Associations Between Cannabis Use, Medication Status And Panic-Anxiety Disorder Symptoms Among Us Adults

The existing body of literature focuses on the onset of panic disorders or other side effects as an association with cannabis use, but does little to address how possible concomitant cannabis use affects symptom presentation in already-diagnosed patients. The present project aims to take a closer look at adults with a lifetime history of DSM-5 diagnosed anxiety disorders, their prescribed (non-cannabis) medication use, cannabis use frequency, and associated symptom severity. In general, we find that cannabis use is associated with higher panic-anxiety symptom severity across panic disorder without agoraphobia, generalized anxiety disorder, and people with combined anxious-distress diagnoses, after controlling for prescription medication status and professional help seeking. However, the difference between users and non-users is often small and not necessarily clinically relevant: only 1 or 2 symptoms. Worth noting is that we found no dose-response relationship for frequency of cannabis use. Being an infrequent user is not significantly different than being a daily user in terms of unique symptom presentation. This means that increasingly higher cannabis use does not necessarily induce increasingly more severe anxiety or distress. Rather, it seems that once an individual’s cannabis use crosses over a certain threshold, symptom presentation increases. For some disorders, this is an all-or-none phenomenon; any cannabis use is associated with more severe symptoms than staying abstinent. For others, only daily users present with higher symptoms than non-users. The sole divergence to this conclusion is that panic without agoraphobia patients who use infrequently seem to have more severe symptoms than non-users and daily users

Measuring investment opportunities using financial statement text

We analyze 10-K texts from EDGAR during 1995-2009 to score firms’ investment opportunity sets on multiple dimensions. We identify 646 unique key words that predict future investments and group them into 62 factors. Industry-specific factors include Bio-Pharmaceutical, Banking, Information Technology, Oil & Gas and Semi-conductor, while more general factors include Impairment, Debt Intensity, Executive Employment, Preferred Stock Buyback and Capital Seeking. Our multi-dimensional measures of firms’ investment opportunities outperform Tobin’s Q and/or industry-fixed effects, in predicting out-of-sample future (2010-15) investments and related corporate policies, and even inform incrementally over lagged dependent variables