1. GENERAL
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SCHOOL |
SCHOOL OF ECONOMIC SCIENCES |
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ACADEMIC UNIT |
DEPARMENT OF ACCOUNTING AND FINANCE |
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LEVEL OF STUDIES |
Undergraduate |
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COURSE CODE |
BA402 |
SEMESTER |
4 | ||
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COURSE TITLE |
Applied Econometrics | ||||
| INDEPENDENT TEACHING ACTIVITIES |
WEEKLYTEACHING HOURS |
CREDITS | |||
| Lectures | 3 | ||||
| Hours Lab | 0 | ||||
| Hours Exercises | 0 | ||||
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Total |
3 | 6 | |||
| COURSE TYPE | Scientific Field, Compulsory, Skills Development | ||||
| PREREQUISITE COURSES | Introduction in Econometrics | ||||
| LANGUAGE OF INSTRUCTION and EXAMINATIONS | Greek | ||||
| IS THE COURSE OFFERED TO ERASMUS STUDENTS | Yes (upon request) | ||||
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COURSE WEBSITE (URL) |
https://
eclass.uowm.gr/courses/BA140
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2. LEARNING OUTCOMES
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Learning outcomes |
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After successful completion of the course, students are expected to be able to: 1. Achieve a complete knowledge of classical tools and methods of applied econometrics 2. Develope their interpretational skills and a critical mind with regard to the use of econometric models within the context of applied econometrics. |
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General Competences |
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• Search for, analysis and synthesis of data and information, with the use of the necessary technology • Decision-making • Working independently |
3. SYLLABUS
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The course content includes: Simple regression models • Econometric estimation methods (such as Ordinary Least Squared method) • Statistical significance and coefficients interpretation • Determination coefficient • Regression residuals • Predictions • Linear estimation models Multiple regression models • Estimation results analysis of multiple regression models • Adjusted determination coefficient • Testing hypotheses (multiple linear models with F-distribution) • Multi-colinearity • Diagnostic tests (specification heteroskeasticity, autocorrelation and normality tests) |
4. TEACHING and LEARNING METHODS - EVALUATION
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DELIVERY |
Face to face, Learning in practice, Working independently | ||||||||||||||||||||||||
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USE OF INFORMATION AND COMMUNICATIONS TECHNOLOGY |
Learning specifis software in lab for projects implementation. The econometric software is easily shared via internet link and students have the possibility to practice with it and work independently. | ||||||||||||||||||||||||
| TEACHING METHODS |
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STUDENT PERFORMANCE EVALUATION |
1. Final Exam(multiple choice, short-answer questions, problem solving) 100% • Laboratory work (30%) • Formal written exams (70%) |
5. SUGGESTED BIBLIOGRAPHY
| -Suggested bibliography: |
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• Chalkos, G.(2020). Applied Econometrics. Disigma (eds). Thessaloniki. • Asteriou, D. and Hall, S. (2018). Applied Econometrics. Propobos (eds). Athens. • Vamvoukas, G. (2007). Modern Econometrics: Analysis and Applications. Economic University of Athens (eds). Athens. • Katos, A. (2004). Econometrics: Theory and practice. Zygos (eds). Thessaloniki. • Gujarati, D. N. (2003). Basic Econometrics. Mc Grow-Hill (eds). New York. • Christou, G. (2002). Introduction in Econometrics. Gutenberg (eds). Athens. • Maddala G.S. (1992). Introductory Econometrics. Prentice-Hall (eds). New York. |
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-Related academic journals: |