Policy-oriented inference and the analyst-client cooperation. An example from small-area statistics
Nicholas T. Longford ()
Statistics in Transition new series, 2015, vol. 16, issue 1, 65-82
We show on an application to small-area statistics that efficient estimation is not always conducive to good policy decisions because the established inferential procedures have no capacity to incorporate the priorities and preferences of the policy makers and the related consequences of incorrect decisions. A method that addresses these deficiencies is described. We argue that elicitation of the perspectives of the client (sponsor) and their quantification are essential elements of the analysis because different estimators (decisions) are appropriate for different perspectives. An example of planning an intervention in a developing country’s districts with high rate of illiteracy is described. The example exposes the deficiencies of the general concept of efficiency and shows that the criterion for the quality of an estimator has to be formulated specifically for the problem at hand. In the problem, the established small-area estimators perform poorly because the minimum mean squared error is an inappropriate criterion.
Keywords: composition; empirical Bayes; expected loss; borrowing strength; exploiting similarity; shrinkage; small-area estimation. (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:csb:stintr:v:16:y:2015:i:1:p:65-82
Access Statistics for this article
Statistics in Transition new series is currently edited by Włodzimierz Okrasa
More articles in Statistics in Transition new series from Główny Urząd Statystyczny (Polska) Contact information at EDIRC.
Bibliographic data for series maintained by Beata Witek ().