- I built this website with notion.
Data
- Where to find data? A document for young or new researchers on how to find data for your new empirical project.
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- Let me also recommend joining Data is Plural, they will send you each week a list of three datasets that are less known. Check the entire database, here.
Professional Development
- Advice to graduate students in economics from Professor Lubotsky
- Great Tips for Writing an Empirical Paper from Plamen Nikolov
- List of Economic Conferences and deadlines to apply. (Anne burton and Barton Willage)
- Where to present crime-papers (Jennifer Doleac)
- More advice on twitter organized by (Jennifer Doleac)
- How to make a website using "Git" (Marisa Carlos)
- Guide to Applying for PhD Programs in Econ (Torsha Chakravorty, Aishwarya Kekre, Prerna Kundu, Lakshya Narula, and Vaibhav Ojha)
- EconThaki - es una organización que tiene como objetivo incrementar la diversidad en la academia en economía en Latinoamérica y el Caribe.
- EconThaki tiene una guía para estudiantes de LAC sobre como comenzar tu camino hacia el doctorado.
- Website created by David Schindler and Chris Roth on advice for all sorts of issues Ph.D. students may run into: https://sites.google.com/view/econgradadvice/
- Guide to Postdocs in Econ/Management by Wei Yang Tham @wytham88
- Guide to Predocs in Econ by Zahra Thabet
- Where do I get at job as an RA? Well you can start here - Barton Willage.
Coding
- Code for making awesome Stata to LaTeX Tables
- How to Sync Notepad++ and STATA
- Really Easy tool to make U.S Maps
- Stata Coding Guide by Julian Reif
- Stata to Latex Guide by Asjad Naqvi
- Want to replicate a paper? Sebastian Kranz compiled a list of papers that have their data available
- Learning how to graph your results in STATA with do-files by John Kane @UptonOrwell
- Data Cleaning guide from IPA
Learn how to ...
- Beamer: Paul Goldsmith-Pinkham posted tips on his website on How to make better Beamer Presentations.
- Machine Learning: Dario Sansone has compiled a great list of articles and other reads to get started with Machine learning
- Causal Inference & ML:
- Matteo Courthoud has created a number of posts regarding ML and causal inference
- A book on causal inference with ML: https://causalml-book.org
- Another interesting set of notes: https://matheusfacure.github.io/python-causality-handbook/landing-page.html
- DiD
- Asjad Naqvi aslo has compiled a website on resources related to DiD you can find it here
Books on Causal Inference in general
- Real Stats by Michael Bailey
- Mastering Metrics
- Online version of Causal Inference: The Mixtape
- Online version of The Effect: An Introduction to Research Design and Causality
- Online version of Impact Evaluation in Practice - Second Edition
- Online version of “Causal Inference: What if”
- Regression Discontinuity: https://www.mdrc.org/sites/default/files/regression_discontinuity_full.pdf
- A book on causal inference with ML: https://causalml-book.org
Workflow
- Todoist is my preferred app for to-do list. This is a video on how I use todoist?
- I use notion for organizing everything! Even doing my website
- Background music & flow
- Ommwriter, is a very simple app, but it is so nice to easy. The point? A distraction free interface for you to write.
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Teaching
Job Market
- Jennifer Doleac has compiled a list of threads that people have written with different advice and takes on many aspects of the job market. You can find the list of threads here.
- I’ve compiled a list of links, podcast episodes, and tweet threads on the job market here. Feel free to visit those and get the info you need!