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Program

Updated A.Y. 2021-2022

OVERVIEW AND PREREQUISITIES

This course provides an introduction to multiple regression techniques focusing on economic applications. The course consists of eighteen theoretical lectures (1 hour and 30 minutes each) and six practice classes with both theoretical and applied exercises. It is intended for students who have taken and passed Mathematics (8011190) and Statistics (8010848).

 

OUTLINE

- Conditional expectation and projection

- Potential outcomes and average treatment effects
 
- Regression
      OLS estimation
      Fundamentals and mechanics
      Inference and interpretation
 
- Instrumental Variables 
      IV Designs
      Homogeneous treatment effects
      Weak instruments
      Heterogeneous treatment effects and LATE
 
- Limited dependent variables  
      Binary and Multinomial outcomes
      Count outcomes

 

TEXTBOOKS AND MATERIAL

The main references are Wooldridge (2010) and Cunningham (2021). For further study in econometrics I sugest: Hansen (2021), Peracchi (2001) and Train (2009), the latter for limiteded dependent variable models. Angrist and Pischke (2009) for applied issues. Lecture notes, slides and Stata codes will be posted in the material section. Suggestions for further reading and a reading list will be provided in class.

Wooldridge J.M., (2016), Introductory Econometrics: A Modern Approach, 6th ed., Cengage Learning.

Wooldridge J.M., (2010), Econometric Analysis of Cross-Section and Panel Data, 2nd ed., MIT Press, Cambridge (MA).

Hansen B.E., (2020), Econometrics. Mimeo

Peracchi F. (2001), Econometrics, Wiley, Chichester (UK).

Train, K. E., (2009), Discrete Choice Methods with Simulation, 2nd ed. New York: Cambridge University Press.

For a focus on applied issues see

Cunningham S., (2021) Causal Inference: The Mixtape. Yale University Press.

Angrist J.D., and Pischke J.-S., (2009), Mostly Harmless Econometrics: An Empiricists’s Companion, Princeton University Press, Princeton.