The Missing Transfers: Estimating Mis-reporting in Dyadic Data

Marcel Fafchamps and Margherita Comola (margherita.comola@universite-paris-saclay.fr)

No 10575, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: Many studies have used self-reported dyadic data without exploiting the pattern of discordant answers. In this paper we propose a maximum likelihood estimator that deals with mis-reporting in a systematic way. We illustrate the methodology using dyadic data on inter-household transfers from the village of Nyakatoke in Tanzania, investigating the role of wealth in link formation. Our results suggest that observed transfers are grounded in mutual self-interest, and we show that not taking reporting bias into account leads to incorrect inference and serious underestimation of the total amount of transfers between villagers. The method introduced here is applicable whenever the researcher has two discordant measurements of the same dependent variable.

Keywords: Dyadic data; Informal transfer; Reporting bias; Social Networks (search for similar items in EconPapers)
JEL-codes: C13 C51 D85 (search for similar items in EconPapers)
Date: 2015-05
New Economics Papers: this item is included in nep-dev and nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Related works:
Journal Article: The Missing Transfers: Estimating Misreporting in Dyadic Data (2017)
Working Paper: The Missing Transfers: Estimating Misreporting in Dyadic Data (2017)
Working Paper: The Missing Transfers: Estimating Misreporting in Dyadic Data (2017)
Working Paper: The Missing Transfers: Estimating Mis-reporting in Dyadic Data (2016)
Working Paper: The Missing Transfers: Estimating Mis-reporting in Dyadic Data (2016)
Working Paper: The Missing Transfers: Estimating Mis-reporting in Dyadic Data (2016)
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