A Method of Estimating the Intercensal Population of Counties

New insights on the impact of coefficient instability on ratio-correlation population estimates

“…A positive MALPE reflects the tendency for the estimates to be too high on average and a negative MALPE reflect the tendency for the estimates to be too low on average. 3 The measures described above are based on the error for a particular geographic area.…”

“…Symptomatic indicators relate to changes in population such as vital events, employment, school enrollment, voter registration, and tax returns. While variations have been developed, the most common regression-based approach for estimating populations is the "ratio-correlation" method introduced and tested by Schmitt and Crosetti [28] and Crosetti and Schmitt [3]. Comparative analysis has shown the ratio correlation method is one of the most accurate approaches for estimating population [1,9,23,30,15].…”

A New Approach in Measuring Local Migration and Population

“…Measuring annual population and population growth following a decennial census is called postcensal population estimation. In efforts to improve measurements of population estimates for states and local areas, a variety of methods have been created, including Component Methods (of I and II) developed by the US Census Bureau (The US Census Bureau, 1947 and1960), Regression Ratio Correlation Methods (Schmitt & Crosetti 1954;Schmitt & Crosetti 1956), Housing Unit Methods (Starsinic & Zitte 1968), Vital Rates/Censal Ratio Methods (Bogue 1950), Composite Methods (Bogue & Duncan 1959), and Survey Methods (Ericksen 1973;Rives 1982). These methods are well documented by a small number of books and also by the Current Population Reports series published by the Census Bureau (Committee on National Statistics 1980;Lee & Goldsmith 1982;Murdock & Ellis 1991;Rives, et al 1995;The Census Bureau 1996, Smith & Cody 1999Bryan 2003).…”

Synthetic Estimates for Small Areas: Statistical Workshop Papers and Discussion.

“…To reduce the variability and skewness of the distribution, it is suggested that variables be written in ratio form. The procedure resembles the ratio correlation technique, first introduced by Snow (1911) and developed by Crosetti and Schmitt (1956), which estimates the multivariate relationship among population growth and predictor variables. Postcensal estimates derived using the ratio correlation method require the fitting of a linear model to selected variables represented in terms of a ratio of measurements taken at the endpoints of the immediately preceeding intercensal period.…”