187: Endogeneity: Myths, Legends, and Facts – Fourth Annual (17127)

Management scholars are increasingly concerned about biases in empirical analyses from endogeneity. When endogeneity is present, any model that does not account for the source of endogeneity will provide biased coefficient estimates. Thus, scholars strive to address endogeneity concerns in their research. Yet, scholars do not share a common understanding of endogeneity and often implement questionable solutions in response to their perceived concerns. Our target audience is Academy members who lack confidence in dealing with endogeneity or who want to improve their methodological ‘tool kit.’ This PDW will provide a learning opportunity about different topics related to endogeneity and how to address it correctly. To do so, we explore the myths, legends, and facts about endogeneity. The PDW will be divided into two parts. Part 1 consists of a selection of presentations on different issues related to endogeneity. Specifically, Dr. Sarah Wolfolds will discuss post-estimation tests, sample size, and instrumental variable techniques, Dr. John Busenbark will discuss simulations as a means of sensitivity analyses for potential bias and efficiency associated with endogeneity, Dr. Lindsey Greco will discuss measurement error and endogeneity, and Dr. Timothy Quigley will share editor’s view of endogeneity in the field. In Part 2, the panelists will answer questions from the audience, from which we will facilitate a scholarly conversation about their views on endogeneity. With this PDW, we hope scholars will understand endogeneity better and learn when and how to account for endogeneity in producing high-quality, credible, and replicable scientific research.