Author:

• Zico Dasgupta

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).

Authors:

• Deepti Goel
• Rosa Abraham
• Rahul Lahoti

The recently released data from the 2017 – 2018 Periodic Labour Force Survey have created a controversy regarding the quantity of employment generated in the past few years in India. Estimates ranging from an absolute increase of 23 million to an absolute decline of 15.5 million have been published. In this paper we show that some of the variation in estimates can be explained by the way in which populations are projected based on Census 2011 data. We estimate the change in employment using the cohort-component method of population projection. We show that for men total employment rose but the increase fell far short of the increase in working age population. For women, employment fell. The decline is concentrated among women engaged in part-time or occasional work in agriculture and construction. 

Authors:

• Paaritosh Nath
• Amit Basole