Endogeneity: How Failure to Correct for it can Cause Wrong Inferences and Some Remedies

Although researchers in business and management are becoming increasingly aware of the importance of endogeneity affecting regression analysis, they frequently do not have the right methodological toolkit to adjust for this issue. In this paper we discuss such a toolkit. There are also areas in business and management research which to date seem to be mostly oblivious about the endogeneity issue. We highlight such an area, which studies the question of whether firms that are cross-listed on a foreign stock exchange are charged premium fees by their auditors. When the same methodology (pooled ordinary least squares) as in the existing literature is used, the existence of an audit fee premium for cross-listed firms seems to be confirmed. However, once methodologies are used which adjust for the various types of endogeneity (i.e. omitted variable bias, simultaneous and dynamic endogeneity) there is no longer support for the existence of such a generalized premium. Hence, not only do we illustrate that failure to adjust for endogeneity has severe consequences such as drawing the wrong inferences, but we also review various ways to control for the different types of endogeneity.