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A Comparison Of Causal Inference Methods And Their Application In Big Data Analytics, Xuan Wang

LSU Doctoral Dissertations

With the rise of Big Data analytics, the new field of causal inference (Pearl, 2009) has received more attention in business research fields such as Accounting (Lawrence, Minutti-Meza, & Zhang, 2011) and Marketing (Manganaris, Bhasin, Reid, & Hermiz Keith, 2010). Traditional statistics focuses on correlation which may lead to misleading conclusions because the estimates can be severely biased even when data sets are large. The objective of causal inference is to obtain estimates from observational data that are unbiased and can thus be interpreted as causal. This study provides a systematic comparison of the performance of four causal inference methods …