Evaluating Population Forecast Accuracy A Regress

Authors: Jeff Tayman Stanley K Smith Stefan Rayer

Publish Date: 2010/06/16

Volume: 30, Issue: 2, Pages: 235-262

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Abstract

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 Using decennial census data from 1900 to 2000 for 2482 counties in the US we construct a large number of county population forecasts and calculate forecast errors for 10 and 20year horizons Then we develop and evaluate several alternative functional forms of regression models relating population size and growth rate to forecast accuracy investigate the impact of adding several other explanatory variables and estimate the relative contributions of each variable to the discriminatory power of the models Our results confirm several findings reported in previous studies but uncover several new findings as well We believe regression models based on data for individual places provide powerful but underutilized tools for investigating the determinants of population forecast accuracyPopulation projections at the state and local levels are used for a wide variety of planning budgeting and analytical purposes Although they are sometimes used simply to trace out the implications of a particular set of hypothetical assumptions they are used most frequently as forecasts of the future population The importance of the purposes for which these forecasts are used—for example opening a new business closing a public school enlarging a power plant or revising local bus routes—makes it essential to evaluate their precision and biasMany studies have investigated the impact of population size and growth rate on forecast accuracy by analyzing forecast errors within broad size and growth rate categories Measuring population size in the launch year and growth rate over the base period these studies have generally found precision to improve with increases in population size and decline with increases in the absolute value of the growth rate eg Keyfitz 1981 Rayer 2008 Smith and Sincich 1992 Stoto 1983 White 1954 They have found bias to have little or no relationship with population size but to be positively related to the growth rate eg Isserman 1977 Rayer 2008 Smith 1987 Tayman 1996 These results have been found so frequently that we believe they can be accepted as general characteristics of population forecast errorsAll of the studies cited above were based on aggregate data that is they focused on average errors for places with particular size or growth rate characteristics It is clear however that errors often vary substantially within given size or growth rate categories For example although small places have larger errors than large places on average some small places have very small errors and some large places have very large errors What is the impact of population size and growth rate on forecast accuracy when analyzed using data for individual places What variables other than size and growth rate also affect accuracy How can these effects best be evaluated These questions have seldom been addressed in the literature

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