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Using the American Community Survey: Benefits and Challenges (2007)

Chapter: PART III: Education, Outreach, and Future Development, 7 Important Next Steps

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Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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PART III
Education, Outreach, and Future Development

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

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Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

7
Important Next Steps

The full implementation of data collection for the American Community Survey (ACS) in 2005–2006 is a historic event for the nation’s statistical system. Based on over 10 years of research and development by the Census Bureau, the ACS is intended to replace the decennial census long-form sample as a source of regularly updated demographic and socioeconomic information on the population and housing of states, counties, cities, and other governmental and statistical areas.

The panel’s assessment is that the ACS will deliver on its promise to provide more timely, frequent, and complete information than the longform sample. Given the survey’s continuous design, however, ACS estimates are not the same as the long-form-sample estimates for a point in time (Census Day, April 1); instead, they represent annually updated period estimates based on 12 months of data and (once sufficient years of data are accumulated) 36 and 60 months of data. Only 60-month estimates (5-year period estimates) will be available for the smallest areas. ACS estimates also have significantly higher sampling errors than the corresponding longform-sample estimates, a feature of particular concern for the smallest areas (small counties, cities, towns, villages, American Indian and Alaska Native areas, and school districts, as well as census tracts and block groups).

While the ACS continuous design presents challenges to users, it also affords opportunities to develop applications that go far beyond what was possible with the long-form sample. Some innovative uses of the ACS will be easier to implement than others. In the same vein, some uses of the ACS to replace long-form-sample data will be easier to implement than others.

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

Overall, there is no doubt that the ACS can be of great benefit to many users, not only in the short term, but also over time as the survey is improved and new measures and applications are developed.

To achieve these goals will require sustained and even expanded resources and effort on a continuing basis, not only for collection and production of the ACS data, but also for user education and outreach and methodological research and evaluation. The Census Bureau should seek adequate funding for the ACS as a top priority. The panel hopes that the user community will express its support and that Congress will provide the needed annual funding as the ACS comes fully online.


Recommendation 7-1: The Census Bureau should continue to make sufficient funding of the ACS one of its top priorities. It should seek adequate funding on a continuing basis, not only for data collection and production, but also for ongoing programs of methodological research and evaluation and user outreach and education.


The Census Bureau has already devoted considerable resources to methodological research and data product design as part of the developmental work for the ACS over the past 10 years. Yet this work cannot stop with full implementation. On the contrary, the sheer volume of estimates means that the full ACS is in many ways brand new to the Census Bureau and the user community, even though the ACS concept and test data have been around for a period of years. Now is therefore the time to expand the resources for evaluation of the full production ACS and for methodological research and experimentation to improve the survey to reflect the evaluation results. Now is also the time to significantly expand the resources to educate and receive feedback from users, as over the next few years they experience for the first time the full panoply of 1-year, 3-year, and 5-year period data products from the ACS.

The purpose of this chapter is to outline this needed effort so that the ACS can evolve to meet its full potential. The chapter starts by describing an education program that is needed to inform users about what the ACS is, how to use its data products, and how interactions between the Census Bureau and the ACS user community can mutually benefit the ACS. The next section reviews the requirements for continued monitoring of basic indicators of data quality. The third section outlines areas for research and evaluation so that the ACS design, data collection, and estimation procedures can be continually improved and users can be more fully informed regarding sampling and nonsampling errors in the data. This section indicates the panel’s priorities for where limited resources can be most usefully directed in the next few years. The final section briefly describes a vision of what the ACS could become as it not only supports applications that

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

previously used the census long-form sample, but also provides the basis for improving and expanding the information that is available to understand and plan for the nation’s growing, diverse communities.

7-A
EDUCATING DATA USERS ABOUT THE ACS

The overriding priority for small-area data users is to adjust their perspective from having long-form-sample point-in-time estimates available once every 10 years to having 1-year, 3-year, and 5-year ACS period estimates available annually for geographic and statistical areas depending on their population size. With some exceptions, notably in the housing and transportation communities, the panel found relatively little preparation for this change on the part of data users. No doubt a key reason has been limited resources. In addition, it is often hard to imagine how to use very different kinds of data that are not yet available for most areas. Chapters 2 and 3 are intended to help users understand the key features of the ACS and to provide guidance for using the data for a range of applications, but much more work remains to be done.

While the Census Bureau has tried to facilitate the transition from the long-form sample to the ACS, the fact is that the full implementation of the ACS will be a sea change for data users. Appropriate reorientation on the part of users will not occur as a result of issuing new documentation or a new web site, essential as those elements of a data dissemination plan are. Appropriate reorientation will occur only as a result of a comprehensive education effort that is based on a plan to provide a set of best practices for data use that are well illustrated, using examples that are meaningful and that clearly explain period estimates and their differences from the pointin-time estimates that are commonly provided by other data sources. The plan must also provide for systematic feedback from users that can help the Census Bureau refine and tailor the education program to user needs. Such feedback should also benefit the Census Bureau by identifying potential problems with the data to follow up and improvements to data products that would facilitate data use.

The education and outreach plan, of which key elements are outlined below, is designed primarily for users who expect to make repeated, multiple uses of the ACS data and who will therefore need to learn about the survey in some detail. However, there are also first-time users, infrequent users, and users who lack resources for participating in educational programs (for example, users in many small governmental jurisdictions). These users need to find key estimates easily and not have to master the complexities of the data. The Census Bureau, in cooperation with the network of organizations that it enlists as partners for education and outreach (see Section 7-A.3 below), should identify ways to help these users. Being

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

proactive in this regard will increase the value of the ACS and reduce the likelihood that users will fail to take advantage of ACS data because they find them too complex.

Approaches to help occasional users will likely also help experienced users. One approach is for the Census Bureau to work with organizations that have a mission to assist data users, such as State Data Centers, to help them develop simple data products and explanatory materials that are specifically designed for occasional or novice users. In addition, the Census Bureau itself could develop additional data products for the first-time, occasional, or resource-constrained user. These products could consist of simple tabulations that meet commonly accepted standards of precision. Similarly, simple tabulations of year-to-year change might be provided whenever there has been a significant increase or decrease in a key estimate, such as the poverty rate. The goal should be to make these products as transparent and accessible as possible, including giving them a special and prominent location on the Census Bureau’s ACS web site that contains a link to the rest of the site for users who want more information.

7-A.1
Key Elements of the Education Strategy

The program of ACS education should have two major components. The first component should aim to provide a foundation of the basics about the ACS and methods to use the data appropriately. Users should be helped to grasp the key elements that make the ACS different from the long-form sample, the most important of which are the change from point-in-time to period estimates of characteristics, the increase in the size of sampling errors, and the opportunities and challenges that will arise with annually updated data for different time periods. After introducing data users to ACS concepts, the goal should be to educate them about the new perspectives they need to have and the new techniques they need to employ in order to make effective use of the data.

The second component should aim to create paths for outreach to and feedback from users that enable the Census Bureau to engage in a continuous dialogue regarding questions and issues that need to be addressed. At this stage of the program, no one, including the Census Bureau, can anticipate all of the questions and issues that will arise from the data user community. The Census Bureau will have an opportunity to accumulate a critical mass of user reactions to the 1-year and 3-year period estimates that should permit the staff to become more responsive to data users before the first 5-year period estimates are released in fall 2010. This will occur only if an adequate mechanism is in place to deliver feedback to the Census Bureau.

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×
7-A.2
Providing a Foundation for the Basics

The Census Bureau’s ACS web site (http://www.census.gov/acs/www) provides a great deal of information on all aspects of the ACS, including access to Using Data from the 2005 American Community Survey, a 31-page guidebook for users; the Guide to the ACS Data Products, an online tool for learning more about the various kinds of tables and other data products; the ACS Data User Training Guide, a set of PowerPoint presentations; and a voluminous ACS Design and Methodology document, which explains ACS operations from sampling to data release and includes facsimiles of the ACS questionnaires (U.S. Census Bureau, 2006). While helpful and necessary, these materials are not sufficient by themselves for educating data users about the ACS.

To build a foundation of knowledge that is meaningful for those who apply the data in their work, the Census Bureau needs to develop userfriendly application-oriented documentation and metadata, including sample applications that can be presented in paper form and on the web in the form of online tutorials. This type of documentation differs markedly from the provision of technical information. Both types of documentation are needed.

Two core features of the Census Bureau’s application-oriented documentation should be, first, to provide key information to assist in the transfer to the ACS from the census long-form sample and, second, to describe methods and best practices to apply the ACS small-area data on the socioeconomic characteristics of the population for a variety of applications. Consultation with major user groups should yield instructive applications for large cities, smaller governments, rural places, transportation interest groups, and other groups that serve the data user community. One benefit of developing these kinds of examples is to enable data users, including key intermediaries, to assist the Census Bureau to establish standards and best practices for using ACS data. A recent publication, developed with input from Census Bureau staff and data users, takes this approach (Taueber, 2006). It is aimed at helping community planners access, interpret, and report on the ACS data for their areas.

The Census Bureau’s consultations should include a wide range of users, including state governments, local governments (including regional and local councils of governments), not-for-profit agencies, academic researchers, the private sector, and the media. Within those sectors, applications should be developed for users with different focal interests: transportation, education, health, social services, criminal justice, economic development, and the environment. Applications should represent an assortment of typical uses: policy development, program planning, budgeting, site selection, fund allocation, and outcomes monitoring.

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

Basic kinds of information that users need to understand in order to make the transition from the long-form sample to the ACS, including the implications of differences for data quality and utility, include:

  • Differences between the long-form-sample and ACS questionnaires: the format of the questionnaires, the application of residence concepts, the reference periods for questions, and the wording of questions.

  • Differences between the long-form-sample and ACS data collection processes: an understanding of how the ACS data are collected, using different modes, from a series of monthly samples supporting annually updated 1-year, 3-year, and 5-year period estimates for different levels of geography.

  • Differences between the long-form sample and the ACS in the accuracy and geographic specificity of population and housing unit controls that are applied to the estimates.

  • How to compare ACS estimates to the 2000 census long-form sample (and other surveys) in light of differences between them—in particular, how to make comparisons for the 2005 ACS estimates, which pertain to households only and do not include group quarters.

Information relevant to methods and practices for using the ACS that users need to understand include:

  • The provision of data from the ACS, including: the various formats for obtaining data, the geographic levels of data availability, and the trade-offs between different data products. Data access needs to be emphasized, via the American FactFinder web portal, data on CDs and DVDs, and data available from the Census Bureau’s FTP sites.

  • The sampling error of estimates for 12-month, 36-month, and 60-month intervals and how to interpret variability.

  • How to interpret multiyear period estimates.

  • How to gauge change over time using multiyear estimates and how to conduct comparisons across areas.

  • Special issues for small-area data, focusing on strategies to increase precision at a small-area level, such as combining information across time and geography.

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×
7-A.3
Building a Network for Education, Outreach, and Feedback

In order to encourage widespread and informed use of the ACS data, the Census Bureau needs to expand its infrastructure in two ways. First, it needs to establish a headquarters ACS users’ staff devoted to education and outreach who would cultivate a network of trained intermediaries to assist with providing a basic ACS education to users. Second, it should form a small informal advisory group of experienced data users that meets with the ACS user staff on a regular basis in person and by conference call. The group would be a key point of contact for considering ideas to improve data products, educational materials, user outreach, and related topics.

Once a network of trained intermediaries is established, it will enable the development of a full-fledged system of regular feedback that can make the ACS education and training program—and appropriate uses of the data—grow and prosper. Feedback in the early years of implementation will assist the Census Bureau to adapt the training program to better meet user needs. In the longer term, user feedback should be a valuable source of ideas for modifying and improving the ACS to serve a wider range of applications and provide an increased return on investment in the data collection.

The Census Bureau is already reaching out to federal agencies to train and assist them in using the ACS. It has established a Federal Agency Information Program (see http://www.census.gov/acs/www/SBasics/fed.htm) through which Census Bureau staff members are available to make presentations to agency staff, provide assistance on specific applications of the ACS, such as in funding formulas, and prepare special data tabulations on a cost-reimbursable basis. The Census Bureau’s work with federal agencies should be helpful to other users, such as state and local governments that interact with those agencies.

To develop an adequate network of intermediaries, however, the Census Bureau (including its regional office staff) should reach out to many organizations outside the federal government. An adequate return on the investment in the ACS can only be achieved if the small-area data are used to the widest extent possible. There are many organizations that the Census Bureau should strive to include in its network:

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

Planning Association, the Association of Public Data Users, the American Association of Public Opinion Research, the Transportation Research Board, the American Library Association);

  • major state and local government organizations (for example, the U.S. Conference of Mayors, the National Governors Association, the National Association of State Legislatures, the National Association of Counties, the National Association of Towns and Townships, the Association of Metropolitan Planning Organizations);

  • local and regional councils of governments and planning agencies (for example, groups concerned with regional transportation plans and environmental issues);

  • not-for-profit groups (local chapters of the United Way, Red Cross, United Hospital Fund);

  • the media (for example, Investigative Reporters and Editors, Inc., and that organization’s computer-assisted reporting program); and

  • other for-profit and not-for-profit groups, such as market research professionals, associations of health professionals, social service agencies, and the variety of groups that serve special populations, such as the disabled, farm workers, veterans, and immigrants.

The involvement of the SDC network is of critical importance since the SDCs will be on the front line of answering information requests for 2010 census and ACS data. The SDCs must be able to effectively present ACS data and assist data users, including making the data understandable to users with a very wide range of experience and expertise. The SDC steering committee is already focusing its efforts on “training the trainers,” so that SDCs have sufficient knowledge to then train the entire network of 1,800 organizations and general data users that they serve. In addition, individual SDCs have already developed helpful explanatory materials for the 2005 ACS data products (see, for example, “Ten Things to Know About the American Community Survey, 2005 Edition,” prepared by the Missouri Census Data Center).1 To move this initiative forward, the Census Bureau should support and encourage local hands-on workshops on the applications of ACS data. At least some of these workshops should be done in coordination with SDC affiliates so that best practices are provided for local users. These workshops can be the basis of an education network that, once established, can serve as an efficient information-sharing mechanism between the Census Bureau and the data user community.

In general, training courses can be developed at many different levels and for many different groups. Some can be in the form of tutorials, to be

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

presented at special workshops or sessions at the annual meetings of many key groups that are already part of the census network as listed above.

7-A.4
Working with the Media

ACS training and education should be adapted to the needs of media organizations. The media need to become a partner in explaining why the ACS is important and how the data can best be used. The media should welcome this partnership, since more frequently updated information will give them opportunities for many new stories over the decade on such topics as immigration, domestic migration, education patterns, and other topics of public concern.

The need for an active media education and partnership program is evident from the press coverage of the August 15, 2006, release of 2005 ACS data for political and statistical areas with 65,000 or more total population. This initial release provided information on age, sex, race, ethnicity, ancestry, place of birth, citizenship, year of immigration, residence last year, language spoken at home, education, disability, marital status, fertility, veteran status, and whether grandparents are caring for grandchildren in their home. A review by panel staff of 57 articles in 44 newspapers around the country published August 15-16, 2006, that used the new ACS data found that interest in the data was high but understanding of them and how to use them was often poor. The ACS was sometimes confused with other programs, such as the census and the population estimates, and understanding of how to compare the 2005 data with the 2000 long-form sample and other sources was limited (see Box 7-1).

The Census Bureau should conduct extensive analyses of news coverage of the 2005 ACS and revise and enhance its user education program and documentation accordingly, not only for the media, but also for other data users. As a top priority, guidance about comparisons of estimates from the 2005 data with the 2000 long-form sample and other sources (including the population estimates program) is clearly needed. Indeed, guidance on comparisons with the 2000 long-form sample will continue to be critical because the ACS cannot itself serve as a comparison source for estimates of change, particularly for small areas, until more years of data are released and analyzed.

7-A.5
Recommendations on User Education, Outreach, and Feedback

As with any major initiative, creating an education and outreach system to accompany the ACS will involve a significant commitment of resources from the Census Bureau and its affiliates, and from the user community as well. The ACS represents a substantial increase in the volume of informa-

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

BOX 7-1

Print Media Treatment of the 2005 American Community Survey

Panel staff reviewed 57 articles in 44 newspapers around the United States, published August 15–16, 2006, that featured the initial release of data from the 2005 ACS on social and demographic characteristics of areas with at least 65,000 people. The newspapers covered included major national papers, such as the New York Times, the Washington Post, and USA Today, other major metropolitan newspapers (for example, the Seattle Post-Intelligencer, the Houston Chronicle), and smaller newspapers (for example, the Anchorage Daily News, the Lexington Herald-Leader, the Toledo Blade).

Six conclusions are drawn from this review:

  1. Interest is high in these data, principally because of their currency and the light they shed on such salient features of American life as increasing racial and ethnic diversity and immigration.

  2. Change over time is of key interest. Three-fourths of the articles featured estimates of change from 2000 to 2005 in total population or characteristics. Most of the articles appeared to use the 2000 long-form sample as the comparison point; two articles used the Census 2000 Supplementary Survey or the 2002 ACS test survey. (Comparisons with the test surveys can be done only for areas with at least 250,000 people or, in the ACS test sites, for areas with at least 65,000 people.) Only two articles expressed caution about ACS comparisons with the long-form sample.

  3. Population numbers are of key interest. Even though the Census Bureau emphasizes the use of the ACS for characteristics, not population counts, one-fifth of the articles explicitly focused on growth or decline in total population from 2000 to 2005. None of the articles discussed that, for many areas, population figures

tion available to decision makers and will become an important national asset if it is used appropriately and to its full potential. Cultivating a data user network that helps users navigate their way through this new maze of methods and issues will help the Census Bureau ensure that all will rise to the challenge of using this valuable tool of the nation’s statistical system.


Recommendation 7-2: The Census Bureau should develop a comprehensive program of user education, outreach, and feedback for the ACS. Two goals of the program should be (1) to educate users in the basics of the ACS, how it differs from the census long-form sample and other data sources, and appropriate methods to use the data; and (2) to develop paths for systematic feedback from users to improve the training materials, identify potential problems with the data, and sug-

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

(total and by age, sex, and race/ethnicity) are from the postcensal population estimates program, but for other areas (for example, cities within counties), the figures are from the ACS and have standard errors associated with them.

  1. Information to help the reader understand the source of the data is sparse. One-fifth of the articles made only a glancing mention of the ACS as the data source, and one-fifth did not mention the ACS at all. Another one-fifth provided incorrect information about the nature of the ACS, confusing it with the census most often (4 articles) or with the population estimates program (1 article), or calling the ACS a mid-decade census (3 articles), a 5-year database (1 article), or a telephone survey (1 article). The remaining two-fifths of the articles provided a brief description of the ACS as a continuing monthly survey that is intended to replace the census long-form sample. The sample size mentioned was the initial size of 3 million households per year, not the 2 million remaining after follow-up.

  2. Acknowledgment of sampling error is spotty. In all, 23 percent of the articles clearly referenced the margin of error in the ACS estimates (two articles stated that the margin of error was so large as to render the data useless), 10 percent made a glancing reference to the margin of error, and the remaining 67 percent made no mention of sampling error.

  3. Particularly in communities that are losing population, press articles questioned the population figures from the 2005 ACS by comparison with 2000. Three-fifths of the articles did not acknowledge a key difference between the 2005 ACS and the 2000 long-form sample that could affect such comparisons—namely, that the ACS is limited to the household population and excluded people living in college dormitories, prisons, and other group quarters. None of the articles mentioned another difference that could affect comparisons—namely, the differences in the accuracy and geographic specificity of population and housing unit controls between the ACS and the long-form sample.

gest ways to improve data products and documentation to maximize the utility of the data and facilitate data use.


Recommendation 7-3: As an integral part of its education, outreach, and feedback program for the ACS, the Census Bureau should establish a dedicated ACS user staff. That staff should partner with organizations that will assist end users, including the State Data Center network as a key partner and many other organizations and groups. The staff should work with the media to help them understand ACS data so that they can explain and showcase the value of the data to communities in an effective and accurate way.


Recommendation 7-4: The Census Bureau should establish an ongoing advisory group of experienced data users with whom to interact about

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

user education materials, web site design, table content, and other aspects of the data products and education and outreach program for the ACS.

7-B
DATA QUALITY MONITORING

A major continuing survey, such as the ACS, requires continued monitoring to ensure that data collection and production processes are performing well, to identify problem areas for investigation and development of improved processes, and to provide information to users about sampling and nonsampling errors of which they should be cognizant. For these purposes, it is essential to develop and track an appropriate set of performance measures.

Some performance measures are for use by survey managers to ensure that survey data collection and processing operations are being carried out as specified and within quality control tolerances and to flag problems for investigation. Such measures may track timely completion of check-in and data capture of mailed-back questionnaires, interviewer productivity, and the like. The panel did not review what measures the Census Bureau uses for quality control of the ACS; we trust that the Census Bureau has developed a set of appropriate measures and periodically reviews them for relevance and usefulness in identifying problems on a timely basis.

Other performance measures are useful not only to survey managers, but also to inform users of the quality of the data across areas and population groups. The Census Bureau has long experience with monitoring and maintaining the quality of its survey operations. For the ACS, it has taken a further step to put up on the ACS web site basic indicators of sampling and nonsampling errors in the data.

7-B.1
Nonsampling Error Measures

The Census Bureau currently provides four indicators of nonsampling errors, which can be accessed from the main ACS web site under “Using the Data” (http://www.census.gov/acs/www, “Quality Measures”). The four measures are sample size, survey coverage rates relative to the 2000 census-based population estimates, survey response rates (unit response), and item nonresponse rates (refer back to Box 2-4). At this time, all four indicators are available for the Census 2000 Supplementary Survey, the ACS 2001–2004 test surveys, and the 2005 ACS for the nation and states.

The panel commends the Census Bureau for providing quality measures for ACS estimates on its web site. For these measures to be useful, it is important that users of the data access them and interpret them correctly. The Census Bureau’s data user advisory group and network of user educa-

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

tion partners (see Section 7-A above) could be a valuable resource to help educate users about the meaning and value of the various indicators.

This network could also help the Census Bureau determine what additional indicators to consider adding to the web site. For example, for the 2005 ACS, it could be very useful to provide all four quality measures for individual public use microdata areas (PUMAs) to help users track basic data quality for substate areas.

Looking ahead, it would be very useful for the Census Bureau to periodically issue reports that highlight patterns of basic quality measures over time for geographic areas and population groups of interest—for example, whether (and which) item nonresponse rates are increasing or decreasing and for which areas and groups. Similarly, it would be useful for the Census Bureau to analyze unit and item nonresponse rates separately by data collection mode (mail, computer-assisted telephone interviewing, CATI, computer-assisted personal interviewing, CAPI) to see if there are patterns by geographic location or such characteristics as education level, family structure, and others. It will also be important for the Census Bureau and its network of user education partners to determine the most useful set of quality measures for the 3-year and 5-year period estimates for small areas in addition to those provided for 1-year period estimates for larger areas.


Recommendation 7-5: The Census Bureau, in collaboration with user education partners, should carry out research on ways to facilitate understanding of the quality measures provided on the ACS web site. The Census Bureau and its partners should also consider what additional quality indicators—for example, some of the indicators presented at a finer level of geographic detail—would be useful to provide for the 2005 ACS and subsequent 1-year period estimates and what indicators to provide for the 3-year and 5-year period ACS estimates when those become available.

7-B.2
Sampling Errors
7-B.2.a
Published Margins of Error

The Census Bureau provides a measure of sampling error for each sample-based estimate that is released in tabular form from the ACS. This measure is developed using a repeated replication method (see U.S. Census Bureau, 2006:Ch. 12). The published measure of sampling error is the margin of error around the estimate (plus or minus) at the 90 percent confidence level (1.65 times the standard error), not the commonly accepted 95 percent level, which is 1.96 times the standard error (see Box 2-5 for explanations of these terms).

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

The estimates of sampling error account for the variability from all the stages of weighting, including the initial sampling, the CAPI subsampling, and the population controls. Some weighting steps (see Section 5-A) are intended to reduce variability. The estimates do not account for other sources of variation, such as that introduced by imputation procedures for item nonresponse, nor for errors arising from inaccuracies in the population estimates used as controls.

Modifications are needed in the computation of the margins of error in some cases. For example, for small estimates, the margins of error shown produce a 90 percent confidence interval that includes zero, when it is not possible to obtain negative estimates (for example, ±113 for an estimate of 97 poor children in single-parent male-headed families for Ann Arbor, Michigan, from Detailed Table B17006 on the American FactFinder web site for 2005 ACS data). At the least, an explanatory note should be provided that the lower bound of the confidence interval is zero.

Sampling error measures are provided not only for population and housing characteristics, but also for estimates of total population, total housing, and basic demographic characteristics for counties, cities, and other areas that are not controlled to the census-based population or housing unit estimates. As described in Section 5-A, the ACS controls are applied for estimation areas, which are large counties and groups of small counties.

In the case of multiyear profiles of 1-year estimates, an indicator of statistical significance at the 90 percent confidence level is provided for the difference between an estimate for a specified year and the corresponding estimate for a current year. Multiyear profiles are available that compare 1-year period estimates from the C2SS and the 2001–2004 ACS test surveys for areas with 250,000 people or more; they are not being issued for the 2005 ACS, even though the 2005 ACS estimates could be compared with the estimates for 2000–2004 for large areas. They will presumably become available again beginning with the 2006 ACS.

7-B.2.b
Guidance on Computing Sampling Errors

The Census Bureau provides general guidance, with just a few examples, for computing approximate estimates of standard errors for sums and differences of estimates for geographic areas and population groups that are shown in the ACS tables. (Taueber [2006[ provides additional examples for local area data users on computing standard errors and other aspects of working with the ACS.) The Census Bureau’s guidance is available in its publication, Using Data from the 2005 American Community Survey

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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(pp. 10-11).2 Generalized variance estimation procedures for estimating sampling errors for user-generated estimates from the public use microdata samples (PUMS) are provided in the “Accuracy Statement” for the PUMS in question.3 In addition, for the first time, the 2005 PUMS provides replicate weights for users to calculate direct estimates of sampling error that are more precise than those from the generalized variance estimation procedures.

For standard errors of differences, the Census Bureau’s guidance applies not only to comparing differences between two areas or population groups, but also to comparing differences between estimates for two points in time for which the individual standard errors are available. However, the guidance is not applicable to every calculation a user might wish to perform from the ACS tables. For example, to save space, many tables do not provide all of the aggregate categories that users may want—such as total children under age 5 with family income below the poverty level (see Detailed Table B17006). While this estimate can be obtained for an area by adding up poor children under age 5 in married-couple and single-parent families from rows in the table, there is no ready way to compute a precise standard error of the combined estimate. The reason is that the individual estimates come from the same sample and so are correlated. If an aggregate table were available that provided the desired sum, then the standard error would be available, but there is not such a table for this example. The guidance alludes to this problem but does not explain it.

7-B.2.c
Recommendation for Sampling Error Documentation

Given the lack of technical sophistication of many users of the ACS data, the Census Bureau needs to evaluate its presentation of sampling errors to be most helpful to the widest range of users. A helpful first step would be to provide 95 percent margins of error for consistency with commonly accepted survey practice. It would also be helpful to provide margins of error that do not include zero, although this would require a different technique to estimate the standard error and a different format for presenting the information.

An even more ambitious step would be to rethink the presentation of tables on the ACS web site. As suggested in Section A above, the Census Bureau could identify key estimates that meet common standards of precision, such as having a standard error that is 10 percent or less of the estimate.

2

Available by clicking on “Survey Methodology” or “Accuracy of the Data” from any ACS table accessed through the American FactFinder web site (http://www.factfinder.census.gov/).

3

See, for example, http://factfinder.census.gov/home/en/acs_pums_2005.html.

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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These quite precise estimates would be highlighted for users who want to know what they can confidently learn from the data and are daunted by the array of table cells with large margins of error.

In addition, the Census Bureau should review its guidance for calculating standard errors for user-constructed estimates of sums and differences. The documentation should provide many more examples for a range of applications to make clear how the guidance can be used. It should also emphasize more strongly when the guidance is not readily applicable.


Recommendation 7-6: The Census Bureau, in consultation with data users and statistical methodologists, should evaluate its presentation of sampling errors of estimates that are published on the ACS web site and also its descriptions of methods for computing approximate estimates of sampling errors for estimates for which sampling errors are not published. Steps should be identified to improve the usability and ease of comprehension of information on sampling errors.

7-C
PRIORITIES FOR ASSESSMENT AND IMPROVEMENT OF SURVEY QUALITY

In addition to monitoring basic quality measures, a major continuing survey such as the ACS requires periodic, in-depth assessments of data quality on a wide range of dimensions across time and among population groups and geographic areas. The benefits of such assessments accrue not only to data users, who can gain deeper understanding of the value and challenges of the data, but also to survey managers who require information to help them identify areas for methodological research and subsequent survey improvement.

7-C.1
Quality Profile

A comprehensive survey evaluation is referred to as a quality profile. Such a document brings together and analyzes the magnitudes of and contributions to sampling and nonsampling errors from various survey component processes for estimates from a survey, generally, and, when possible, for specific questionnaire items. A quality profile also typically includes comparisons of selected survey estimates with estimates from other surveys or administrative records. Examples of quality profiles include those developed for the American Housing Survey (Chakrabarty, 1996); the Residential Energy Consumption Survey (Energy Information Administration, 1996); the Schools and Staffing Survey (Kalton et al., 2000); and the Survey of Income and Program Participation (U.S. Census Bureau, 1998).

A quality profile for the ACS would be complex to prepare and require

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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significant time and effort to pull together, analyze, and present information on all of the topics that should be included. Nonetheless, work on an ACS quality profile needs to begin now, building on the evaluation studies that were conducted of the Census 2000 Supplementary Survey and the 2000 long-form sample. The first step is to develop the framework, or outline, for the quality profile. The outline could then be used to plan a research program for assessing specific aspects of the ACS and using the results as the basis of a program of survey improvement. As research findings are accumulated, they can form the basis for chapters of the quality profile. To be most useful not only for users, but also for survey managers, the various chapters should be issued and updated on an ongoing basis. If staff resources are insufficient to manage the profile materials, the Census Bureau could seek outside assistance for the work.

The topics to include in an outline of an ACS quality profile fall under two main categories. The first category includes reports of what is known about sampling and nonsampling errors for estimates of interest, including differences in the magnitude of errors for geographic areas and population groups. The second category includes the results of analyses to determine the sources of various types of error in the estimates, particularly the effects of the various components of the survey design and operations, such as sample design, data collection mode, questionnaire design, weighting, imputation, and others. Results of experiments with alternative methods should also be included.

More specifically, the outline might cover such headings as:

  • Sources of nonsampling and sampling errors and their extent and effects:

    • Sampling frame: completeness, currency, and accuracy of the Master Address File (MAF) for housing units and group quarters in geographic areas; assessments of the quality and usefulness of various MAF updating operations.

    • Sample design: effects on standard errors of estimates of different initial sampling rates, particularly among states with different numbers and types of small jurisdictions and among similarsized small jurisdictions; benefits and drawbacks of alternative designs.

    • Sample design: effects on standard errors of CAPI subsampling rates.

    • Data collection mode: patterns of response by mode for population groups and geographic areas; effects of mode differences on precision and bias for questionnaire items; correlates of mode differences; results of experiments to reduce mode differences.

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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  • Questionnaire design and wording: effects on response rates, response variance, and response bias for content items; results of experiments with alternative wording.

  • Residence rules: how respondents and interviewers interpret the 2-month residence rule compared with the decennial census usual residence rule and the effects on population coverage in the ACS.

  • Weighting: effects of each weighting stage on the precision of 1-year period estimates.

  • Population and housing unit controls: accuracy of controls at different levels of geography and for population groups and geographic areas; how their use affects 1-year, 3-year, and 5-year period estimates.

  • Imputation: patterns of item imputation for geographic areas and population groups; the effects of imputation on precision and bias of estimates.

  • Inflation adjustments (if retained): accuracy of methods for inflating income and housing dollar amounts for 1-year, 3-year, and 5-year period estimates for geographic areas and population groups; pros and cons of alternative methods.

  • Confidentiality protection: extent of data suppression to protect confidentiality for geographic areas and population groups; risks and benefits of alternative protection methods.

  • Table collapsing for precision: extent of collapsing for geographic areas and population groups; pros and cons of alternative collapsing schemes.

  • Variance estimation: estimates of the variance not accounted for due to item imputation and other sources.

  • Comparability of ACS estimates with other data sources:

    • Comparability of aggregate estimates for as many content items as possible, taking account of differences between the ACS and the comparison source(s).

    • Consistency of microlevel data from matching studies of ACS records with records from an administrative system (for example, Food Stamp Program records or Social Security records).

    • Regression analyses of correlates of differences between the ACS and other sources.

  • Regularly repeated, summary assessments of precision (variance) for geographic areas and population groups.

  • Regularly repeated, summary assessments of measurement error (bias) for key content items, drawing on all available information.

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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To measure the magnitudes of various kinds of errors and to analyze sources of error, various methods are available. They include

  • aggregate comparisons of ACS estimates with estimates from other surveys or administrative records;

  • exploratory, graphical, and regression analyses to identify geographical and other patterns in the data that suggest hypotheses for further analysis (for an example, see National Research Council [2004b:186-193], which reports on graphical and regression analyses of 1990 and 2000 census tract mail return rates by geographic area and population characteristics);

  • microlevel matches of individual ACS records with records from other sources (for examples, see Coder, 1991, 1992, which report on exact matches of Internal Revenue Service (IRS) earnings records with the Current Population Survey (CPS) and Survey of Income and Program Participation, respectively);

  • reinterviews of samples of ACS respondents (reinterviews are included in the ACS Methods Panels, see Section 7-C.2 below);

  • designed experiments using cognitive testing and other structured interview techniques with small samples;

  • designed experiments with large samples of households (the ACS methods panels provide examples—see Section 7-C.2 below); and

  • sensitivity and other simulation analyses with existing data.

The different methods have advantages and disadvantages in terms of the time and resources required to carry them out, the questionnaire items for which they are feasible, the robustness of their results in terms of sampling and nonsampling errors, and whether they contribute to understanding sources of error and not just the magnitudes of error in the ACS estimates.

In designing an ongoing assessment program for the ACS and selecting priority topics for research in the short term and longer term, the Census Bureau must balance important uses of the data against feasibility and resource constraints. Input from the Census Bureau’s network of user education partners should be helpful in this regard. In turn, it will be important for educating users to provide the results of data quality assessments not only in technical reports but also in user-friendly formats. Because users of the ACS will undoubtedly want to know the distributions of data quality assessments across time and among geographic areas and population groups and not simply U.S. or state totals, Census Bureau analysts will need to become facile with modern graphical analysis tools and exploratory data analysis techniques. The Census Bureau historically has not made much use of these methods, but they are essential for identifying and displaying

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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temporal, spatial, and demographic patterns of interest from a data set as large as the ACS (see, e.g., National Research Council, 2001:App. B). In turn, the ability to more readily identify data quality patterns should facilitate planning for in-depth research and evaluation to identify ways to improve the ACS.


Recommendation 7-7: The Census Bureau should develop and publish an ongoing quality profile for the ACS to inform users of the survey’s data quality, to guide the development of a continuing program of data quality assessments, and to identify areas for survey improvement. The Census Bureau should seek input from users on priority topics for assessment and design reports that they would find to be useful additions to the technical reports.

BOX 7-2

2006 and 2007 American Community Survey Methods Panels

“Methods panel” is a term used by the Census Bureau to refer to samples of households that are used for testing and experimentation for a continuing household survey. For the ACS, the Census Bureau fielded a 2006 methods panel (see Federal Register, vol. 70, no. 45, March 9, 2005: 11609-11610). It is planning to field a 2007 methods panel later in the year (see Federal Register, vol. 71, no. 94, Tuesday, May 16, 2006:28302-28305).


2006 ACS Methods Panel


The 2006 ACS Methods Panel (also known as the 2006 ACS Content Test) was designed to test new questionnaire content to be considered for inclusion in the ACS in 2008 and modification of existing content to improve response. The test included four stages:

  1. Determination, with input from federal agency stakeholders, of eligible content for the test.

  2. Cognitive laboratory pretesting, expert reviews, and other methods to develop alternative versions of the eligible questions. Eleven of 25 existing housing questions, 15 of existing population questions, and 3 new population questions were identified for inclusion in stage 3.

  3. National sample field test of about 50,000 housing unit addresses. About half the sample served as the control panel, receiving the existing ACS questionnaire; the other half served as the test panel, receiving alternative versions of the questionnaire. Mailed out to all sample addresses were advance letters, questionnaires, and reminder postcards, followed by second questionnaires to

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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7-C.2
Methods Panels

The Census Bureau recently began a program to field large samples of households, called methods panels, as the vehicle for large-scale experimentation with features of the ACS. The 2006 Methods Panel included 50,000 households and was used to test alternative wording for existing and new questions. A 2007 Methods Panel, which is to include almost 70,000 households, is planned to test not only question wording and questionnaire format, but also strategies to improve mail response (see Box 7-2).

The Census Bureau is to be commended for initiating the ACS methods panels. The program should be continued because of the continuing need for large-scale experimentation on questionnaire format, question wording, instructions for reporting residence, the effects of data collection mode, and other aspects of the ACS data collection. The need for continuing largescale experimentation exists because federal data requirements from the ACS can be expected to evolve over time, as socioeconomic conditions and concerns change. Also, respondent behavior may change in ways that affect

nonrespondents. After 4 weeks, nonrespondents were followed up by CATI; 4 weeks later, remaining nonrespondents were followed up by CAPI. There was no telephone questionnaire assistance or telephone edit follow-up, which could have influenced respondents’ answers. After data collection, a subsample of mail, CATI, and CAPI respondents who furnished a telephone number were followed up by CATI to measure simple response variability and response bias by comparing answers from the first interview (by mail, CATI, or CAPI) and the second CATI interview.

  1. Analysis of results and recommendations for new and revised content for the ACS beginning in 2008—expected in early 2007.

2007 ACS Methods Panel


The 2007 ACS Methods Panel is designed with two tracks:

  1. The first track will address new and improved content, including a new question on field of bachelor’s degree and a modified format for the basic demographic questions (age, sex, race, ethnicity, household relationship). Four different questionnaires will be mailed to a total of 30,000 housing units, with CATI and CAPI follow-up and a CATI content reinterview.

  2. The second track will address ways to increase mail response and thereby contain costs. One strategy for testing is to make another mailing to nonrespondents for which a telephone number is lacking (three different mailing pieces will be sent to 6,000 housing units each). Another strategy for Puerto Rico and targeted areas of the United States with the lowest levels of mail response is to include a motivational piece in the questionnaire package. Two different mailing pieces will be sent to 10,000 housing units each in the targeted areas in the United States.

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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data quality and costs (for example, mail response could decline), which would require testing of new ways to improve response.

The Census Bureau should carefully evaluate its experience with the 2006 ACS Methods Panel with regard to costs and statistical power for the intended analyses. It may be that some testing can be done with fewer sample cases.


Recommendation 7-8: The Census Bureau should continue to seek funding with which to implement methods panels (large samples of households) for experimentation with questionnaire design, question wording, residence rules, data collection mode, and other features of the ACS. The methods panels should be conducted annually so that the survey can be kept current in meeting data needs and collecting responses in the most efficient and effective ways.

7-C.3
The Panel’s Priorities for Assessment

Even with the significant resources that the panel believes should be provided for ACS research and evaluation (see Recommendations 7-1 and 7-8), the program cannot investigate every aspect of this detailed, complex survey and certainly not on the same time schedule. It is important to establish priorities in consultation with methodologists and data users.

In Chapters 4, 5, and 6, the panel identified areas for research and evaluation. The panel’s complete list covers many aspects of ACS data collection, processing, estimation, and data. Acknowledging the need for prioritization, the needed research and evaluation topics are grouped into two categories below: high priority and other. Note that the priority categorization does not necessarily imply a time frame in which the research should be completed. Some high-priority analyses will require extended work, while others can be more quickly completed. Some analyses may be one-time efforts; other will need to be repeated on a continuing basis.

Many high-priority analyses are not costly in that they do not involve field data collection, or the costs can be shared with other programs in the Census Bureau. The panel recognizes, however, that Census Bureau analysts have many responsibilities, and the panel encourages the Bureau to augment its staff resources to the extent possible through fellowships, internships, and other collaborative arrangements with outside researchers.

7-C.3.a
High-Priority Areas for ACS Research and Evaluation

The panel has identified seven areas as high priority for evaluation, followed by research and development to improve the ACS on the basis of the results: sample size and allocation; the MAF; population controls;

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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residence rules; estimates of change; comparisons with other surveys and administrative records; and the development of automated tools for data quality review. Each of these areas is important not only for the usefulness of the ACS, but also for its credibility with users as a satisfactory replacement for the rich (but outdated) small-area information that was previously provided by the census long-form sample. Failure to address these seven topics could harm the quality of the ACS data and make it difficult for users to adapt their long-form-sample applications to this new survey with its continuous design.


Sample Size and Allocation A critically important issue for assessment, which requires a combination of research, consultation with users, and consideration of budget resources, is the ACS sample size and its allocation across the various governmental units (see Recommendation 4-4). The panel is concerned about the much larger sampling errors of ACS estimates compared with long-form-sample estimates, particularly for estimates for small governmental units, which, unlike census tracts and block groups, do not lend themselves to combination into larger areas. It seems imperative to develop strategies for improving the precision of the ACS estimates. The costs and benefits of alternative approaches can be evaluated using low-cost simulation methods; no new data collection will be required. Whether a solution can be found that is acceptable to users and to Congress (for funding) is not clear, but the effort to explore alternatives, including trade-offs (for example, perhaps giving up school district oversampling to increase the sample for other small jurisdictions) should be made. At a minimum, users should be fully informed of the trade-offs and the implications of alternative approaches for a range of applications. They should also be given specific guidance on strategies for increasing the precision of estimates by collapsing categories and combining estimates over time and across geographic areas.


Master Address File Research to evaluate and improve the MAF is critical for the completeness and accuracy not only of the 2010 census, but also of the ACS. Errors in the MAF can lead to omission of households, duplication of households, and assigning households to incorrect geographic locations. MAF research and development can be costly in that it often involves field work to identify problems and evaluate alternative approaches for improvement. Consequently, it may not be feasible to carry out much MAF research in the immediate future that is not part of the 2010 census planning.

Major work on the 2010 census MAF will not begin until late in the decade, when a complete block canvass and local review are conducted. However, beginning with the 2005 ACS, systematic examination of the dif-

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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ferences between the housing unit controls that are used for the ACS and the MAF could contribute importantly to MAF evaluation and improvement in its coverage (see Reese, 2007). In particular, identification of large differences, positive and negative, could provide the basis for targeted field evaluations to determine reasons for discrepancies and suggest methods to improve the MAF in areas with particular kinds of address problems, such as small multiunit structures (see Recommendations 4-1, 4-2, 4-3, and 5-2). Ideally, research and development on the MAF would proceed on a continuous basis after 2010 so that the ACS MAF is as kept as up to date and accurate as possible.


Population Controls Another critically important area for assessment is the accuracy and application of the population control adjustments to the survey weights. The adjustments may adversely affect the accuracy of estimates for some kinds of areas, such as those experiencing seasonal population fluctuations or rapid population growth or decline. They also will not capture differential rates of population growth in small areas within estimation areas (large counties and groups of small counties). ACS estimates produced with population controls for a census year will likely differ—sometimes substantially—from the census counts for many areas, producing discontinuities in time series of ACS estimates.

Full evaluation of the current procedures for producing the controls, as well as of alternative procedures that are under development (see Section 7-D.4 below and Recommendation 5-3), requires 2010 census counts for comparative assessment. However, work can proceed now to design the evaluation program. Moreover, it could be helpful to conduct more extensive analyses that compare the 1999 population estimates with the 2000 census counts (see Section 5-D). In addition, analysis should be conducted, beginning with the 2005 ACS data, of how much difference the controls make to the ACS survey weights and to identify systematic patterns of large upward and downward adjustments that merit investigation. Also, research should be conducted to assess the effects of errors in the population controls on ACS estimates of characteristics, and users should be made aware of the results.

Evaluation of the population controls requires research that should be low cost, although given the many responsibilities of Census Bureau staff, the Bureau may want to arrange for outside researchers to work collaboratively with Bureau analysts. Additional resources will be required for work to improve the methods for producing the population (and housing) controls on the basis of evaluation results and to implement new methods on a production basis. However, the costs can be spread over several Census Bureau programs, not just the ACS, given the many uses of the population estimates.

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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Residence Rules For many purposes, including comparisons with the 2010 census and with the annual population estimates, it is critical to conduct research to understand the implementation of the 2-month residence concept in the ACS and its effects on estimates for geographic areas and population groups. Experiments should be included in the ACS methods panels to determine how respondents interpret the 2-month residence rule in deciding whom to include and not include on the questionnaire and how their responses differ when they are asked to apply the census usual residence rule (see Recommendation 4-6). Such research could identify needed changes to question wording and instructions for reporting residence that would make reporting more consistent with the rules. The Census Bureau plans—and the panel supports—a program of annual methods panels, so that there should be little additional cost of the recommended research.


Estimates of Change A major focus for many data users in using the ACS is to examine estimates of change—from the preceding year, from the last census—for geographic areas and population groups of interest. The ACS provides successive 1-year and (once the necessary data are accumulated) 3-year and 5-year period estimates, but not direct estimates of change. As discussed in Chapters 3 and 6, using period estimates to track trends over time, particularly the 3-year and 5-year estimates, is not straightforward and the interpretation may often be unclear. Users will need specific, detailed guidance on how to work with the period estimates for time-trend analyses if they are not to be frustrated in their use of the ACS.


Comparisons with Other Data Sources It is important that the Census Bureau periodically compare selected ACS estimates with the corresponding estimates from other surveys and administrative records—for example, comparing ACS estimates of income and employment with those from the CPS and the IRS Statistics of Income, or comparing ACS estimates of housing characteristics with those from the American Housing Survey and administrative records. The Census Bureau established a precedent for this kind of work when it performed a large number of aggregate comparisons between estimates from the Census 2000 Supplementary Survey and the 2000 long-form sample; these comparisons helped establish the validity of the ACS (see Section 2-B).

It is often difficult to develop valid comparisons given that data sources differ in details of definitions, data collection operations, and other features. Moreover, analysts cannot assume that a particular comparison source is a gold standard of truth, as all data sets contain errors. Nonetheless, when well executed, aggregate comparisons can document differences in estimates and suggest reasons for differences. In turn, these findings can stimulate further research on which data source—the ACS or another—appears to be

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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more accurate and ways to improve the ACS, the other source, or both. In addition, such comparisons are important to establish face validity of the ACS for users who have long relied on other data sources.


Automated Tools and Standardized, Well-documented Procedures for Data Quality Review While the Census Bureau has made strides in this area, it should conduct further testing and implementation of tools and procedures that can facilitate careful and timely review of the quality of ACS estimates by Bureau analysts (see Recommendation 4-14). When multiple estimates—1-year, 3-year, and 5-year period estimates for geographic areas and population groups—begin to pour out of the data collection and processing system (beginning in 2008 for 3-year period estimates and 2010 for 5-year period estimates), the Census Bureau must be in a position to cope with them. Users will expect the Census Bureau to keep to its announced schedule of releasing all estimates within 8–10 months of the end of data collection and, at the same time, to minimize obvious errors in the estimates (for example, assigning a group quarters to an incorrect geographic location or misaligning the decimal place in coding income). Having the best automated tools and documented procedures possible will be essential to enable the Census Bureau’s analysts to do a good job of data quality review under tight time schedules and constrained staff resources.

7-C.3.b
Other Areas for ACS Research and Evaluation

In addition to the seven high-priority topics discussed in Section 7-C.3.a above, the panel believes that six other areas are important to include in the ACS research program. Work in these areas should move forward to the extent that resources permit.

Four of the six areas involve research and consultation with users that, if possible, would be useful to complete in time to make decisions on whether to change certain features of the ACS 3-year and 5-year period data products before these products are first released. The required research in each of these four areas could be largely based on low-cost simulations of the advantages and disadvantages of alternative approaches:

  • Determination of the universe for the survey—specifically, whether to drop some or all group quarters from the ACS to save resources, and, if some or all group quarters are retained, which tables to present for the total population, household population, and group quarters population to be most useful for users (see Recommendations 4-7 and 4-12).

  • Refinement of confidentiality protection procedures for 3-year and 5-year period estimates to recognize the protection afforded by

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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averaging over 36 and 60 months of data and consideration of including month of interview in the PUMS (see Recommendations 4-8 and 4-9).

  • Assessment of the inflation adjustments for 1-year, 3-year, and 5-year period income and housing value and cost estimates to determine if the current procedures best serve the needs of users and the costs and benefits of alternative procedures, including no adjustments at all (see Recommendation 4-11). In addition, guidance should be developed to help users interpret ACS dollar estimates with the current inflation adjustment procedures, and provisions should be made to provide unadjusted estimates to users who need them them.

  • Determination of geographic areas for publication (see Recommendation 4-13): Does it makes sense—considering user needs, feasibility, and effects on precision of estimates—to reduce the population threshold for 1-year period estimates from 65,000 to 50,000 and to develop and publish 3-year (and possibly 1-year) period estimates for components of PUMAs?

The other two areas that would benefit from research involve data collection modes and weighting adjustments:

  • Experimentation on the response effects of the different data collection modes used in the ACS—mailout-mailback, CATI, and CAPI (see Recommendation 4-5). This topic is important because of the large proportion of responses that the ACS obtains from CAPI or CATI and not the original mailout mode and the likelihood that mode of collection differentially affects responses. Mode effect experiments could be included in an ACS methods panel.

  • Assessment of the effects of the various steps in the weighting process for producing 1-year period estimates (that is, the steps other than the housing unit and population controls) (see Recommendation 5-1). Although not as important as research on the population and housing controls, analysis of the other weighting steps could be useful to identify possible ways to simplify the process and modify one or more steps to improve the precision and accuracy of the ACS estimates.

The quality profile outline provided in Section 7-C.1 above lists other topics for research and evaluation in addition to those the panel specifically addressed. Although these topics were not singled out by the panel, they should not be lost sight of when the Census Bureau is allocating research resources. In particular, two related topics that warrant investigation

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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whenever resources become available are methods to impute missing data responses and methods to include the variability from item imputation in addition to sampling error in estimating the standard errors of ACS estimates. Item nonresponse is less of a problem than it was in the 2000 long-form sample, but the effects of the imputation procedures should still be investigated. The Census Bureau should also investigate the utility of using more sophisticated imputation methods than those currently being employed. It should evaluate alternative methods for including the variability from item imputation in the estimates of the sampling errors for estimates from the ACS (see Bell [2006] for research on including imputation in variances for estimates from the 2000 census).

Finally, it will be important for the Census Bureau to have a process for periodically reviewing its research and evaluation priorities and adjusting them as appropriate. It may be that an area thought to be of pressing concern appears less so upon initial investigation, whereas an area that was not high priority to begin with becomes of increasing concern for uses of the data. Close consultation with users and monitoring of ACS data quality will help the Census Bureau keep its research and evaluation program on track.

The Census Bureau will also need to periodically reevaluate its research priorities in light of available funding and staff. The Census Bureau should plan its research and evaluation program from the beginning to involve both intramural projects by its own staff and extramural work by outside researchers. In this way, it can better ensure that there are always highly qualified researchers actively assessing the ACS even if in-house staff are pulled away on production and other priorities.

7-C.3.c
Recommendation for Research Priorities

Recommendation 7-9: The Census Bureau should assign priority to the following topics for research and development: sample size and allocation; the MAF; population controls; residence rules; estimates of change with multiyear averages; comparisons with other surveys and administrative records; and the development of automated tools for data quality review of ACS products.

7-D
A VISION FOR THE FUTURE

At the present time, the ACS is viewed by the Census Bureau and data users primarily as a replacement for the long-form sample. While the panel agrees with that thrust in the short term, neither the Census Bureau nor the user community should lose sight of the vast potential for the ACS to

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

contribute to new and improved measurement over the longer term. The continuous design of the ACS, which may initially challenge users to adapt their long-form-sample-based applications to the new data, provides the platform for developing important innovative applications for the future.

There are at least five ways in which the ACS could contribute to new and improved measurement. They involve (1) more timely and accurate measures of key indicators for small geographic areas by combining information from the ACS, other surveys, and administrative records; (2) measures of seasonal population fluctuations and multiple residences; (3) cost-effective, up-to-date data collection for rare populations; (4) improved population estimates; and (5) improved estimates from other household surveys (other surveys may also help improve the ACS).

7-D.1
Small-Area Estimates

The planned ACS estimates for geographic areas involve accumulating and averaging 12, 36, and 60 months of data, depending on population size. For small counties, cities, and other areas for which 3-year or 5-year period estimates are provided, many users would very likely prefer continuously updated 1-year estimates for the latest year rather than estimates that represent an average over a longer period of time.

Modern small-area estimation methods that borrow information across time, geography, and data sources could be used to develop indirect 1-year period estimates for key indicators, such as poverty, unemployment, food stamp participation, and others, for all counties and cities (not just those with fewer than 65,000 people). Statistical models could use data from the ACS and relevant administrative records to generate indirect estimates that would likely improve on the direct ACS estimates in precision, accuracy, and currency. Depending on the availability of administrative records, the indirect estimates might lag the latest release of the period estimates, although models could possibly be developed to project the indirect estimates forward 1 or 2 years to represent the latest year.

Small-area estimation models that use the ACS could also incorporate estimates from other surveys when those surveys are believed to provide estimates of higher quality than the ACS estimates. For example, the Current Population Survey (CPS) very likely provides more accurate measures of labor force, employment, and unemployment status than the ACS (see Section 2-B.2.e). The CPS includes a more detailed set of questions and has other design features, such as a fixed reference week for measurement, to reduce nonsampling error.4 Although the CPS sample size, even when accumulated for 12 months, does not support precise estimates for subnational

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

areas except for a few large states, it could play an important role in small-area model-based estimates from the ACS by providing controls so that the ACS estimates reflect the best available national and regional estimates.

A substantial amount of work needs to be carried out to make indirect estimation a reality for the ACS. The Census Bureau has already taken some important initial steps (see Bell, 2006; Chand and Alexander, 1997; Huang and Bell, 2005). In addition, the Census Bureau’s Small Area Income and Poverty Estimates (SAIPE) models and its Small Area Health Insurance Estimates (SAHIE) models are closely related to the models that might be worthwhile to develop for the ACS, as are the models used for the Bureau of Labor Statistics’ Local Area Unemployment Statistics (LAUS) program.5

The SAIPE models of poverty and median income for states, counties, and school districts currently use data from the CPS Annual Social and Economic Supplement (CPS ASEC), federal income tax records, food stamp records, the 2000 census long-form sample, and census-based population estimates. Census Bureau researchers have conducted work on the potential for school lunch program records, earned income tax credit records, and Medicaid records to improve the SAIPE models. The SAHIE models of health insurance coverage for states and counties currently use data from the CPS ASEC, federal income tax records, food stamp records, Medicaid records, and census-based population estimates.

The LAUS models of employment and unemployment for states and a few other large areas currently use data from the monthly CPS (current and historical estimates); the monthly Current Employment Statistics (CES) program, which surveys a large number of nonfarm business establishments; and state unemployment insurance (UI) records. The LAUS estimates for smaller areas, such as counties and cities, are constructed through a building-block approach that uses data from the CPS, the CES program, state UI systems, and the 2000 census long-form sample.

Presumably, the inclusion of the ACS in all of these models, which are designed to improve the CPS estimates, could result in small-area estimates that are more precise than the current model-based estimates. As noted above, models could also be developed to improve the ACS direct estimates by producing more precise small-area estimates that represent a current (or recent) time period instead of averages over a longer time period.

Three caveats are in order. First, it is not clear how strong a predictive model can be developed that would improve on the ACS period estimates for many of the characteristics of interest. Second, the effort required to

5

For SAIPE, see National Research Council, 2000a, 2000b; http://www.census.gov/hhes/www/saipe/saipe.html; for SAHIE, see http://www.census.gov/hhes/www/sahie/index.html; for LAUS, see http://www.bls.gov/lau/lauov.htm.

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

generate a set of indirect estimates for one characteristic, say, the poverty rate, may not provide much information for the development of indirect estimates for another characteristic, say, employment. Third, if a multi-variate approach is used to exploit the correlations that exist among ACS estimates, the complexity of the modeling task is greatly increased. Consequently, a program to develop a large number of indirect estimates would take substantial time and resources. Yet the payoffs could be great from selected indirect estimates that are continuously updated for such purposes as fund allocation.

7-D.2
Seasonal and Multiple Residences

The long-form sample could not provide information on seasonal fluctuations in population, which characterize many localities, because it was conducted at a point in time and asked only about the location of the respondent’s usual residence. In contrast, the ACS is conducted continuously and asks respondents to employ a 2-month residence rule. The current data processing and estimation system for the ACS ignores the month-by-month information, producing instead period estimates for 1, 3, and 5 years that are controlled to census-based population and housing unit estimates as of July 1 of a specific year. However, the Census Bureau’s use of monthly data to produce pre– and post–Hurricane Katrina and Rita profiles for affected areas in the Gulf Coast demonstrates that it could be not only feasible, but also very valuable to produce such profiles for other areas.

To investigate the feasibility of producing part-year data for specified areas on a regular basis, the Census Bureau should conduct research on the extent to which the ACS monthly data exhibit significant seasonal variations in total population and key characteristics for localities expected to have such variations. It would be important to inform this analysis from the results of the test recommended by this panel and the Panel on Residence Rules in the Decennial Census on how respondents record their residence using the ACS 2-month rule compared with the census usual residence rule. This test may identify responses that do not accord with the 2-month rule that can be ameliorated by changes in question wording and instructions for the ACS.

The outcome of research on seasonal residence could be special data products for areas that have significant seasonal fluctuations, which would represent a major addition to the stock of useful information for them. One problem concerns sample size, given that seasonal change may be evident only for small areas. To the extent that seasonal patterns tend to be repeated each year, it would be possible, and likely essential, to combine multiple years of data in order to produce sufficiently precise estimates of part-year populations for affected areas.

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

In addition to estimates of seasonal population fluctuations, the ACS could be a vehicle for information about multiple residences more generally—for example, people with weekday and weekend homes or students away at college or boarding school. Questions that may be needed to improve reporting of residence using the 2-month rule, such as whether a household member has another residence, could also provide useful information on multiple residences. Such information would be valuable not only for planning and research, but also for designing coverage improvement programs for the decennial census.

7-D.3
Surveying Rare Populations

The census long-form sample has historically provided the basis for follow-up surveys for specific, relatively small, or “rare,” populations, such as scientists and engineers and low-income minorities. By using the long-form sample to identify a population of interest for follow-up after the census, targeted postcensus surveys could be more cost-effective than nontargeted stand-alone surveys, which require much larger sample sizes to capture enough cases of the rare population of interest.

The ACS can similarly provide the basis for sampling a small targeted population by serving as the initial screener to identify specific households or persons for interview. (ACS data can also be used to identify areas with a higher percentage of the target population for selecting a sample, using more current data than the long-form sample.) The ACS has the advantage that it can be used for this purpose more often than once a decade, although care will need to be taken to minimize respondent burden and provide for informed consent for any follow-on survey.

There is a procedure for identifying and testing new questions to be included in the ACS, which could potentially expand its use as a screener. For example, a question on field of bachelor’s degree is planned for testing in the 2007 Methods Panel. If the question is added to the ACS, it will be used to target a sample of people in science and engineering fields to support the work of the National Science Foundation. Of course, there is a limit on how many questions can be added to the ACS without an adverse effect on response rates and public perception of the survey, unless some questions can be identified for deletion. Moreover, all ACS questions are mandatory, which makes it incumbent on the Census Bureau to consider the response burden of any new questions very carefully.

7-D.4
Improving Population Estimates

There is a pressing need for the Census Bureau to conduct research on methods to improve the estimates of population by age, sex, race, and ethnicity that are used as controls for the ACS and serve so many other

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

important purposes, such as providing factors for fund allocation formulas, controls for other household surveys, and denominators for vital rates. Information from the ACS on place of birth, citizenship, and year of immigration is already used to generate estimates of net migration from abroad for the population estimates program, and the Census Bureau is interested in examining other components of the estimates that might benefit from ACS information. For example, ACS estimates might supplement IRS tax records to estimate internal migration at the county level and perhaps for smaller geographies.

The ACS could also possibly improve the population estimates and its own coverage of population and housing through linkages with the Census Bureau’s E-StARS program (see Section 4-A.4). The E-StARS Master Address Auxiliary File could be used to improve the MAF, which would in turn improve the ACS coverage of housing units. (At present, the MAF provides input to E-StARS, but there is no feedback loop back to the MAF.) Going a next step, ACS estimates of occupancy rates and persons per household could possibly be used with an improved MAF count to generate an alternative set of population estimates to compare with the estimates that are produced from the current component method (see Section 5-C). Yet another approach is to use E-StARS to provide population controls for subcounty areas within the framework of the existing population estimates. The Census Bureau has begun work along these lines, which should be pursued.

Critical to making progress toward improved population estimates is for the Census Bureau to design and conduct an extensive evaluation program of alternative estimation methods and data sources in conjunction with the 2010 census. In planning and evaluating its research, the Census Bureau should involve knowledgeable users and producers of population estimates, such as the members of the Federal State Cooperative Program for Population Estimates.

7-D.5
Improving Survey Estimates

Most items on the ACS questionnaire are covered in other household surveys, often in much more detail. For example, as noted in Section 7-D.1 above, the monthly CPS, which provides the nation’s official measure of unemployment, includes additional questions about work status beyond those used in the ACS to determine each respondent’s labor force situation. Other surveys that overlap with the ACS include the American Housing Survey, the CPS Annual Social and Economic Supplement, the Survey of Income and Program Participation, the National Health Interview Survey, and the National Household Travel Survey. These other surveys not only obtain extensive information about their primary topic, but also typically include a large number of additional variables for use in analysis. However, they rarely provide state, or substate, estimates.

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

A critical question for the future of federal statistics is in what ways the ACS can contribute to and in what ways it can borrow strength from the other major national household surveys. At this early stage of implementation of the ACS, it would be foolish to think about dropping or curtailing another survey because its content overlaps with the ACS. Instead, what is needed is in-depth research to compare estimates, determine the strengths and weaknesses of each, and develop methods to improve both the ACS and other surveys. Each will undoubtedly continue to have an important role to play—the ACS primarily by providing small-area estimates and other household surveys primarily by supporting rich, multivariate policy analysis and basic social science research. The challenge will be to integrate the ACS and other surveys in ways that strengthen them all.

One way in which the ACS can help other household surveys involves the MAF sampling frame. Assuming that the advent of the ACS will lead to continuous updating and improvement of the MAF (see Section 4-A.4), it should be possible to update the sampling frames for other surveys more than once a decade. Indeed, the Census Bureau plans to adopt the MAF as the sampling frame for its other household surveys. In addition, responses to the ACS could be used to identify population groups of interest for oversampling in other surveys.

With regard to improved estimates for overlapping content items, the ACS could likely help other surveys—and vice versa—in several ways. For example, if research establishes that ACS estimates of a particular item are comparable with those for that item in another survey, the ACS could provide valuable controls for the other survey. But if research establishes that the ACS estimates are less accurate than those from another survey, estimates from the other survey might be used to calibrate the ACS estimates for small subgroups in some simple model-based way.

For key items of national importance, it might become possible to use the ACS, other surveys, and administrative records to develop the best estimates for the nation, states, and, possibly, substate areas. These estimates could be published as independent time series, similar to the estimates of gross domestic product, which draw on many data sources.

7-D.6
Recommendation for Future Research and Development

Recommendation 7-10: As part of its research and development program for the ACS, the Census Bureau should dedicate a portion of resources to pursue innovative, longer term projects. While short-term research and development must focus on the ACS as a replacement for the census long-form sample, research must also address how the ACS can improve the nation’s information on population and housing in ways that were not possible with the long-form sample and may not even be envisioned today.

Suggested Citation:"PART III: Education, Outreach, and Future Development, 7 Important Next Steps." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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The American Community Survey (ACS) is a major new initiative from the U.S. Census Bureau designed to provide continuously updated information on the numbers and characteristics of the nation’s people and housing. It replaces the “long form” of the decennial census. Using the American Community Survey covers the basics of how the ACS design and operations differ from the long-form sample; using the ACS for such applications as formula allocation of federal and state funds, transportation planning, and public information; and challenges in working with ACS estimates that cover periods of 12, 36, or 60 months depending on the population size of an area.

This book also recommends priority areas for continued research and development by the U.S. Census Bureau to guide the evolution of the ACS, and provides detailed, comprehensive analysis and guidance for users in federal, state, and local government agencies, academia, and media.

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