In econometrics, a threshold effect is a relationship that changes character once a variable crosses a critical value. Below the line, one regime; above it, another. The relationship is not linear, and pretending it is will mislead you precisely when the stakes are highest.
Most of the questions I study live on lines like these. The moment a breach becomes reportable. The day a disclosure deadline arrives. The point at which a board stops treating security as an IT expense and starts treating it as a governance problem. My dissertation asks what mandatory disclosure timing actually does — to markets, to organizations, and to boards — and the honest answer so far is that the interesting action is almost never in the average. It is at the thresholds.
The name is also, admittedly, an echo of Threshold Data Sciences, the consulting practice where the research meets paying problems. The pun was sitting right there.
What to expect
Research notes as the dissertation moves toward defense — methods, measurement decisions, and the occasional dead end, because dead ends are data too. Commentary on disclosure regulation as it keeps evolving. Notes from teaching entrepreneurship and small business accounting, and from nearly twenty years of telecom operations that keep the empirical questions honest.
The cadence will be honest rather than ambitious: I will write when I have something worth saying, and not otherwise. If that suits you, there is an RSS feed.