B3154 - Empirical Methods for the Analysis of Energy System

Learning outcomes

The course is intented to equip students with the skills necessary to analyze the essential features of energy systems. They will learn quantitative methods used in the literature to study the social cost of carbon and electricity markets and the links between energy and the macroeconomy from an econometric perspective.

Course contents

1: Introduction to Energy Systems and Empirical Analysis

2: Descriptive Statistics and Data Visualization

3: Basics of Statistical Inference

4: Regression Analysis in Energy Systems

5: Time Series Analysis in Energy Systems

6: Case Studies and Applications in Energy Systems

Readings/Bibliography

- Slides provided by the teacher

- Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data. MIT press.

- Hansen, B. (2022). Probability and Statistics for Economists. Princeton University Press.

- Hansen, B. (2022). Econometrics. Princeton University Press.

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TBA

Teaching methods

Interactive slide presentations integrated with hands-on exercises using real-world datasets

Assessment methods

The exam evaluates whether the student has mastered the foundational objectives of performing empirical analysis on energy system components. The examination is in written form.

 

The grading system is on a 0-30 range. The maximum possible score is 30 cum laude, in case everything is correct, complete, and formally rigorous. The following grid applies:

<18 failed
18-23 sufficient
24-27 good
28-30 very good
30 e lode excellent.

Students must inform the lecturer in writing (via email) if they intend to reject their grade; the deadline for this notification will be provided when exam results are released. After the deadline, grades will be officially recorded electronically.

Teaching tools

All the material will be available on the course's page

Office hours

See the website of Luca Neri