In a new report, members of the Bureau of Economic and Business Research (BEBR) Population Program at the University of Florida investigate the accuracy of several sets of state and county population projections published by BEBR over the last 30 years.
The key to Gainesville's fortunes will be for the population to grow faster than projected over the next 30 years, according to economist David Denslow.
The Population Studies Program makes population estimates for counties and all incorporated cities in Florida and population projections by age, sex, race and Hispanic origin for the state and each county. These estimates and projections are used for a wide variety of planning, budgeting, and analytical purposes by state and local government agencies, businesses, research analysts, the media, and members of the general public. The links shown below provide descriptions of the data and techniques used to produce these estimates and projections.
An unexpected outgrowth of the worst recession in 70 years: Sarasota has quietly become more cosmopolitan.
While hard times discouraged Midwesterners and New Englanders from moving here, more Peruvians, Italians, Brazilians, Ukranians and many others made the Gulf Coast home.
Population projections are judged primarily by their accuracy. The most commonly used measure for the precision component of accuracy is the mean absolute percent error (MAPE). Recently, the MAPE has been criticized for overstating forecast error and other error measures have been proposed. This study compares the MAPE with two alternative measures of forecast error, the Median APE and an M-estimator. In addition, the paper also investigates forecast bias.
Population forecasts for subcounty areas are used for a wide variety of planning and budgeting purposes. Given the importance of many of these uses, it is essential to investigate which techniques and procedures produce the most accurate forecasts. In this report, we describe several simple trend extrapolation techniques and several averages and composite methods based on those techniques. We evaluate the precision and bias of forecasts derived from these techniques using data from 1970–2005 for subcounty areas in Florida.
As the elderly population of the United States grows in absolute number and as a proportion of total population, accurate projections of that population become increasingly important for sound policy decisions. Cohort component techniques are typically used for state and local projections of the elderly population, but are often outdated or even nonexistent for many local areas. This paper suggests an altemative approach, based on Medicare data and simple projection techniques.
