ethnicity. Respondents also tended to be US citizens (92.1%) with some college education (57.1%) and in very good to excellent health (60.8%). The proportion of respondents using acupuncture for treatment of a specific health problem, as opposed to promotion of general wellness, was 84.7% in 2002 and 55.3% in 2012. Conclusions: Our data suggest a growing development of acupuncture in the USA. We anticipate that the findings of our analysis of the changes in acupuncture use over the 10-year period from 2002 to 2012 will provide information for users, acupuncturists, researchers and the general public to help better understand the status of acupuncture and reasons for its usage, and to anticipate future trends for acupuncture use in the USA.

An ecosystem is an environment that contains interacting organisms. An entrepreneurial ecosystem (EE) consists of people affiliated with organizations interacting within a physical environment with the goal of promoting entrepreneurship. This case study describes the EE in Durham, North Carolina – the people and organizations primarily located downtown who embrace this mission. I interviewed the individuals acknowledged in Appendix A and drew from reports, blog posts, newspaper articles and data sources to write the case study. I frame this study in two ways. First, while important in their own right I do not examine social ventures or local ventures – startups that serve and entirely depend upon the local market. Instead, I focus on successful startups that can grow to have major impacts on the city’s economic base. Since these new firms tap regional, national and/or global markets, they are not constrained by the size of the local market. These companies exemplify growth entrepreneurship. Second, Durham is part of the growing Research Triangle region. The region’s EE developed before the EE in Durham and continues to support it in various ways. The people and organizations located in downtown Durham help budding and established entrepreneurs thrive. In an era of internet-based social media and virtual communication, I underscore the importance of having a vibrant downtown, and I consider how its density, compactness, connectivity and walkable design have enhanced growth entrepreneurship.