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 |
BA304 |
SEMESTER |
3 | ||
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COURSE TITLE |
Introduction in 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 | - | ||||
| LANGUAGE OF INSTRUCTION and EXAMINATIONS | Greek | ||||
| IS THE COURSE OFFERED TO ERASMUS STUDENTS | Yes (under request) | ||||
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COURSE WEBSITE (URL) |
https://
eclass.uowm.gr/courses/BA139
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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. Specify an econometric model 2. Estimate a classical linear econometric model 3. Interprete econometric results of estimated linear models 4. Estimate time series models and make economic predictions |
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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 • Production of new research ideas • Project planning and management |
3. SYLLABUS
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The course content includes: • Basics of Econometrics- Types of Statistical data and datasources • Statistical meanings: standard deviation, variance, covariance, correlation, paprameters. • Linear and non-linear regression models • Ordinary least squared methodology • Statitistical estimations in linear models and making predictions • Statistical testing hypotheses, confidence intervals • Gauss- markov theorem • Autocorrelation test • Dummies variables • Time series analysis • System equation models • Learning in practice of econometric programs such as Eviews and Gretl softwares |
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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• Katrakilidis, K., Konteos, G. and Sariannidis, N. (2020). Modern Econometric Analysis. Alexandros IKE (eds).Kozani. • 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: |