A (surprising) profile, a surprising result,a Maharaja(h) in the Yorkshire Dales, Driverless Cars and (non)ergodicity

Can you guess what this article is about, who has written it, and when?

The dirty little secret on Wall Street is that the men responsible for its current reputation were not exceptionally bad. They were just ordinary people placed in unusual circumstances.

“Knowing somebody” to “get the job done” is older than you thought, is applicable in more places than you’d expect, and last across a longer time horizon than you’d have expected. Well, I don’t know about you, but each of these was true in my case.

The main empirical analysis of this article compares a snapshot of the location of mission stations in Africa in 1903 to the precise locations of projects funded by the World Bank in 1995–2014. The unit of analysis is derived from a grid of 55km×55km square cells covering the African mainland and Madagascar. The results imply that the presence of (at least) one mission station increases the probability that an area is allocated a development project by approximately 50 percent.

A rather macabre excerpt, but to me a revealing one. On “The Maharajah of the Yorkshire Dales

The first ethnically Indian minister in Britain was Parmjit Dhanda. He too found a rural seat, out in the West Country, in Gloucestershire. People were almost always polite and pleasant to him, but one morning he came out and found a severed pig’s head on the bonnet of his car.

The year was 2010.

 

Vox explains the current state of affairs when it comes to driverless cars, and how long that might take (short answer? A little bit longer, but no idea exactly how long. Sorry.)

There are two core statistics useful for evaluating how advanced a self-driving car program is. One is how many miles it has driven. That’s a proxy for how much training data the company has, and how much investment it has poured into getting its cars on the road.

The other is disengagements — moments when a human driver has to take over because the computer couldn’t handle a situation — per mile driven. Most companies don’t share these statistics, but the state of California requires that they be reported, and so California’s statistics are the best peek into how various companies are doing.

On both fronts, Google’s sister company Waymo is the clear leader. Waymo just announced 20 million miles driven overall, most of those not in California. In 2018, Waymo drove 1.2 million miles in California, with 0.09 disengagements every 1,000 miles. Coming in second is General Motors’ Cruise, with about half a million miles and 0.19 disengagements per 1,000 miles. (Cruise argues that since it tests its cars on San Francisco’s difficult streets, these numbers are even more impressive than they look.)

A topic that more students of economics should know about: (non)-ergodicity.

First is a very micro level concern: behavioural biases. The whole idea of endowment effects and loses aversion make sense in a world dominated by non-ergodic processes. We hate losing what we have because it decreases our ability to make future gains. Mathematics tells us we should avoid being on one of the many losing trajectories in a non-ergodic process.

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