Introduction to Econometrics@NJU

Learning to use data to explore economic and social logic in China and the world

Spring 2025
Business School
Nanjing University

Instructor

Time and Location

  •   Thursday
  •   14:00–17:00
  •   Yifu Building B-410
  •   Xianlin Campus

Course Logo

News

Warning
  • Warning
    • The Second Assignment HW2 is released in 教学立方 and Homework now. The deadline is 5/13. Please check it if you can download it. If you have any questions, please feel free to ask me or TA by email or via 教学立方.

  • 4/23, Tomorrow, we will discuss the Matching method, which is non-parametric and also powerful method to estimate the causal effect. You can download slides without details from the schedule now. And last week, our TA uploaded the answer to the first assignment HW1 in 教学立方,please check it if you can download it.

  • 4/17 This afternoon we discussed several threats to empirical validity, including measurement error, misspecification, simultaneity, and missing data and sample selection. Detailed slides are now available on the schedule page.

  • 4/17 Today we will discuss other threats or endogeneity to the validity of empirical studies, including measurement error, misspecification, simultaneity, and miss data and sample selection etc. You can download slides without details from the schedule now.

  • 4/10 Today we dove deep into omitted variable bias (OVB) and the art of choosing control variables - the econometrician’s secret sauce for credible causal effects. You can download the fully detailed slides from the schedule now.

  • 4/9, Tomorrow, we will discuss the validity of empirical study, which is one of the most important part in econometrics. You can download slides with blanks in the lecture from the schedule.

  • 4/4, Slides with all details for the nonlinear regression in terms of LPM, Probit and Logit are updated in the schedule.And I also uploaded R and Stata lab slides in the lab in case you want to practice the exercises in R and Stata.

  • 4/3, today we will discuss the nonlinear regression models in Y in terms of LPM, Probit and Logit. You can download slides with no details from the schedule.

  • 3/27, today we discussed the nonlinear OLS regression in Xs in terms of polynomial, logarithmic, and interaction terms. You can download slides with all details in the lecture from the schedule now.

  • 3/26, tomorrow we will extend OLS regression to nonlinear regression. You can download slides with blanks in the lecture from the schedule, which is updated.

  • 3/21, the first Assignment HW1 is released in 教学立方 and Homework. Please check it if you can download it. If you have any questions, please feel free to ask me or TA by email or via 教学立方.

  • 3/20, today we have learned that how to use Hypothesis Testing and Confidence Intervals in OLS regression. You can download slides with all details in the lecture from the schedule now which is updated.

  • 3/19 Tomorrow, I will review the basic idea of Hypothesis Testing in your statistics courses at first, then extend it in OLS regression.You can download slides without details from the schedule.

  • 3/13 Today, I extended the simple OLS regression to multiple OLS regression.Hope you have a good understanding of the content. If you have any questions, please feel free to ask me.You can download slides with details from the schedule. Next week, I will introduce the hypothesis testing and confidence intervals in regression. If possible, you’d better review the content of hypothesis testing and confidence intervals in statistics courses.

  • 3/6 Today,I will introduce the first method and the most important method in this course: regression.You can download slides without details from the schedule.

  • Tomorrow will be the first lecture of the course. I have prepared a few slides for it. You can download them from the schedule. Looking forward to meeting you all tomorrow.

  • Welcome to the course website for the 2025 edition of Introduction to Econometrics, also known as “Intro’Metrics”(计量经济学). This course is delivered by Prof. Zhaopeng Qu and his teaching assistants at the Business School, Nanjing University.

Course Description

This course introduces students to modern econometrics, mainly focusing on causal inference techniques, and their applications in economics and other social sciences. The course focuses more on intuition and practical examples, while keeping the mathematical content to a minimum. Notably, matrix notation is not used.

The goal is to help students 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 several common econometric research design techniques that aim to credibly estimate causal effects on economic and social relationships:

  • Randomized Controlled Trial(RCT)

  • Regression(OLS)

  • Matching(Matching)

  • Instrumental Variables(IV)

  • Regression Discontinuity Designs(RDD)

  • Panel Data and Differences-in-Differences(DID)

At the end, students will use at least one of them above to finish a team-based empirical research proposal.

Acknowledge

This course has greatly benefited from materials shared by Scott Cunningham and Ed Rubin. Their slides and the textbook Data Analysis for Business, Economics and Policy by Gábor Békés and Gábor Kézdi have enriched the content. The website is built with Quarto and inspired by Andrew Heiss.