283 karmaJoined Jul 2020


Research Assistant at World Bank DIME. DC-based. I like talking about development, economics, trade, and DEI.

How I can help others

Happy to chat about
- teaching yourself to code and getting a software engineer role
- junior roles at either World Bank or IMF
- picking a Master's program for transitioning into public policy
- selling yourself from a less privileged background
- learning math (I had a lot of mental blocks on this earlier)
- dealing with self-esteem and other mental health issues
- applications for Econ PhD programs (haven't done it yet, but people are surprised by how much I thought about the process)

Fastest way to reach me is geoffreyyip@fastmail.com but I do check messages here occasionally


Thanks so much for this! I don't know why I ever thought about decomposing the idea of corruption but it seems like a really obvious framework now that you've mentioned it. Hoping to give that a read sometime.

Hi Khai, this depends on what you want to do in the future. The short answer is no. Both statistics and maths are broad fields with solid generalizability and respectability. They also tend to vary a bit in difficulty, rigor and focus across schools.

Math is prob better for keeping the option of various fields of academia open. Stats is prob better for industry. But it’ll depend on the classes you take too.

The most generalizable classes will be:

  • Calculus Sequence
  • Linear Algebra
  • intro to probability and statistics

These are used in a very wide range of fields. But after that it branches out pretty quickly and you want to focus on domain knowledge or technical classes specific to a field

Economics has its own approach to stats called econometrics which deviates quite a bit culturally and technically in its focus. Andrew Gelman has some blog posts you can search on that

Stuff I don’t know which other stats people are more likely to know:

  • Markov chains
  • Monte Carlo simulations
  • really any simulation technique
  • Bayesian stats
  • information theory
  • textual analysis or ML stuff

…and a lot more. And I can / will learn a few of these in the future for work or interest. But they’re not immediately useful

Quick thought on the tangent, which I’d also love to hear more thoughts on from other people.

I’m skeptical that corruption is a big obstacle to growth and development. Measurement and historical comparisons are tricky here, but corruption seems to be a pervasive feature across many societies.

Even the United States had its local political machines and share of bribery before the Progressive Movement in the 1920s tried to filter it out. And conventional wisdom credits the Industrial Revolution (of the 19th century before the US reduced its corruption) with our modern wealth.

I suspect if we applied our same concern of corruption to currently-developed countries to their past, we’d find they (1) would fare just as bad and (2) had their development periods before they dealt with the corruption

My 2 cents:

Good advice but I’ll add that many of these things (solo projects, getting internships, writing, etc.) benefit substantially from attending a school with good training (which correlates somewhat with prestige and cost-of-attending).

Feedback, mentorship, and direction are bottlenecks for executing impressive projects and sometimes the best way (or only way) for someone to access these is through the conventional schooling route.

Conventional education and independent projects complement each other

Hi Ozzie, what’s the ask and intended audience here?

The problems here seem interesting and maybe even approachable to a dedicated newbie. So I was wondering if my background was any use. I used to work in software engineering with JavaScript and now work in data cleaning research assistance with R.

But I can’t tell if this is an open call to submit pull requests to an open source library on GitHub, a request for advice, or a request for someone to work part-time / full-time

I wish I could strong-upvote this three times over. It’s that good of a piece.

This reads very clearly to me today, and I think younger less-knowledgeable-with-research-world me would follow it too.

It’s a legible example of

  • how research is increasingly a team effort with many behind-the-scenes people (with Principal Investigators arguably deserving little of the credit in some cases)
  • what work there is to be done adjacent to research
  • a theory of change (make it possible -> … -> make it required)
  • how movement building and grant making rely more on heuristics than explicit cost-effectiveness

Also cool was the flavor you gave different fields, and the benefits meta-science might have in each. (I broke out laughing reading the anecdote of an economist objecting to the title slide of a presentation.)

Minor typo:

Clinical Decision Support in Health Care

ack in the mid-2010s

This was a good nudge for me to lower the frequency on all my notifications (especially the karma one to weekly, which I’ve been checking more than I’d like lately)

Hi Nick,

Ah I missed only a third of Ugandans cooking with charcoal (I’m guessing a third of Ugandan households since that’s usually how these surveys work). That does suggest we can bump up the estimate by 3x.

I don’t think we can 5x the savings because of family size. Household savings go up (compared to my individual model) but so do household expenses. So the percent income gain from charcoal savings stays the same if both scale the same.

(Technical detail: I’m not following how you got back to 1000-1500 USD from my 0.6 USD per-adopter estimate. That’s about 1500-2500x bigger than what I had!)

Another point of ignorance is what the cooks are doing when not cooking. (Linch raised a related point in a sibling comment.) If someone’s home all day, has a reliable reserve of both beans and fuel, and cooks on a regular basis, then soaking sounds free. I’m sure these are all things you’ll find out while asking around though.

On a final meta note, I’m not sure if you want the benefits here to be as large as possible. You’ve mentioned calculating on the conservative end but it’s not obvious to me that larger benefits are always good

If the charcoal savings benefit is too large, the household would have realized it on their own. To exaggerate this, suppose households could double their income by soaking beans but still weren’t doing it. There’s likely a big obstacle preventing them from soaking beans that we’d have to figure out.

Put abstractly, importance goes up but tractability goes down with larger immediate benefits.

Surprised no one’s done the per-capita income comparison, since extra income from less charcoal usage would be a big selling point in an information campaign.

I did a very rough back-of-the-envelope calculation and estimated only 0.006% extra income via charcoal savings per year per adopter from soaking beans. I suspect that means lower tractability

If 1% of 50 million Ugandans adopt, we have 0.5 million adopters.

If 5-year savings for less charcoal used are 1.5 million USD, then annual savings are 0.3 million USD

So per-adopter savings (annually) is 0.6 USD.

And that seems low. Compare that against per-capita Uganda GDP of 1000 USD and we’re talking 0.006% extra income per year.

(Also glanced quickly at a few other indicators like median daily income, per capita GDP in PPP terms, and they seem ballpark similar)

To put that into a scale my first-world brain can understand, 0.006% over 100,000 USD is 60 USD. It’s definitely something but also feels low return for the habit change. And at that price, could easily see someone reverting back to cooking beans w/o soaking for the convenience.

Like this a lot, especially the plot designs.

Surprised there’s not much in demographic differences even with all the caveats that go with interpreting disparities there. Not sure what to make of that yet but will be chewing on that for a while.

Lastly, got a question. Do you have any sense of what a good baseline for the mental health section might be? The question of “has your mental health increased / decreased/ stayed the same since getting involved with X” is new to me

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