The identity fragmentation bias
Files
First author draft
Date
2019-12-15
Authors
Lin, Tesary
Misra, Sanjog
Version
First author draft
OA Version
Citation
Tesary Lin, Sanjog Misra. "The Identity Fragmentation Bias." SSRN Electronic Journal, https://doi.org/10.2139/ssrn.3507185
Abstract
Consumers interact with firms across multiple devices, browsers, and machines; these interactions are often recorded with different identifiers for the same individual. The failure to correctly match different identities leads to a fragmented view of exposures and behaviors. This paper studies the identity fragmentation bias, referring to the estimation bias resulted from using fragmented data. Using a formal framework, we decompose the contributing factors of the estimation bias caused by data fragmentation and discuss the direction of bias. Contrary to conventional wisdom, this bias cannot be signed or bounded under standard assumptions. Instead, upward biases and sign reversals can occur even in experimental settings. We then propose and compare several corrective measures, and demonstrate their performances using an empirical application.