Introductory Econometrics

Taught Courses

• ECON 3885, Spring 2020 at Fordham University

• ECON 3885, Fall 2019, Fordham University

Notes on Introductory Econometrics

Based on Wooldridge, J. (2019). Introductory Econometrics: A Modern Approach. Boston, MA: Cengage.

• Chapter 1: The Nature of Econometrics and Economic Data
• Chapter 2: The Simple Regression Model
• Chapter 3: The Multiple Regression Analysis: Estimation
• Chapter 4: The Multiple Regression Analysis: Inference
• Chapter 5: The Multiple Regression Analysis: OLS Asymptotics
• Chapter 6: Multiple Regression Analysis: Further Issues
• Chapter 7: Multiple Regression Analysis with Dummy Variables
• Chapter 8: Heteroskedasticity
• Chapter 9: Specification and Data Issues
• Chapter 10: Basic Regression Analysis with Time Series Data
• Chapter 11: Issues in Using OLS with Time Series Data
• Chapter 12: Serial Correlation and Heteroskedasticity in Time Series Regressions
• Chapter 13: Pooling Cross Sections across Time: Simple Panel Data Methods
• Chapter 14: Advanced Panel Data Methods
• Chapter 15: Instrumental Variables Estimation and Two-Stage Least Squares
• Chapter 16: Simultaneous Equation Models
• Chapter 17: Limited Dependent Variable Models: Logit and Probit
• Chapter 18: Advanced Time Series Topics
• Chapter 19: Carrying Out an Empirical Project

Notes on Practical Data Science With R

Based on Zumel, N., & Mount, J. (2014). Practical Data Science With R. Manning Publications Co.

• Chapter 2: Starting with R and Data
• Chapter 3: Exploring Data: Summary Statistics and Plots
• Chapter 4: Managing Data
• Chapter 5: Data Engineering and Data Shaping
• Chapter 6: Choosing and Evaluating Models
• Chapter 7: Linear and Logistic Regression
• Chapter 8: Advanced Data Preparation
• Chapter 9: Unsupervised Methods

Additional Material

• Introduction to Basic Graphs in R for Econometricians
• Correlation in R
• Reporting and Comparing Regression Results in R
• Time Series Analysis and Visualization in R
• Panel Data Visualization in R
• Data Visualization Using ‘googleVis’
• Data Manipulation and Visualization in R with ‘tidyverse’
• Interactive Apps Using ‘shiny’ In R
• Topics in Advanced Econometrics
• Nonparametric Econometrics in R
• Advanced Time Series Analysis in R
• Quantile Regressions in R
• Simple Machine Learning Algorithms in R
• K-Nearest Neighbors Algorithm in R