FINANCIAL ECONOMETRICS

This course is aimed at providing students with the skills required to undertake independent applied research using modern microeconometrics methods. It supplies a balance between theory and applied research.
This course provides an understanding of basic (micro)-econometric techniques and applied finance research. The course covers modern econometric methods on the basis of an intermediate textbook. The technique of regression will be discussed, as well as various extensions of this estimation technique in order to deal with issues such as endogenous regressors, non-linear models (e.g. probit, logit model). The course will also go through examples of econometric estimation of personal finance equations using micro data in STATA.

Throughout the duration of this course, students will be tasked with completing empirical assignments that necessitate the utilization of the software package, STATA. These assignments are designed to equip students with practical skills and knowledge in the field of econometrics.
By the end of the course, students will have developed the following skills:
- carry out an econometric analysis on cross-sectional data set.
- interpret and critically evaluate the results of several estimation and testing procedures.
- apply appropriate estimation techniques for relatively simple empirical problems.
- use a statistical package (we use STATA for this course) for estimating standard econometric models.

You are expected to know the contents of the Probability Theory and Basic Econometrics course. It is highly recommended that you know some basics about using STATA. You can find "Introduzione a STATA/Introduction to STATA" on Moodle to get an introduction to STATA.

An introduction to linear regression
Review
1. Probability theory and statistics
2. Review of linear algebra

An introduction to linear regression
1. The algebra of OLS
2. Linear regression model
3. Small sample properties of OLS
4. Hypothesis testing
5. Asymptotic properties of OLS

Applied session I: Practical STATA


Interpreting regression models
1. Interpretation
2. Model misspecification
3. Selecting regressors

Applied session II: Practical STATA

Heteroskedasticity and autocorrelation
1. Consequences for the OLS estimator
2. Heteroskedasticity and testing for heteroskedasticity
3. Autocorrelation and testing for autocorrelation

Endogeneity and IV
1. Endogeneity
2. Instrumental Variables

Applied session III: Practical STATA

Maximum likelihood estimation

Binary choice models
1. Latent variables and Random Utility Theory
2. Linear probability models
3. Probit and Logit

Tobit models
- 1. The standard Tobit model
- 2. The Tobit II model

Applied session IV: Practical STATA

Verbeek, M. (2017). A guide to modern econometrics. John Wiley & Sons.

During this course, students will engage in hands-on empirical assignments that require the use of the STATA software package. These assignments are thoughtfully crafted to provide students with practical insights and knowledge in the field of econometrics.

Regarding the assessment, please note that the final grade will be determined solely by the final exam, which constitutes 100% of the overall evaluation.

Lectures and practice sessions.
For any course-related information, students can follow Moodle.

English

The course is carried out in collaboration with the extended partnership AGE-IT Age-It - Ageing well in an agening society” (PE0000015), CUP H73C22000900006, public notice no. 341/2022 of the National Recovery and Resilience Plan ("NRRP"), Mission 4 - Component 2 - Investment 1.3, funded by the European Union - NextGenerationEU.
As part of the course, meetings with companies’ testimonials involved in the project may be offered, focusing on the development of practical knowledge in the subject matter, as well as the results of the project itself.
This course covers topics related to Spoke 6 The Silver Economy. Work, participation, and welfare at older ages – WP2

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