ID:

SJH

Tipo Insegnamento:

Obbligatorio

Durata (ore):

###### 64

CFU:

8

SSD:

###### ECONOMETRIA

Url:

ECONOMIA E FINANZA/APPLIED ECONOMICS Anno: 1

Anno:

2024

ID:

SJH

Tipo Insegnamento:

Obbligatorio

Durata (ore):

64

CFU:

8

SSD:

ECONOMETRIA

Url:

ECONOMIA E FINANZA/APPLIED ECONOMICS Anno: 1

Anno:

2024

Secondo Semestre (03/02/2025 - 10/05/2025)

1) to be able to perform estimation and testing in linear regression models, and to be comfortable with asymptotic theory for linear models,

2) to be able to implement econometric methods as needed for an empirical analyses in economics and finance.

Roughly corresponding to Appendices A-D of the Greene's book (see below)

Project work + 3 weekly assignments (both to be done in groups) - 70% (50% + 20%) of the final grade

+

2 hours final written exam with 1 theory question and 1 exercise in MATLAB - 30% of the final grade

The project work (to be handed in a week before the written exam) will be orally presented by the group members before the written exam

- Exam in June 2024 and following dates:

3 hours written exam with 2 theory questions and 1 exercise in MATLAB - 100% of the final grade

No carry over of the grades from project works and weekly assignments after May 2024

Greene, William, Econometric Analysis, Prentice Hall

Heteroskedasticity. Generalized least square estimator.

Systems of equations. Measurement Error. Simultaneous equations model. Omitted variables. Instrumental variables estimation. Models for Panel Data. Generalized Method of Moments.

The course will focus on the main econometric tools to perform quantitative analyses of economic data. This course provides analytical resources that will enable students to autonomously investigate the empirical validity of economic theory and to predict economic data.

Applying knowledge and understanding:

The students will be able to:

• Carry out univariate and multivariate linear regression analyses

• Determine the possible presence of causal relationships between economic variables

• Adopt the most common estimation methods: linear projections, maximum likelihood, method of moments.

Making judgements:

We expect students to be able to set up and estimate econometric models and to interpret the outcomes in a sensible way.

Students are asked to use the software MATLAB to gain insights on the econometric methodologies and their implementation.

Learning skills:

This course will contribute to empower learners giving them the theoretical, econometric and programming tools to autonomously study economic and financial data and test economic theories.

Assignments of the project works will be discussed with the teacher and the teaching assistant.

Laurea Magistrale

2 anni

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