Conflicts in the Use of the ACS by Federal Agencies Between Statutory Requirements and Survey Methodology

Nesse, Katherine; Rahe, Mallory L.

doi:10.1007/s11113-014-9352-7

Cited by 5 publications

(3 citation statements)

References 13 publications

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“…The prosperity index is benchmarked to the national average and uses a 0‐1 threshold approach that represents a county's relative position. The 2000 index was constructed using data from the Decennial Census long‐form, however replacement of this once a decade survey instrument with the American Community Survey (ACS) rolling samples and multi‐year estimates affects the ability of researchers to understand and measure change over time (Nesse and Rahe ). Smoothing the effects over five years may produce a better understanding of some economic data like unemployment rates and poverty rates, but while non‐sampling error has declined, total sample sizes have too and even after combining five years of estimates measuring small populations in rural areas can still produce unacceptably high margins of error (Citro and Kalton ).…”

Section: Methodsmentioning

confidence: 99%

Rural prosperity and federal expenditures, 2000–2010

Wilson

Rahe

2016

Regional Science Policy & Practice

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Abstract. Rural development policy in the US lacks coordination and coherence, but sustaining prosperous rural communities should be a primary aim. We identify rural non-core counties that remained prosperous during the recent recession and use regression analysis to model the relationship between rural prosperity and per capita federal expenditures. The number of prosperous rural non-core counties increased from 2000 to 2010. Social capital and educational attainment are now more important predictors of rural prosperity than economic diversity. Prosperous rural non-core counties are associated with higher rates of expenditure and the distribution of federal expenditures across these counties exhibits positive spatial dependence.JEL classification: R58, R11, I31, H50

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Section: Methodsmentioning

confidence: 99%

Rural prosperity and federal expenditures, 2000–2010

Wilson

Rahe

2016

Regional Science Policy & Practice

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“…A second caveat to note is our use of spatial interpolation to create grid-level demographic measures also means that our demographic data should be treated as estimates as well, particularly since they already were drawn from a sample (the American Community Survey) that has a margin of error associated with it (for discussions on the strengths and limitations of the ACS, see Nesse and Rahe, 2015). Again, while this is certainly not ideal, the benefits of a stable number of neighborhoods and equally sized aerial units make this a sacrifice worth tolerating for our analyses.…”

Section: Limitationsmentioning

confidence: 99%

St. Louis’s “urban prairie”: Vacant land and the potential for revitalization

Prener

Braswell

Monti

2018

Journal of Urban Affairs

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As part of a larger project to understand the relative health and disorder of St. Louis City neighborhoods, this paper presents estimates of the number of vacant parcels in the city. These estimates, which are considerably higher than previously published ones, are heavily concentrated in the city's disinvested and segregated North side. We term this heavy concentration of vacancy as "urban prairie". After accounting for other factors as well as possible sources of statistical error, we identify both long-term population loss since 1970 and the proportion of African American residents as significant covariates associated with the amount of urban prairie land per neighborhood. These high levels of concentrated vacancy lead us to critique the City's existing approaches as being too limited in scope, and to suggest a range of possibilities for revitalizing portions of North St. Louis while allowing prairie land to continue to exist in others.

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“…Annual estimates are published for any geographic area that has over 65,000 people. Three-year estimates are published for geographic areas that have over 20,000 people, and five-year estimates are published for most geographic areas down to the census tract level [1]. Each year the period estimates are updated by dropping the samples from the oldest year and re-averaging the estimate with samples from the newest year.…”

Section: Overview Of the American Community Surveymentioning

confidence: 99%

The American Community Survey: practical considerations for researchers

Donnelly

2013

Reference Services Review

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -This paper seeks to provide researchers and librarians with an overview of the US Census Bureau's American Community Survey (ACS), with a specific focus on practical issues that users must face when choosing and using ACS datasets. Design/methodology/approach -Each of the following issues are explored subsequent to a general overview of the ACS: choosing among census datasets from different census programs, interpreting and choosing between the different ACS period estimates, selecting census geography, understanding and recalculating margins of error, and accessing the data. Samples of ACS tables and formulas for creating derived estimates are used to illustrate how to interpret and work with the data. Findings -The ACS datasets are fundamentally different from the decennial census as they are period estimates created from rolling sample surveys. The ACS has a steeper learning curve; this complexity is due in part to the number of choices users must make between datasets, but the primary challenge is learning how to understand and work with estimates as opposed to population counts. Originality/value -While other papers have discussed the benefits and challenges of the ACS, this paper is structured around the practical issues that researchers must face when using it. Special consideration is given to calculating derived estimates using spreadsheet formulas, as this is a key task that many users will need to perform and spreadsheets are the most likely tool users will employ to manipulate the data.

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Conflicts in the Use of the ACS by Federal Agencies Between Statutory Requirements and Survey Methodology

Cited by 5 publications

References 13 publications

Rural prosperity and federal expenditures, 2000–2010

Rural prosperity and federal expenditures, 2000–2010

St. Louis’s “urban prairie”: Vacant land and the potential for revitalization

The American Community Survey: practical considerations for researchers

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