75367 - Econometrics

Learning outcomes

At the end of the course the student is introduced to the basic concepts of econometrics, with particular focus on time series analysis. The student masters the basic least squares and maximum likelihood techniques. As for time series analysis, the student is able to apply standard ARIMA methods, with introduction to fractional integration. The student learns to apply these models using Mathlab.

Course contents

1. Moment-conditions based estimation. Least squares and quasi maximum likelihood

2. Large-sample OLS-based inference in linear models with stochastic regressors

3. Large-sample quasi maximum likelihood inference

4. Univariate time series models for conditional means and conditional variances. Estimation and inference

Important remark. For the successful completion of the course, students are highly recommended to have followed an elementary introduction to econometrics, at the level of Chapters 4-7 of Stock and Watson's Introduction to Econometrics (3d edition). These chapters are suitable for self study by students with no preliminary exposure to econometrics. Students are also expected to be familiar with matrix algebra. At the beginning of the course, the students' entry level will be evaluated by a small test on matrix algebra and elementary econometrics.

Readings/Bibliography

Hansen B. (2017). Econometrics (downloadable)

Tsay R. (2002). Analysis of Financial Time Series. Wiley

Teaching methods

Traditional lectures, empirical examples in a computer lab and individual exercises

Assessment methods

The final grade is min{[0.25 P + 0.75 E]+B, 31}, where

- P is a problem sets grade in [0,30],

- E is a written exam grade in [0,30].

- B is a Moodle forum participation bonus in [0,2].

Two problem sets will be assigned during the lecture period and individual solutions will be due one week after each assignment.

Students who do not submit problem sets solutions will have to solve an extra exercise at the written exam, with no extension of the duration of the exam. The grade for the extra exercise will substitute P in the calculation of the final grade.

The final exam will have the duration of 90 to 120 minutes (to be decided) and will have two parts: theoretical exercises and questions based on estimation output. During the exam students may consult a two-sided self-written A4 sheet with whatever contents they find appropriate; this sheet should be handed in together with the answers to the exam questions.

Two discussion forums will be opened in Moodle during the lecture period. Participation in forum discussions is optional.

Teaching tools

Software econometrico: Gretl (not Matlab, as stated in the learning outcomes section)

Links to further information

https://iol.unibo.it/course/view.php?id=22296

Office hours

See the website of Iliyan Georgiev