Improving Survey Quality using Para Data: Lessons from the India Working Survey

Deepti Goel, Azim Premji University

Rosa Abraham, Azim Premji University

Rahul Lahoti, ETH Zurich

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The efficacy of survey-based policy recommendations is primarily dictated by the quality of data collected in the first place. Is the survey truly representative of the population it claims to characterise? Are respondents voicing their true opinions or are they playing to the gallery? Did enumerator bias creep into the data? These are questions that most users of surveys have, but are typically brushed aside in the race to get the analyses out. While there are no foolproof measures to ensure that survey data are authentic, certain steps can be taken to improve their dependability. One such is the use of what is called ‘para data’ (data about the process of data collection), to streamline enumerator practices, and thereby improve the reliability of the data being collected. This report details our experience of using para data to improve the quality of the India Working Survey (IWS).

Keywords: Surveys

Goel, Deepti, Rosa Abraham, and Rahul Lahoti. 2021. “Improving Survey Quality Using Para Data: Lessons from the India Working Survey”. Centre for Sustainable Employment Working Paper #43, Azim Premji University, Bangalore.