QUANTITATIVE METHODS

Course Information
TitleΠΟΣΟΤΙΚΕΣ ΜΕΘΟΔΟΙ / QUANTITATIVE METHODS
CodeΔΟ15
FacultySocial and Economic Sciences
SchoolEconomics
Cycle / Level2nd / Postgraduate
Teaching PeriodWinter
CoordinatorAthanasios Tsadiras
CommonNo
StatusActive
Course ID100001216

Programme of Study: PPS Administration and Economy (2013-today)

Registered students: 9
OrientationAttendance TypeSemesterYearECTS
Economic and Regional DevelopmentElective Courses116
International and European EconomicsElective Courses116

Class Information
Academic Year2016 – 2017
Class PeriodWinter
Faculty Instructors
Weekly Hours3
Class ID
600060837
Course Type 2016-2020
  • General Knowledge
  • Scientific Area
  • Skills Development
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
Digital Course Content
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Instruction)
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Work in teams
  • Generate new research ideas
  • Design and manage projects
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Part 1: Frontier estimation & Efficiency Analysis Frontiers' estimation (production, cost, profit) - Short introduction to alternative parametric and nonparametric methods - Measurement and estimation of the efficiency of business units - emphasis on Data Envelopment Analysis (DEA) - nonparametric method Part 2:Dynamic Programming Introduction. Basic characteristics of dynamic programming problems. Bellman's optimization principle. Deterministic and stochastic dynamic programming models. Dynamic programming algorithm. Applications. Part 3: Introduction to Discrete Choice Models Introduction. Assumptions, data and stochastic utility. Logit and Probit models for binary choice. Model estimation. Marginal effects, elasticities and economic valuation of choice attributes. Interpretation of model coefficients. Statistical inference, goodness of fit tests, prediction of individual behaviour, model selection, demand and policy analysis. Examples with SPSS, using data from choice experiments.
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
Description
Part 1: Power Point, MS Excel. Part 3: Powerpoint, SPSS.
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures23
Laboratory Work16
Total39
Student Assessment
Description
Part 1: Frontier estimation & Efficiency Analysis: team assignments Part 2: Written exam Part 3: Written exam
Student Assessment methods
  • Written Exam with Short Answer Questions (Summative)
  • Written Assignment (Summative)
Bibliography
Additional bibliography for study
Ενότητα 1: Frontier estimation & Efficiency Analysis - Ray, Subhash (2004) Data Envelopment Analysis, Cambridge University Press, Cambridge Προαιρετικά: Cooper, W.W., L.M. Seiford and Joe Zhu (2004) “Data Envelopment Analysis” in W.W. Cooper, L. M. Seiford, and J. Zhu, eds. Handbook on Data Envelopment Analysis, Kluwer Academic Publishers, Boston, 2004, chapter 1 Kerstens. K. and D. Prior (2006) Productivity and Efficiency Analysis Software http://selene.uab.es/dep-economia-empresa/codi/docs_efficiency_2005_06/SOFTWARE%20ON%20PRODUCTIVITY%20AND%20EFFICIENCY%20ANALYSIS.pdf Kumbhakar, Subal C, and C.A. Knox Lovell (2000) Stochastic Frontier Analysis, Cambridge University Press, Cambridge Zhu, J http://www.deafrontier.com/ Ενότητα 2: Richard Bellman (2010)Dynamic Programming. Princeton University Press Martin L. Puterman (2005) Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley Series Ενότητα 3: Train, K. (2009).Discrete Choice Methods with Simulation (2nd Edition). Cambridge University Press. Available at http://elsa.berkeley.edu/books/choice2.html Greene, W. Η. (2011). Econometric Analysis. 7th Edition, Prentice Hall. Chapters 17-18 (Models for Discrete Choice).
Last Update
19-08-2013