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Forecasting Subnational Monthly Births and Deaths using Seasonal Time Series Methods

dc.contributor.authorBravo, Jorge Miguel
dc.contributor.authorCoelho, Edviges
dc.contributor.institutionNOVA Information Management School (NOVA IMS)
dc.contributor.institutionInformation Management Research Center (MagIC) - NOVA Information Management School
dc.date.accessioned2019-09-16T22:54:33Z
dc.date.available2019-09-16T22:54:33Z
dc.date.issued2019-07
dc.descriptionBravo, J. M., & Coelho, E. (2019). Forecasting Subnational Monthly Births and Deaths using Seasonal Time Series Methods. In Evidence-based territorial policymaking: formulation, implementation and evaluation of policy: 26th APDR Congress Proceedings (pp. 1079-1088). Associacao Portuguesa para o Desenvolvimento Regional (APDR).
dc.description.abstractForecasts of monthly births and deaths are a critical input in the computation of monthly estimates of resident population since they determine, together with international net migration, the dynamics of both the population size and its age distribution. Empirical time series data for births and deaths exhibits strong evidence of the presence of seasonality patterns at both national and subnational levels. In this paper, we evaluate the forecasting performance of alternative linear and non-linear time series methods (seasonal ARIMA, Holt-Winters and State Space models) to birth and death monthly forecasting at the sub-national level. Additionally, we investigate how well the models perform in terms of predicting the uncertainty of future monthly birth and death counts. We use the series of monthly birth and death data from 2000 to 2018 disaggregated by sex for the 25 Portuguese NUTS3 regions to compare the model's short-term (oneyear) forecasting accuracy using a backtesting time series cross- validation approach. Our results provide valuable insights regarding the forecasting performance of alternative time series models in small population forecasting exercises and on the validity of using such models as predictors of population forecast uncertainty.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent10
dc.format.extent1188647
dc.identifier.isbn978-989-8780-07-2
dc.identifier.otherPURE: 14707037
dc.identifier.otherPURE UUID: 2c9ded2d-757e-4233-bd9e-3a8f401550cb
dc.identifier.otherORCID: /0000-0002-7389-5103/work/61988653
dc.identifier.urihttp://apdr.pt/data/documents/ATAS_APDRcongress2019.pdf
dc.identifier.urlhttp://apdr.pt/data/documents/ATAS_APDRcongress2019.pdf
dc.language.isoeng
dc.peerreviewedyes
dc.publisherAPDR - Associação Portuguesa para o Desenvolvimento Regional
dc.subjectHolt-Winters method
dc.subjectTime series methods
dc.subjectSeasonality
dc.subjectState-Space models
dc.subjectSARIMA
dc.subjectPopulation forecasting
dc.titleForecasting Subnational Monthly Births and Deaths using Seasonal Time Series Methodsen
dc.typeconference object
degois.publication.firstPage1079
degois.publication.lastPage1088
degois.publication.titleEvidence-based territorial policymaking: formulation, implementation and evaluation of policy
degois.publication.title26th APDR Congress
dspace.entity.typePublication
rcaap.rightsopenAccess

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