Introduction to Econometrics (ECON 113, Summer 2015)

  • Instructor: Jae Hoon Choi

  • Class info (Syllabus)

    • Summer session II (July 27th - August 28th)

    • Class time: Monday & Wednesday & Friday 9:00AM - 11:30PM

    • Class location: Physical Sciences Building 114 (Map)

    • Grade distribution

      • Assignment 15%

      • Midterm 1 5%

      • Midterm 2 30%

      • Final 50%

  • This course is an introduction to the theory and application of statistics to economic problems. This course focuses on the techniques used in empirical research with a particular focus on intuitive understanding. Weekly problem sets will introduce real world applications and teach you the fundamentals of statistical programming. No prior knowledge of computer programming is required. Class meets three times a week for lectures which are mandatory, and once per week for section which are strongly suggested though not mandatory. You are expected to maintain the standards of academic integrity delineated here. Any violations of academic integrity standards will be dealt with in accordance with University policy.

  • TA: Kyle Neering

  • Section: Thursday 9:00AM - 10:10AM, Physical Sciences Building 114

  • Office hours: Tuesday 3:00PM - 4:00PM, Engineering 2 403G

  • Contact: kneering at

  • LSS Tutor: Lindsey Newman

Lecture Notes

  • Lecture 1: Introduction, Population & Sample, Mean and Variance, Biased/unbiased estimator

  • Lecture 2: Probability

  • Lecture 3: Statistical inference (Significance test, Confidence Interval, P-value)

  • Lecture 4: Relationship between two variables (Covariance, Correlation), Simple regression

  • Lecture 5: OLS estimator, Gauss-Markov assumptions

  • Lecture 6: Guass-Markov assumptions, Goodness-of-fit measures, Interpretation of OLS estimates

  • Lecture 7: Multiple regression, Omitted variable bias

  • Lecture 8: Quadratic terms, Comparing parameters, Multiple restrictions,

  • Lecture 9: Adjusted R-squared, Standardizing coefficients, Interaction term

  • Lecture 10: Dummy variable, Instrumental variable

  • Lecture 11: Difference-in-differences

  • Lecture 12: Measurement error, Heteroskedasticity (Breusch-Pagan test, White test, WLS)




  • Jeffrey M. Wooldridge “Introductory Econometrics: A Modern Approach.” 5th edition (recommended)

Software and data