ECONOMETRICS II

Course Information
TitleΟΙΚΟΝΟΜΕΤΡΙΑ ΙΙ / ECONOMETRICS II
Code03ΥΔ03
FacultySocial and Economic Sciences
SchoolEconomics
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
CoordinatorKonstantinos Katrakylidis
CommonNo
StatusActive
Course ID100000862

Class Information
Academic Year2018 – 2019
Class PeriodSpring
Faculty Instructors
Instructors from Other Categories
Weekly Hours4
Class ID
600123470
Course Type 2016-2020
  • Background
Course Type 2011-2015
General Foundation
Mode of Delivery
  • Face to face
Digital Course Content
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Make decisions
  • Work in an international context
  • Work in an interdisciplinary team
  • Generate new research ideas
  • Design and manage projects
Course Content (Syllabus)
Special estimation methods. The ordinary least square method with restrictions and the filter method. The violation of the basic hypothesis. Non linear models. Multicollinearity: ways of finding and confronting. Heteroskedasticity: criteria to detect. Autocorrelation: Test to detect first-order autocorrelation and methods to face it. Tests for special cases. Wallis, Bresch-Godfrey and ARCH tests. Stochastic explanatory variables. The method of auxiliary variables. Model of distributed time lags. Combination of a number of linear regressions. The SUR method. Systems of interdepend linear regressions. Two-stage least square method. The application of least squares, under specific restrictions. Three-stage least squares and the maximum likelihood test. Generally about dynamic systems. Basic principles of optimal control and applications in economic programming. Stationarity tests. The unit-root subject. The Dickey-Fuller and Phillips-Peron tests. Cointegration and relative tests. Error Correction models. Cranger Causality. Vector Autoregressive models (VAR). Estimating the cointegrating vectors with the maximum likelihood method. Discussion of specialized subjects of economics.
Educational Material Types
  • Notes
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures52
Laboratory Work20
Project
Total72
Student Assessment
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Summative)
  • Written Exam with Short Answer Questions (Summative)
  • Written Exam with Problem Solving (Summative)
  • Labortatory Assignment (Summative)
Last Update
24-09-2013