Python for Econometrics

Unlock the power of Python to analyze economic data, build econometric models, and make data-driven decisions.
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Python Fundamentals and Econometric Setup

Unit 1: Setting Up Your Python Environment

Unit 2: Python Fundamentals for Econometrics

Unit 3: Essential Libraries for Econometrics

Data Wrangling and Linear Regression

Unit 1: Introduction to Data Wrangling with Pandas

Unit 2: Data Transformation and Cleaning

Unit 3: Linear Regression with scikit-learn

Unit 4: Linear Regression with statsmodels

Time Series and Panel Data Analysis

Unit 1: Introduction to Time Series Analysis

Unit 2: ARIMA Models

Unit 3: Volatility Modeling with GARCH

Unit 4: Panel Data Analysis

Advanced Econometric Methods and Causal Inference

Unit 1: Discrete Choice Models: Logit and Probit

Unit 2: Instrumental Variables Regression

Unit 3: Causal Inference Techniques

Hypothesis Testing, Machine Learning, and Automation

Unit 1: Hypothesis Testing in Python

Unit 2: Machine Learning for Econometric Modeling

Unit 3: Automating Econometric Workflows