10532 - Applied Econometrics

Learning outcomes

At the end of the course the student is able to develop a basic econometric analysis using lineare regression. The student is able to understand the output of a regression analysis and interpret the magnitude of coefficients. Moreover, the student is able to implement regression models using STATA.

Course contents

• What is econometrics? Introduction to the subject with case studies and practical examples.
• The linear regression model: the Ordinary Least Squares Estimator and goodness-of-fit measures.
• Hypothesis testing and confidence intervals.
• Omitted variable bias.
• Binary regressors in linear regression models.
• The multiple linear regression model.
  
• Non linear regression models: polynomials, logarithmic transformations and interaction between variables.
• Advanced topic: panel data, binary outcome variables and instrumental variables.

Every theoretical concept will be followed by an empirical application based on real-world data.

Readings/Bibliography

Stock, J.H., Watson, M.W. "Introduzione all'econometria", 4a edizione (2016), Pearson Education Italia.

Further material will be communicated and/or distributed in class.

Teaching methods

Traditional lecture-style instruction with debate over real-world practice examples. For each theoretical concept, an empirical application will be illustrated.

Computer-based review sessions complete the teaching by providing useful tools which will allow students to interpret and discuss empirical results.

Assessment methods

Student evaluation is based on class participation and on two tests:

• problem set: take-home exam using the STATA software that students can solve in groups with at most 4 people (1 week);
  
• written exam: application of econometric tools to a case study (1 hour) plus optional oral exam.

The software STATA is available on university's computers.

Those students who decide to NOT ATTEND classes must inform the professor before the class starts.

Teaching tools

• Slides available on eLearning;
• Stata software, available on computers at the lab, Department of Economics.

Office hours

See the website of Marco Magnani