|SCHOOL||AGRICULTURAL AND FORESTRY SCIENCES|
|LEVEL OF STUDIES||7|
|COURSE TITLE||APPLIED ECONOMETRICS|
If the ECTS Credits are distributed in distinct parts of the course e.g. lectures, labs etc. If the ECTS Credits are awarded to the whole course, then please indicate the teaching hours per week and the corresponding ECTS Credits.
|TEACHING HOURS PER WEEK||ECTS CREDITS|
|Lectures and practice exercises course||(3+2)||5|
|Please, add lines if necessary. Teaching methods and organization of the course are described in section 4.|
Background, General Knowledge, Scientific Area, Skill Development
|TEACHING & EXAMINATION LANGUAGE:||Greek|
|COURSE OFFERED TO ERASMUS STUDENTS:||Yes (in English)|
- LEARNING OUTCOMES
|Please describe the learning outcomes of the course: Knowledge, skills and abilities acquired after the successful completion of the course.|
|Upon the completion of the course the students
· will have acquired the basic knowledge to study the validity of the economic theory with the use of Statistics and Mathematics through the estimation and evaluation of economic models
|Name the desirable general skills upon successful completion of the module|
|Search, analysis and synthesis of data and information,
Adaptation to new situations
Working in an international environment
Working in an interdisciplinary environment
Production of new research ideas
|Project design and management
Equity and Inclusion
Respect for the natural environment
Demonstration of social, professional and moral responsibility and sensitivity to gender issues
Promoting free, creative and inductive reasoning
| Knowledge on Statistics, Economic Theory and Mathematics
• Ability to implement theories on the survey of existing economic theories
• Ability for analysis and Synthesis
- COURSE CONTENT
|1. General Concepts (Random variables, Expected value of a random variable Variance, Standard deviation of a random variable, covariance of two random variables, X,Y Expected value of a random variable, variance, standard deviation of a random variable.
2. Useful distributions (Normal distribution, , chi square _ distribution, Τ-distribution, F-distribution),
3. Simple regression (Two variable model) (Economic Theory, Basic assumptions of the linear model Υ = β1 + β2Χ + e, Sample Regression,
4. The method of ordinary least squares (application to the model: Υ = β1 + β2Χ + e), (Solution with sums, Matrix solution,
5. Application of regression Variance-Covariance of random error, Attributes of b estimate),
6. Hypothesis testing (t-ratio of b , The coefficient of determination r2 , Correlation coefficient r, Evaluation of the sub – sample),
7. General Model Y = β Χ + β Χ +…+ β Χ + e (By the method of matrix-tables) (Presentation of the model Y = b X + b X +…+ b X + e, Appraisers fluctuations – covariance of rates, the coefficient of multiple determination R, Sums squares tabular assessment model, assessment of individual factors, Evaluation of the entire design),
8. Resolving the three variables model Y = b + b X + b X + e checksum (Solving the three variables model, the coefficient of multiple determination R, the corrected coefficient multiple determination, and Some Simple Coefficient of determination, coefficient of determination Simple, Some factors identification, assessment of the variability of the disturbing term fluctuations b, b,
9. Testing of Linear restrictions on some coefficients regression, the statistical relationship between F and the coefficient of determination R2,
10. Violations of Linear Model assumptions (Multi collinearity, Testing the existence of multi collinearity, Estimation methods of models with multi – collinearity
11. Autocorrelation, Autocorrelation of first order, Consequences of autocorrelation,
12. Autocorrelation tests (Graphical depict of the residuals, Durbin-Watson Test, t-statistic test, h Durbin criterion), Test for autocorrelation of greater order ( Breusch-Godfrey Test, F-criterion test), Estimation methods of models with autocorrelation,
13. Heteroscedasticity, Heteroscedasticity tests, (Spearman coefficient of correlation, Goldfeld-Quand criterion, White criterion), Estimation methods of models with heteroscedasticity.
- LEARNING & TEACHING METHODS – EVALUATION
Face to face, Distance learning, etc.
|Face to face, Distance Learning|
|USE OF INFORMATION & COMMUNICATIONS TECHNOLOGY (ICT)
Use of ICT in Teaching, in Laboratory Education, in Communication with students
|§ Power point
The ways and methods of teaching are described in detail.
Lectures, Seminars, Laboratory Exercise, Field Exercise, Bibliographic research & analysis, Tutoring, Internship (Placement), Clinical Exercise, Art Workshop, Interactive learning, Study visits, Study / creation, project, creation, project. Etc.
The supervised and unsupervised workload per activity is indicated here, so that total workload per semester complies to ECTS standards.
Description of the evaluation process
Assessment Language, Assessment Methods, Formative or Concluding, Multiple Choice Test, Short Answer Questions, Essay Development Questions, Problem Solving, Written Assignment, Essay / Report, Oral Exam, Presentation in audience, Laboratory Report, Clinical examination of a patient, Artistic interpretation, Other/Others
Please indicate all relevant information about the course assessment and how students are informed
Written exams at the end of the semester both on theory and exercises
- SUGGESTED BIBLIOGRAPHY
| Maddala G.S. (2010). Introduction to Econometrics, 4th Edition Wiley-Blackwell, West Sussex, UK.|
ANNEX OF THE COURSE OUTLINE
Alternative ways of examining a course in emergency situations
|Teacher (full name):||Eleni Zafeiriou|
|Supervisors: (1)||Eleni Zafeiriou|
|Evaluation methods: (2)||Final Exams written|
|Implementation Instructions: (3)||The subjects of the exams will be provided through a file that will be uploaded in the field projects for a specific time period according to the program of exams.
The answers by the students will be provided by the students through multimedia files.
Each exercise will be graded while the exam contribution will be 100%,
The exam is simultaneous for all the students
The participation in the exams can be done with the use of their institutional account.