In the housing unit method, population is calculated as the number of households times the average number of persons per household (PPH), plus the population residing in group quarters facilities. Estimates of households and the group quarters population can be derived directly from concurrent data series, but estimates of PPH have traditionally been based on previous values or estimates for larger areas. In our study, we developed several regression models in which PPH estimates were based on symptomatic indicators of PPH change.
A number of studies have evaluated the accuracy ofprojections of the size of the total population, but few have considered the accuracy of projections by age group. For many purposes, however, the relevant variable is the population of a particular age group, rather than the population as a whole. We investigated the precision and bias of a variety of age-group projections at the national and state levels in the United States and for counties in Florida.
The housing unit (HU) method is the most commonly used method for making small-area population estimates in the United States. These estimates are used for a wide variety of budgeting, planning, and analytical purposes. Given their importance, periodic evaluations of their accuracy are essential. In this article, we evaluate the accuracy of a set of HU population estimates for counties and subcounty areas in Florida, as of April 1, 2000.
The temporary migration of elderly adults has a major impact on the resident populations of both sending and receiving communities. This article presents a methodology for estimating temporary migration and provides insights into migratory patterns that cannot be achieved by focusing solely on changes in place of usual residence.
The 2004 hurricane season was the worst in Florida’s history, with four hurricanes causing at least 47 deaths and some $45 billion in damages. In order to collect information on the demographic impact of those hurricanes, we surveyed households throughout the state and in the local areas sustaining the greatest damage. We estimate that one-quarter of Florida’s population evacuated prior to at least one hurricane; in some areas, well over half the residents evacuated at least once and many evacuated several times.
Most migration statistics in the United States focus on changes in permanent residence, thereby missing temporary moves such as the daily commute to work, business trips, vacations, and seasonal migration. In this paper, we analyze temporary migration streams in Florida, focusing on moves that include an extended stay. Using several types of survey data, we examine the characteristics of non-Floridians who spend part of the year in Florida and Floridians who spend part of the year elsewhere.
Many researchers have used time series models to construct population forecasts and prediction intervals at the national level, but few have evaluated the accuracy of their forecasts or the out-of-sample validity of their prediction intervals. Fewer still have developed models for subnational areas. In this study, we develop and evaluate six ARIMA time series models for states in the United States.
The elderly population of the United States is large and growing rapidly. In 2000, there were 35 million persons aged 65 and older, making up 12% of the total population. This population is projected to exceed 86 million by 2050, making up 21% of the total (U.S. Census Bureau, 2004). The oldest segment of the elderly population is growing particularly rapidly, with the population aged 85 and over projected to grow more than five-fold between 2000 and 2050, from 4 million to 21 million.
The effects of population size and growth rate on population forecast accuracy have been well documented. For example, we know that small places generally have larger errors than large places; that errors are generally higher for places with high growth rates than places with low growth rates; and that size of error generally remains more stable over time than does the direction of error. In this paper, we delve more deeply into these relationships using data for 2,482 counties in the United States and expand the analysis to include a third explanatory variable, prior forecast error.
By most measures, the 2004 hurricane season was the worst in Florida’s history. Four hurricanes blasted through the state between August 13 and September 25, with Charley making landfall on the southwest coast near Punta Gorda, Frances on the southeast coast near Stuart, Ivan in the panhandle near Pensacola, and Jeanne nearly retracing the route followed by Frances. This was the first time in recorded history that four hurricanes had struck Florida in a single year. Most parts of the state were hit by at least one of the hurricanes and some were hit by two or even three.