Lastly, a shout-out to my co-author Manisha Jain, the study participants, and the Dutch Research Council (NWO) for making this research possible. (4/4)

- People with higher risk tolerance were much more likely to participate, increasing the risk of sampling bias on risk preferences.
- To improve participation rates, funds should prioritize data security, better communication materials, and an insurance scheme. (3/4)

- People were, on average, hesitant to share their DNA with researchers, primarily due to the risk of privacy violations.
- Financial incentives were not very effective in persuading people to accept these risks. (2/4)

The scenes in the Oval Office today will shame the US for decades. They’ll never be forgotten.

A world leader, fighting for his country against the 21st century’s Nazis, came to the US and was attacked & abused by a gangster regime siding with the fascist invaders.

A historic disgrace.

The preprint is also available on medRxiv:
www.medrxiv.org/content/10.1...

I mislabelled this cut-out version of the figure, it should read "Risk of any disease for males (MDC-males)" and NOT "prostate cancer".

(4/4) We also find that if the take-up rate remains <50%, or if the genetic-test accuracy does not improve as much as expected, then the selection pressure may remain more manageable. In this case, complete bans on genetic information in critical illness insurance markets could be feasible policy.

(3/4) Under widespread take-up of genetic tests (>50%), we find evidence of substantial opportunity for selection from future PGIs (both at lower/upper bounds). Disease bundling reduces the selection noticeably, but is not sufficient to circumvent the problem fully. But most people are not tested.

(2/4) We first predict the risk of seven critical illnesses, e.g., prostate cancer, while adjusting for both (i) observable risk factors, and (ii) the measurement error of the current PGI technology. We then leverage these predictions to model a realistic insurance policy covering many conditions.

Sounds awesome, but could be hit or miss. What is the main argument?

We are going to look back at a lot of empty steel, glass, and concrete, wishing we had built a positive return capital stock instead.

We have now had at least 25 years of crisis rates, QE, or a combination of both. The capital stock built up during this time will be found unproductive in the coming years (educations with negative returns, hotels/offices/malls/airbnb with negatjve returns, CRE in general).

Few people have experience woth factoring in this uncertainty in their evonomic or financial decisions.

And if the mark-to-market value would lead to financial institutions failing, the central banks are likely to let the financial institutions get rid of their Bitcoin based on historical cost accounting = massive wealth transfer.

I often recommend The Effect to my thesis students to fresh up on regression methodology and inference: theeffectbook.net