Using the American Community Survey

Benefits and Challenges

Panel on the Functionality and Usability of Data from the American Community Survey

Constance F. Citro and Graham Kalton, Editors

Committee on National Statistics

Division of Behavioral and Social Sciences and Education

NATIONAL RESEARCH COUNCIL
OF THE NATIONAL ACADEMIES

THE NATIONAL ACADEMIES PRESS

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Using the American Community Survey: Benefits and Challenges Using the American Community Survey Benefits and Challenges Panel on the Functionality and Usability of Data from the American Community Survey Constance F. Citro and Graham Kalton, Editors Committee on National Statistics Division of Behavioral and Social Sciences and Education NATIONAL RESEARCH COUNCIL OF THE NATIONAL ACADEMIES THE NATIONAL ACADEMIES PRESS Washington, D.C. www.nap.edu

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Using the American Community Survey: Benefits and Challenges THE NATIONAL ACADEMIES PRESS 500 Fifth Street, N.W. Washington, DC 20001 NOTICE: The project that is the subject of this report was approved by the Governing Board of the National Research Council, whose members are drawn from the councils of the National Academy of Sciences, the National Academy of Engineering, and the Institute of Medicine. The members of the committee responsible for the report were chosen for their special competences and with regard for appropriate balance. The project that is the subject of this report was supported by contract number YA132304CN0006 between the National Academy of Sciences and the U.S. Census Bureau. Support of the work of the Committee on National Statistics is provided by a consortium of federal agencies through a grant from the National Science Foundation (award number SBR-0453930). Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the organizations or agencies that provided support for the project. Library of Congress Cataloging-in-Publication Data Using the American community survey : benefits and challenges / Panel on the Functionality and Usability of Data from the American Community Survey, Constance F. Citro and Graham Kalton, editors ; Committee on National Statistics, Division of Behavioral and Social Sciences and Education. p. cm. Includes bibliographical references and index. ISBN-13: 978-0-309-10672-6 (pbk. perfect bound : alk. paper) ISBN-10: 0-309-10672-9 (pbk. perfect bound : alk. paper) 1. American community survey. 2. Household surveys—United States. 3. United States—Census. I. Citro, Constance F. (Constance Forbes), 1942- II. Kalton, Graham. III. National Research Council (U.S.). Panel on the Functionality and Usability of Data from the American Community Survey. IV. National Research Council (U.S.). Committee on National Statistics. HA37.U55U85 2007 317.3—dc22 2007024090 Additional copies of this report are available from the National Academies Press, 500 Fifth Street, NW, Washington, DC 20001; (800) 624-6242 or (202) 334-3313 (in the Washington metropolitan area); Internet, http://www.nap.edu Printed in the United States of America Copyright 2007 by the National Academy of Sciences. All rights reserved. Suggested citation: National Research Council. (2007). Using the American Community Survey: Benefits and Challenges. Panel on the Functionality and Usability of Data from the American Community Survey, Constance F. Citro and Graham Kalton, Editors. Committee on National Statistics, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

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Using the American Community Survey: Benefits and Challenges THE NATIONAL ACADEMIES Advisers to the Nation on Science, Engineering, and Medicine The National Academy of Sciences is a private, nonprofit, self-perpetuating society of distinguished scholars engaged in scientific and engineering research, dedicated to the furtherance of science and technology and to their use for the general welfare. Upon the authority of the charter granted to it by the Congress in 1863, the Academy has a mandate that requires it to advise the federal government on scientific and technical matters. Dr. Ralph J. Cicerone is president of the National Academy of Sciences. The National Academy of Engineering was established in 1964, under the charter of the National Academy of Sciences, as a parallel organization of outstanding engineers. It is autonomous in its administration and in the selection of its members, sharing with the National Academy of Sciences the responsibility for advising the federal government. The National Academy of Engineering also sponsors engineering programs aimed at meeting national needs, encourages education and research, and recognizes the superior achievements of engineers. Dr. Charles M. Vest is president of the National Academy of Engineering. The Institute of Medicine was established in 1970 by the National Academy of Sciences to secure the services of eminent members of appropriate professions in the examination of policy matters pertaining to the health of the public. The Institute acts under the responsibility given to the National Academy of Sciences by its congressional charter to be an adviser to the federal government and, upon its own initiative, to identify issues of medical care, research, and education. Dr. Harvey V. Fineberg is president of the Institute of Medicine. The National Research Council was organized by the National Academy of Sciences in 1916 to associate the broad community of science and technology with the Academy’s purposes of furthering knowledge and advising the federal government. Functioning in accordance with general policies determined by the Academy, the Council has become the principal operating agency of both the National Academy of Sciences and the National Academy of Engineering in providing services to the government, the public, and the scientific and engineering communities. The Council is administered jointly by both Academies and the Institute of Medicine. Dr. Ralph J. Cicerone and Dr. Charles M. Vest are chair and vice chair, respectively, of the National Research Council. www.national-academies.org

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Using the American Community Survey: Benefits and Challenges PANEL ON THE FUNCTIONALITY AND USABILITY OF DATA FROM THE AMERICAN COMMUNITY SURVEY GRAHAM KALTON (Chair), Westat, Rockville, MD PAUL P. BIEMER, RTI International, Research Triangle Park, NC NANCY DUNTON, School of Nursing, University of Kansas, Kansas City MARTIN R. FRANKEL, Zicklin School of Business, Baruch College, New York D. TIM HOLT, University of Southampton, United Kingdom (emeritus) SHARON LOHR, Department of Mathematics and Statistics, Arizona State University, Tempe CHARLES L. PURVIS, Metropolitan Transportation Commission, Oakland, CA JOSEPH J. SALVO, New York City Department of City Planning HAL S. STERN, Department of Statistics, University of California, Irvine CONSTANCE F. CITRO, Co-Study Director MICHAEL L. COHEN, Co-Study Director DANIEL L. CORK, Senior Program Officer BARBARA A. BAILAR, Consultant F. JAY BREIDT, Consultant MEYER ZITTER, Consultant AGNES E. GASKIN, Senior Program Assistant

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Using the American Community Survey: Benefits and Challenges COMMITTEE ON NATIONAL STATISTICS 2006-2007 WILLIAM F. EDDY (Chair), Department of Statistics, Carnegie Mellon University KATHARINE ABRAHAM, Department of Economics, University of Maryland, and Joint Program in Survey Methodology ROBERT BELL, AT&T Research Laboratories, Florham Park, NJ WILLIAM DuMOUCHEL, Lincoln Technologies, Inc., Waltham, MA JOHN HALTIWANGER, Department of Economics, University of Maryland V. JOSEPH HOTZ, Department of Economics, University of California, Los Angeles KAREN KAFADAR, Department of Mathematical Sciences, University of Colorado at Denver and Health Sciences Center DOUGLAS MASSEY, Department of Sociology, Princeton University VIJAY NAIR, Department of Statistics and Department of Industrial and Operations Engineering, University of Michigan JOSEPH NEWHOUSE, Division of Health Policy Research and Education, Harvard University SAMUEL H. PRESTON, Population Studies Center, University of Pennsylvania KENNETH PREWITT, School of International and Public Affairs, Columbia University LOUISE RYAN, Department of Biostatistics, Harvard University NORA CATE SCHAEFFER, Department of Sociology, University of Wisconsin–Madison ALAN ZASLAVSKY, Department of Health Care Policy, Harvard Medical School CONSTANCE F. CITRO, Director

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Using the American Community Survey: Benefits and Challenges Acknowledgments The Panel on the Functionality and Usability of Data from the American Community Survey (ACS) wishes to thank the many people who contributed to the panel’s work. As the sponsor of the project, the U.S. Census Bureau—under the leadership of director Louis Kincannon and then-deputy director Hermann Habermann—provided consistent and strong support as we reviewed the utility of ACS estimates and data products and related issues. As associate director for decennial census, and in his new role as deputy director, Preston J. Waite set the basic direction for the 2010 census and the replacement of the traditional census long-form sample with the new ACS; he provided considerable advice during the panel’s meetings and also served as a discussant at a session at the 2006 Joint Statistical Meetings in Seattle describing the panel’s work. The communication between the panel and Census Bureau throughout the study was greatly facilitated by the efforts of Philip Gbur as contracting officer and David Hubble (now of Westat) as lead technical liaison. Both were always readily accessible and extremely helpful in providing answers to questions. Before his retirement from the Census Bureau, Rajendra Singh ably assisted in interactions with the panel, for which we are grateful. Further, a number of Census Bureau staff made very informative presentations to the panel or provided useful materials, including Teresa Angueira, Lisa Blumerman, Robert Fay, Deborah Griffin, Douglas Hillmer, David Hubble, Lawrence McGinn, J. Gregory Robinson, and Signe Wetrogan. We are also greatly indebted to Mark Asiala, Alfredo Navarro, Michael

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Using the American Community Survey: Benefits and Challenges Starsinic, and Lynn Weidman for answering detailed methodological questions and for carrying out computations that were requested by the panel. Finally, Census Bureau staff made available an early draft of a technical report on ACS design and methodology (U.S. Census Bureau, 2006, see http://www.census.gov/acs/www), which the panel found very useful in its work. Unfortunately, our panel did not have the ability to directly interact with the late Charles (Chip) Alexander, the key architect of the data collection program that would become the ACS. His death in 2003 left a void that the Census Bureau—indeed, the entire federal statistical system—still struggles to fill. Throughout our work, though, we have benefited from the ideas embodied in his writings and greatly appreciate them. As consultant to the panel, F. Jay Breidt (Department of Statistics, Colorado State University) prepared two extremely useful papers and associated presentations on alternative estimands from the ACS multiyear data and the use of population controls for ACS estimates at various levels of aggregation. These papers helped the panel develop its ideas on these important topics, and we are greatly pleased to include them as appendixes to this report. In April 2005, the panel convened a special meeting on user perspectives, emphasizing the current uses of census long-form-sample data by state and local organizations, as well as the media, and the prospects for use of ACS data by these constituencies. Panel members Nancy Dunton, Chuck Purvis, and Joe Salvo were particularly instrumental in assembling this group. We thank the participants in that meeting for their time and insightful comments: Sarah Breshears (State Data Center, University of Arkansas at Little Rock), Warren Brown (Cornell Institute for Social and Economic Research), Nathan Erlbaum (New York State Department of Transportation), Linda Gage (California Department of Finance, Demographic Research Unit), Jeff Hardcastle (University of Nevada, Reno), John McHenry (Demographic Data for Decision-Making, Inc.), Paul Overberg (USA TODAY), Richard Rathge (Department of Agribusiness and Applied Economics, North Dakota State University), Ed Schafer (San Diego Association of Governments), and David Swanson (Department of Sociology and Anthropology, University of Mississippi). Subsequent discussions with Gage, Hardcastle, and Overberg were also very helpful to the panel. Over the course of our regular meetings, we benefited from presentations and discussions from a wide variety of data users from federal and state agencies. We thank Chris Chapman (National Center for Education Statistics), George Hough (Oregon State Data Center and Portland State University), Sandra Mason (Bureau of Labor Statistics), Elaine Murakami (Federal Highway Administration), Thomas Nardone (Bureau of Labor Statistics), Donald Oellerich (Office of the Assistant Secretary for Plan-

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Using the American Community Survey: Benefits and Challenges ning and Evaluation, U.S. Department of Health and Human Services), William O’Hare (Annie E. Casey Foundation), Alan Pisarski (consultant), Ann Poliska (Bureau of Labor Statistics), Susan Schechter Bortner (then of the U.S. Office of Management and Budget), Marilyn Seastrom (National Center for Education Statistics), and Ronald Sepanik (U.S. Department of Housing and Urban Development). Another of our panel meetings included presentations by Jay Breidt on his commissioned papers and very helpful comments and suggestions from four discussants: David Binder (Statistics Canada, retired), Wayne Fuller (Iowa State University), Eric Slud (University of Maryland), and Alan Zaslavsky (Harvard Medical School Department of Health Care Policy). We also appreciate the comments offered by Allen Schirm (Mathematica Policy Research, Inc.) as a discussant on the panel’s work at a session of the 2006 Joint Statistical Meetings. Our panel was one of three concurrent panel studies conducted by the Committee on National Statistics (CNSTAT) on aspects of the decennial census. Though the panels covered substantially different subject areas, we benefited from interactions with members of our sister panels, the Panel on Residence Rules in the Decennial Census and the Panel on Correlation Bias and Coverage Measurement in the 2010 Census. Paul Voss (Department of Rural Sociology, University of Wisconsin-Madison, emeritus) merits particular credit; during his period of service as chair of the residence rules panel, he also participated in several of our panel’s meetings (including the April 2005 special meeting on user perspectives) and provided very important comments throughout the process. The panel is especially indebted to Constance Citro, director of CNSTAT, who drafted most of the chapters of the report and provided much of the insight on the use of census long-form-sample data products for which the ACS is serving as a replacement. Her wide experience on census issues, her extremely clear writing style, and the clarity of her reasoning were of essential importance to the panel’s success. Michael Cohen, assisted by Daniel Cork and Meyer Zitter, organized the work of the panel’s meetings and interactions with Census Bureau staff, data users, and others. Barbara Bailar, serving as consultant to the panel, took the lead in the initial drafting of two chapters of the report. Christine McShane provided expert technical editing of the draft report. Finally, Agnes Gaskin provided all of the administrative support for the panel, smoothly arranging travel and meetings, including two off-site meetings, and Bridget Edmonds assisted in preparation of the manuscript. In addition to a session at the 2006 Joint Statistical Meetings, the panel made use of other opportunities to discuss the general nature of its work and to solicit ideas. In particular, we benefited from interaction with the Association of Public Data Users; at their 2004 annual meeting, members of the panel discussed general themes and issues for its work and

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Using the American Community Survey: Benefits and Challenges received extremely helpful feedback in response. An update was provided at the association’s 2006 annual meeting. Similarly, we gained insight from comments by Andrew Reamer (The Brookings Institution) and others on presentations at a November 2006 Washington Statistical Society seminar and at meetings of the Federal State Cooperative Program for Population Estimates (FSCPE). We also appreciated the opportunity to mention the panel’s work at a meeting of the Census Information Center/FSCPE/State Data Center steering committee in early 2007. Most importantly, I am indebted to the members of the Panel on the Functionality and Usability of Data from the American Community Survey. They were extremely hard working, providing draft text and comments on several rounds of drafts on a difficult subject. Special kudos go to Tim Holt, who happily traveled across the Atlantic for the work of the panel, and Joe Salvo, who took the lead on sections of the report dealing with user education and applications of the data. He was assisted in the preparation of a case study (in Chapter 3 of the report) by Jennifer Jensen of the New York City Department of City Planning. This report and appended papers have been reviewed in draft form by individuals chosen for their diverse perspectives and technical expertise, in accordance with procedures approved by the Report Review Committee of the National Research Council (NRC). The purpose of this independent review is to provide candid and critical comments that will assist the institution in making the published report as sound as possible and to ensure that the report meets institutional standards for objectives, evidence, and responsiveness to the study charge. The review comments and draft manuscript remain confidential to protect the integrity of the deliberative process. We thank the following individuals for their participation in the review of the report or the papers: Katharine G. Abraham, Joint Program in Survey Methodology, University of Maryland; Patricia C. Becker, President, APB Associates, Southfield, MI; David Binder, Methodology Branch, Statistics Canada (retired); Manning Feinlieb, Bloomberg School of Public Health, Johns Hopkins University; Ken Hodges, Data Research and Development, Claritas Inc., Ithaca, NY; James Lepkowski, Institute for Survey Research, University of Michigan; Elaine Murakami, Office of Planning, Federal Highway Administration, U.S. Department of Transportation; Jean Opsomer, Department of Statistics and Center for Survey Statistics and Methodology, Iowa State University; Eric V. Slud, Department of Mathematics, University of Maryland; David A. Swanson, Department of Sociology and Anthropology and Center for Population Research, University of Mississippi; John H. Thompson, Executive Vice President, The National Opinion Research Center, Chicago, IL; and Alan M. Zaslavsky, Department of Health Care Policy, Harvard Medical School.

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Using the American Community Survey: Benefits and Challenges Although the reviewers listed above provided many constructive comments and suggestions, they were not asked to endorse the conclusions or recommendations nor did they see the final draft of the report or the papers before their release. The review of the report was overseen by Douglas Massey, Department of Sociology, Princeton University. Appointed by the NRC, he was responsible for making certain that an independent examination of the report was carried out in accordance with institutional procedures and that all review comments were carefully considered. Responsibility for the final content of this report rests entirely with the authoring panel and the institution. Graham Kalton, Chair Panel on the Functionality and Usability of Data from the American Community Survey

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Using the American Community Survey: Benefits and Challenges Contents     Executive Summary   1 1   Introduction   13      1-A  Panel Charge,   14      1-B  Historical Background,   15      1-B.1  Evolution of the Long-Form Sample,   15      1-B.2  Why Seek an Alternative to the Long-Form Sample?,   16      1-B.3  Evolution of the ACS,   20      1-C  Issues for the Panel,   23      1-D  Overview of the Report,   24 PART I:  Using the American Community Survey     2   Essentials for Users   29      2-A  ACS Design Basics,   29      2-A.1  Population Coverage (Universe),   30      2-A.2  Residence Rules,   31      2-A.3  Content and Reference Periods,   31      2-A.4  Sample Design and Size,   33      2-A.5  Data Collection,   40      2-A.6  Data Products,   42      2-A.7  Data Processing—1-Year Period Estimates,   43      2-A.8  Data Processing—3-Year and 5-Year Period Estimates,   48

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Using the American Community Survey: Benefits and Challenges      2-B  ACS Benefits,   49      2-B.1  Timeliness and Frequency,   49      2-B.2  Data Quality,   51      2-C  ACS Challenges,   61      2-C.1  Period Estimates,   61      2-C.2  Sampling Error,   63      2-D  Summary Assessment,   74 3   Working with the ACS: Guidance for Users   77      3-A  Federal Agency Uses,   79      3-A.1  Allocation of Federal Funds,   80      3-A.2  Determination of Median Incomes for Counties,   87      3-B  State Agency Uses,   94      3-B.1  Allocating State Funds to Localities,   95      3-B.2  Strategies for Using ACS Data in State Fund Allocations,   96      3-B.3  Example of a Simple Updating Procedure,   96      3-C  Local Government Uses,   98      3-C.1  Large City Applications of the ACS,   99      3-C.2  Small Jurisdiction Applications of the ACS,   113      3-C.3  Special Case of Seasonal Populations,   115      3-D  Transportation Planning Uses,   117      3-D.1  Using the ACS 1-Year PUMS Files,   119      3-D.2  Using the ACS TAZ Data,   120      3-D.3  Conclusion on Using the ACS for Transportation Planning,   121      3-E  Academic Research Uses,   121      3-E.1  Using Summary Files for Research,   122      3-E.2  Using PUMS Files for Research,   122      3-F  Media and General Public Uses,   123      3-F.1  Using ACS Profiles and Rankings,   124      3-F.2  Comparisons with Other Data Sources,   125      3-G  What Happens in a Decennial Year?,   127      3-H  Preparing to Use the ACS,   130      3-H.1  General Guidelines for ACS Use,   130      3-H.2  Suggestions for Users During the Ramp-up Period,   134 PART II:  Technical Issues     4   Sample Design and Survey Operations   141      4-A  Sampling Operations for Housing Units,   142      4-A.1  Developing the Initial Sample,   142      4-A.2  Initial Sampling Rates,   144

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Using the American Community Survey: Benefits and Challenges      4-A.3  Subsampling for CAPI Follow-up,   147      4-A.4  MAF Concerns and Recommendations,   148      4-A.5  Sample Design Concerns,   152      4-B  Data Collection for Housing Units,   160      4-B.1  Mode of Collection,   160      4-B.2  Residence Rules,   163      4-C  Group Quarters Sampling and Data Collection,   167      4-C.1  Group Quarters and the MAF,   167      4-C.2  Sample Design for Group Quarters,   168      4-C.3  Data Collection for Group Quarters,   170      4-C.4  Concerns About Group Quarters,   170      4-C.5  Recommendation for Group Quarters,   172      4-D  Data Preparation,   173      4-D.1  Confidentiality Protection,   173      4-D.2  Collapsing Tables for Large Sampling Errors,   177      4-D.3  Inflation Adjustments,   179      4-D.4  Tabulation Specifications,   181      4-D.5  Data Quality Review,   183 5   The Weighting of ACS 1-Year Period Estimates   184      5-A  Overview,   184      5-B  The 1-Year Nine-Step Weighting Process,   186      5-B.1  Base Weights,   187      5-B.2  Variation in Monthly Response Factor,   188      5-B.3  Noninterview Factors 1 and 2,   191      5-B.4  Mode Bias Noninterview Factor,   192      5-B.5  Housing Unit Control Factor 1,   194      5-B.6  Population Control Factor,   194      5-B.7  Housing Unit Control Factor 2,   194      5-B.8  Adjustments to Eliminate Extreme Weights,   195      5-B.9  Rounding of Weights,   195      5-B.10  Recommendation,   196      5-C  Housing Unit Controls,   196      5-D  Population Controls,   201 6   Weighting and Interpreting ACS Multiyear Estimates   209      6-A  Alternative Estimands from Multiyear Data,   210      6-A.1  Single-Year Estimands from Multiyear Data,   210      6-A.2  Multiyear Period Estimand from Multiyear Data,   211      6-B  Multiyear Period Estimation,   212

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Using the American Community Survey: Benefits and Challenges      6-C  Estimation of Change Over Time,   214      6-C.1  Interpreting Estimates of Change Between Multiyear Period Estimates,   215      6-C.2  Precision of Estimates of Change Between Multiyear Period Estimates,   218      6-C.3  Conclusions,   220      6-D  Effects of Changes in Population Size and Characteristics,   221 PART III:  Education, Outreach, and Future Development     7   Important Next Steps   227      7-A  Educating Data Users About the ACS,   229      7-A.1  Key Elements of the Education Strategy,   230      7-A.2  Providing a Foundation for the Basics,   231      7-A.3  Building a Network for Education, Outreach, and Feedback,   233      7-A.4  Working with the Media,   235      7-A.5  Recommendations on User Education, Outreach, and Feedback,   235      7-B  Data Quality Monitoring,   238      7-B.1  Nonsampling Error Measures,   238      7-B.2  Sampling Errors,   239      7-C  Priorities for Assessment and Improvement of Survey Quality,   242      7-C.1  Quality Profile,   242      7-C.2  Methods Panels,   247      7-C.3  The Panel’s Priorities for Assessment,   248      7-D  A Vision for the Future,   254      7-D.1  Small-Area Estimates,   255      7-D.2  Seasonal and Multiple Residences,   257      7-D.3  Surveying Rare Populations,   258      7-D.4  Improving Population Estimates,   258      7-D.5  Improving Survey Estimates,   259      7-D.6  Recommendation for Future Research and Development,   260     References   261

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Using the American Community Survey: Benefits and Challenges APPENDIXES     A  Acronyms and Abbreviations   267 B  Controlling the American Community Survey to Postcensal Population Estimates,  F. Jay Breidt   269 C  Alternatives to the Multiyear Period Estimation Strategy for the American Community Survey,  F. Jay Breidt   290 D  Biographical Sketches of Panel Members and Staff   313 Index to Executive Summary and Chapters 1-7   319

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Using the American Community Survey: Benefits and Challenges Tables 2-1   Types of Residences in the American Community Survey (ACS),   32 2-2   Items on the 2005 ACS Questionnaire and the 2000 Census Long Form,   34 2-3a   Housing Unit Addresses, 2005 ACS and 2000 Census Long-Form Sample: Approximate Initial Block-Level Sampling Rates,   37 2-3b   Housing Unit Addresses, 2005 ACS and 2000 Census Long-Form Sample: Census Tract-Level CAPI Subsampling Rates in the 2005 ACS for Mail/CATI Nonrespondents,   38 2-3c   Housing Unit Addresses, 2005 ACS and 2000 Census Long-Form Sample: Illustrative Rates of Completed Sample Cases,   39 2-4   Types of Governmental Units by Population Size in 2000,   41 2-5   Major Types of Geographic Areas for Which 1-Year, 3-Year, and 5-Year Period Estimates Are Available from the American Community Survey,   46 2-6   Release Year and Calendar Year of Period Estimates from the ACS,   50 2-7a   Illustrative, Approximate Relative Standard Errors (Coefficients of Variation, or CVs) for an Estimate of 15 Percent Poor School-Age Children from the ACS and the 2000 Census Long-Form Sample, by Population Size of Area,   68

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Using the American Community Survey: Benefits and Challenges     2-7b   Illustrative, Approximate 90 Percent Margins of Error (MOEs), Plus or Minus an Estimate of 15 Percent Poor School-Age Children from the ACS and the 2000 Census Long-Form Sample, by Population Size of Area,   70 2-7c   Illustrative, Approximate 90 Percent Confidence Intervals (CIs) Around an Estimate of 15 Percent Poor School-Age Children from the ACS and the 2000 Census Long-Form Sample, by Population Size of Area,   71 2-8   Illustrative, Approximate Relative Standard Errors (Coefficients of Variation, or CVs) for an Estimate of 15 Percent Poor People from the ACS and the 2000 Census Long-Form Sample, by Population Size of Area,   73 3-1   Hypothetical Inflation Adjustments for Person Income in the ACS,   91 3-2   Example of Simple Method to Update ACS 5-Year Period Estimates for 2010–2014 to Latest Year (2014), Four Small Counties (A, B, C, D) in State X, Using Data for Two Public Use Microdata Areas (PUMAs),   97 3-3   School-Age Poverty Rates for BIG CITY/COUNTY and Three Subareas, Illustrative ACS 1-Year, 3-Year, and 5-Year Period Estimates for 2010–2014,   101 3-4   Analyzing Trends Over Time for School-Age Poverty Rates, Illustrative ACS 1-Year Period Estimates, 2010–2014, BIG CITY and VERY BIG CITY,   104 3-5   Analyzing Trends Over Time for School-Age Poverty Rates, Illustrative ACS 5-Year Period Estimates, SMALL CITY or Subarea of BIG CITY with 50,000 People and 10,000 School-Age Children, 2010–2019,   106 3-6   Hypothetical County in Florida with Winter Influx of Residents,   116 3-7   Hypothetical Effect of Decennial Census on ACS 1-Year Period Estimates, BIG CITY, 2008–2012,   129 4-1   Weighted Distribution of Respondents by Mode for Census Tracts with Concentrations of Race and Ethnicity Groups, Census 2000 Supplementary Survey,   162 5-1   Mean Absolute Percentage Error (MAPE) of April 1, 2000, County Housing Unit Estimates Compared to April 1, 2000, Census Counts, by 1990 Size of County,   198 5-2   Distribution of the Housing Unit Control Factor 1 Across Counties in the 2004 ACS,   199 5-3   Mean Absolute Percentage Error (MAPE) of April 1, 2000, County Population Estimates (Official Series) Compared with April 1, 2000, Census Counts by County Population in 2000,   203

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Using the American Community Survey: Benefits and Challenges     5-4   Mean Absolute Percentage Error (MAPE) of July 1, 1999, Estimation Area Population Estimates Compared with April 1, 2000, Census Counts, by Cells Based on Combinations of Sex, Ethnicity, and Age (Excludes Cells with Fewer Than 500 People in the 2000 Census),   204 5-5   Percentage Ratio of July 1, 1999, Estimation Area Population Estimates to April 1, 2000, Census Counts, by Cells Based on Combinations of Sex, Ethnicity, and Age (Excludes Cells with Fewer Than 500 People in the 2000 Census),   206 6-1   Estimates of Poor Families in an Area Assuming a 1 Percent Annual Increase, in Percent,   216 6-2   Estimates of Poor Families in an Area Assuming a 3 Percent Increase in Year 6, in Percent,   217 6-3   Standard Errors of Estimates of Change for Various Values of the Gap Between Two Period Estimators as Multiples of the Standard Errors of a 1-Year Estimator,   218 6-4   Standard Errors of Estimates of Change for Various Values of the Gap Between Two Period Estimators as Multiples of the Standard Errors of the Corresponding Period Estimator,   220

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Using the American Community Survey: Benefits and Challenges Boxes 1-1   Continuous Measurement in Three Countries,   21 2-1   The Puerto Rico Community Survey (PRCS),   30 2-2   Data Products from the American Community Survey,   44 2-3   Sources of Sampling and Nonsampling Error in Survey Estimates,   52 2-4   Four Quality Measures Available for the American Community Survey,   54 2-5   Brief Descriptions of Statistical Terms Used in This Report,   64 3-1   Selected Federal Agency Uses of Census Long-Form-Sample Data,   80 3-2   Selected Uses of Long-Form-Sample Estimates in Federal Fund Allocation Formulas,   82 4-1   Developing the Initial ACS Sample, Phases One and Two, Area X with 20,000 Housing Units (50,000 People),   144 4-2   Illustration of the Effect of CAPI Subsampling on Precision of ACS Estimates,   157 4-3   Residence Rule Guidance on the ACS Mail Questionnaire,   165 4-4   Illustrative Calculation for Suppressing Table Cells with Large Sampling Error, 1-Year ACS Period Estimates,   178 5-1   The Nine-Step Weighting Process for Housing Units and Household Members in 1-Year ACS Data Files,   186 5-2   The Weighting Process for Residents of Group Quarters (GQ) in the 2006 ACS,   187 7-1   Print Media Treatment of the 2005 American Community Survey,   236 7-2   2006 and 2007 American Community Survey Methods Panels,   246

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