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E-grāmata: Realizing the Potential of the American Community Survey: Challenges, Tradeoffs, and Opportunities

  • Formāts: 314 pages
  • Izdošanas datums: 24-Feb-2015
  • Izdevniecība: National Academies Press
  • Valoda: eng
  • ISBN-13: 9780309366793
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  • Formāts: 314 pages
  • Izdošanas datums: 24-Feb-2015
  • Izdevniecība: National Academies Press
  • Valoda: eng
  • ISBN-13: 9780309366793

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The American Community Survey (ACS) was conceptualized as a replacement to the census long form, which collected detailed population and housing data from a sample of the U.S. population, once a decade, as part of the decennial census operations. The long form was traditionally the main source of socio-economic information for areas below the national level. The data provided for small areas, such as counties, municipalities, and neighborhoods is what made the long form unique, and what makes the ACS unique today. Since the successful transition from the decennial long form in 2005, the ACS has become an invaluable resource for many stakeholders, particularly for meeting national and state level data needs. However, due to inadequate sample sizes, a major challenge for the survey is producing reliable estimates for smaller geographic areas, which is a concern because of the unique role fulfilled by the long form, and now the ACS, of providing data with a geographic granularity that no other federal survey could provide. In addition to the primary challenge associated with the reliability of the estimates, this is also a good time to assess other aspects of the survey in order to identify opportunities for refinement based on the experience of the first few years.



Realizing the Potential of the American Community Survey provides input on ways of improving the ACS, focusing on two priority areas: identifying methods that could improve the quality of the data available for small areas, and suggesting changes that would increase the survey's efficiency in responding to new data needs. This report considers changes that the ACS office should consider over the course of the next few years in order to further improve the ACS data. The recommendations of Realizing the Potential of the American Community Survey will help the Census Bureau improve performance in several areas, which may ultimately lead to improved data products as the survey enters its next decade.

Table of Contents



Front Matter Summary 1 Vision for the American Community Survey 2 Sample Design and Precision of Estimates 3 Data Collection Methods 4 Data Processing and Analytic Issues 5 Data Dissemination 6 Survey Content References Appendix A: Usability Analysis: Tract-Level 2008-2012 ACS Data Appendix B: Examples of Differences Between Census Counts and ACS Population Estimates Appendix C: Data Quality Filtering Rates, 1-Year ACS Data, 2012 Appendix D: Data Quality Filtering Rates, 3-Year Data, 2010-2012 Appendix E: 2014 American Community Survey Mail Questionnaire Appendix F: ACS Questions by Year Introduced and Agency Appendix G: Biographical Sketches of Panel Members and Staff Committee on National Statistics
Summary 1(12)
1 Vision for the American Community Survey
13(10)
The ACS in Concept and Implementation
14(2)
Panel Charge
16(1)
Panel Approach and Initial Assessment
17(2)
Challenges and Opportunities for Enhancing the ACS
19(4)
2 Sample Design and Precision of Estimates
23(23)
Precision of the ACS and Census Long-Form Samples
24(1)
Usability of Tract Data from the 2008-2012 ACS
25(9)
Efforts to Improve Precision
34(11)
Conclusions and Recommendations
45(1)
3 Data Collection Methods
46(13)
Data Collection Modes
47(2)
Nonresponse Follow-Up
49(4)
Adaptive Design
53(3)
Mode Effects and Data Quality
56(3)
4 Data Processing and Analytic Issues
59(19)
Population Controls
59(4)
Data Review
63(2)
Using Administrative Records
65(3)
Small Area Estimation
68(10)
5 Data Dissemination
78(21)
ACS Data Products and Dissemination Methods
78(6)
Data Product and Dissemination Challenges
84(15)
6 Survey Content
99(22)
Current Content and Uses
100(4)
ACS Content Review
104(3)
Possibilities for Modification
107(4)
The ACS Content Change Process
111(10)
References
114(7)
Appendixes
A Usability Analysis: Tract-Level 2008-2012 ACS Data
121(8)
B Examples of Differences Between Census Counts and ACS Population Estimates
129(8)
C Data Quality Filtering Rates, 1-Year Data, 2012*
137(33)
D Data Quality Filtering Rates, 3-Year Data, 2010-2012*
170(3)
E 2014 American Community Survey Mail Questionnaire
173(15)
F ACS Questions by Year Introduced and Agency
188(20)
G Biographical Sketches of Panel Members and Staff
208