Why I left Duke economics Ph.D. program (and why you should consider too)
Advice for Phd Students in Economics (by Chris Roth & David Schindler)
Amy Finkelstein’s advice on how to write great research papers in economics
Preparation for meeting with faculty (by John Asker)
The 2019 AEA Continuing Education: Time-Series Econometrics (James H. Stock, Mark W. Watson)
The 2021 AEA Continuing Education: Industrial Organization (Steven Berry, Philip Haile)
How to write paper, checklists, Claudia Sahm’ We need to talk more blog post
Real footage of Stata user using R
Journals with short paper options where economists might publish
Federal Bureau of Investigation Crime Data Explorer
WISQARS Fatal Injury Data Visualization
Find Economic Articles with Data and codes
RTutor: Interactive R Problem Sets with data and solution
If you want a summary of papers and a reference list use https://perplexity.ai
Rdatasets is a collection of 2127 datasets
Sebastian Tello-Trillo’s resources: Where to find data? pdf version | Resources page
Research data search in google
The Fjelstul World Cup Database By Josh Fjelstul
Data Resources on Medical Providers:
Repository of CMS hospital cost report (HCRIS) data and processing code:
Data Resources on Health Care Encounter Data:
Hospital Financial Characteristics Datasets:
LobbyView dataset: Advancing data science research in interest group politics
Sebastian Bauhoff’s Household datasets for development economic research:
J-PAL’s Catalog of Administrative Data Sets
Grid cell-month environmental and conflict data (AfroGrid) by Justin Schon and and Ore Koren
Christoph Kronenberg’s way to Literature review plots
CMS Hospital Compare Data 2004-2016:
The Early County Business Pattern Files: 1946-1974
Medical Expenditure Panel Survey (MEPS):
NASA’s Common Metadata Repository (CMR) with 350 datasets
Longitudinal datasets of potential interest to health economists
International GIS Data: Global:
Accessing OpenStreetMap data with R:
Mapping Routes - mapping routes with tidygeocoder and osrm:
National Sample Survey of Registered Nurses (NSSRN):
Education Data at Your Fingertips:
Transport for London open data:
Institute for Development Research Riinvest:
Law Enforcement Management and Administrative Statistics (LEMAS):
The Early County Business Pattern Files: 1946-1974
The European Social Survey (ESS):
Global Data Hub On Human Trafficking:
Facebook Social Connectedness Index:
American Community Survey Data via FTP:
Union Membership, Coverage, and Earnings from the CPS:
Input-Output matrix from 1997-2020:
Online Tool Provides Individual Energy Sustainability Scores data:
Bureau of Economic Analysis data: bulk downloads
U.S. Bureau Of Labor Statistics data:
World Bank’s Open Night Lights tutorial:
The California Health Interview Survey (CHIS) :
Time-Series Econometrics (James H. Stock, Mark W. Watson)
Advanced Data Analytics in Economics By Nick Hagerty
introductory environmental and resource economics By John Whitehead
Kevin Murphy teaching developing the monocentric city model 6 videos
Pen and paper exercises in machine learning: michaelgutmann github
Videos’ to teach economics: Economics Media Library or econ.video
Teaching economics with baking cakes: (https://www.bakeonomics350.com/spring2022)
Teaching Health Economics in the time of COVID-19: (https://www.healtheconomics.org/page/COVID19)
Using Music to Teach Agricultural, Applied, and Environmental Economics: (https://www.aaea.org/UserFiles/file/AETR_2021_002RProofFinal.pdf)
Illustration of the two-way fixed effects estimator decomposition: (https://hhsievertsen.shinyapps.io/twowayfedecomp/)
Lists of statistical packages for Recent Difference-in-Differences methods (https://twitter.com/lihua_lei_stat/status/1480993321900146688)
Implementing fixed effects panel models in R: (http://karthur.org/2019/implementing-fixed-effects-panel-models-in-r.html)
Asjad Naqvi’s website to that tracks the recent developments in the Difference-in-Difference (DiD) literature (https://asjadnaqvi.github.io/DiD/)
Literature on Recent Advances in Applied Micro Methods: (https://christinecai.github.io/PublicGoods/applied_micro_methods.pdf)
Health Economics Teaching Materials Repository: (https://www.ashecon.org/teaching-materials-repository/)
Amanda Gregg’s statistics/econometrics simulations site
Christine Cai’s resources of applied econometrics, PhD-level class materials, coding in Stata and R (https://christinecai.github.io/items/PublicGoods.html)
Seeing Theory A visual intoduction to probablit and statistics: (https://seeing-theory.brown.edu/)
The recordings of our Symposium on the Economics and Law of Pharmaceutical Regulation: (https://vimeo.com/showcase/8070909)
What are the most important statistical ideas of the past 50 years?: (http://www.stat.columbia.edu/~gelman/research/unpublished/stat50.pdf)
All the codes needed for applied econometrics: (https://sites.google.com/site/waynelinchang/r-code)
Masayuki Kudamatsu’s Tips for economist to apply phd in economics, proceed life with Phd, choosing research topic: (https://sites.google.com/site/mkudamatsu/tips4economists)
NickHK education videos: (https://www.nickchk.com/videos.html)cy
BREAD-IGC Virtual Ph.D. Course, Spring 2022 (https://www.theigc.org/event/bread-igc-virtual-phd-course-spring-2022/)
Econometrics Academy(https://sites.google.com/site/econometricsacademy/)
Ivan Canay’s Econometrics course ECON 480 and ECO 481
Applied Econometrics at NYU Stern: (https://github.com/chrisconlon/applied_metrics)
Machine Learning by Jordan Boyd-Graber: (https://home.cs.colorado.edu/~jbg/teaching/CSCI_5622/)
A history of econometric debates: (https://twitter.com/Undercoverhist/status/1105851715461570560)
Geocomputation with R and Python
Econometric data science, forecasting, and time series by Francis X. Diebold
Handbook of Regression Modeling in People Analytics by Keith McNulty
Structural Bayesian Techniques for Experimental and Behavioral Economics by James Bland
Data Management in Large-Scale Education Research By Crystal Lewis
Chicago Price Theory with video
Introduction to Geographic Data Science by Francisco Rowe codes
[Introduction to Data Science by Rafael A. Irizarry] (http://rafalab.dfci.harvard.edu/dsbook/)
Statistical Tools for Causal Inference by Sylvain Chabé-Ferret
Tidy Finance book by Christoph Scheuch, Stefan Voigt, and Patrick Weiss
Data Analysis for Business, Economics, and Policy, by Gábor Kézdi
Tidy Modeling with R by Max Kuhn and Julia Silge
Computational Thinking for Social Scientists
Applied Economics with R by Hans H. Sievertsen
Introduction to R by Hans H. Sievertsen
The Effect: An Introduction to Research Design and Causality, by Nick Huntington-Klein and data resources
Causal Inference: The Mixtape, by Scott Cunningham
Crime by the Numbers: A Criminologist’s Guide to R, by Jacob Kaplan
Models in Microeconomic Theory (‘She’ Edition), by Martin J. Osborne and Ariel Rubinstein
Supervised Machine Learning for Text Analysis in R by Emil Hvitfeldt, Julia Silge
Introduction to Probability for Data Science by Stanley H. Chan
Mastering Shiny by Hadley Wickham
Shiny tips & tricks for improving your apps and solving common problems
Causal Inference for The Brave and True
Analyzing US Census Data: Methods, Maps, and Models in R by Kyle Walker
Big Book of R which lists all the book avialable using R
Data Science at the Command Line Obtain, Scrub, Explore, and Model Data with Unix Power Tools
Mastering Spark with R by Javier Luraschi, Kevin Kuo, Edgar Ruiz
Regression and Other Stories by Andrew Gelman, Jennifer Hill, and Aki Vehtari
Golden comments on Double Machine Learning
Free Causal Inference Resources BY Matteo Courthoud
Introduction to Modern Causal Inference By Alejandro Schuler Mark van der Laan
Which causal inference book you should read: A flowchart and a list of short book reviews: (https://www.bradyneal.com/which-causal-inference-book)
Miguel Hernán’s Causal Diagrams: Draw Your Assumptions Before Your Conclusions: (https://www.edx.org/course/causal-diagrams-draw-your-assumptions-before-your)
UPenn’s course: A Crash Course in Causality: Inferring Causal Effects from Observational Data: (https://www.coursera.org/learn/crash-course-in-causality)
Columbia University’s Causal Inference-I (https://www.coursera.org/learn/causal-inference) and Causal Inference-II (https://www.coursera.org/learn/causal-inference-2)
Andrew Heiss’s course materials from Andrew Young School of Policy Studies at Georgia State University: Program Evaluation for Public Service, Microeconomics for Public Policy, and Data Visualization (https://www.andrewheiss.com/teaching/)
Data science for economists: (https://github.com/uo-ec607/lectures)
Ben Elsner’s Causal Inference – Online Lectures (https://www.youtube.com/playlist?list=PLyvUJLHD8IsJCB7ALqwjRG1BjL5JxE__H)
Brady Neal - Causal Inference (https://www.youtube.com/watch?v=DXBPtpBhGqo&list=PLoazKTcS0RzZ1SUgeOgc6SWt51gfT80N0)
Online Causal Inference Seminar: (https://sites.google.com/view/ocis/)