Sample Survey Calibration: An Informationtheoretic perspective

Martin Wittenberg

No 41, SALDRU Working Papers from Southern Africa Labour and Development Research Unit, University of Cape Town

Abstract: We show that the pseudo empirical maximum likelihood estimator can be recast as a calibration estimator. The process of estimating the probabilities pk of the distribution function can be done also in a maximum entropy framework. We suggest that a minimum cross-entropy estimator has attractive theoretical properties. A Monte Carlo simulation suggests that this estimator outperforms the PEMLE and the Horvitz-Thompson estimator. This is a joint SALDRU/DataFirst Working Paper as part of the Mellon Data Quality Project. For more information about the project visit www.datafirst.uct.ac.za.

Keywords: sample weights; calibration; pseudo-empirical maximum likelihood estimation; cross entropy (search for similar items in EconPapers)
Date: 2009-10
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://opensaldru.uct.ac.za/bitstream/handle/11090/14/2009_41.pdf?sequence=1 Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ldr:wpaper::41

Access Statistics for this paper

More papers in SALDRU Working Papers from Southern Africa Labour and Development Research Unit, University of Cape Town Contact information at EDIRC.
Bibliographic data for series maintained by Alison Siljeur ().