Multilevel time series modelling of mobility trends in the Netherlands for small domains

H.J. Boonstra, J. van den Brakel*, S. Das

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Web of Science)

Abstract

The purpose of the Dutch Travel Survey is to produce reliable estimates on mobility of the Dutch population. In this paper mobility trends are estimated at several aggregation levels, using multilevel time series models. The models account for discontinuities induced by two survey redesigns and outliers due to less reliable outcomes in one particular year. The input for the model is direct annual estimates with their standard errors for the period 1999–2017 for a detailed cross-classification in 504 domains. Appropriate transformations for the direct estimates and generalized variance functions to smooth the standard errors of the direct estimates are proposed. The models are fitted in an hierarchical Bayesian framework using MCMC simulations. From the model outputs smooth trend estimates are computed at the most detailed domain level. Predictions at higher aggregation levels obtained by aggregation of the most detailed domain predictions result in a numerically consistent set of trend estimates for all target variables.
Original languageEnglish
Pages (from-to)985-1007
Number of pages23
JournalJournal of the Royal Statistical Society Series A-Statistics in Society
Volume184
Issue number3
DOIs
Publication statusPublished - 1 Jul 2021

Keywords

  • global local shrinkage
  • hierarchical Bayesian models
  • MCMC simulation
  • official statistics
  • small area estimation
  • structural time series models
  • SMALL-AREA ESTIMATION
  • HIERARCHICAL BAYES ESTIMATION
  • PRIOR DISTRIBUTIONS
  • INFORMATION
  • INCOME
  • LEVEL

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