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Using Selective Sampling for Binary Choice Models to Reduce Survey Costs

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Author Info
Donkers, A.C.D.
Franses, Ph.H.B.F.
Verhoef, P.C. (Erasmus Research Institute of Management (ERIM), RSM Erasmus University)

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Abstract

Marketing problems sometimes concern the analysis of dichotomous variables, like for example ``buy'' and ``not buy'' and ``respond'' and ``not respond''. It can happen that one outcome strongly outnumbers the other, for example when many households do not respond (to a direct mailing, for example). Standard econometric methods would imply the collection of many data to obtain precise estimates and this can be rather costly. To cut back costs, we propose to implement a non-random sampling scheme and to correct for the subsequent sample selection bias in the econometric model. In this paper we put forward the relevant method, which does not lead to a loss in precision. Our illustration suggests an opportunity to collect 60\% less data points.

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File URL: http://hdl.handle.net/1765/131
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Publisher Info
Paper provided by Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam. in its series Research Paper with number ERS-2001-67-MKT Revision_Date: 2009-11-06.

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Date of creation: 01 Jan 2001
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Handle: RePEc:dgr:eureri:2001127

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Related research
Keywords: Outcome-dependent sampling; sample size; survey design; binary outcomes; logit model;

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This page was last updated on 2009-12-16.


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