1 Guide
Guide to Efficient Computational Work in Economics 經(jīng)濟學coding入門指南
A curated collection of links for economists. Part of the "Awesome X" series.
Economic research requires writing documents, and often writing code. How can economists avoid drowning in a mess of different versions?
Resources at the intersection of Economics and Data Science
2 Course
This repo hosts the exercise solutions for Econ 280 written in Julia and C++.
This is a PhD level course in Applied Econometrics at NYU Stern.
This is meant to be a first PhD course in Empirical Industrial Organization.
XMU茅家銘老師principles-of-economics課程
3 Econometrics
replication of mostly-harmless-eonometrics
Introduction to Econometrics with R is an interactive companion to the well-received textbook Introduction to Econometrics by James H. Stock and Mark W. Watson (2015).
Economics students new to both econometrics and R may find the introduction to both challenging. However, if their text is "Introductory Econometrics: A Modern Approach, 6e" by Jeffrey M. Wooldridge, they are in luck!
A curated list of awesome Causal Inference resources.
The goal of this list is to serve a starting point for getting familiar with causality.
Source Codes for the book "Mostly Harmless Quantitative Finance(Chinese)"
基本無害的量化金融學
appelpy: Applied Econometrics Library for Python
4 Data
R package containing a host of datasets useful for economic research.
Links to Econ Data
以上只是Economics in Github的冰山一角，歡迎補充，該系列未來將繼續(xù)完善~
