ΑΝΑΣΤΑΣΙΟΥ ΑΘΑΝΑΣΙΟΣ
ΑΝΑΠΛΗΡΩΤΗΣ ΚΑΘΗΓΗΤΗΣ
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
Ε-mail: athanastas (at) uop (dot) gr
Short CV
Ο Αθανάσιος Αναστασίου είναι Αναπληρωτής Καθηγητής στο Τμήμα Διοικητικής Επιστήμης και Τεχνολογίας του Πανεπιστημίου Πελοποννήσου. Κατέχει διδακτορικό δίπλωμα στα Οικονομικά και έχει 20ετή διδακτική εμπειρία στην τριτοβάθμια εκπαίδευση, τόσο στην Ελλάδα όσο και στην Κύπρο. Τα ερευνητικά του ενδιαφέροντα είναι στον τομέα της Μακροοικονομίας, της Δημόσιας Διοίκησης και Οικονομίας, της Οικονομικής Ανάπτυξης, της Διεθνούς Οικονομίας και της Ευρωπαϊκής Ολοκλήρωσης. Έχει διατελέσει μέλος της συντακτικής επιτροπής του International Journal of Behavioural and Healthcare Research, έχει δημοσιεύσει αρκετές επιστημονικές εργασίες και έχει συμμετάσχει σε πολλά συνέδρια σχετικά με τη Μακροοικονομία, τη Διεθνή Οικονομία, τη Δημόσια Οικονομία και Διοίκηση και τη Μακροοικονομία της Ευρωπαϊκής Ένωσης. Επίσης, τα ερευνητικά του ενδιαφέροντα είναι στην εφαρμοσμένη οικονομετρία με έμφαση στις μεθόδους εκτίμησης κατά Bayes και η προηγούμενη έρευνά του επικεντρώθηκε σε θέματα πολιτικής ανεξαρτησίας της Ευρωπαϊκής Ένωσης και της Κεντρικής Τράπεζας. Έχει ασχοληθεί ερευνητικά με τον τομέα της Περιβάλλουσας Ανάλυσης Δεδομένων και έχει δημοσιεύσει εργασίες που χρησιμοποιούν αυτή την προσέγγιση στη μέτρηση της αποτελεσματικότητας του βιομηχανικού τομέα για τους τομείς των τραπεζών και της εκπαίδευσης.
Short CV
Athanasios Anastasiou is Associate Professor at the Department of Management Science and Technology of the University of Peloponnese. He possesses PhD in Economics and has 20 years teaching experience in higher education, both in Greece and in Cyprus. His research interests are in the area of Macroeconomics, Public Administration and Economics, Economic Growth, International economics and European Integration. He has been editorial board member at International Journal of Behavioural and Healthcare Research, has published several scientific papers and he has participated in numerous conferences related to Macroeconomics, International Economics, Public Economics and Administration and Macroeconomics of the European Union. Also, his research interests are in applied econometrics with emphasis to Bayesian estimation methods and his past research was concentrated on European Union and Central Bank independence policy issues. He has been working in research in the area of Data Envelopment Analysis and has published papers that utilise this approach in measuring industrial sector efficiency for the banking and Education sectors.
knownledge Object: Οικονομική Ανάπτυξη και Μεγέθυνση [ ΦΕΚ 1038/Γ΄/07-05-2021 ]
Science Interest:
Μακροοικονομία
Δημόσια Διοίκηση και Οικονομία
Οικονομική Ανάπτυξη
Διεθνής Οικονομική Θεωρία και Ευρωπαϊκή Ολοκλήρωση
Μακροοικονομικά της Ευρωπαϊκής Ένωσης
Εφαρμοσμένη Οικονομετρία
Μεθοδολογία Έρευνας και Ποσοτικές Μέθοδοι
Science Interest:
Macroeconomics
Public Administration and Economy
Economic Development
International Economic Theory and European Integration
Macroeconomics of the European Union
Applied Econometrics
Research Methodology and Quantitative Methods