Modelling Monthly Births and Deaths Using Seasonal Forecasting Methods as an Input for Population Estimates

Jorge Miguel Bravo () and Edviges Coelho ()
Additional contact information
Jorge Miguel Bravo: Universidade Nova de Lisboa (NOVA IMS)
Edviges Coelho: ECEO – ULHT, Statistics Portugal, Lisboa, Portugal & Departamento de Economia e Gestão

Chapter Chapter 14 in Demography of Population Health, Aging and Health Expenditures, 2020, pp 203-222 from Springer

Abstract: Abstract Forecasts of monthly births and deaths are a critical input when computing monthly estimates of a resident population because 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 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 (i.e., seasonal ARIMA, Holt-Winters, and State Space models) to death and birth 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 death and birth data from 2000 to 2018, disaggregated by sex for the 25 Portuguese NUTS3 regions, to compare the model’s short-term (i.e., 1-year) 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.

Keywords: Time series methods; Seasonality; Population forecasting; ARIMA; Holt-Winters; State-space; C53; C52; Q56; R23; J10 (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ssdmcp:978-3-030-44695-6_14

Ordering information: This item can be ordered from
http://www.springer.com/9783030446956

DOI: 10.1007/978-3-030-44695-6_14

Access Statistics for this chapter

More chapters in The Springer Series on Demographic Methods and Population Analysis from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().