# Econ-ResearchMethods

**Repository Path**: zhiyuanryanchen/econ-research-methods

## Basic Information

- **Project Name**: Econ-ResearchMethods
- **Description**: This repository contains course materials for the graduate-level course of economics research methods.
- **Primary Language**: Unknown
- **License**: MulanPSL-1.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 2
- **Forks**: 19
- **Created**: 2020-11-09
- **Last Updated**: 2025-06-13

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Econ-ResearchMethods Introduction
This Gitee repository contains course materials for the graduate-level Research Methods for Economics and Management. 

Please go to https://github.com/zhiyuanryanchen/econ-research-methods for the Github repository

## Description
This course is intended to train students in frontier research methods
for good empirical and quantitative studies in economics and management studies. 

It emphasizes a collaboration of various quantitative skills in conducting
empirical research, as well as a tight connection between the theory
and empirical facts. The course begins by introducing classical causal inference framework based on potential outcomes, and then moves to AI-powered causal inference methods.  Then it introduces `Stata` and `Python` programming skills using
 various applications. Importantly We will further discuss to what extent researchers can rely on Diff-in-Diff approach to learn from data and guide policymaking.  Some fundamentals and recent developments
in machine learning and artificial intelligence  will be introduced. The course concludes by discussing the modern academic research using LLM-based research agents. 

## Prerequisites 
This course will assume a knowledge of graduate-level microeconomics,
macroeconomics, and econometrics. Some experience in working with
`Stata`, `Python`, and `Jupyterlab`.
is preferred, but not a must for this course. With the advancement in LLM-assisted programming (such as `Copilot, Cursor, Trae`, etc.), students are encouraged to learn the basic programming skills in `Python`.