NDLI: Making the Housing Unit Method Work: An Evaluation of 2010 Population Estimates in Florida

Content Provider	Springer Nature Link
Author	Smith, Stanley K. Cody, Scott
Copyright Year	2013
Abstract	The housing unit (HU) method—in which population estimates are derived from estimates of occupied HUs—is the most commonly used method for making small-area population estimates in the United States. It is widely used because it is conceptually simple, can utilize a wide variety of data sources, can be applied at virtually any level of geography, and often produces reliable estimates. Yet the HU method is more nearly a general approach to population estimation than it is a specific methodology. In this paper, we describe and evaluate several data sources and estimation techniques that can be used in applying the HU method. Using a set of county and subcounty estimates produced by the Bureau of Economic and Business Research (BEBR) at the University of Florida for April 1, 2010, we analyze errors by population size and growth rate, calculate errors for each of the three components of the HU method, and investigate the accuracy of estimates based on several different data sources and estimation techniques. We compare the accuracy of the 2010 estimates with previous BEBR estimates and estimates produced by the U.S. Census Bureau. We conclude that although some data sources and estimation techniques work better than others, the HU method can be tailored to produce reliable population estimates for a wide variety of geographic areas.
Starting Page	221
Ending Page	242
Page Count	22
File Format	PDF
ISSN	01675923
Journal	Population Research and Policy Review
Volume Number	32
Issue Number	2
e-ISSN	15737829
Language	English
Publisher	Springer Netherlands
Publisher Date	2013-01-11
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Population estimates Housing unit method Estimation accuracy Households Household size Group quarters population Demography Sociology Population Economics
Content Type	Text
Resource Type	Article
Subject	Demography Management, Monitoring, Policy and Law

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