# Macro forecast for 20190101

This is a forecast of macroeconomic variables automatically generated for the coming year by David Dewhurst’s SERIES (Stochastic Expected Return Integrating Empirical Series) time series prediction software.

Uncertainty, risk, and loss

This is a forecast of macroeconomic variables automatically generated for the coming year by David Dewhurst’s SERIES (Stochastic Expected Return Integrating Empirical Series) time series prediction software.

A recent CNN article notes that “The Transportation Security Administration is considering eliminating passenger screening at more than 150 small and medium-sized airports” in the United States. Paul Cruickshank, a terrorism analyst for CNN, intones that this policy change might incite al Qaida and ISIS to attack small airliners to create “a great amount of panic.” Politico Playbook authors Anna Palmer and Jake Sherman, journalists I greatly admire, forwarded the CNN story this morning with the commentary “What could go wrong…”, assumedly implying that this was a poor policy choice relative to the status quo.

Here’s a quick overview of a naturally-bounded Weiner process (I’ll explain what that is momentarily) and an application to election prediction. In particular, we will see why it isn’t really at all surprising that Donald Trump won the 2016 presidential election.

Awhile ago—in fact, too long ago—I noted that Peter Dodds and I were working on a short paper regarding continuum preferential attachment processes. Well, here it is. We submitted it to Physical Review E and got a “reject with resubmit” late last fall; I haven’t yet had a chance to resubmit.

Here is a very enjoyable theorem due to Bonferroni. Let \(n \geq 2 \) and consider the probability triple \( (\Omega, \mathcal{F}, P) \) and a collection of sets of \( \Omega \) in \( \mathcal{F} \) denoted \( ( A_i )_{i=1}^n \). Then the following holds:

It often happens in research that one writes a considerable amount of code only to find that it won’t turn out to be useful in whatever project one is working on. Such was the case with me today: I wrote a solver for the diffusion equation only to find that it won’t suit the purpose for which I originally wrote it. Oh well! Check out these cool numerical solutions anyway.

Here is a simple yet beautiful problem in quantum mechanics: find the explict form of the wavefunction in the position basis for a single free particle (or multiple, noninteracting, distinguishable free particles) confined to move on the surface of the two-dimensional torus \(\mathbb{T}^2\).

Here’s a simple mechanism for formulating a carbon-trading market. This won’t be the fanciest thing ever, but it is efficient (defined in a very precise way) and guarantees a cap on total emissions into the infinite future, provided cheating the mechanism isn’t possible.

Here is an interesting problem I encountered in Mike Wilson’s analysis course: let \(u \in \mathbb{R}^d \) be a unit vector and define the function \(f: \mathbb{R}^d \rightarrow \mathbb{R} \) by

Health insurance has been front-and-center in the news recently, following Congressional Budget Office (CBO) reports that the current House and Senate healthcare bills may cause millions of Americans to lose their healthcare coverage while also removing several taxes imposed by the Affordable Care Act, colloquially known as Obamacare. Insurers haven’t been silent; some have stated that the proposed restructuring of Affordable Care Act exchanges would do wonders for their business, while others have vocally advocated for retaining the individual mandate. Here, I’ll outline a simple model of a health insurance company to demonstrate why the problem of covering as many people as possible while also ensuring low premiums for those who can’t afford insurance is so difficult. I’ll also suggest guidelines for future policy.

Peter Dodds, myself, and some other friendly folks affiliated with the Computational Story Lab just published a paper in Physical Review E detailing an inherent first-mover advantage in Herbert Simon’s preferential attachment model. Check it out!