Introduction to Econometrics@NJU

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

Spring 2026
Business School
Nanjing University

Instructor

Teaching Assistant

Time and Location

  •   Thursday
  •   14:00–17:00
  •   TBA
  •   Xianlin Campus

Course Logo

News

Important

  • 4/8 Tomorrow we will finish the last part of Inference in Multiple OLS Regression and start learning about Nonlinear Regression in Multiple OLS Regression. The slides for Lecture 5 (in a simplified form, without detailed explanations) have just been uploaded. You can find them on the schedule page in case you want to review the lecture or preview it before the next class.

  • 4/1 Tomorrow we will finish the last part of Estimation in OLS Regression and start learning about Hypothesis Test in OLS Regression. The slides for Lecture 4 (in a simplified form, without detailed explanations) have just been uploaded. You can find them on the schedule page if you’d like to preview them before class. We will also have our 1st Homework after the class, the details of which will be announced in the 智慧南雍 platform and homework page.

  • 3/25 Tomorrow we will wrap up simple OLS regression and begin exploring its extended version: Multiple OLS Regression. The slides for Lecture 3 (in a simplified form, without detailed explanations) have just been uploaded. You can find them on the schedule page if you’d like to preview them before class.

  • 3/20 The complete, detailed slides for Lecture 2 have just been uploaded. You can find them on the schedule page in case you want to review the lecture or preview it before the next class.

  • 3/19 Hi everyone, today we will learn the most fundamental and powerful tool in econometrics: regression. The simplified version of lecture slides have been uploaded to the schedule page if you want to preview the lecture before the class. The detailed version will be available after the lecture.

  • 3/13 The complete, detailed slides for Lecture 1 have just been uploaded. You can find them on the schedule page.

  • 3/11 Hi everyone! I’ve just uploaded the Lecture 1 slides in a simplified version, without extra details. This should help you focus on the main ideas in the lecture without getting distracted by the math. You can find them on the schedule page. The detailed slides will be available after the lecture.

  • 3/8 Hello everyone! We’ve just had our first class—how did it feel? If you have any feedback about the course content, pace, or anything else, please feel free to share it with me or the TA. The slides from our first session have been uploaded to the schedule page for your review and preview. See you next week!

  • Welcome to the course website for the 2026 edition of Introduction to Econometrics, also known as “Intro’Metrics” (计量). The course is taught by Prof. Zhaopeng Qu and teaching assistant Xiaotian Yu at the Business School of 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(causal inference), 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.