An Evaluation of Persons per Household (PPH) Estimates Generated by the American Community Survey: A Demographic Perspective

The American Community Survey (ACS) is a U.S. Census Bureau product designed to provide accurate and timely demographic and economic indicators on an annual basis for both large and small geographic areas within the United States. Operational plans call for ACS to serve not only as a substitute for the decennial census long-form, but as a means of providing annual data at the national, state, county, and subcounty levels. In addition to being highly ambitious, this approach represents a major change in how data are collected and interpreted. Two of the major questions facing the ACS are its functionality and usability. This paper explores the latter of these two questions by examining “persons per household (PPH),” a variable of high interest to demographers and others preparing regular post-censal population estimates. The data used in this exploration are taken from 18 of the counties that formed the set of 1999 ACS test sites. The examination proceeds by first comparing 1-year ACS PPH estimates to Census 2010 PPH values along with extrapolated estimates generated using a geometric model based on PPH change between the 1990 and 2000 census counts. Both sets of estimates are then compared to annual 2001–2009 PPH interpolated estimates generated by a geometric model based on PPH from the 2000 census to the 2010 census. The ACS PPH estimates represent what could be called the “statistical perspective” because variations in the estimates of specific variables over time and space are viewed largely by statisticians with an eye toward sample error. The model-based PPH estimates represent a “demographic perspective” because PPH estimates are largely viewed by demographers as varying systematically and changing relatively slowly over time, an orientation stemming from theory and empirical evidence that PPH estimates respond to demographic and related determinants. The comparisons suggest that the ACS PPH estimates exhibit too much “noisy” variation for a given area over time to be usable by demographers and others preparing post-censal population estimates. These findings should be confirmed through further analysis and suggestions are provided for the directions this research could take. We conclude by noting that the statistical and demographic perspectives are not incompatible and that one of the aims of our paper is to encourage the U.S. Census Bureau to consider ways to improve the usability of the 1-year ACS PPH estimates.     

Comparison of Census 2000 and American Community Survey 1999–2001 Estimates: San Francisco and Tulare Counties, California

Data from the United States 2000 decennial census long form sample is compared to the U.S. Census Bureau’s fledgling American Community Survey (ACS) that was designed to replace the census long form in 2010. This article concentrates on two California counties, San Francisco and Tulare, which were part of the demonstration phase of the ACS. These counties are described and an overall comparison of the demographic, social, economic, and housing variables is presented. The project data and measures of census and survey quality such as self-response rates and nonresponse rates are displayed and discussed. Differences in the census and survey results are noted in the context of statistically significant and meaningful differences. Finally, strategies for analyzing and using ACS data are suggested.     

Moving from a decennial census to a continuous measurement survey: factors affecting nonresponse at the neighborhood level

The Census Bureau is testing a continuous measurement program, known as the American Community Survey (ACS), which will provide census “long form” data annually, though with slightly higher levels of sampling variability. This paper focuses on the 1999–2001 ACS in the Bronx, 1 of 31 ACS test sites. It examines whether the quality of ACS data in the Bronx varies across neighborhoods, focusing specifically on how neighborhood sociodemographic factors influence nonresponse, as measured by mail return and allocation rates. It also examines whether these neighborhood factors have a differential impact on nonresponse in the ACS and the 2000 decennial census, and discusses reasons why this may be so.The ACS mail return rates are not only lower than those of the census, but are highly sensitive to race and socioeconomic distress. Despite this initial disadvantage, the ACS has lower levels of allocation on key variables, relative to the 2000 Census. Moreover, the effect of neighborhood socioeconomic distress on allocation rates in the ACS was minimal, compared to its effect on census allocation. We find that the overall quality of ACS data in the Bronx is superior to that of the decennial census. Our analysis of Bronx data suggests that the proposed elimination of the decennial long form and its replacement with the ACS is a reasonable tradeoff for users of small area data.     

The American Community Survey: general commentary on the findings from external evaluations

As part of the Census Bureau’s effort to prove the operational feasibility of the American Community Survey (ACS), the Bureau contracted with local experts to conduct comparative analyses of the 1999–2001 ACS estimates with the 2000 Census data for various test counties. One of the goals of the ACS is to replace the decennial census long form. The resulting research papers analyzed various quality measures (response rates, allocation rates, and so on), conceptual differences in the two instruments, and statistical reliability in an effort to add to our assessment of the ACS as an adequate replacement instrument for collecting long form data. This paper discusses the results of these four research efforts and presents conclusions and recommendations for further Census Bureau action and research. The quality of traditional long form data, the importance of accurate population estimates and an accurate Master Address File (MAF), and continued research on the quality of small area data are discussed.     

Residential expansion as a continental threat to U.S. coastal ecosystems

Spatially extensive analysis of satellite, climate, and census data reveals human-environment interactions of regional or continental concern in the United States. A grid-based principal components analysis of Bureau of Census variables revealed two independent demographic phenomena, α-settlement reflecting traditional human settlement patterns and β-settlement describing relative population growth correlated with recent construction in non-agricultural areas, notably in coastal, desert, and “recreational” counties and around expanding metropolitan areas. Regression tree analysis showed that β-settlement was differentially associated with five distinct combinations of seasonality, summer heat or cool, intensity of agriculture, and extent of “barren” land. Beta-settlement was greatest in coastal and desert areas, and coincided with national concentrations of threatened and endangered species.     

An Application of Bayesian Methods to Small Area Poverty Rate Estimates

Efforts to estimate various sociodemographic variables in small geographic areas are proving difficult with the replacement of the Census long-form with the American Community Survey (ACS). Researchers interested in subnational demographic processes have previously relied on Census 2000 long-form data products in order to answer research questions. ACS data products promise to begin providing up-to-date profiles of the nation’s population and economy; however, unit- and item-level nonresponse in the ACS have left researchers with gaps in subnational coverage resulting in unstable and unreliable estimates for basic demographic measures. Borrowing information from neighboring areas and across time with a spatiotemporal smoothing process based on Bayesian statistical methods, it is possible to generate more stable and accurate estimates of rates for geographic areas not represented in the ACS. This research evaluates this spatiotemporal smoothing process in its ability to derive estimates of poverty rates at the county level for the contiguous United States. These estimates are then compared to more traditional estimates produced by the US Census Bureau, and comparisons between the two methods of estimation are carried out to evaluate the practical application of this smoothing method. Our findings suggest that by using available data from the ACS only, we are able to recreate temporal and spatial patterns of poverty in US counties even in years where data are sparse. Results show that the Bayesian methodology strongly agrees with the estimates produced by the SAIPE program, even in years with little data. This methodology can be expanded to other demographic and socioeconomic data with ease.     

Aboriginals as unwilling immigrants: Contact, assimilation and labour market outcomes

Like immigrants, aboriginal populations' economic success may be enhanced by the acquisition of skills and traits appropriate to the “majority” culture in which they reside. Using 1991 Canadian Census data, we show that Aboriginal labour market success is greater for Aboriginals whose ancestors intermarried with non-Aboriginals, for those who live off Indian reserves, and for those who live outside the Yukon and Northwest Territories. While these three “facts” could also be explained by a combination of other processes, such as discrimination, physical remoteness, and selection, only the skill/trait acquisition, or “assimilation” hypothesis is consistent with all three. Received: 04 August 1998/Accepted: 12 October 2000     

Demographic comparison between self-response and personal visit interview in Census 2000

During Census 2000, over 95 percent of the housing units were in mailback areas. In these areas either the United States Postal Service or Census Bureau staff delivered the census questionnaire. In urban and suburban areas of the country, the United States Postal Service delivered the census questionnaires between March 13 and 15 of 2000. The addresses in these areas are predominately city style; house number and street name. In more rural areas of the country with predominately non-city style addresses, Census Bureau staff delivered the questionnaire during March of 2000. Respondents completed their census questionnaires and returned them through the mail. Returns from these housing units are classified as self-response. Respondents which did not complete and return their census questionnaire by April 18, 2000 were interviewed during the nonresponse followup operation (personal visit interview). This paper will examine the demographic characteristics of persons enumerated on the mail return questionnaire (self-response) and the persons enumerated during the nonresponse followup operation (personal visit interview).     

Selective Out-Migration from Florida

I test if selective out-migration of unhealthy seniors explains why disability rates are so much lower for Florida, as compared to the national average. This particular area of research is timely given the significant demographic changes relating to aging. Moreover, this study contributes to the body of literature examining migration with respect to disability and widowhood. Using State Federal Information Processing Standard (FIPS) and Public Use Microdata Areas (PUMA), I create national maps showing disability rates for the following age-groups: 50–59, 60–69, and 70+. After creating maps in ARCGIS and conducting univariate and clustering analysis on mobility disability and personal care limitation, I employ multinomial logit (MNL) analysis to test if individuals with disability are more likely to out-migrate from Florida. The regression analyses lend support to the relaxed Litwak and Longino (The Gerontologist, 27(3): 266–272, 1987) second-move hypothesis, which claims individuals with progressively worse health are more likely to undertake another move to be closer to family and friends. I state “relaxed” because the data does not allow one to determine the reason for migration—only that migration occurred during the past year. This research informs policy-makers to recognize that elderly in better health may migrate to places such as Arizona and Florida due to amenity-seeking behavior, but unhealthy elderly are more likely to leave these states due to assistance-seeking behavior. This out-migration can place excess demand on health services for the incoming regions, which requires state and local government to ensure resources are in place. Also noteworthy, my results are less likely to be flawed by erroneous age and sex data in the public use microdata samples (IPUMS) since I stack the 2006 and 2007 American Community Survey (ACS). A recent working studies by Alexander et al. (Inaccurate age and sex data in the Census PUMS files: Evidence and implications. Munich: CESifo, 2010) shows inaccuracies in the IPUMS for the 1 and 5% 2000 Census, the 2003–2006 ACS, the 2005–2007 3-year ACS, and the 2004–2009 current population survey (CPS) files.     

American Community Survey overview and the role of external evaluations

In 2010 the U.S. Census Bureau will achieve its goal of eliminating the long form sample from the decennial census and will produce its first set of five-year data products from the full sample American Community Survey (ACS). This paper provides an overview of the call for change that prompted the Census Bureau to pursue the development of a new approach to collecting socioeconomic and housing data. The paper details the evolution of the ACS from its earliest origins to its current design and describes that design in detail. The current design has benefited from external debate and consultation. Work such as that described later in this journal exemplifies the key role that external users and advisors have played, and will continue to play, in the evolution of the ACS. Over the past 10 years, the Census Bureau has undertaken research and testing to demonstrate operational feasibility and to assess survey quality. Research has also compared ACS and Census 2000 data. ACS staff are involved in survey improvement efforts and continue to confront survey challenges. In the next few years the ACS will give priority to developing user tools to aid all users in the correct interpretation of multi-year estimates. The ultimate validation of the ACS is, however, in the hands of users. Continued input from the people who are responsible for administering and evaluating programs, identifying local needs, and planning for the future will allow the ACS to grow in value and utility.     

Identifying race and ethnicity in the 1979 National Longitudinal Survey of Youth

The 1979 National Longitudinal Survey of Youth is among the few surveys to provide multiple reports on respondents’ race and ethnicity. Respondents were initially classified as Hispanic, black, or “other” on the basis of data collected during 1978 screener interviews. Respondents subsequently self-reported their “origin or descent” in 1979, and their race and Hispanic origin in 2002; the latter questions conform to the federal standards adopted in 1997 and used in the 2000 census. We use these data to (a) assess the size and nature of the multiracial population, (b) measure the degree of consistency among these alternative race-related variables, and (c) devise a number of alternative race/ethnicity taxonomies and determine which does the best job of explaining variation in log-wages. A key finding is that the explanatory power of race and ethnicity variables improves considerably when we cross-classify respondents by race and Hispanic origin. Little information is lost when multiracial respondents are assigned to one of their reported race categories because they make up only 1.3% of the sample.

Region of Birth and Disability Among Recent U.S. Immigrants: Evidence from the 2000 Census

This study aimed to test the “healthy immigrant” hypothesis and assess health heterogeneity among newly arrived working-age immigrants (18–64 years) from various regions of origin. Using the 5% sample of the 2000 U.S. Census (PUMS), we found that, compared with their native-born counterparts, immigrants from all regions of the world were less likely to report mental disability and physical disability. Immigrants from selected regions of origin were, however, more likely to report work disability. Significant heterogeneity in disabilities exists among immigrants: Those from Eastern Europe and Southeast Asia reported the highest risk of mental and physical disability, and those from East Asia reported the lowest risk of physical disability. Furthermore, Mexican immigrants reported the lowest risk of mental disability, and Canadian immigrants reported the lowest risk of work disability. Socioeconomic status and English proficiency partially explained these differences. The health advantage of immigrants decreased with longer U.S. residence.     

Integrating Census Data to Support a Motion for Change of Venue

This applied demography case study illustrates the practical application of demographic concepts and methods to an issue facing the court. We show how census data can be used to support a legal motion for a change of venue. “Change of venue,” the legal term for moving a trial to a new location, usually is sought to avoid prejudice against one of the parties to a lawsuit. The case study will interest demographic practitioners, and it can be used as an instructional case in teaching applied demography: students can replicate it using data for any particular pair of populous metropolitan communities. By doing so, students would gain proficiency working with Public Use Microdata Sample (PUMS) household records—and the person records within household records—to identify and categorize family and nonfamily relationships among household members, and practical experience translating legal issues into questions that can be answered empirically using American Community Survey (ACS) data.     

Quality of Community Life Among Rural Residents: An Integrated Model

The purpose of this research was to explore the relationships among housing satisfaction, community attachment and community satisfaction and the complex mechanisms involved in predicting community satisfaction among residents in rural communities. The role of housing satisfaction and community attachment in predicting community satisfaction was of particular interest. A structural equation model of community satisfaction was tested with mail survey data drawn from a randomly selected rural sample of 974 households. The results of this study confirmed the influences and mediating role of community attachment and housing satisfaction in predicting community satisfaction. “Spillover” effects from “lower levels of life concerns” (e.g., satisfaction with local services, assessment of current housing conditions) in perceived community satisfaction were found that support previous research (Sirgy and Cornwell in Social Indicators Research 59:79–114, 2002).     

Research Note: What Counts as a House? Comparing 2010 Census Counts and Administrative Records

As a tool for fulfilling data needs for small area (subcounty) analysis, demographers are increasingly turning to administrative records such as building permits and tax assessor records as a source of data for use in producing small area demographic estimates. While Census counts are considered to be the “gold standard,” administrative records provide a fine level of spatial detail and a valuable source of information for intercensal years. However, there is uncertainty about the quality of administrative records data for use in estimation. This analysis builds upon earlier research by comparing administrative records-based housing unit estimates developed during the 2000s decade with housing counts from the 2010 Census in San Diego County. Results show that both administrative records and Census counts have strengths and weaknesses that should be understood by the data user.     

Social Structure and Child Poverty

Child poverty, as a critical indicator of the QOL, is intricately related to the social structure of the community. This hypothesis is explored for the 159 counties of Georgia for the year 2000. The influence of demographic, economic, family and health factors upon child poverty are explored through models of total, black and white child poverty. Factor analyses of factors uncovered by the models identify the social-structural features of counties in relation to child poverty. Counties considered “Deprived/rural” harbor child poverty, while counties described as “Business/money” and “Progressive/urban” bear a negative relationship to child poverty. Positively associated with child poverty are residential stability, unemployment, low educational achievement, youth and age dependency, single-parent female household heads with children, grandparent child care, and health disability of child, elders and of working-age persons. Structural factors militating against child poverty are persons with greater education, higher population density, out migration, larger married population, higher retail sales, larger middle class families, higher weekly wages, and other structural features of the county.     

Cohort Succession in the US Housing Market: New Houses, the Baby Boom, and Income Stratification

Federal housing policy in the US across the postwar period supported the construction of new houses more than public provision or renovation of older structures as a means of ensuring a sufficient supply of quality dwellings. Understanding trends in new housing in particular is thus crucial to understanding the housing regime. Following Myers (Housing demography: Linking demographic structure and housing markets. University of Wisconsin Press, 1990; Housing Studies, 14, 473–490,1999), this paper conceptualizes historical change in the housing stock within a demographic framework as the movement of cohorts of households through cohorts of housing stock. Recent evidence suggests that a new cohort of houses arose in the 1980s and 1990s (larger with more amenities than past vintages), and that buyers of those new houses were increasingly affluent. In this paper, I link the succession to a new cohort of houses to household cohort succession and examine the increasing affluence of new house buyers by age and cohort, focusing especially on the entry of the Baby Boom generation exactly when the new cohort of houses arrived. I use US Census microdata for 1960–2000 to develop a cohort longitudinal dataset, and analyze historical change in stratification in new house ownership. I find significant shifts between cohorts in income inequality among new house buyers, with implications for the capacity of the housing regime to meet the future needs of an increasingly diverse population.

Housing Adjustment Among Immigrants in Israel: Application of Complementary Non-Metric and Metric Techniques

This study applies two different complementary statistical techniques to examine the structure and determinants of homeownership and consumption of household goods among immigrants in Israel. Findings from partial-order analysis (POSAC) reveal significant differences between immigrant groups by type, rather than level, of household characteristics. Suppliers of entertainment (television) and of information-communication (computer) are the items that most strongly distinguish between immigrants. The joint direction of the partially ordered space corresponds with home and car ownership. Immigrant groups are dispersed in different parts of the household typology; with increased duration of residence in Israel immigrants move, albeit in varied rhythms, toward improved housing conditions. A complementary logistic regression analysis, which controls for socio-demographic variation and detailed tenure in Israel, show a likelihood of convergence of immigrants from all origin countries with the core native-born group in owning a home. For other household goods, the findings largely coincide with the typology derived from POSAC. The findings are discussed in reference to three conceptual expectations of “cultural norms”, “adjustment”, and “structural-environmental considerations”.

Diversity and change in Cambodian households, 1998–2006

Extant ethnographic studies suggest that the nuclear family has been the predominant living arrangement in Cambodia, and the country’s rapid socioeconomic transformation since the early 1990s may have accentuated that dominance. To examine these claims, we analyse here household structure in Cambodia between 1998 and 2006, based on data from the 1998 Census, two nationally-representative surveys (2000 and 2005), and a continuing demographic surveillance system (from 2000 on). Our analysis confirms the large prevalence of nuclear families, but not an unequivocal trend toward their increasing prevalence. First, nuclear families are less prevalent in urban than in rural areas, and nationwide, they appear to have receded slightly between 2000 and 2005. We find that increases in the prevalence of extended households correspond to periods of faster economic growth, and interpret these contrasted trends as signs of tensions during this transitional period in Cambodia. While the nuclear family may still be the cultural norm, a high degree of pragmatism is also evident in the acceptance of other living arrangements, albeit temporary, as required by economic opportunities and housing shortage in urban areas.     

The American Community Survey in counties with “seasonal” populations

The U.S. Census Bureau designed the American Community Survey (ACS) to provide annual estimates of social and economic characteristics for states, counties, municipalities, census tracts, and block groups. Because of its April 1 reference date, in northern nonmetropolitan counties with substantial seasonal population fluctuations the decennial census provides a statistical representation of the demographic and social characteristics of the population at a time when the population is close to its annual minimum. The year-round monthly ACS sample survey has the potential to provide local communities with an unprecedented understanding of the average population characteristics over the course of a year. In the future, the ACS even has the potential for providing social and economic characteristics of the population by season. This paper examines four ACS pilot data collection counties, Oneida and Vilas Counties in northern Wisconsin, and Lake and Flathead Counties in northwest Montana. We hypothesize that the ACS will reflect a resident population over the course of the year that is different from the traditional April 1 decennial census population. While the ACS holds much promise, our research uncovered some sampling problems that are not yet fully resolved. In addition, our analysis was not able to examine ACS estimates for minor civil divisions (MCDs), which are functioning governmental units in many states. The fact that these MCDs often have very small populations, together with the fact that estimated standard errors at the much larger census tract level in these counties are disconcertingly large, raises (currently unanswerable) questions concerning the eventual statistical quality of ACS estimates for small MCDs. Consequently, the adequacy of the ACS as a replacement for the census long form may depend on the ability of the Census Bureau to effectively address the concerns presented in this analysis.