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Esri demographic data most accurate in blind study

Redlands, US: Esri data estimates proved to be the most accurate in a recent blind data study. Several top demographers conducted this unprecedented study of demographic forecasts that covered the entire US at four geography levels.

Esri commissioned the study from Cropper GIS, which included estimates from Esri and four other leading US data vendors to measure the accuracy of each company’s demographic forecasts benchmarked against Census 2010 results. Of the five vendors used in this research, Esri was determined to be the most accurate across all geographies, especially at smaller geographies that are more difficult to forecast.

“Because an analysis of this magnitude—especially at the census tract and block group geography levels—has never before been undertaken, the research provides groundbreaking insight into error analysis and the testing of error measurement,” said Lynn Wombold, Esri Chief Demographer.

To conduct the study, Cropper GIS assembled a renowned team of demographers and geographers who specialise in population and housing forecasting. The team consisted of Jerome N. McKibben, PhD, McKibben Demographic Research; David A. Swanson, PhD, University of California, Riverside; Jeff Tayman, PhD, University of California, San Diego; and Matthew Cropper, GISP, Cropper GIS.

Drs. McKibben, Swanson and Tayman are noted authorities on small-area forecasts and measures of forecast accuracy and have written and presented papers extensively on these subjects. Cropper has a broad background in geographic information systems (GIS) and demographic analysis. The researchers did not know the identity of the vendors or the methodologies the vendors used to update their data.

Demographic forecasts are used extensively for government fund allocation, school districting, real estate development, locating health and emergency services, and other applications. Reduced data error ensures that funds and services are provided in areas where the need is greatest.

Source: Esri