The study of social, economic, technological and natural phenomena in a particular region (large or small scale), the exploration of the relationships that exist between different variables (temporal and spatial) as the "increasing pressure" that is observed as regards planning and rational decisions make more and more necessary the creation of theoretical and empirical models that can support these above analysis.
Τhe course consists of 13 lectures covering the major scientific fields of econometric methods that help to analyze the regional and spatial development.
The course presents and analyzes (a) the major principles of econometrics, (b) the most useful econometrics models and (c) the modern statistical and econometric methodology applied to the investigation, control and prediction of phenomena, especially in conditions of uncertainty. Emphasis is given to (1.) the empirical application of econometrics as regards socio - economic and spatial questions and (2.) the interpretation of the results according to the possibilities and limitations offered by the econometrics methods.
In this course the following topics are developed:
Lecture 1: Introduction to Econometrics: Definitions, purpose and types of models
Lecture 2: The classical linear models
Lecture 3: The Generalized Linear Model
Lectures 4 and 5: Application of linear models: from theory to empirical applications
Lectures 6 and 7: Violations of the major assumptions of linear models (Autocorrelation, Heteroskedasticity, Multicorrelation, Specification errors of models)
Lecture 8: Examination of models
Lectures 9 and 10: Time series: estimate - forecast (Classical methods of analysis. Stochastic Analysis)
Lectures 11 and 12: Models with discrete dependent variables: Probit and Logit model
Lecture 13: ANCOVA Model
The central aim of the course is to offer knowledge and skills to students in order to be able to articulate the theoretical perspectives and theories with actually observed data. The Econometrics, like Statistics are sciences serving the above purposes and this, of course, in direct combination with the use of Information Technology and other advanced econometric software. The more complex are the relations and the evolution / change of socio-economic phenomena, the greater the need to develop efficient and adapted tools for their analysis.
More specifically, this course aims to contribute to:
1. acquire the proven knowledge and understanding of statistical and econometric methods of analysis relative to socio-economic phenomena that have important spatial dimension
2. Obtain - through the systematic application of relevant methods - the necessary aptitude of adjustment to research procedures, specifically as regards the collect the treatment and the interpretation of reliable spatial data.
3. Acquire skills related to the development of critical analysis, evaluation and synthesis of complex and multi-dimensional concepts.
4. Participate to the advancement of the knowledge society
Students’ performance evaluation is based on:
(a) a final written exam (60% of final grade) including theoretical questions and exercises and
(b) a Take-home assignment (40%) with oral presentation. The Take-home assignment is mandatory.
- Wooldridge J. (2013), Εισαγωγή στην οικονομετρία, Αθήνα: Παπαζήση.
- Ανδρικόπουλος Α. (2003), Οικονομετρία: Θεωρία και εμπειρικές εφαρμογές, Τόμος Α, Αθήνα: Εκδόσεις Ευγ. Μπένου, 3η έκδοση.
- Κιντής Α. (1999), Στατιστικές και Οικονομετρικές Μέθοδοι, Αθήνα: Εκδ. Gutenberg.
- Μαυρομάτης Γ. (1999), Στατιστικά Μοντέλα και Μέθοδοι Ανάλυσης δεδομένων. Θεσσαλονίκη: University Studio Press, (Κεφ. 1 – 3).
- Ashenfelter O., Levine P.B., Zimmerman D.J. (2003), Statistics and Econometrics: Methods and Applications, New-York: Ed.