B2222 - ECONOMETRICS FOR DECISION MAKING

Learning outcomes

The course aims to provide a methodological and applied overview of the modern econometric methods for decision-making in a number of contexts (investment, financing, innovating, etc.). A central role is played by panel data, in which at least two dimensions of observations are present: classically, we can have cross-sectional time series data (CSTS); recently, the multiple aspects of economic decisions emerge from multilevel data, such as firms within industries within regions within countries, observed over time. A pervasive aspect of the methods will concern the measurement of complex phenomena, such as heterogeneity, innovation and intangibles, uncertainty and disagreement.

Course contents

The course aims to provide a discussion of some alternative methodological and empirical analyses available with panel data.

It begins by considering panel data as suitable for multilevel models, where one wants to take into account the different levels of aggregation that may be present in the data.
It then moves on to examine estimates of heterogeneous parameters through meta-analysis, where regression can be used to study the relationship between covariates and effect size.

Applications will be based on topics such as corporate capital structure, green innovation and the role of uncertainty perception.

Clearly there are necessary prerequisities, specifically for Erasmus students:

1. At this page you can take a look at the content of courses like Econometrics for Individual Data, Corporate governance: an international perspective, International accounting, Industrial Economics, Python for Economists, Environmental Economics.

2. A knowledge, at least basic, of STATA software is also required

Readings/Bibliography

Discussion papers, commented notes & slides, stata programmes and datasets will be available on the VIRTUALE platform and explained during the lectures.

Some references are

Snijders, T. and Bosker, R. (2012) Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Analysis, 2nd edition, Sage

Hanga, M. and Geyer-Klingeberga, J. and Rathgebera, A. W. and Stöcklb, S. (2018) Measurement matters—A meta-study of the determinants of corporate capital structure, The Quarterly Review of Economics and Finance, 68, 211-225

Yin, S. and Jia, F. and Chen, L. and Wang, Q. (2023) Circular economy practices and sustainable performance: A meta-analysis, Resources, Conservation and Recycling, 190, 106838

Teaching methods

During the lectures, the methodologies will be accompanied by empirical applications based on Stata econometric software (available using the CAMPUS licence and student university credentials [https://www.unibo.it/secure/software-stata/] ).

You will be involved in implementing and commenting the empirical analyses, so have your laptop with you. Of course, attending and participating the lectures is highly recommended.

Assessment methods

During the course, you will be given an assignment to do at home (alone or in a group of up to three people) and to post on VIRTUALE at the deadline set by the lecturer. This is a research question relevant to the topics seen in class (the lecturer will provide datasets and questions), to be developed empirically, giving reasons. The homework contributes 30% to the overall assessment.
The final exam, compulsory and subject to registration on AlmaEsami, contributes the remaining 70%. It consists of an individual presentation in the classroom (maximum time 15 minutes) of an empirical analysis conducted on panel data. You can decide together with me which topic you would like to explore in more depth or agree that I will assign you a research question. The assessment focuses on your ability to analyse the topic in a theoretical and applied manner.

The overall grading scale is:
30 cum laude: impeccable work
28-30: excellent work, which demonstrates a thorough and comprehensive knowledge of the topic, as well as excellent comprehension and analytical skills.
24-27: good work that denotes an appreciable degree of knowledge of the subject.
18-23: there is disorder, with theoretical and methodological inaccuracies.
<18: failure of the test

 

Teaching tools

Theoretical lectures are associated with working sessions; during them you will receive the suggestions needed to run your own empirical analysis. The data-sets and the programming files to perfom applied analyses will be provided during the lectures. The distributed material will be make available on the Virtuale platform. A virtual room on TEAMS will be available in case you cannot physically attend a lecture and to communicate via chat.

Software STATA: click here [https://scienzeaziendali.unibo.it/en/department/technical-and-administrative-services/software-with-campus-licenses]

Office hours

See the website of Maria Elena Bontempi