Jung Hyun Kim

✨Bell postdoctoral fellowship has allowed me to challenge my assumptions and to see beyond my understandings of society. If you're looking to grow by standing on the shoulders of giants, this might be the position for you!

Feel free to reach out if you'd like to hear more about the experience :)

The evidence keeps accumulating that Brexit was an astonishing self-inflicted economic policy disaster. The fact that it is a slow-moving one bodes ill for those who think that populist economic mismanagement will translate into voters punishing populists. www.nber.org/system/files...

Replication code as a cornerstone of the credibility revolution 2.0 This opinion piece argues that code sharing is a key yet underutilized component of research transparency and the ongoing “Credibility Revolution 2.0.…

📢 Excited to share my first academic opinion piece—now out #OpenAccess in the Journal of Behavioral and Experimental Economics!
🔗 www.sciencedirect.com/science/arti...

👇Thread: Why replication code is essential for the future of credible science 🧵

A good peer reviewer - who engages thoughtfully and constructively, teaches, notes what's good about a paper and what can be improved - is such a positive force. As a mentor (and as an editor and an author), I send out deep thanks to everyone who works hard to write kind and useful reviews.

Amazing PhD opportunity to research Alzheimer's and Parkinson's disease with Anja and the team! ✨

This is so nice! Thanks for sharing :)

I think this question was probably the starting point of Dube, Lester, and Reich's (2010) “local estimators comparing all contiguous counties” approach...! At the very least, spatial heterogeneity would be less concerning than simply including state FE.

Conceptual Framework of Transfer Learning Method

We use transfer learning, a machine learning approach that addresses the deviation-variance tradeoff.

It combines large source data with small target data to create a dementia estimation algorithm.

🔎 Replication R code 👉 github.com/TL-dementia/...

Funding: ERC #Episky #Dementia

Improving accuracy in the estimation of probable dementia in racially and ethnically diverse groups with penalized regression and transfer learning Abstract. Algorithmic estimations of dementia status are widely used in public health and epidemiological research, however, inadequate algorithm performan

🚨 Underrepresentation of racially and ethnically diverse populations in dementia studies is a challenge.

"How can we make better use of the data we have?"

With @mariaglymour.bsky.social, Kenneth Langa, and @anjaleist.bsky.social, now in American Journal of Epidemiology🔓

👉 doi.org/10.1093/aje/...

Fantastic news before Christmas! :) Congratulations 👏👏👏

A hypothetical intervention on the use of hearing aids for the risk of dementia in people with hearing loss in UK Biobank Abstract. Observational studies have reported that hearing aid (HA) use is associated with a reduced risk of dementia diagnosis, suggesting a possible prot

Very happy to see our project masterfully led by Dr Jure Mur now published 🎉 An emulated trial design on the question of effectiveness of hearing aid use to modify #dementia risk.
#Episky
Data #UKBiobank
Funding #ERC
doi.org/10.1093/aje/...

YouTube video by Berkeley Population Sciences 6. The unintended effects of a large minimum wage increase on health: Evidence from South Korea

Here is our 9-minute YouTube video explaining the findings!
www.youtube.com/watch?v=s4bT...

The unintended effects of a large minimum wage increase on health: Evidence from South Korea The 2018 minimum wage increase in South Korea was a major policy change that impacted employment and labour productivity, but its effects on health ha…

💡How does a large minimum wage increase impact health? 🤔

Excited to share our new paper with @anjaleist.bsky.social
& Marc Suhrcke, now published in Social Science & Medicine (Open Access!) 🔓

www.sciencedirect.com/science/arti... #Econsky #Episky

Maternal genetic risk for depression and child human capital We here address the causal relationship between the maternal genetic risk for depression and child human capital using UK birth-cohort data. We find t…

@giorgiamenta.bsky.social has a fantastic paper on "Maternal genetic risk for depression and child human capital" using the Avon Longitudinal Study of Parents and Children (ALSPAC) survey. www.sciencedirect.com/science/arti...

Welcome @anjaleist.bsky.social to Bluesky 🌐✨

Her research centers on health inequalities, cognitive aging, and dementia. Check out her recently completed ERC-funded project here: cognitiveageing.uni.lu

Research update: we have a new version of our pharma M&A paper! AND, we posted the data we collected on m&a deals. Links below, main takeaways in thread.
Paper summary: lucamaini.com/working-pape...
Full draft: lucamaini.com/s/feng_hwang...
Data: www.lucamaini.com/data

Thank you so much. It means a lot. I just sent the WP, hope you enjoy reading them!

Check out our session ✨Health and the Minimum Wage✨ at ASHEcon chaired by @mpbitler.bsky.social.

I will give two talks covering Korean and US minimum wage policies. The central focus remains the same: older workers.
Feel free to reach out ☕ #ASHEcon2024

ashecon.confex.com/ashecon/2024...

Invited Commentary: Where Do the Causal DAGs Come From? Abstract How do we construct our causal DAGs, e.g. for life course modelling and analysis? In this commentary I review how the data-driven construction of causal DAGs (causal discovery) has evolved, what promises it holds and what limitations or caveats must be considered. In conclusion I find that expert- or theory-driven model building might benefit from some more checking against the data and causal discovery could bring new ideas into old theories.

Very brief commentary by Vanessa Didelez on causal discovery and the role of expert knowledge when building DAGs: academic.oup.com/aje/advance-...
Already suspected that I would like this after her talk yesterday, but I really do dig her writing -- it's very crisp and accessible.

This is incredibly helpful, thank you for the transparency and the courage to share this!

NEW PAPER out today in the BMJ

TRIPOD+AI: reporting recommendations for studies developing or validating prediction models for use in healthcare that use #machinelearning methods

bmj.com/content/385/...

#ArtificialIntelligence #AIstandards #OpenAccess

Maria Glymour on LinkedIn: Public health ideas that blew my mind: common mistakes shouldn’t be dea... #publichealth #epidemiology #graduateschool #injury #motorvehicle #rural

I'm trying to write down some of the core public health ideas that I think are truly amazing -ideas I wish were part of popular understanding of health. Here's my first effort: www.linkedin.com/posts/maria-... (forgive slightly maudlin language and AI cover art). Suggestions welcome.

[📣Workshop on Determinants of Adult Mortality, Morbidity, and Healthy Aging in LMICs📣] by CEDA/CBPH.

- 2-day virtual workshop on determinants of adult mortality, morbidity, and healthy aging in LMICs
- Day 1: 2/23 & Day 2: 3/1

Register/Details: populationsciences.berkeley.edu/conferences/...

An invaluable review paper that brings together recent developments in causal inference and life-course epidemiology.

My ERC team has created an account where they will share updates of the Stata and R packages they are working on, follow them! bsky.app/profile/erct...