Hampton Gaddy

In our new paper (BMJ Global Health), we systematically collected 923 historical growth studies covering 122 countries from 1814–2016.

By harmonising height-by-age data, we reconstruct stunting patterns over two centuries.

Link: doi.org/10.1136/bmjg...

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Come join our workshop on excess mortality methodology! It will be two great days of expert talks, discussion groups, and me revealing the results of our many analyst project! 40+ teams have signed up to estimate 1918 pandemic deaths with the method of their choice -- results should be fascinating!

Doing a review right now and I'm faced with "X exerts an independent association with Y"

My research means I spend a lot of timing thinking about the conditions under which people stop trying to preserve their health and well-being. Why do people continue to smoke even when they know the risks of cancer? Why do people refuse to wear a seatbelt or a helmet when they know the risks?

📣 Call for papers:
We are inviting you to submit contributions to a Special Collection on the Socioeconomic Inequalities in Mortality in the Long-Run, organized by K. Thompson, T. Riswick & S. Clouston. Submissions to this collection are possible from January 28, 2026 until June 28, 2026. (1/2)

My partner has done the Belgian application before, always selected German, and never failed to receive all materials in English 😂

Did the 1918 influenza pandemic cause a 1920 baby boom? Demographic evidence from neutral Europe In 1919–20, the European countries that were neutral in the First World War saw a small baby bust followed by a small baby boom. The sparse literature on this topic attributes the 1919 bust to indi...

And for all the 1918 flu cohort studies that compare 1919 to all surrounding cohorts, including 1920, the water is doubly muddied: fertility patterns make it look like any compositional changes persisted into 1920, causing bias in the opposite direction too (2/2)

doi.org/10.1080/0032...

Like the authors talk about, this also happened during the 1918 flu, with the 1919 cohort being poorer from birth than (at least in the US). As much as I wish differently, this casts doubt on the whole premise of cohort discontinuity studies of the effects of pandemics! (1/2)

Fascinating

Screenshot of title page including the following abstract: To minimise confounding bias and disentangle warranted from unwarranted disparities, researchers examining sentencing discrimination have traditionally sought to control for as many legal factors as possible. However, over the past decade, a growing number of scholars have questioned this strategy, noting that many legal factors are themselves subject to judicial discretion and that controlling for them can introduce post-treatment bias. Here, we use directed acyclic graphs (DAGs) to provide a formal and comprehensive assessment of the different types of bias that may arise from different choices of controls. In addition, we propose a new modelling framework to facilitate the selection of controls and reflect the model uncertainty created by the trade-off inherent in judicially-defined legal factors and other factors with a similar dual causal role. We apply this framework to examine race disparities in US federal courts and gender disparities in the England and Wales magistrates’ court. We find substantial model uncertainty for gender disparities and for race disparities affecting Hispanic offenders, rendering estimates of the latter inconclusive. Disparities against black offenders are more consistent and — under specific conditions — could be interpreted as evidence of direct discrimination.

Thrilled to share my latest paper entitled, "Estimating Discrimination in Sentencing: Distinguishing between Good and Bad Controls"

Led by @jpinasanchez.bsky.social, the paper introduces a framework for examining discrimination in criminal justice processes.

🧵 1/10

publicera.kb.se/ejels/articl...

Retraction Watch has covered the problem of the “national IQ” database. Should be noted I’m far from alone in working to remove these publications. The spreadsheet of pubs which use NIQ - linked to in the article - was started by @kohngregory.bsky.social; a project also worked on by Cathryn Townsend

The line "excess mortality is often treated like 'data', but ultimately it's a model" is definitely going in the welcome slides for the workshop

bsky.app/profile/adam...

If you want to channel your frustration with bad excess mortality modelling into some productive science, come join our "One Epidemic, Many Estimates" (1EME) project! Sign-ups are welcome through January/February!

www.lse.ac.uk/Economic-His...

The other part is that populations with polygyny often have strong pro-marriage norms, meaning that marriage markets are more "efficient" at getting men married. There's a nice parallel with China and Japan, re the impact of sex-selective abortion on marriage markets (2/2)

bsky.app/profile/hgga...

Thanks! One part is that marriage markets with polygyny are usually skewed feminine, rather than split 50/50. The biggest reason for this is a ~10 year age gap at marriage meaning that men marry women from larger birth cohorts, plus there are issues of mortality, migration, and preferences (1/2)

Register for IPUMs International Online Session Please use this form to register for the IPUMs International Session hosted by the Historical Economic Demography Group at LSE. The session will be on Zoom from 15:15-16:30 UK Time on 12 November 202...

Curious about using census microdata in your research? 📊

Join us for a webinar on IPUMS International, the world’s leading repository of harmonized census data.

🗓️ 12 Nov 2025 | 🕒 15:15–16:30 UK | 💻 Zoom
Register: forms.gle/oqTDNU4Zpn2s...

Hosted by the LSE Historical Economic Demography Group.

That looks right to me! Those results are consistent with our results -- it just depends on how you think about expectations. I wonder what the ratio of F 20-60 / M 30-60 looks like (which would match my framing above better)?

Plus, in contemporary polygynous populations, men marry women 5-10 years younger on average, so maybe the bands should be shifted from each other. But, cutting the female group off at 45 also means that you treat men who do marry a wife of a similar age as unmarried once they age past 45 (2/2)

I think that code should work! One question is whether you think that all men 20-60 and all women 20-45 would expect to be married, or whether they just expect to be married at some point in their lives. People who divorce or get widowed can marry single people (1/2)

Thanks for adding this! I'm curious, are there any papers reporting an adverse causal effect on child health that you're methodologically confident in?

Happy to talk through the evolutionary implications of the work! We focus a lot on the political science implications in the write up. @rebeccasear.bsky.social might have more thoughts

But the essence of our argument is actually that sex ratios don't matter a ton, at least in the populations represented by our census data. For example, controlling for sex ratios doesn't explain away the negative association between polygyny and unmarried men (4/4)

I think your point raises the issue of reverse causality, which we talk about! Ember (1974): conflict could promote polygyny by skewing sex ratios. I'm just not sure it makes sense to characterise human sex differentials in mortality as mostly due to competition (3/4)

www.jstor.org/stable/3773112

For example, here's a classic bit of demography on 1950s-60s African marriage markets that comes to that conclusion using a counterfactual approach that's different in spirit from ours (2/4)

bsky.app/profile/hgga...

The results show that it's also due to age gaps at marriage and men marrying 2nd+ wives at older ages (like we see in the real world). And it's definitely possible to get the result that there are no/few excess men without assuming (big) mortality differentials (1/4)

Great piece by @davidwlawson.bsky.social highlighting three new papers on polygamy. It's complicated but the effects aren't what you think: polygamy usually doesn't create "excess" men, usually doesn't disadvantage child health, and can even be an economic hedge!

theconversation.com/rethinking-p...

Looking forward to it! Sorry for the maybe frighteningly quick reply haha, your posts were at the top of my feed 🙃

We don't model pairing preferences, partly because tractable assumptions about preferences do weird things, like your model shows with all the unmarried women. But you can see how we try to think through preferences in supplement S2.1: we argue that they should ↑ the sustainability, not ↓ (3/3)

If you want a cool throwback to some really old school demography, Etienne van de Walle (1968) made a very similar point to us (pics attached but let me know if you want the PDF, it's hard to find). Goldman & Pebley is another classic source here (OA link: publishing.cdlib.org/ucpressebook...) (2/3)

This is interesting, thanks! Like you said further down in your thread, I'm wondering how the two different approaches lead to such different results. Building on refs. 35-40 in the paper, we model "availability ratios" of male-female age pairings, rather than whole marriage market (1/3)