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The US fertility transition in the nineteenth century is unusual. Not only did it start from a very high fertility level and very early in the nation’s development, but it also took place long before the nation’s mortality transition, industrialization, and urbanization. This paper assembles new county-level, household-level, and individual-level data, including new complete-count IPUMS microdata databases of the 1830–1880 censuses, to evaluate different theories for the nineteenth-century American fertility transition. We construct cross-sectional models of net fertility for currently-married white couples in census years 1830–1880 and test the results with a subset of couples linked between the 1850–1860, 1860–1870, and 1870–1880 censuses. We find evidence of marital fertility control consistent with hypotheses as early as 1830. The results indicate support for several different but complementary theories of the early US fertility decline, including the land availability, conventional structuralist, ideational, child demand/quality-quantity tradeoff, and life cycle savings theories.

Population censuses collect socio-demographic and economic information regularly and in an institutionalized manner. The decision of what topics to include in their questionnaires reflects political priorities, but also it is a materialization of symbolic power (Bourdieu, 1991; Loveman, 2005). Gender practices – including budgeting, policy-making, implementation and monitoring of programs – depend significantly on census results. Understanding the institutional dynamics of public statistics sheds light on structural obstacles to exercise gender rights. To study this phenomenon, the authors look at the last century of the Brazilian and Ecuadorian censuses. The research provides a better understanding about the process of including or rejecting questions related to gender, specifically the arguments used in the process of selecting questions. Brazil and Ecuador were chosen because of the different profiles of each of their statistical institutions. The Brazilian institute, IBGE, is a larger, stable and semi-autonomous statistical office; Brazil has conducted population censuses since the nineteenth century. The Ecuadorian institute, INEC, is a smaller and more politically dependent statistical office; it has conducted population censuses since 1950.

Using archival analysis within the questionnaires and interviewing key demographers, activists and statisticians in both countries, the authors argue that the presence or absence of gender questions in the Brazilian and Ecuadorian censuses is historically and politically contingent. In contrast to the dominant narrative that suggests that changes in the vision of public statistics is correlated with the modernization of the state, it appears that the statistical visibility of gender issues in each society does not follow a linear path.

In this chapter, we examine the notion of ethnic diversity with a view to explore Europe-wide differences in defining and managing ethnic diversity and equality. When compared to gender diversity, ethnic diversity does not enjoy similar level of success in Europe. Our analyses show that this is due to the fact that ethnicity and ethnic categories are national. In fact, there are different levels of discussion on ethnicity, where the debate is limited due to historical, cultural and legal differences.

Micro hospitals are a new form of for-profit health-care facility with rapid expansion in some parts of the country. They continue to grow in Texas without in-depth public understanding or explicit policy guidance on their role in the health-care system. Our project aims to define socioeconomic and demographic characteristics of areas served by micro and regular hospitals, and by doing so help assess micro hospitals' impact in expanding health-care access for disadvantaged populations in Texas.

We (1) estimated hospital service areas (catchment areas) with a spatial model based on advanced Geographic Information System (GIS) methods using a proprietary ESRI traffic network; (2) assigned population socioeconomic measures to the catchment areas from the 2014–2018 American Community Survey 5-Year Estimates, weighted with an empirically tested Gaussian distribution; (3) used two-tailed t-tests to compare means of population characteristics between micro and regular hospital catchment areas; and (4) conducted logistic regressions to examine relationships between selected population variables and the associated odds of micro hospital presence.

We found micro hospitals in Texas tend to serve a population less stressed in health-care access compared to those who are more in need as measured by various dimensions of disadvantages.

Our analysis takes a cross sectional look at the population characteristics of micro hospital service areas. Even though the initial geographic choices of micro hospitals may not reflect the long-term population changes in specific neighborhoods, our analysis can provide policy makers a tool to examine health-care access for disadvantaged populations at given point in time. As the population socioeconomic characteristics have long been associated with health-care inequality, we hope our analysis will help foster structural policy considerations that balance growing health-care delivery innovations and their social accountability.

We used GIS based spatial modeling to dynamically capture the potential patient basis by travel time calculated with a street network dataset, rather than using the traditional static census tract to define hospital service areas. By integrating both spatial and nonspatial dimensions of healthcare access, we demonstrated that the policy considerations on the implications of equal opportunity for health-care access need to take into account the social realities and lived experiences of those experiencing the most vulnerability in our society, rather than a conceptual “equality” existing in the spatial and market abstraction.

We document long-run trends in interstate migration rates, using individual-level data from the U.S. Census for the period 1850–1990. Two measures of migration are calculated. The first considers an individual to have moved if she is residing in a state different from her state of birth. The second considers a family to have moved if it is residing in a state different from the state of birth of one of its young children, allowing us to estimate the timing of moves more precisely. Overall migration propensities have followed a U-shaped trend since 1850, falling until around 1900 and then rising until around 1970. We examine variation in the propensity to make an interstate move by age, sex, race, nativity, region of origin, family structure, and education. Counterfactuals based on probit estimates of the propensity to migrate suggest that the rise in migration of families since 1900 could be explained by increased educational attainment, although education may be serving as a proxy for unmeasured covariates. The decline of interstate migration in the late nineteenth century remains to be explained.

The pattern of racial segregation in U.S. elementary and secondary schools has changed significantly over the last 25 years. This chapter examines the relationship between the racial composition of schools and the choices white parents make concerning the schools their children attend. Restricted access files at the Bureau of the Census allow us to identify each household's Census block of residence and, in turn, suburban public school districts and urban public school attendance areas. We find that the racial composition of schools and neighborhoods are very important in the school and location decisions of white families.

Data fusion and the combination of multiple data sources have been part of travel survey processes for some time. In the current context, where technologies and information systems spread and become more and more diverse, the transportation community is getting more and more interested in the potential of data fusion processes to help gather more complete datasets and help give additional utility to available data sources. Research is looking for ways to enhance the available information by using both various data collection methods and data from various sources, surveys or observation systems. Survey response rates are decreasing over the world, and combining survey modes appears to be an interesting way to address this problem. Letting interviewees choose their survey mode allows increasing response rates, but survey mode could impact the data collected. This paper first discusses issues rising when combining survey modes within the same survey and presents a method to merge the data coming from different survey modes, in order to consolidate the database. Then, it defines and describes the data fusion process and discusses how it can be relevant for transportation analysis and modelling purposes. Benefiting from the availability of various datasets from the Greater Montréal Area and the Greater Lyon Area, some applications of data fusion are constructed and/or reproduced to illustrate and test some of the methods described in the literature.