Econometrics Fall 2025 Econometrics Ii Session 02 Ipynb At Github

Leo Migdal

-Nov 17, 2025, 6:34 AM

econometrics fall 2025 econometrics ii session 02 ipynb at github

There was an error while loading. Please reload this page. Econometrics II projects and exercises for undergraduate Economics students. Learning starts with Excel for basic calculations and continues with Python. There was an error while loading. Please reload this page.

Econometrics II projects and exercises for undergraduate Economics students. Learning starts with Excel for basic calculations and continues with Python. There was an error while loading. Please reload this page. This repository contains the lecture materials and supporting content for the undergraduate course Advanced Econometrics (Econometrics II) that I offered at the University of Bonn. The course builds on the basic econometrics course in three directions:

The course is designed for students with prior exposure to basic statistics and econometrics. The empirical illustrations are implemented in Python. Course Website: https://vladislav-morozov.github.io/econometrics-2/ Prerequisites: Prior coursework in statistics and econometrics Welcome! This is the repo where you'll find all the material seen in class.

It is also the place you'll be pushing all your assignments to. This repo is meant to resemble a typical industry-grade project. This means you'll have to pass a few tests for your code to be accepted. In this class, you're expected to submit your code by creating a new branch, pushing your changes and passing a few builds. This will enable you to merge your branch into develop, which will later be merged on to main. The goal of this workflow is to help you understand how code is written and shared in modern companies.

It will familiarize you with: By following these guidelines, you won't be taken by surprise when someone asks you to open a PR to squash a bug or implement a new feature. There was an error while loading. Please reload this page. Advanced Econometrics builds on the basic econometrics course in three directions. First, the course discusses a range of practical methods used in economics and business.

Second, it addresses both causal inference and forecasting. Third, it offers a deeper discussion of the underlying theory. Instructor: Vladislav Morozov Email: morozov [at] uni-bonn.de Office Location: Adenauerallee 24-42, IFS, Statistics Section Office Hours: Virtual, by appointment Course Website: eCampus and this website Lectures: 8:30-10:00; Wednesdays (Room 0.042), Fridays (Lecture Hall N)... Level: Undergraduate Prerequisites: basic courses in statistics and econometrics Textbooks: the course draws on several textbooks: Brockwell, P.

J., & Davis, R. A. (2016). Introduction to Time Series and Forecasting. Springer International Publishing. There was an error while loading.

Please reload this page. Automate your workflow from idea to production GitHub Actions makes it easy to automate all your software workflows, now with world-class CI/CD. Build, test, and deploy your code right from GitHub. Hosted runners for every major OS make it easy to build and test all your projects. Run directly on a VM or inside a container.

Use your own VMs, in the cloud or on-prem, with self-hosted runners. Save time with matrix workflows that simultaneously test across multiple operating systems and versions of your runtime. Econometrics II (CMU course number 73-374) is an advanced undergraduate course on Econometrics with a focus on methods used in practice in contemporary empirical economic research. Topics include causal inference, panel data, nonlinear methods, and time series, with a focus on real data applications and code examples in R. As the name suggests, the course is designed to be a successor to Econometrics I, and so presumes familiarity with probability and statistics, linear regression, and the R statistical programming language. The primary texts for the course are Introductory Econometrics: A Modern Approach (4th edition) by Jeffrey Wooldridge and Mastering ’Metrics by Joshua Angrist and Jörn-Steffen Pishke, with some coverage of additional topics not covered...

The following files, derived from the lecture slides for the course and containing both text and R code, are provided as-is, as a resource for students and researchers interested in the topics. Additional course materials, including syllabi, problem sets, practice problems, and project assignments, may be available upon request. If you have questions, comments, or criticisms of the material, please contact me.

Econometrics Fall 2025 Econometrics Ii Session 02 Ipynb At Github

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