Pitfalls in Population Forecasts and Projections

Estimates of age-specific reductions in HIV prevalence in Uganda: Bayesian melding estimation and probabilistic population forecast with an HIV-enabled cohort component projection model

BACKGROUND

Much of our knowledge of the epidemiology and demography of HIV epidemics in Africa is derived from models fit to sparse, non-representative data. These often average over age and other important dimensions, rarely quantify uncertainty, and typically do not impose consistency on the epidemiology and the demography of the population.

OBJECTIVE

This work conducts an empirical investigation of the history of the HIV epidemic in Uganda and Tanzania through the late 1990s, focusing on sex-age-specific incidence, uses those results to produce probabilistic forecasts of HIV prevalence ten years later, and compares those to measures of HIV prevalence at the later time to describe the sex-age pattern of changes in prevalence over the intervening period.

METHODS

We adapt an epidemographic model of a population affected by HIV so that its parameters can be estimated using both the Bayesian melding with IMIS estimation method and maximum likelihood methods. Using the Bayesian version of the model we produce probabilistic forecasts of the population with HIV.

RESULTS

We produce estimates of sex-age-specific HIV incidence in Uganda and Tanzania in the late 1990s, produce probabilistic forecasts of the HIV epidemics in Uganda and Tanzania during the early 2000s, describe the sex-age pattern of changes in HIV prevalence in Uganda during the early 2000s, and compare the performance and results of the Bayesian and maximum likelihood estimation procedures.

CONCLUSIONS

We demonstrate that: (1) it is possible to model HIV epidemics in Africa taking account of sex and age, (2) there are important advantages to the Bayesian estimation method, including rigorous quantification of uncertainty and the ability to make probabilistic forecasts, and (3) that there were important age-specific changes in HIV incidence in Uganda during the early 2000s.

Stability over time in the distribution of population forecast errors

A number of studies in recent years have investigated empirical approaches to the production of confidence intervals for population projections. The critical assumption underlying these approaches is that the distribution of forecast errors remains stable over time. In this article, we evaluate this assumption by making population projections for states for a number of time periods during the 20th century, comparing these projections with census enumerations to determine forecast errors, and analyzing the stability of the resulting error distributions over time. These data are then used to construct and test empirical confidence limits. We find that in this sample the distribution of absolute percentage errors remained relatively stable over time and data on past forecast errors provided very useful predictions of future forecast errors.

A survey of Census Bureau population projection methods

"Population projections methods of the U.S. Census Bureau draw upon several different traditions of forecasting: demographic accounting, judgmental, time series, deterministic, and explanatory. This paper reviews each of the forecasting traditions in population projections, describes the U.S. Census Bureau's current methods for national and state population projections, and proposes new hybrid approaches such as demographic-time series methods for national fertility projections and economic-demographic methods for state migration projections. Throughout the article, possible parallels with forecasting in other disciplines are noted."

Methods for national population forecasts: a review

"Three widely used classes of methods for forecasting national populations are reviewed: demographic accounting/cohort-component methods for long-range projections, statistical time series methods for short-range forecasts, and structural modeling methods for the simulation and forecasting of the effects of policy changes. In each case, the major characteristics, strengths, and weaknesses of the methods are described. Factors that place intrinsic limits on the accuracy of population forecasts are articulated. Promising lines of additional research by statisticians and demographers are identified for each class of methods and for population forecasting generally."

How accurate are the U.S. Bureau of the Census projections of total live births

"The accuracy of total live birth forecasts issued by the U.S. Bureau of the Census was analysed. Forecast accuracy has not improved significantly since 1950. Further, the forecasts are not more accurate than several naive alternatives. Moving from a period methodology to a cohort methodology improved forecast accuracy for certain forecasts. [It is demonstrated that] the Bureau of the Census systematically underestimated total births in the upswing and overestimated in the downswing."

Development and accuracy of projections of population and households in the united states

The history of the official U. S. projections of population and house-holds in recent decades is briefly reviewed, with particular attention to methodology and the relation of the methodology to the accuracy of the projections. The introduction of the cohort-component procedure in the 1930’s opened the way for separate analysis of the trend of the components of births, deaths, and net immigration in connection with making population projections. As a further development, the period-fertility method of projecting births gave way in the 1960’s to the cohort-fertility method. Consideration is now being given to various methods involving parity-progression procedures. Some alternative methods and problems of measuring the accuracy of population projections are then considered. The percent “error” in the projected population growth, by components and age, and the range from high to low expressed as a percent should also be examined in addition to the percent “error” in the total population. However accuracy is measured, the projections made in the 1930’s and 1940’s were often wide of the mark, and those made in the 1950’s and 1960’s failed to anticipate the sharp changes which occurred, even though the actual figures usually fell within the range projected. Elaboration of projection methodology has not resulted in any great increase in the precision of the projections, largely because birth rates have fluctuated widely, and the fluctuations have proven difficult, if not impossible, to predict. The projections of households have had a roughly similar history, and the methods and problems of evaluation are somewhat similar. Their development has been characterized by the introduction of alternative and changing “headship” rates and increasing disaggregation of the data and procedures. The paper concludes with some generalizations based on U. S. experience. Although refinement of methods may contribute little to accuracy, accuracy is only one aspect of the usefulness of projections. The need for conditional projections and their analytical usefulness are such that there is no question that we should confidently continue to make them.