Christopher RootTechnology adoption is widely regarded as critical to agricultural development. However, survey based data on technology adoption is costly to collect. This research is an attempt to lower this cost by using locally based enumerators and tablets. The hypothesis this research tests is that the 'local enumerator approach' will reduce costs while maintaining data quality. This hypothesis is tested by comparing adoption data collected through the local enumerator approach with that collected through a conventional survey in India. Means comparison tests indicate statistically significant differences in adoption estimates derived from the two approaches. Regression analysis, controlling for village fixed effects, covariates and enumerator fixed effects, is used to identify adoption measurement differences between the local and the conventional enumerator approaches. However, none of these analytical approaches are able to eliminate all the differences in adoption estimates, implying significant differences in data quality generated by these two approaches. The study design however was not able to control several potential confounding factors, such as enumerator training method, differences in questionnaire design, and data collection application tools that may have influenced data quality. Although costs are found to be comparable between the two approaches, over the long run, there is potential for costs of local enumerator approach to decrease relative to the conventional approach because of cost efficiencies. However, more effort is needed to ensure data quality before this approach can be considered a cost-effective and a reliable method of data collection in developing countries.
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