Accuracy of the Ratio-Correlation Method for Estimating Postcensal Population

Schmitt, Robert C.; Crosetti, Albert H.

doi:10.2307/3144384

Cited by 41 publications

(13 citation statements)

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“…This case study also serves as an affirmation of the benefits provided by the Schmitt and Crosetti (1954) ratio-correlation method that, among other positive features, serve to free it from the presence of autocorrelation, an adverse condition to which any regression model using time-ordered data is particularly at risk. Whether or not Robert Schmitt and Al Crosetti were consciously aware of this and other positive features, it is a testament to their judgment and insights that led them to develop a regression-based estimation method that avoids the autocorrelation problem inherent in the Nevada Regression Model.…”

Section: Discussionmentioning

confidence: 99%

“…Many of the methods commonly used by applied demographers to estimate subnational population have been subjected to peer review through discussions and evaluations in the academic literature (Bogue 1950;Bousfield 1977;Cannan 1895;Eldridge 1947;Erickson 1974;Hamilton 1964;Krotki 1978;Land & Hough 1986;Mandell & Tayman 1982;McVey 1974;Morrison 1982;Namboodiri 1972;Namboodiri & Lalu 1971;O'Hare 1976O'Hare , 1980Purcell & Kish 1980;Rives et al 1989;Roe et al 1992;Rosenberg 1968;Schmitt 1952;Schmitt & Crosetti 1954, Schmitt & Grier 1966Shryock 1938;Siegel et al 1954;Smith & Lewis 1980;Smith & Cody 1994;Smith et al 2002;Snow 1911, Spar & Martin 1979Starsinic & Zitter 1968;Swanson 1980;Swanson & Tedrow 1984;Zitter & Shryock 1964; U.S. Bureau of the Census 1949).…”

Section: Introductionmentioning

confidence: 99%

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Advancing Methodological Knowledge Within State and Local Demography: a Case Study

Swanson

2004

Population Research and Policy Review

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Abstract. Much of the academic literature dealing with state and local demography involves the development and evaluation of methods for estimating population. The focus on estimation methods is not surprising because they are used in many states to allocate resources. The quality control in regard to the validity and reliability afforded these methods by the traditional academic peer review process is important because, among other things, it serves to reduce the high potential for conflict that exists when resources are at stake. There are, however, methods being used by state and local demographers that have not been subject to peer review. While not necessarily unsound, these ''fugitive'' methods serve to keep the potential for conflict high because of the uncertainty regarding their validity and reliability. This paper examines just such a situation in the form of a case study. It is a discussion of a regression model developed in Nevada following the 2000 census that led to conflict over its use to estimate the population of Clark County, Nevada in 2002. The discussion reveals statistical and methodological shortcomings in this model that lead to an alternative model not subject to these shortcomings. This example illustrates how this type of analysis and discussion can lead to a wider understanding of methods on the part of practitioners through the corrective process of academic peer review. It also suggests that states in which estimates are used to allocate resources would be well-served by subjecting new methods being considered for use to academic peer review before they are adopted.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Advancing Methodological Knowledge Within State and Local Demography: a Case Study

Swanson

2004

Population Research and Policy Review

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“…It is lowest among slowly growing counties, followed by rapidly growing counties., followed by counties losing population (4,5,6,7,8,9, la, 11 ) • 4. In general, assuming that the available data are of high quality, direct data usually produce more accurate estimates than indirect data produce.…”

Section: General Considerations In Selecting Data and Methodsmentioning

confidence: 99%

“…Often, the best estimate is a weighted average of such alternative estimates. A self-correcting character has been imputed to this procedure and comparative evidence has shown that consistently lower average error can be attained by averaging together estimates made by different methods (4,5,6,7,8,9,10,11).…”

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confidence: 99%