Computer-assisted telephone interviews (CATI) through mobile phones are a low-cost, rapid and safe way to collect data. However, decisions for how such mobile phone surveys are designed and implemented, and their data analysed, can have implications for the sample reached, and in turn affect the generalisability of sample estimates. In this practice paper, we propose a framework for extending the use of CATI–mobile phone surveys in India, which can be applied broadly to future surveys conducted using this method. Across the stages of design, implementation and analysis, we outline challenges in ensuring that the data collected through such surveys are representative and provide recommendations for reducing non-coverage and non-response errors, thereby enabling practitioners in India to use CATI–mobile phone surveys to estimate population statistics with lower bias. We support our analysis by drawing on primary data that we collected in five mobile phone surveys across nine Indian states in 2020. Our recommendations can help practitioners in India improve the representativeness of data collected through mobile phone surveys and generate more accurate estimates.
We examine the use of publicly available voter rolls for household survey sampling as an alternative to household listings or field-based sampling methods. Using voter rolls for sampling can save most of the cost of constructing a sampling frame relative to a household listing, but there is limited evidence about their accuracy and completeness. We conducted a household listing in 13 polling stations in India comprising 2,416 households across four states and compared the listing to voter rolls for the same polling stations. We show that voter rolls include 91% of the households found in the household listing. We conduct simulations to show that sampling from voter rolls produces estimates of household-level economic variables with minimal bias. These results suggest that voter rolls may be suitable for constructing household sampling frames, particularly in rural India.
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