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dc.contributor.authorPflaumer, Peter-
dc.date.accessioned2014-08-19T11:26:59Z-
dc.date.available2014-08-19T11:26:59Z-
dc.date.issued2012-11-
dc.identifier.citationJSM Proceedings, Social Statistics Section. Alexandria, VA: American Statistical Association, 2012, 4967-4981en
dc.identifier.isbn978-0-9839375-2-4-
dc.identifier.urihttp://hdl.handle.net/2003/33580-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-4505-
dc.description.abstractPopulation forecasts have received a great deal of attention during the past few years. They are widely used for planning and policy purposes. In this paper, the Gompertz growth curve is proposed to forecast the U.S. population. In order to evaluate its forecast error, population estimates from 1890 to 2010 are compared with the corresponding predictions for a variety of launch years, estimation periods, and forecast horizons. Various descriptive measures of these forecast errors are presented and compared with the accuracy of forecasts made with the cohort component method (e.g., the U.S. Census Bureau) and other traditional time series models. These models include quadratic and cubic trends, which were used by statisticians at the end of the 19th century (Pritchett and Stevens). The measures of errors considered are based on the differences between the projected and the actual annual growth rate. It turns out that the forecast accuracies of the models differ greatly. The accuracy of some simple time series models is better than the accuracy of more complex models.en
dc.language.isoende
dc.publisherAmerican Statistical Associationen
dc.subjectDemographyen
dc.subjectTime Seriesen
dc.subjectPopulation Projectionen
dc.subjectForecast Accuracyen
dc.subject.ddc310-
dc.titleForecasting the U.S. Population with the Gompertz Growth Curveen
dc.typeTextde
dc.type.publicationtypeconferenceObjectde
dcterms.accessRightsopen access-
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