Time and space correlation

Chair: Jan van den Brakel

Time and space correlation is a powerful way of borrowing strength and improving the efficiency of small area estimators. This section contains three contributions that introduce some new methodologies that borrow strength across areas and across time and/or that take into account for spatial correlations. The contributions contain applications to estimating survey discontinuities, to data subject to boundary changes and to predicting employment status by economic activity.

Domain Estimation of Survey Discontinuities

National Statistical Institutes (NSIs) conduct repeated sample surveys with the aim of analyzing change over time. Although NSIs try to maintain consistent survey design methodologies, modifications and redesigns of long-standing survey processes are sometimes necessary. Redesigning a survey can affect non-sampling errors and therefore can lead to systematic differences on survey estimates over time. These […]

Investigating stability in confidence in a policing: a Bayesian spatiotemporal small area estimation approach.

Improving understanding of public confidence at the local level willbetter enable the police to conduct proactive confidence interventions to meet the concerns of local communities. Neighbourhood level approaches to modelling public confidence in the police are hampered by the small number problem and the resulting instability in the estimates and uncertainty in the results. Furthermore, […]

Small Area specific estimators that borrow strength across areas and across time

In this work a Small Area-specific estimation approach that borrows strength across areas and across time is presented to obtain Labor Force Estimators by economic activity. Several small area model-based estimators are considered, which are derived from additive regression models based on auxiliary information, with and without random effects. Often, for a given area and […]

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