A note on the measurement of accuracy for subnational demographic estimates

Swanson, David A.; Tayman, Jeff; Barr, Charles F.

doi:10.2307/2648121

Cited by 35 publications

(48 citation statements)

References 10 publications

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“…Some authors (e.g., Swanson, et al, 2000) have noted that measures based on percentage errors are often highly skewed, and therefore transformations (such as logarithms) can make them more stable. See Coleman and Swanson (2004) for further discussion.…”

Section: Measures Based On Percentage Errorsmentioning

confidence: 99%

Another look at measures of forecast accuracy

Hyndman

Koehler

2006

International Journal of Forecasting

3,776

1,912

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Section: Measures Based On Percentage Errorsmentioning

confidence: 99%

Another look at measures of forecast accuracy

Hyndman

Koehler

2006

International Journal of Forecasting

3,776

1,912

View full text Add to dashboard Cite

“…An important criterion in the development and evaluation of population estimates (and projections) is accuracy (National Research Council 1980;Smith et al 2001;Swanson 1980Swanson , 1981Swanson et al 2000). However, it is not just for reasons of professional pride that accuracy is important; the estimates are used to distribute resources, and in many of these distributions each person estimated generates thousands of dollars over the course of a decade (Murray 1992;U.S.…”

Section: The Housing Unit Methodsmentioning

confidence: 99%

An Evaluation of Persons per Household (PPH) Estimates Generated by the American Community Survey: A Demographic Perspective

Swanson

Hough

2012

Popul Res Policy Rev

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The American Community Survey (ACS) is a U.S. Census Bureau product designed to provide accurate and timely demographic and economic indicators on an annual basis for both large and small geographic areas within the United States. Operational plans call for ACS to serve not only as a substitute for the decennial census long-form, but as a means of providing annual data at the national, state, county, and subcounty levels. In addition to being highly ambitious, this approach represents a major change in how data are collected and interpreted. Two of the major questions facing the ACS are its functionality and usability. This paper explores the latter of these two questions by examining ''persons per household (PPH),'' a variable of high interest to demographers and others preparing regular post-censal population estimates. The data used in this exploration are taken from 18 of the counties that formed the set of 1999 ACS test sites 123Popul Res Policy Rev (2012) 31:235-266 DOI 10.1007 estimates respond to demographic and related determinants. The comparisons suggest that the ACS PPH estimates exhibit too much ''noisy'' variation for a given area over time to be usable by demographers and others preparing post-censal population estimates. These findings should be confirmed through further analysis and suggestions are provided for the directions this research could take. We conclude by noting that the statistical and demographic perspectives are not incompatible and that one of the aims of our paper is to encourage the U.S. Census Bureau to consider ways to improve the usability of the 1-year ACS PPH estimates.

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“…The rescaled version, MAPE-R, was introduced by , given a limited empirical test by Swanson et al (2000), and conceptually and computationally refined by Coleman and Swanson (2007). MAPE-R is based on a power transformation of the error distribution underlying the MAPE.…”

Section: Introductionmentioning

confidence: 99%

“…However, MAPE-R has not had the benefit of a major empirical test, which is the central focus of this paper, along with providing criteria for its implementation. The initial investigations of MAPE-R included empirical illustrations in the form of case studies for estimates (Swanson et al 2000) and for forecasts . However, the case study data were not intended to provide a comprehensive empirical portrait of MAPE-R, its features and characteristics, which this paper is designed to do.…”

Section: Introductionmentioning

confidence: 99%

MAPE-R: a rescaled measure of accuracy for cross-sectional subnational population forecasts

Swanson

Tayman

Bryan³

2011

J Pop Research

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Accurately measuring a population and its attributes at past, present, and future points in time has been of great interest to demographers. Within discussions of forecast accuracy, demographers have often been criticized for their inaccurate prognostications of the future. Discussions of methods and data are usually at the centre of these criticisms, along with suggestions for providing an idea of forecast uncertainty. The measures used to evaluate the accuracy of forecasts also have received attention and while accuracy is not the only criterion advocated for evaluating demographic forecasts, it is generally acknowledged to be the most important. In this paper, we continue the discussion of measures of forecast accuracy by concentrating on a rescaled version of a measure that is arguably the one used most often in evaluating cross-sectional, subnational forecasts, Mean Absolute Percent Error (MAPE). The rescaled version, MAPE-R, has not had the benefit of a major empirical test, which is the central focus of this paper. We do this by comparing 10-year population forecasts for U.S. counties to 2000 census counts. We find that the MAPE-R offers a significantly more meaningful representation of average error than MAPE in the presence of substantial outlying errors, and we provide guidelines for its implementation.

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A note on the measurement of accuracy for subnational demographic estimates

Cited by 35 publications

References 10 publications

Another look at measures of forecast accuracy

Another look at measures of forecast accuracy

An Evaluation of Persons per Household (PPH) Estimates Generated by the American Community Survey: A Demographic Perspective

MAPE-R: a rescaled measure of accuracy for cross-sectional subnational population forecasts

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