Applied Econometrics


COURSE OUTLINE

 

  1. GENERAL
SCHOOL AGRICULTURAL AND FORESTRY SCIENCES
DEPARTMENT AGRICULTURAL DEVELOPMENT
STUDY LEVEL Undergraduate
COURSE CODE ECO0012 SEMESTER 8th
COURSE TITLE APPLIED ECONOMETRICS
INDEPENDENT TEACHING ACTIVITIES

 

TEACHING HOURS PER WEEK ECTS
Lectures and laboratory course (3+2) 5
COURSE TYPE Specialization
PREREQUISITE COURSE(S):
LANGUAGE (TEACHING AND EXAMS) Greek
THE COURSE IS OFFERED TO ERASMUS STUDENTS Yes (in English)
COU

RSE WEBSITE (URL)

 

  1. TEACHING OUTCOMES
Teaching outcomes
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 capabilities
§  Knowledge on Statistics, Economic Theory and Mathematics

·      Ability to implement theories on the survey of existing economic theories

·      Ability for analysis and Synthesis

 

  1. COURSE CONTENT
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. Useful distributions Χρήσιμες Κατανομές (Normal distribution, , chi square _ distribution, Τ-distribution, F-distribution), Simple regression (Two variable model) (Economic Theory, Basic assumptions of the linear model Υ = β1 + β2Χ + e, Sample Regression, The method of ordinary least squares (application to the model: Υ = β1 + β2Χ + e), (Solution with sums, Matrix solution, Application of regression Variance-Covariance of random error, Attributes of b estimate), Hypothesis testing (t-ratio of b , The coefficient of determination r2 , Correlation coefficient r, Evaluation of the sub – sample), 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), 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, Control of Linear restrictions on some coefficients regression, the statistical relationship between F and the coefficient of determination R2,Violations of Linear Model assumptions (Multi collinearity, Testing the existence of multi collinearity, Estimation methods of models with multi – collinearity, Autocorrelation, Autocorrelation of first order, Consequences of autocorrelation, 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, Heteroscedasticity, Heteroscedasticity tests, (Spearman coefficient of correlation, Goldfeld-Quand criterion, White criterion), Estimation methods of models with heteroscedasticity

 

  1. TEACHING AND LEARNING ASSESSMENT METHODS
DELIVERING METHOD In classroom
IT USE §  Power point

§  e-class

 

TEACHING ORGANIZATION Activity Semester workload

 

Lectures 39
Laboratory courses 26
Individual study 60
Course total

(25-hour workload per credit unit)

 

125

STUDENT ASSESSMENT

 

Written exams at the end of the semester both on theory and exercises

 

 

  1. PROPOSED LITERATURE
§  Maddala G.S. (2010). Introduction to Econometrics, 4th Edition Wiley-Blackwell, West Sussex, UK.