Forecast Accuracy and Bias

Stanley K. Smith, Jeff Tayman and David A. Swanson
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Stanley K. Smith: University of Florida, Bureau of Economic and Business Research
Jeff Tayman: University of California-San Diego, Economics Department
David A. Swanson: University of California Riverside, Department of Sociology

Chapter Chapter 13 in A Practitioner's Guide to State and Local Population Projections, 2013, pp 323-371 from Springer

Abstract: Abstract Population projections are typically viewed as forecasts of future population change, regardless of any disclaimers the producers of those projections may make. Given the many critical decisions based on those projections, it is essential to evaluate the forecast accuracy and bias of commonly used projection methods. This chapter provides such an evaluation. We start with a description and discussion of various statistics that can be used to measure forecast accuracy and bias. We then provide an overview of the empirical evidence, focusing on the effects of differences in projection methodology, population size, growth rate, length of base period, length of forecast horizon, and launch year. We consider the possibility of producing forecasts by combining several projections and close with a discussion of uncertainty in population forecasting.

Keywords: Forecast Error; Prediction Interval; Forecast Accuracy; Base Period; Population Projection (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssdmcp:978-94-007-7551-0_13

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DOI: 10.1007/978-94-007-7551-0_13

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