Estimating Mis-Reporting in Dyadic Data: Are Transfers Mutually Beneficial?

41 Pages Posted: 6 Dec 2014

See all articles by Margherita Comola

Margherita Comola

Paris School of Economics (PSE); Université Paris I Panthéon-Sorbonne

Marcel Fafchamps

Stanford University - Freeman Spogli Institute for International Studies

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 (gifts and loans) from the village of Nyakatoke in Tanzania, investigating whether observed transfers are mutually beneficial, i.e. in the self-interest of both parties involved. Our results suggest that mutual self-interest is not a necessary condition for transfers between households who are sufficiently close socially and geographically to take place, and we show that not taking reporting bias into account leads to serious underestimation of the total amount of transfers between villagers.

Keywords: social networks, dyadic data, reporting bias, informal transfers

JEL Classification: C13, C51, D85

Suggested Citation

Comola, Margherita and Fafchamps, Marcel, Estimating Mis-Reporting in Dyadic Data: Are Transfers Mutually Beneficial?. IZA Discussion Paper No. 8664, Available at SSRN: https://ssrn.com/abstract=2534692

Margherita Comola (Contact Author)

Paris School of Economics (PSE) ( email )

48 Boulevard Jourdan
Paris, 75014 75014
France

Université Paris I Panthéon-Sorbonne ( email )

17, rue de la Sorbonne
Paris, IL 75005
France

Marcel Fafchamps

Stanford University - Freeman Spogli Institute for International Studies ( email )

Stanford, CA 94305
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
14
Abstract Views
243
PlumX Metrics