86530 - ECONOMETRICS

Learning outcomes

The aim of the course is to provide students with adequate knowledge of the basic econometric tools for empirical investigations of cross-sectional and time series data. Drawing on critical discussion about microeconomic and financial applications, students develop the basic skills to perform empirical work using econometric software. At the end of the course students are able to: (a) choose between different econometric models and estimation techniques; (b) discuss the empirical results of the economic and financial analyses proposed in class; (c) to perform one’s own analysis using econometric/statistical software.

Course contents

The course is articulated according to the points below.

• What is econometrics? The research question and the different types of data: cross-sections, time-series & panel data.
  
• The classical linear regression model (CLRM) and the OLS estimator: the assumptions of the method.
• Validate and interpred the OLS: specification tests and estimated results in simple and multiple regression models: omitted variables bias and multicollinearity, qualitative explanatory variables, parameters' heterogeneity.
  
• What to do when OLS assumptions are no longer valid? Alternative models' specifications and functional forms (log, quadratic forms, ..), heteroskedasticity, robust standard errors, the generalised least squares and instrumental variables approaches.
• An introduction to time series: stationarity, unit root tests, autocorrelation, static & dynamic models (AR, ARMA, ARDL), volatility models (ARCH, GARCH), information criteria and parameters' instability.

Readings/Bibliography

The material (articles, notes, programs and data-sets) will be distributed during the lectures and make available on the platform Virtuale.

The reference textbook is:
Wooldridge J.M. 2020 Introductory Econometrics. A Modern Approach, Cengage, 7th Edition.

Teaching methods

To provide a smooth transition from theory to practice in the
discipline of econometrics, theoretical lectures are associated with working sessions. During the hands-on empirical applications, students will use the laptop, an econometric software (Gretl is free, while Stata is available using the CAMPUS license and students' university credentials).
At the end of the course, participants will be able to critically evaluate articles that present empirical analyses, and to model and estimate their regression of interest, with the most appropriate methods based on the problem they face.

Assessment methods

Students will have a written examination on theoretical and applied issues, with open ended questions aimed at assessing their capacity in understanding models' specifications and estimated results, and in evaluating the strengths and weaknesses of alternative estimating methods. During the exam students will use the computer and the econometric software.

According to the pandemic situation, the exams could be either in presence or online, but this will not alter the assessment methods.
Students have to register in Almaesami so as to receive the link to the virtual class in Zoom. Also, students will have to access to EOL (Exams Online) by using their institutional credentials.

The possible grades are:
< 18 failed
18-23 sufficient
24-27 good
28-30 very good
30L (cum laude) excellent

Teaching tools

Theoretical lectures are associated with working sessions; during them students will receive the suggestions needed to run their own empirical analysis. The data-sets and the programming files to perfom applied analyses will be provided during the lectures. The distributed material (articles, notes, programs, and data-sets) will be make available on the Virtuale platform.

Software STATA: click here

Links to further information

https://sites.google.com/site/mariaelenabontempi/home/teaching/econometrics

Office hours

See the website of Maria Elena Bontempi

See the website of Graziano Moramarco