COURSE OUTLINE
 GENERAL
SCHOOL  AGRICULTURAL AND FORESTRY SCIENCES  
DEPARTMENT  AGRICULTURAL DEVELOPMENT  
LEVEL OF STUDIES  7  
COURSE CODE  ECO0012  SEMESTER  8^{th}  
COURSE TITLE  APPLIED ECONOMETRICS  
TEACHING ACTIVITIES 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.  
COURSE TYPE
Background, General Knowledge, Scientific Area, Skill Development 
Specialization  
PREREQUISITES:

–  
TEACHING & EXAMINATION LANGUAGE:  Greek  
COURSE OFFERED TO ERASMUS STUDENTS:  Yes (in English)  
COURSE URL:  https://eclass.duth.gr/courses/OPE01263/  
 LEARNING OUTCOMES
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 

General Skills  
Name the desirable general skills upon successful completion of the module  
Search, analysis and synthesis of data and information,
ICT Use Adaptation to new situations Decision making Autonomous work Teamwork 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 Sustainability Demonstration of social, professional and moral responsibility and sensitivity to gender issues Critical thinking 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, Τdistribution, Fdistribution), 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 VarianceCovariance of random error, Attributes of b estimate), 6. Hypothesis testing (tratio 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 matrixtables) (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, DurbinWatson Test, tstatistic test, h Durbin criterion), Test for autocorrelation of greater order ( BreuschGodfrey Test, Fcriterion test), Estimation methods of models with autocorrelation, 13. Heteroscedasticity, Heteroscedasticity tests, (Spearman coefficient of correlation, GoldfeldQuand criterion, White criterion), Estimation methods of models with heteroscedasticity. 
 LEARNING & TEACHING METHODS – EVALUATION
TEACHING METHOD 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
§ e–class 

TEACHING ORGANIZATION
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. 


Student Evaluation
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 WileyBlackwell, West Sussex, UK. 
ANNEX OF THE COURSE OUTLINE
Alternative ways of examining a course in emergency situations
Teacher (full name):  Eleni Zafeiriou 
Contact details:  ezafeir@agro.duth.gr 
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. 