Estimates and projections for small areas are used extensively in the public and private sectors, and demand for them has been growing. Because of population size and data availability issues, estimates and projections for small areas face methodological challenges not commonly encountered at larger geographical scales.
Many studies have evaluated the impact of differences in population size and growth rate on population forecast accuracy. Virtually all these studies have been based on aggregate data; that is, they focused on average errors for places with particular size or growth rate characteristics. In this study, we take a different approach by investigating forecast accuracy using regression models based on data for individual places.
The Bureau of Economic and Business Research Population Program, under contract with the Florida Legislature, has been making three sets of population projections (low, medium, and high) for Florida and its counties for many years. Many decisions in both the public and private sectors are based on expectations of future population change. Planning for schools, hospitals, shopping centers, housing developments, electric power plants, and many other projects is strongly influenced by expected population growth or decline.
The older population in many countries is large and growing rapidly, raising the number of people with disabilities and driving up the need for accessible housing. In a previous
study, we projected the number of households in the United States with at least one disabled resident and estimated the probability that a newly built single-family detached
unit will house at least one disabled resident during its expected lifetime. In this study, we extend our analysis to the subnational level by constructing similar estimates and
Projections of total population have been evaluated extensively, but few studies have
investigated the performance of projections by age. Of those that did, most focused on
projections for countries or other large areas. In this article, we evaluate projections by age for
Florida and its counties, as produced and published between 1996 and 2010 by the Bureau of
Economic and Business Research (BEBR) at the University of Florida. We first compare the
precision and bias of projections of total population with the precision and bias of projections by
Small area population forecasts are used for a wide variety of planning and budgeting purposes.
Using 1970–2005 data for incorporated places and unincorporated areas in Florida, we evaluate
the accuracy of forecasts made with several extrapolation techniques, averages, and composite
methods, and assess the effects of differences in population size, growth rate, and length of
forecast horizon on forecast errors. We further investigate the impact of adjusting forecasts to
The housing unit (HU) method—in which population estimates are derived
fromestimates of occupiedHUs—is themost commonly usedmethod formaking smallarea
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
- Stanley K. Smith, Ph.D.
- Scott Cody, M.B.A
Florida’s population has grown rapidly in recent decades, but growth rates have fluctuated considerably from one year to the next. For example, the state’s population grew by more than 400,000 between 2004 and 2005 but by less than 100,000 between 2008 and 2009. What caused this high degree of volatility? To answer this question, we must look at the components of growth.
Annual Population Change, Florida, 2000-2012