Showing papers by "Mark H. Lang published in 2016"

The Evolution of 10-K Textual Disclosure: Evidence from Latent Dirichlet Allocation

Abstract: While characteristics of quantitative accounting data have received substantial attention in the academic literature, much less is known about the accompanying text. We document marked trends in 10-K disclosure over the period 1996-2013, with increases in length, boilerplate, stickiness, and redundancy and decreases in specificity, readability, and the relative amount of hard information. We use Latent Dirichlet Allocation (LDA) to examine specific topics and find that new FASB and SEC requirements explain most of the increase in length and that 3 of the 150 topics — fair value, internal controls, and risk factor disclosures — account for virtually all of the increase. These three disclosures also play a major role in explaining the trends in the remaining textual characteristics. Our results are potentially relevant to regulators in understanding trends in, and topical sources of textual characteristics amid concerns about increasingly onerous accounting disclosures.

Do Managers Really Guide Through the Fog? On the Challenges in Assessing the Causes of Voluntary Disclosure

Abstract: Guay, Samuels, and Taylor (2016) document that firms with longer and more complex 10-Ks provide relatively more voluntary disclosure, which they interpret as evidence that managers use voluntary disclosure to mitigate negative effects of complex mandatory disclosure. We review the results of Guay et al. and focus on two main challenges to inferring causality: (1) the coincidence of upward over-time trends in annual report length, complexity, and voluntary disclosure, and (2) the potential for omitted correlated variables, such as changes in firm economics, to drive changes in 10-K textual characteristics and voluntary disclosure. While the results in Guay et al. are extensive and robust, we argue that economic drivers of, and trends in, voluntary disclosure present important avenues for future research.