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Syllabus

EN IT

Updated A.Y. 2022-2023

OVERVIEW AND PREREQUISITES

This course introduces students to statistical and econometric methods. Generally speaking, econometrics fills a gap between being a “student of economics” and being a “practitioner”. In particular, the students will apply estimation techniques using microdata applied to different contexts from business, education, and labor.  For example, students will be able to predict a product's sales or test if a new ad campaign is actually increasing them. The course also aims at developing microdata analysis skills useful for the preparation of research projects. The course consists of 36 hours. For each topic, we will first introduce the relevant theory and then move to its empirical application using the software Stata. Special emphasis will be placed on the economic interpretation of the results. Attending classes is important especially to learn the empirical topics of the course.

 

OUTLINE

  • Ordinary Least Squares
  • Maximum Likelihood estimation 
  • Binary dependent Variables 
  • Unordered dependent Variables 
  • Ordered dependent Variables 
  • Panel Data 

 

TEXTBOOK AND MATERIAL

  • Hill, R. C., Griffiths, W. E., & Lim, G. C. "Principles of Econometrics" (4th edition, International Student Version), Wiley 2011 (English).
  • Hill, R. C., Griffiths, W. E., & Lim, G. C. (2018) Using Stata for Principles of Econometrics, 5th edition, John Wiley & Sons.

The slides used during classes, sketches of training sessions, exercise solutions, codes, and mock exams will be made available for download on the Teams course web page. Students will be asked to register to that platform at the start of the classes.

 

ASSESSMENT METHODS

The exam is written and it lasts 1 hour. It is composed of two different sections.
The first section is theoretical, and it consists of 5 multiple-choice questions. The second is both empirical and theoretical, and it consists of 11 questions whose answers should be computed using Stata. Each answer is valid 2 points max;