Academic Year 2022/2023

  • Teaching Mode: Traditional lectures
  • Campus: Forli
  • Corso: Second cycle degree programme (LM) in Economics and management (cod. 9203)

    Also valid for Second cycle degree programme (LM) in Economics and management (cod. 9203)

Learning outcomes

The course aims at providing students theoretical and practical knowledge of the methods for conducting empirical research through the specification of the classical linear regression model (CLRM) and the use of alternative functional forms; the estimation of parameters; the evaluation of the nature of the error term and hypotheses testing; the conditions to obtain sensible results with a causal interpretation; how to critically understand empirical articles. Data samples and an econometric software will be used to estimate models during hands-on sessions.

Course contents

Nowadays, applied work in business and management requires a solid understanding of econometric methods to support decision-making. The course aims at deepening theoretical and practical knowledge of the methods for conducting empirical research through the specification of a testable empirical econometric model; the estimation of unknown parameters based on observed data (cross-sections, time series, and panel data); the evaluation of the nature of the error term and hypotheses testing; the conditions to obtain sensible results with a causal interpretation; how to critically understand empirical articles. Data samples and programming instructions for the econometric software will be presented and used to estimate models during hands-on sessions.

Specifically, the course is articulated according to the points below:

  • A recap of the classical linear regression model (CLRM) and the OLS method to estimate parameters.
  • Validate the method: specification tests; different problems in simple and multiple regression models; alternative functional forms; parameters' heterogeneity.
  • Panel data: dealing with cross-sections, time-series, and other levels of analysis.
  • A brief introduction of the fundamental methods to estimate models on panel data.

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 ensure a smooth transition from theory to practice in the
discipline of econometrics, theoretical lectures are combined with working sessions. During the hands-on empirical applications, students will use the laptop and the STATA econometric software, which is available under the CAMPUS license and students' university credentials.
At the end of the course, participants will be able to critically evaluate articles presenting empirical analyses, and to model and estimate their regression of interest, using the most appropriate methods according to the problem they face.

Assessment methods

During the course students will have the opportunity to create teamwork groups through which they can test their knowledge and increasing expertise in applying the econometric method. Students will have a final and individual written examination on theoretical and applied issues, with open questions designed to assess their capacity in understanding models' specifications and estimated results, as well as to evaluate 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

SDGs

Quality education Gender equality Decent work and economic growth Reduced inequalities

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.