Evaluating Linearly Interpolated Intercensal Estimates of Demographic and Socioeconomic Characteristics of U.S. Counties and Census Tracts 2001–2009

Published in: Population Research and Policy Review, v. 34, no. 4, Aug. 2015, p. 541-559

Posted on RAND.org on April 15, 2016

by Margaret M. Weden, Christine E. Peterson, Jeremy N. V. Miles, Regina A. Shih

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The American Community Survey (ACS) multiyear estimation program has greatly advanced opportunities for studying change in the demographic and socioeconomic characteristics of U.S. communities. Challenges remain, however, for researchers studying years prior to the full implementation of the ACS or areas smaller than the thresholds for ACS annual estimates (i.e., small counties and census tracts). We evaluate intercensal estimates of the demographic and socioeconomic characteristics of U.S. counties and census tracts produced via linear interpolation between the 2000 census and both the 2010 census and 2005–2009 ACS. Discrepancies between interpolated estimates and reference estimates from the Population Estimates Program, the Small Area Income and Poverty Estimates, and ACS are calculated using several measures of error. Findings are discussed in relation to the potential for measurement error to bias longitudinal estimates of linearly interpolated neighborhood change, and alternative intercensal estimation models are discussed, including those that may better capture non-linear trends in economic conditions over the 21st century.

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