Practical issues to consider when working with big data

Abstract

Increasing access to alternative or “big data” sources has given rise to an explosion in the use of these data in economics-based research. However, in our enthusiasm to use the newest and greatest data, we as researchers may jump to use big data sources before thoroughly considering the costs and benefits of a particular dataset. This article highlights four practical issues that researchers should consider before working with a given source of big data. First, big data may not be conceptually different from traditional data. Second, big data may only be available for a limited sample of individuals, especially when aggregated to the unit of interest. Third, the sheer volume of data coupled with high levels of noise can make big data costly to process while still producing measures with low construct validity. Last, papers using big data may focus on the novelty of the data at the expense of the research question. I urge researchers, in particular PhD students, to carefully consider these issues before investing time and resources into acquiring and using big data.