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ECONOMETRICS-MOD. ESTIMATION METHODS AND APPLICATIONS

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ECONOMETRICS-MOD. ESTIMATION METHODS AND APPLICATIONS

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Academic year 2024/2025

Course ID
SEM0186A
Teachers
Margherita Borella (Lecturer)
Year
1st year
Teaching period
First semester
Type
Distinctive
Credits/Recognition
6
Course disciplinary sector (SSD)
SECS-P/05 - econometrics
Delivery
Formal authority
Language
English
Attendance
Optional
Type of examination
Written
Type of learning unit
corso
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Sommario del corso

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Course objectives

The main purpose of this course is to give a general and comprehensive overview of the different econometric methodogies and approaches, focusing on what is relevant for doing and understanding empirical work. The number of econometric techniques that can be used is numerous and their validity often depends crucially upon the validity of the underlying assumption. This course attempts to guide students through this array of estimation and testing procedures by also offering real world empirical cases.

 

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Results of learning outcomes

- Knowledge and understanding: this course will provide students with a deep and up-to-date knowledge of modern econometric theories and related estimation and testing techniques.

- Applying knowledge and understanding: students will learn how to apply econometrics techniques to actual economic problems. 

- Making judgements: the students will learn how to assess the validity of the assumptions of a wide range of econometric models with the purpose of realizing potential drawbacks or dangers in their application to relevant empirical economic questions.

- Communication skills: students will learn how to effectively organize ideas both in written and oral form, possibly with the help of presentation of scientific papers during the course.

- Learning skills: this course will enable students to understand the recent developments in econometrics and will be a suitable basis for further research work in the area.

 

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Program

  • The Classical Linear Regression Model and Its Violations
  • Endogeneity, Instrumental Variables and GMM 
  • MaximumLikelihood Estimation and Specification Tests 
  • Models with Limited Dependent Variables 
  • Panel data

 

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Course delivery

The course consists of 48 lecture hours. Strong interaction between teachers and students is warmly encouraged.

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Learning assessment methods

1 h. and 15 m. (max.) written exam at the end of the course. The exam paper is made up of three questions. Specific quantitative scores are allocated to each question and communicated to students before the exam. Scores sum up to 30/30.

Suggested readings and bibliography

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Handouts, references and suggested readings will be circulated when classes start.

All teaching materials will be available on the Moodle page of the course.



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