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 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.     

How surveys are changing at the U.S. Bureau of the Census

"This article describes the survey activities of the U.S. Census Bureau and recent efforts by the bureau to move toward a more fully automated environment....[It] focuses on four areas in which the Census Bureau is changing its approach to surveys: (1) redesigning the questionnaire for the Current Population Survey to better reflect current labor force conditions; (2) redesigning the same questionnaire to gain advantages from computer-assisted interviewing; (3) redesigning the samples for household surveys to be used during the next decade, a task undertaken after every decennial census; and (4) progress in changing to a computer-assisted survey information collection (CASIC) system and developing a data management network for all Census Bureau surveys."     

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.     

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.     

An evaluation of the American Community Survey: results from the Oregon test site

The American Community Survey (ACS) is a 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 for Census 2010 call for ACS to replace the decennial census long form (Census LF), pending the results of evaluation studies. This plan represents a major change in that variables that traditionally have been collected on a “snapshot” basis once every 10 years would be collected on a “rolling” annual basis. Using a loss function analysis and other tools, this paper reports preliminary findings from a comparison of ACS and Census 2000 results in Multnomah County, Oregon, one of five national “local expert” test sites set up to compare ACS data collected at the time of Census 2000. The preliminary findings suggest that there are notable differences between some of the corresponding variables found in the ACS and Census LF that require more detailed examination. For example, the loss function analysis reveals notable differences for race and disability variables. In other comparisons of corresponding variables between ACS and Census 2000, differences are found within each of the four major areas of interest: (1) demographic characteristics, (2) social characteristics, (3) economic characteristics, and (4) housing characteristics, with housing characteristics showing the least similarity overall. These results also suggest that more detailed examinations are needed to understand differences between corresponding variables collected by ACS and the Census LF.     

Inferring Directional Migration Propensities from the Migration Propensities of Infants in the United States

Beginning with the 2010 decennial census, the U.S. Census Bureau plans to drop its long-form questionnaire and to replace it with the American Community Survey (ACS). The resulting absence of the larger sample provided by the census count will complicate the measurement and analysis of internal migration flows. In addition, the strategy of averaging accumulated samples over time will mix changing migration patterns. The migration question will refer to a one-year time interval instead of the five-year interval used in the censuses between 1960 and 2000, complicating historical comparisons and the production of multiregional projections based on five-year age groups. Consequently, students of territorial mobility increasingly will find it necessary to complement or augment possibly inadequate data collected on migration with estimates obtained by means of “indirect estimation.” A method is presented that allows one to infer age-specific directional migration propensities at the regional level from birthplace-specific infant population data, which approximates infant migration propensities, and from these infers the migration propensities of all other ages. The method is applied to at the nine-division spatial scale.     

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.     

The equivalence of united states census data for persons of Russian stock or descent with American Jews: An evaluation

While the U.S. Bureau of the Census has had a long-standing policy of abstaining from enumerating the religious beliefs or backgrounds of the American people, at least two-thirds of the Jewish population of the United States has been enumerated in decennial censuses and sample surveys in the guise of persons of Russian stock or origin. This has come about through the migration policy of the old Russian Empire and the statistical categories utilized by American immigration authorities and by the U. S. Bureau of the Census for immigrants and their children. Comparisons between the returns from an ethnic survey and a survey on the religious composition demonstrate the close congruence between persons of Russian stock or descent and American Jews on the national level.     

The business of demographics

The emergence of "demographics" in the past 15 years is a vital tool for American business research and planning. Tracing demographic trends became important for businesses when traditional consumer markets splintered with the enormous changes since the 1960s in US population growth, age structure, geographic distribution, income, education, living arrangements, and life-styles. The mass of reliable, small-area demographic data needed for market estimates and projections became available with the electronic census--public release of Census Bureau census and survey data on computer tape, beginning with the 1970 census. Census Bureau tapes as well as printed reports and microfiche are now widely accessible at low cost through summary tape processing centers designated by the bureau and its 12 regional offices and State Data Center Program. Data accessibility, plummeting computer costs, and businessess' unfamiliarity with demographics spawned the private data industry. By 1984, 70 private companies were offering demographic services to business clients--customized information repackaged from public data or drawn from proprietary data bases created from such data. Critics protest the for-profit use of public data by companies able to afford expensive mainframe computer technology. Business people defend their rights to public data as taxpaying ceitzens, but they must ensure that the data are indeed used for the public good. They must also question the quality of demographic data generated by private companies. Business' demographic expertise will improve when business schools offer training in demography, as few now do, though 40 of 88 graduate-level demographic programs now include business-oriented courses. Lower cost, easier access to business demographics is growing as more census data become available on microcomputer diskettes and through on-line linkages with large data bases--from private data companies and the Census Bureau itself. A directory of private and public demographic resources is appended, including forecasting, consulting and research services available.     

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.     

Some aspects of the use of birth expectations data from sample surveys for population projections

The value of national sample survey data relating to birth expectations for projecting births is reassessed in the light of data limitations pointed out by Ryder and Westoff among others and of the methods of projection used by the United States Bureau of the Census. The annual level of fertility under the cohort-fertility projection method depends on the assumptions regarding completed fertility, about which the available survey data are fairly informative, and on the assumptions regarding the timing of births, about which the survey data tell us very little. Test calculations suggest that Ryder and Westoff have overstated the significance of timing relative to completed family size for the level of future births. We believe that the fall in the annual total fertility rate in the first half of the sixties is to be explained only in part by a general delay in childbearing; a moderate to substantial decrease in completed family size has also occurred. Analysis of the latest set of fertility projections of the Census Bureau also suggests that the assumptions about completed fertility are a much more important determinant of the level of future births than timing, both in the short and long term. Although the available expectations data cannot help in predicting short-term annual changes in fertility, they appear useful for making long-term projections of annual fertility. Expansion of the size, frequency, and content of the sample surveys and incorporation of parity and birth interval into the projection method may improve projections.     

Plans for the 1970 census of population and housing

The Nineteenth Decennial Census of the United States, covering both population and housing, will be conducted as of April 1, 1970. Planning, testing, and preparatory activities have been underway since early in the decade. Extensive discussions with users of census data led to relatively minor changes in subject content as compared to 1960, but a major increase in the amount of statistics to be tabulated, especially for small geographic areas. For about 60 to 65 percent of the population, the information will be collected through a new mail-out/mail-back system. The rest of the country will be covered by house-to-house canvass. Special efforts to alleviate the serious problem of underenumeration are being undertaken, particularly in the hard-to-enumerate portions of the big cities. The geographic program includes an “address coding guide” through which location identification in most urban areas can be made to specific side of block; this will permit tabulations for new types of small areas. Processing of the data will be performed with the Census Bureau’s Fosdic equipment and advanced computers. Dissemination of the census results will be in the traditional type of printed reports but also, in substantially greater subject and area detail, through magnetic tape, special printouts, etc. To help users exploit the potentialities of the latter material, the Bureau has instituted a “data access” informational program. As in previous censuses, there will be a number of studies to evaluate the 1970 procedures and results.     

The Quality of Male Fertility Data in Major U.S. Surveys

Researchers continue to question fathers’ willingness to report their biological children in surveys and the ability of surveys to adequately represent fathers. To address these concerns, this study evaluates the quality of men’s fertility data in the 1979 and 1997 cohorts of the National Longitudinal Survey of Youth (NLSY79 and NLSY97) and in the 2002 National Survey of Family Growth (NSFG). Comparing fertility rates in each survey with population rates based on data from Vital Statistics and the U.S. Census Bureau, we document how the incomplete reporting of births in different surveys varies according to men’s characteristics, including their age, race, marital status, and birth cohort. In addition, we use Monte Carlo simulations based on the NSFG data to demonstrate how birth underreporting biases associations between early parenthood and its antecedents. We find that in the NSFG, roughly four out of five early births were reported; but in the NLSY79 and NLSY97, almost nine-tenths of early births were reported. In all three surveys, incomplete reporting was especially pronounced for nonmarital births. Our results suggest that the quality of male fertility data is strongly linked to survey design and that it has implications for models of early male fertility.     

Census 2000 Partnership and Marketing Program Evaluation

To evaluate the Census 2000 integrated marketing strategy, the Census Bureau contracted with the National Opinion Research Center (NORC) to conduct a national representative sample survey. In addition to having a nationalrepresentative sample, NORC oversampled populations whichare historically undercounted in the census. Using threecross-sectional mixed mode surveys, NORC obtained baseline,pre- and post-census measures of awareness, attitudes, knowledge,and mailback intentions over the period of the census. This paperreports on some of the preliminary results from the NORC reportof the Partnership and Marketing Program (PMP) evaluation.     

Misclassifying New York’s Hidden Units as Vacant in 2010: Lessons Gleaned for the 2020 Census

The Local Update of Census Addresses (LUCA) program allowed local governments to include hard-to-find units in the Census Bureau’s Master Address File (MAF), which is the cornerstone of the mailout/mailback decennial census. These improvements have allowed the Census Bureau to penetrate the more marginal parts of the housing stock, where units are often not formally labeled, and where their very existence can be difficult to determine. In New York City, where address updating included two rounds of LUCA, the Census Bureau acknowledged an increase of 170,000 housing units between 2000 and 2010. However, there was a dramatic growth in vacant units, equivalent to almost one-half of the total increase in housing units. The increase in vacant units was disproportionately concentrated in 2 of the 18 local census offices in New York City. The paper uses local administrative data on new construction, property foreclosures, and property values; data from the United States Postal Service; as well as survey data from the New York City Housing and Vacancy Survey and the American Community Survey to show why this concentrated increase in vacant units is untenable. From the standpoint of the enumeration, units added in LUCA would challenge the best enumerator, but these hurdles were largely overcome, but for the two local census offices. The paper goes on to discuss how the Census Bureau can adopt measures in 2020 to ensure that housing units and their occupancy status are accurately enumerated in New York and across the nation.     

Quality and the 2010 Census

The U.S. Census Bureau has a long tradition of evaluating the results of its censuses. This paper presents evaluation results from the 2010 Census, comparing them to earlier results. The paper discusses net coverage at the national and state level, as well as by age, sex, race, and ethnic group. It discusses components of error, including estimated number missed and counted in error. It also presents data on whole-person and item imputation.     

Some sources of error and their effect on census statistics

Often the reliability of survey data is examined only in relationship to sampling variances, excluding many other potential sources of error. If the sampling variance dominates the mean-square error, then few mistakes result by considering sampling variance only; however, if sampling variance is only a small part of the mean-square error, serious mistakes in inference could be made. The Bureau of the Census has developed a model describing the joint effect of sampling and nonsampling errors on census statistics. This article shows how a study of the components of error may lead to methods of improving the accuracy and reliability of survey data.     

Metropolitan Influence and Land Use Competition in Potential Biomass Crop Production: A Spatial Demographic Analysis

Biomass is one alternative energy source that is currently being investigated to combat the growing U.S. dependence on foreign oil. In this study, we explore where traditional farming practices and metropolitan influence will compete for land use against farmland located in optimal biomass crop production zones. To date, no consideration of the impact of urbanization and human development has been taken into account. Here we make a take a seminal approach to examining this relationship given previous analyses. We use overlapping LISA statistics to identify significant clusters of counties facing competition for land use. To measure competition for land use in counties located within biomass zones circa 2000, we use population growth and housing data from Census Bureau estimates, farmland data from the Census of Agriculture, and remotely sensed land use/cover data from the United States Geological Survey. The implications of these factors and how they will potentially affect biomass crop production are discussed.