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.
social networks dyadic data reporting bias informal transfers