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)
07.05.2025 08:49 — 👍 0 🔁 0 💬 0 📌 0
- 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)
07.05.2025 08:49 — 👍 1 🔁 0 💬 1 📌 0
- 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)
07.05.2025 08:49 — 👍 0 🔁 0 💬 1 📌 0
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.
28.02.2025 18:11 — 👍 5886 🔁 1732 💬 76 📌 64
Seems like central banks have completely lost control of the only thing they are supposed to control: the money supply.
05.02.2025 18:48 — 👍 0 🔁 0 💬 0 📌 0
I mislabelled this cut-out version of the figure, it should read "Risk of any disease for males (MDC-males)" and NOT "prostate cancer".
27.01.2025 15:02 — 👍 0 🔁 0 💬 0 📌 0
While assuming 50% genetic test takeup, the figure displays minimum implicit tax up to the 80th percentile of risk within the standard risk class for the single-disease and multiple-disease CII contracts, in the four scenarios. The striped blue area corresponds to the range of the implicit tax observed by Hendren (2013, Econometrica) in market segments that had not unraveled, and the striped red area corresponds to the range for market segments that had unraveled. The breaks at the top of the tallest bars indicate that these bars' heights exceed the figure's.
(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.
27.01.2025 14:51 — 👍 2 🔁 1 💬 0 📌 0
The figure displays minimum implicit tax up to the 80th percentile of risk within the standard risk class for the single-disease and multiple-disease CII contracts, in the four scenarios. The striped blue area corresponds to the range of the implicit tax observed by Hendren (2013, Econometrica) in market segments that had not unraveled, and the striped red area corresponds to the range for market segments that had unraveled. The breaks at the top of the tallest bars indicate that these bars' heights exceed the figure's.
(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.
27.01.2025 14:51 — 👍 0 🔁 0 💬 1 📌 0
Left panel: distribution of the risk of contracting any of the six diseases in the male multiple-disease contract by age 65, conditional on various information scenarios. The vertical blue line marks the average risk in the standard risk class. The standard risk class individuals are shown in blue; insurers treat these individuals identically, so the blue distribution corresponds to the distribution of private risk for these individuals. Right panel: implicit tax for consumers in the standard risk class as a function of their percentile private risk of contracting one of the diseases, for each scenario.
(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.
27.01.2025 14:51 — 👍 0 🔁 0 💬 2 📌 0
Genetic Prediction and Adverse Selection
The predictive power of genetic data has been increasing rapidly and is reaching levels of clinical utility for many diseases. Meanwhile, many jurisdictions hav
(1/4) Excited to announce our new method that can estimate the predictive performance of _future_ genetic tests for common diseases (polygenic indexes, PGIs). We showcase the method by evaluating the impact of this fast-improving technology on critical illness insurance. SSRN: tinyurl.com/37rtbujx
27.01.2025 14:51 — 👍 5 🔁 2 💬 2 📌 1
It appears that the law of demand is not applicable to asset/speculative demand, because often as the price of an asset rises, so does the demand for the appreciating asset. This must in part explain the inherent instability of markets, Minskey-style?!
26.12.2024 15:01 — 👍 0 🔁 0 💬 0 📌 0
Sounds awesome, but could be hit or miss. What is the main argument?
26.12.2024 02:40 — 👍 0 🔁 0 💬 0 📌 0
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.
25.12.2024 15:07 — 👍 0 🔁 0 💬 0 📌 0
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).
25.12.2024 15:05 — 👍 0 🔁 0 💬 1 📌 0
Few people have experience woth factoring in this uncertainty in their evonomic or financial decisions.
25.12.2024 15:02 — 👍 0 🔁 0 💬 0 📌 0
When central banks make use of interest rates as a gas and break pedal, the interest rate will never be exactly right for the prevailing circumstances. Artificially set interest rates will therefore cause misinvestent. The deeper the misinvestment, the more painful the next crisis will be.
25.12.2024 15:01 — 👍 0 🔁 0 💬 1 📌 0
In not too long, counterparty risk will be a serious consideration and transaction cost that most ordinary people typically do not experience when ordering a new car or kitchen.
22.12.2024 17:06 — 👍 0 🔁 0 💬 1 📌 0
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.
27.11.2024 09:45 — 👍 3 🔁 0 💬 0 📌 0
Thought of this morning: as the interest in Bitcoin among financial institutions increases, it is not unthinkable that Bitcoin will end up on the balance sheet of central banks during future quantitative easing efforts.
27.11.2024 09:42 — 👍 2 🔁 0 💬 1 📌 0
I often recommend The Effect to my thesis students to fresh up on regression methodology and inference: theeffectbook.net
22.02.2024 05:44 — 👍 1 🔁 0 💬 0 📌 0
Postdoc @ IBG, Colorado. Research interests: ageing, frailty, dementia, genetic epidemiology & preventive medicine 🏳️🌈
I am developing machine learning approaches to harness the information contained in the electronic health records, national registries and biobanks for improved disease diagnosis and healthcare resource allocation. Based at FIMM, University of Helsinki.
asst prof | clinical psychologist | some sort of geneticist | not a neuroscientist | mass general & harvard med | engagement ≠ endorsement
Postdoctoral researcher at the Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki. @fimm-uh.bsky.social
Research Group Leader MPRG Biosocial | Max Planck Institute for Human Development | Jacobs Foundation Fellow
PhD student interested in human genomics. Mostly here to keep up with articles:)
Epidemiologist, Universität Münster
Research Associate at the Social, Genetic & Developmental Psychiatry Centre, Kings College London. Interests: developmental psychology, data science, coffee. www.bignardi.co.uk
Group Leader in Human Genetics, Wellcome Sanger Institute
Postdoctoral fellow @uni_regensburg interested in transdiagnostic traits, genes, and the brain
Clinical geneticist in training @ Amsterdam UMC | assistant professor working towards treatment for rare genetic diseases @ Emma Center for Personalized Medicine
Senior Scientist, Department of Biology, Emory University, Atlanta, GA.
Molecular Biologist. RNA Scientist. Yeast Geneticist 🧬. British🇬🇧. Runner 🏃🏻…. Opinions are my own.
Interests: RNA Decay, RNA Processing, RNA & Disease.
Aotearoa New Zealand Research group in search of Eating Disorder Genetics - Otago University Christchurch - follow for more information
Medical Researcher studying substance use disorders with statistical genetics, biomarker data, and machine learning/AI.
Professor of Psychology and Genetics at University of Surrey
Fitness Expert | Writer | Brown University Public Health Alum
domenicangelino.com
instagram.com/domenichealth
Population #Genomics & Environment in #Mentalhealth | studying #psychiatricgenetics #behaviorgenetics | directed by Roseann Peterson| SUNY Downstate | VCU_VIPBG
https://www.pop-gem-lab.com/
Statistical Geneticist, Associate Professor @PittPublicHealth
#academicmom #statgen #genetics #education #rstats #biostatistics #likeablebadass #mothersleadingscience
Studying genomics, machine learning, and fruit. My code is like our genomes -- most of it is junk.
Assistant Professor UMass Chan, Board of Directors NumFOCUS
Previously IMP Vienna, Stanford Genetics, UW CSE.