Research Resources

Tools, textbooks, courses — various useful links.

General

Kagi — a paid ad-free search engine with bells and whistles
Obsidian — take notes
Bear — take notes
Overleaf — collaborative LaTeX
Mermaid — draw diagrams
Airtable — no-code database builder with a spreadsheet interface
Toggl — tracking your time
Zapier — automating stuff
Julia Evans on How to Ask Good Questions
Trey Causey's Do You Have Time for a Quick Chat?
Chicago Booth Clark Center Panels — regularly polls three diverse panels of expert economists
VoxDevLits — living literature reviews on policy-relevant topics in development economics
Ungated Research — publicly available working papers for research in leading economics journals

Coding & Data

[book] R for Data Science 2e
[book] Kieran Healy's The Plain Person's Guide to Plain Text Social Science
Quarto — "An open-source scientific and technical publishing system"
RStudio Desktop IDE
Positron on GitHub IDE
GitHub — version control
GitLab — version control
[paper] Karl Broman & Kara Woo on Data Organization in Spreadsheets
[paper] Hadley Wickham's Tidy Data
Julia Evans' Oh Shit, Git! zine

Methods & Stats

How are econometric methods applied by researchers in development economics? | VoxDev Blog
[book] Ethan Bueno de Mesquita & Anthony Fowler's Thinking Clearly with Data
[book] Joshua Angrist & Jörn-Steffen Pischke's Mastering 'Metrics
[book] Joshua D. Angrist & Jörn-Steffen Pischke's Mostly Harmless Econometrics
[book] Aki Vehtari, Andrew Gelman, & Jennifer Hill's Regression and Other Stories
[paper] Andrew Gelman, Aki Vehtari and others on Bayesian Workflow
[book] Jeffrey Wooldridge's Introductory Econometrics: A Modern Approach
[book] Nick Huntington-Klein's The Effect
[book] Scott Cunningham's Causal Inference: The Mixtape
[paper] Susan Athey & Guido W. Imbens' Machine Learning Methods That Economists Should Know About
[book] Dani Rodrik's Economics Rules
[paper] Angus Deaton & Nancy Cartwright's Understanding and Misunderstanding Randomized Controlled Trials
[book] Graeme Blair, Alexander Coppock, & Macartan Humphreys' Research Design in the Social Sciences
[paper] Sayash Kapoor and others — REFORMS: Consensus-based Recommendations for Machine-learning-based Science
[book] Chester Ismay and Albert Kim's ModernDive Statistical Inference via Data Science in R
[book] Geocomputation with R — geographic data analysis, visualization and modeling by Robin Lovelace, Jakub Nowosad and Jannes Muenchow. See also the geocompx project
[paper] Natalie Ayers, Gary King and others: Statistical Intuition Without Coding (or Teachers)
Seeing Theory — interactive stats 101 visualizations
Common statistical tests are linear models by Jonas Kristoffer Lindeløv
IZA's methods write-ups
Evidence in Governance and Politics (EGAP) Methods Guides
The World Bank's Curated List on Technical Topics
J-PAL's Research Resources

Data Collection

J-PAL's resource on survey programming (small contribution by me)
SurveyCTO — see also the free Community Subscription
J-PAL's Repository of measurement and survey design resources

Dataviz

From data to viz — leads you to the most appropriate graph for your data, with code and common caveats
RawGraphs
Tableau (public)
Datawrapper
Flourish
Data Visualization Society
J-PAL's resource on data visualization (small contribution by me)
Data by Design — "An Interactive History of Data Visualization"
Frank Elavsky's Chartability — heuristics for accessible data visualizations

LLMs

Tools for coding with LLMs

Understanding LLMs

The Financial Times' Generative AI exists because of the transformer
Transformer Explainer — interactive visualization for learning about Transformers through GPT-2
Andrej Karpathy's Intro to Large Language Models — an accessible one-hour overview
Quanta Magazine: When ChatGPT Broke an Entire Field: An Oral History — on the state of NLP

Ways of conceptualising LLMs

Sam Barrett's Amplifiers of Epistemic Posture
Ted Chiang's ChatGPT is a blurry JPEG of the web
Anthropic: Considerations in constructing Claude's character — and Patrick House's complement: The Lifelike Illusions of A.I.

Practical guides and workflows

LLM style tips — Matthew Honnibal on getting better outputs
Claude Code: My Workflow — a potential research/academic workflow by Pedro H. C. Sant'Anna
Simon Willison: Agentic engineering patterns
Oxide Computer: Using LLMs at Oxide — reflections on using LLMs responsibly within an organisation

Critical perspectives and general reading

[book] AI Snake Oil by Arvind Narayanan and Sayash Kapoor — see also A Guide to Understanding AI as Normal Technology
Vicki Boykis's list of "no-hype" reads on LLMs
Jessica Hullman: When are AI/ML models unlikely to help with decision-making?
Simon Willison: The Lethal Trifecta
Simon Couch: An interesting breakdown of AI energy use — a rough calculation of personal usage and how to put it in perspective

Staying up to date

Simon Willison's blog
VoxDev: AI and Development Economics — Early Evidence and How to Keep Up — resources compiled for keeping up with what's going on from a development economics perspective

NLP

[book] Emil Hvitfeldt and Julia Silge's Supervised Machine Learning for Text Analysis in R
[book] Julia Silge and David Robinson's Text Mining with R
The STM R package for structural topic modelling
The textnets R package
The Quanteda R package for working with text data
BERTopic — Python package for topic modelling with embeddings
spaCy and their demo projects for text categorization or custom Named Entity Recognition

Courses

Harvard's CS50: Introduction to Computer Science
Harvard's CS50: Introduction to R
Grant McDermott's Data science for economists
EconDL — blog on deep learning applications in economics

Writing

[book] Benjamin Dreyer's Dreyer's English: An Utterly Correct Guide to Clarity and Style — see also Katy Waldman's review The Hedonic Appeal of "Dreyer's English"
[book] Verlyn Klinkenborg's Several Short Sentences About Writing
[book] The Chicago Manual of Style, 18th Edition

Fitness

[book] Casey Johnston's LIFTOFF: Couch to Barbell — a great starting point for weight lifting
Megan Gallagher's Stronger by the Day — focused on the three main compound lifts, progressive overload at its core
Macrofactor — no-nonsense nutrition tracker with a useful projection model