Intro to 'Metrics
Course taught by Professor Zhaopeng Qu at Business School of Nanjing University
Introduction to Econometrics @ Business School, Nanjing University
Spring,2023
News
Hello everyone! Time flies so fast. Tomorrow will be the last lecture for this course. The slides, including an introduction to SCM and a brief final review, have already been uploaded here. See you tomorrow!
Introduction
Welcome to the course website for the 2023 edition of Introduction to Econometrics, colloquially known as just “Intro’Metrics”(Jiliang), delivered by Prof. Zhaopeng Qu and his TAs at Business School, Nanjing University.
This course introduces students to modern causal inference,times series and machine learning methods for analyzing data in economics and other social sciences.The course is as light as possible on maths, but heavy on intuition and practical examples; matrix notation is not used.
The goal is to help you develop a solid theoretical background in introductory level econometrics, an ability to implement modern econometric methods, and a critical thinking about empirical studies in economics and other social sciences.
Specifically, we will learn six common econometric research design techniques that aim to credibly estimate causal effects and reliably make prediction on economic and social relationships:
- Randomized Controlled Trial(RCT)
- Regression(OLS)
- Instrumental Variables(IV)
- Regression Discontinuity Designs(RDD)
- Panel Data and Differences-in-Differences(DID)
- Times Series and Machine Learning(TS and ML)
At the end, students will use at least one of them above to finish an empirical research proposal.
Main Content
Homeworks
Other Resources
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Stata
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Markdown
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教学立方系统
Acknowledge
I acknowledge Gábor Békés and Gábor Kézdi, who are authors of one brilliant textbook for the course,Data Analysis for Business, Economics and Policy. Thank them for providing the LaTeX code for the lecture slides, which has been a great help to the course material.