Emerging Techniques in Applied Demography by M.Nazrul Hoque, Lloyd B. Potter
By M.Nazrul Hoque, Lloyd B. Potter
By bringing jointly top-notch demographers, sociologists, economists, statisticians and public health and wellbeing experts from Asia, Africa, Europe, and North the USA to check a large choice of private and non-private concerns in utilized demography, this e-book spans a variety of themes. It evaluates inhabitants estimates and projections opposed to real census counts and indicates additional development of estimates and projection ideas and evaluate approaches; new concepts are proposed for estimating households and families and specific awareness is paid to the much-discussed subject of entry to health and wellbeing care. insurance extends to elements influencing overall healthiness prestige and elder abuse, baby bearing and exertions industry research and the consequences of schooling on hard work marketplace results of local white American and immigrant ecu populations.
Methodologically rigorous and pragmatically beneficial, Emerging suggestions in utilized Demography also examines a wide selection of private and non-private matters below the sphere of utilized demography. It presents a wide review of analysis themes and in addition displays immense improvement within the box of utilized demography. It additionally bridges the distance among thought and learn by way of delivering numerous examples of labor of distinctive utilized demographic.
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As an alternative, we constructed a set of prediction intervals based solely on data for Florida counties. Using the distribution of errors for projections with launch years 1980, 1985, and 1990, we calculated two-thirds prediction intervals for 5-, 10-, and 15-year horizons through target year 1995. We applied these intervals to projections with launch years 1995, 2000, and 2005 and counted the number of counties whose populations fell within the intervals in target years 2000, 2005, and 2010.
We can be more confident in the results for counties, but only when those results are aggregated. Average errors are much more predictable than errors for individual places. 3. With respect to bias, however, we cannot make any predictions. There is simply no way to know in advance whether a given set of projections will turn out to be predominantly too high or too low. Results for individual counties, of course, are much less predictable than results based on averages. Given this uncertainty, data users should consider several possible alternatives rather than a single scenario when using county projections for decision-making purposes.
The second approach provides explicit measures of this uncertainty. County Projections Since the mid-1980s, BEBR’s low and high county projections have been based on an analysis of population forecast errors for a sample of 2,971 counties in the United States (Smith 1987). These errors were drawn from projections covering several combinations of launch year and projection horizon between 1950 and 1980. Using this data set, BEBR calculated the 67th largest absolute percent error for counties in several population size and/or growth rate categories and used those errors to construct low and high projections for each county.