Quarterly figures on Dutch health by time series models

cover discussion paper
Estimation of quarterly figures on Dutch health during the Covid-19 pandemic by structural time series models.
The Dutch Health Survey is designed to produce reliable direct estimates at an annual frequency. Data collection is based on web interviewing (CAWI) and face-to-face interviewing (CAPI). During the Covid-19 lockdown CAPI partially or completely stopped, which resulted in a sudden change in measurement and selection effects in the survey outcomes. Furthermore, the production of annual data about the effect of Covid-19 on health-related themes with a delay of about one year compromises the relevance of this survey. The sample size of the survey does not allow the production of figures for shorter reference periods. Both issues are solved by developing a bivariate structural time series model (STM) to estimate quarterly figures for a selection of eight key variables. The method based on the bivariate STM is compared with two alternative methods. The first one is a univariate STM where no correction for the lack of CAPI is applied to the estimates The second one is a univariate STM that also contains an intervention variable that models the effect of the loss of CAPI response during the lockdown