Π.Μ.Σ στη «Χρηματοοικονομική και Τραπεζική»

## Econometrics and Introduction to R

Full Time// 1st Semester, Course Code: ΜΕΧΡΗ329

Part Time // 2nd Semester, Course Code: ΜΕΧΡΗ-Μ329

Credits: 6

## Learning Outcomes

Upon successful completion of the course, the student

(a) will know the fundamental assumptions for the application of the linear model and its estimation by the method of least squares, but also by alternative methods,

(b) will be able to interpret the estimated parameters of the linear model as well when the logarithm of an explanatory or dependent variable is used. It will also be able to draw conclusions from the standard tables produced by econometric software packages,

(c) will be aware of the effects of violating the classical assumptions, such as when there is heteroscedasticity, multicollinearity or when an explanatory variable has been omitted,

(d) will be able to test for heteroscedasticity and know how to deal with it;

(e) will be able to use dummy variables and interpret the estimated coefficients,

(f) will know the purpose and basic properties of important non-linear models (probit, logit),

(g) will know the basic principles of the Instrumental Variables method for treating the problem of endogeneity,

(h) will have acquired a basic familiarity with the R language and will know its basic functions, which are needed data processing, and be able to use R in applications of the taught econometric methods

## General Competences

Within the framework of the combined skills that the graduate will acquire by attending all the courses of the study program, this course aims at the graduate to acquire abilities:

(a) in the search for, analysis and synthesis of data and information, with the use of the necessary technology,

(b) in decision-making

(c) in working independently

(d) to promote free, creative and inductive thinking

(e) in exercising criticism and self-criticism

## Course Content

The course focuses on the following sections:

1) Introduction to Linear Regression

The nature of Econometrics

The statistical generating mechanism and regression models.

Linear regression models, simple regression models, the classic multiple regression model.

The Simple Linear Regression Model

2) The classic assumptions.

Least squares estimators, sample moments estimators, method of moments.

Properties of estimators, Gauss-Markov theorem, distributions of estimators.

Multiple Regression Analysis

3) The case of k independent variables

Interpreting the least squares regression equation

Expected value and variance of least squares estimators

Hypothesis testing and confidence intervals

Checking multiple linear constraints

Asymptotic properties of least squares: Consistency and efficiency of estimators

Consequences of multicollinearity

Heteroscedasticity

4) Implications for the least squares estimator

Heteroscedasticity “robust” inference

Testing for Heteroscedasticity

Weighted and Generalized Least Squares

5) Regression Analysis with Qualitative Information: binary (or dummy) variables

Regression with one dummy (binary) variable

Dummy variables for multiple categories

A binomial dependent variable: the linear probability model

6) Special issues

The Probit and Logit models

Endogeneity and the method of Instrumental Variables

During the course there will be an introduction to the R language and the use of the RStudio interface, including:

Basic R functions for data manipulation

Examples are presented using the appropriate R functions for regression analysis, according to the course outline.
Special emphasis is placed on the interpretation of the results obtained from the use of these functions.

## Student Performance Evaluation

Formative and conclusive evaluation is carried out. The final evaluation of the students is done by a written exam or an oral exam. It is based on problem solving, short-answer questions and open-ended questions.

## Bibliography

Suggested Bibliography

• Tutor’s Notes
• Introductory Econometrics: A Modern Approach, 6th edition (J. Woodrifge) – Greek edition, Papazisis ed.)

• Econometric Reviews, Econometric Theory
• Journal of Econometrics
• Journal of Applied Econometrics

Master of Science (M.Sc.) in
«Banking and Finance»

Specialization in
«Banking and Financial Management»