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High nonresponse rates have become a rule in survey sampling. In panel surveys there occur additional sample losses due to panel attrition, which are thought to worsen the bias resulting from initial nonresponse. However, under certain conditions an initial wave nonresponse bias may vanish in...
Persistent link: https://www.econbiz.de/10013494126
Recently, several institutions have increased their forecast horizons, and many institutions rely on their past forecast errors to estimate measures of forecast uncertainty. This work addresses the question how the latter estimation can be accomplished if there are only very few errors available...
Persistent link: https://www.econbiz.de/10010465566
Modern systems of official statistics require the timely estimation of area-specific densities of sub-populations. Ideally estimates should be based on precise geo-coded information, which is not available due to confidentiality constraints. One approach for ensuring confidentiality is by...
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In self-reported data usually a phenomenon called 'heaping' occurs, i.e. survey participants round the values of their income, weight or height to some degree. Additionally, respondents may be more prone to round off or up due to social desirability. By ignoring the heaping process a severe bias...
Persistent link: https://www.econbiz.de/10011325727
Among a variety of small area estimation methods, one popular approach for the estimation of linear and non-linear indicators is the empirical best predictor. However, parameter estimation using standard maximum likelihood methods is not possible, when the dependent variable of the underlying...
Persistent link: https://www.econbiz.de/10011703587
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across...
Persistent link: https://www.econbiz.de/10014478337
This article presents a computationally efficient approach to sample from Gaussian state space models. The method is an instance of precision-based sampling methods that operate on the inverse variance-covariance matrix of the states (also known as precision). The novelty is to handle cases...
Persistent link: https://www.econbiz.de/10014336195