Course Information
FacultyEconomic and Political Sciences
Cycle / Level2nd / Postgraduate
Teaching PeriodWinter
CoordinatorIoannis Kyritsis
Course ID600012685

Class Information
Academic Year2017 – 2018
Class PeriodWinter
Faculty Instructors
Weekly Hours3
Class ID
Digital Course Content
Language of Instruction
  • Greek (Instruction, Examination)
Learning Outcomes
1: Frontier estimation & Efficiency Analysis 2:Dynamic Programming 3: Introduction to Discrete Choice Models
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Make decisions
  • Work autonomously
  • Work in teams
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.
Efficiency Analysis ; Dynamic Programming ; to Discrete Choice Models
Educational Material Types
  • Notes
  • Slide presentations
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
Part 1 :Power Point, MS Excel Part 3 :SPSS
Course Organization
Laboratory Work120.4
Reading Assigment1404.7
Interactive Teaching in Information Center10.0
Student Assessment
Part 1 :The final grade will be based on the projects. Part 2 :One final written exam (100%) Part 3 :One final written exam (100%)
Student Assessment methods
  • Written Exam with Extended Answer Questions (Summative)
  • Written Exam with Problem Solving (Summative)
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