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How accurate are recall data ? evidence from coastal India


  • de Nicola, Francesca
  • Gine, Xavier


This paper investigates the accuracy of recall data by comparing administrative records with retrospective, self-reported survey responses to income and asset questions for a sample of self-employed households from coastal India. It finds that the magnitude of the recall error increases over time, in part because respondents rely less on memory and instead infer earnings based on past earnings. Individuals tend to recall monthly earnings more accurately when they are higher than the median. These results imply that the variance estimated from the self-reported earnings distribution will be lower than the real one. The paper also finds that data reported by income earners are more accurate than those by their wives. In addition, the use of time cues can worsen accuracy if they are not relevant to the respondent. Where the recall questions are placed in the two-hour long survey, however, does not affect accuracy.

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  • de Nicola, Francesca & Gine, Xavier, 2012. "How accurate are recall data ? evidence from coastal India," Policy Research Working Paper Series 6009, The World Bank.
  • Handle: RePEc:wbk:wbrwps:6009

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    References listed on IDEAS

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    12. Jed Friedman & Kathleen Beegle & Joachim De Weerdt & John Gibson, 2016. " Decomposing response error in food consumption measurement: implications for survey design from a survey experiment in Tanzania," Working Papers LICOS Centre for Institutions and Economic Performance 537166, KU Leuven, Faculty of Economics and Business, LICOS Centre for Institutions and Economic Performance.
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    15. Asian Development Bank Institute, 2017. "Risk Financing for Rural Climate Resilience in the Greater Mekong Subregion," Working Papers id:11761, eSocialSciences.
    16. Andrea Guariso & Thorsten Rogall, 2017. "Rainfall Inequality, Political Power, and Ethnic Conflict in Africa," LICOS Discussion Papers 39117, LICOS - Centre for Institutions and Economic Performance, KU Leuven.
    17. Ragui Assaad & Caroline Krafft & Shaimaa Yassin, 2016. "Comparing Retrospective and Panel Data Collection Methods to Assess Labor Market Dynamics," Working Papers 994, Economic Research Forum, revised Apr 2016.
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    19. Godlonton, Susan & Hernandez, Manuel A. & Murphy, Mike, 2016. "Anchoring bias in recall data: Evidence from Central America:," IFPRI discussion papers 1534, International Food Policy Research Institute (IFPRI).

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    Access to Finance; Statistical&Mathematical Sciences; Educational Sciences; Fiscal&Monetary Policy; Economic Theory&Research;

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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