Counting on count regression: overlooked aspects of the Negative Binomial specification

Abstract: Negative Binomial regression is a staple in Operations Management empirical research. Most of its analytical aspects are considered either self-evident, or minutiae that are better left to specialised textbooks. But what if the evidence provided by trusted sources disagrees? In this note I set out to verify results about the Negative Binomial regression specification presented in widely-cited academic sources. I identify problems in how these sources approach the gamma function and its derivatives, with repercussions on the Fisher Information Matrix that may ultimately affect statistical testing. By elevating computations that are rarely specified in full, I provide recommendations to improve methodological evidence that is typically presented without proof.