Documentation of the File Drawer Problem at Finance Conferences: A Follow-Up Study

Abstract

1. Manoela N. Morais 1. is a graduate student in the department of finance at Pace University in New York. (mm78341n{at}pace.edu) 2. Matthew R. Morey 1. is professor in the department of finance at Pace University in New York. (mmorey{at}pace.edu) 1. To order reprints of this article, please contact David Rowe at d.rowe{at}pageantmedia.com or 646-891-2157. The file drawer problem is a publication bias where journal editors are much more likely to accept empirical papers with statistically significant results than those with statistically nonsignificant results. As a result, papers that have nonsignificant results are not published and relegated to the file drawer, never to be seen by others. In a previous paper, Morey and Yadav (2018), examined the file drawer problem in finance journals and found evidence that strongly suggests that such a publication bias exists in finance journals. In this follow-up study, we examine the prevalence of the file drawer problem at finance conferences. As such we are the first article in finance that we know of to attempt such an analysis. To do this, we examine every single empirical paper presented at the annual Financial Management Association (FMA) conference from 2014–2018. In an examination of 3,425 empirical papers, we found less than one-half of one percent of these papers had statistically nonsignificant results. These results suggest that there is also a significant file drawer problem at finance conferences. TOPIC: [Statistical methods][1] Key Findings [1]: https://www.iijournals.com/topic/statistical-methods