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

Author

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  • Comola, Margherita

    (Paris School of Economics)

  • Fafchamps, Marcel

    (Stanford University)

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.

Suggested Citation

  • Comola, Margherita & Fafchamps, Marcel, 2014. "Estimating Mis-reporting in Dyadic Data: Are Transfers Mutually Beneficial?," IZA Discussion Papers 8664, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp8664
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    References listed on IDEAS

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    Cited by:

    1. Arun Advani & Bansi Malde, 2014. "Empirical methods for networks data: social effects, network formation and measurement error," IFS Working Papers W14/34, Institute for Fiscal Studies.

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    Keywords

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    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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