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Advanced Efficiency and Productivity Analysis

6 LP


#70102 / #2

SS 2016 - SS 2017

Fakultät VII

H 33

Institut für Volkswirtschaftslehre und Wirtschaftsrecht

37311500 FG Volkswirtschaftlehre, insb. Wirtschafts- und Infrastrukturpolitik

Hirschhausen, Christian

Hirschhausen, Christian

POS-Nummer PORD-Nummer Modultitel
130040 28095 Advanced Efficiency and Productivity Analysis

Learning Outcomes

A range of econometric, nonparametric and semiparametric methods has been developed to analyze the productivity and efficiency of various decision making units (firms, industries, municipalities etc.) The aim of this course is to give the students the ability to formulate, estimate and interpret productivity and efficiency analysis models of various types. A key ingredient of the course is the application of these methods to actual data in programming sessions.


Performance measurement is important in various fields of an economy. This course gives an overview of basic and advanced methods for quantitatively evaluating productivity and efficiency of different decision making units. The course will start with a review of production economics. It focuses then on three frontier concepts: 1) Nonparametric efficiency analysis with a special focus on inference in nonparametric methods, partial frontiers, environmental variables and conditional efficiency. 2) Parametric efficiency analysis with production and cost function formulation and estimation, panel data in SFA, testing and inference and 3) Semiparametric efficiency analysis such as stochastic non-smooth envelopment of data (StoNED) and the Fan, Li and Weersink (1996) estimator. Finally the frontier concepts are put in a broader context and related to other productivity measurement concepts. The course focuses on two aspects: in a first part, theoretical background of the nonparametric, semiparametric and econometric methodologies will be discussed. In the second part, the course focuses on applications with firm level -data in various regulated industries such as the energy and water sector. Various case studies are analyzed in the tutorials: the emphasis will be primarily on the practical implementation of the methods with the appropriate software and the interpretation of the empirical results. Data and measurement issues are discussed relating to the collection of data on inputs, outputs and prices for use in efficiency and productivity studies.

Module Components


All Courses are mandatory.

Course Name Type Number Cycle Language SWS
Advanced Efficiency and Productivity Analysis IV 71 150 L 5509 SS English 4

Workload and Credit Points

Advanced Efficiency and Productivity Analysis (IV):

Workload description Multiplier Hours Total
Class attendance 15.0 4.0h 60.0h
Course preparation and follow up 15.0 4.0h 60.0h
Exam preparation 1.0 30.0h 30.0h
Preparation of presentation 1.0 15.0h 15.0h
Problem sets 1.0 15.0h 15.0h
180.0h(~6 LP)
The Workload of the module sums up to 180.0 Hours. Therefore the module contains 6 Credits.

Description of Teaching and Learning Methods

Block scheduling with lectures and tutorials. Additional programming tutorials with Stata and R (introductory course in the beginning of the course – no prerequisite).

Requirements for participation and examination

Desirable prerequisites for participation in the courses

Basic knowledge in microeconomics and microeconometrics, basic knowledge in nonparametric efficiency analysis from the Network and Infrastructure Regulation useful

Mandatory requirements for the module test application

No information

Module completion



Type of exam:

Portfolio examination



Typ of portfolio examination

No information

Test elements

Name Categorie Duration/Extent
Presentation 25 No information
Problem Sets 25 No information
Written Exam 50 No information

Grading scale

No grading scale given

Test description (Module completion)

The portfolio examination consists of the following elements, adding up to a maximum of 100 credits. The grading follows the joint conversion key of the School of Economics and Management (decision of the school's council dated May 28, 2014 - FKR VII-4/8-28.05.2014).

Duration of the Module

This module can be completed in one semester.

Maximum Number of Participants

This module is not limited to a number of students.

Registration Procedures

Please register via e-mail to

Recommended reading, Lecture notes

Lecture notes

Availability:  unavailable

Electronical lecture notes

Availability:  unavailable


Recommended literature
Bogetoft, P. and Otto, L. (2011) Benchmarking with DEA, SFA, and R, Springer.
Chambers, R. (1988) Applied Production Analysis: A Dual Approach, 4. edition, Cambridge University Press, Cambridge, Massachusetts.
Coelli, T., Rao, D., O’Donnell, C. and Battese, G. (2005) An Introduction to Efficiency and Productivity Analysis, 2. edition, Springer.
Fan, Li and Weersink (1996): Semiparametric Estimation of Stochastic Frontier Models. In: Journal of Business & Economic Statistics, Vol. 14 (4), pp. 460-468.
Färe, R., Grosskopf, S. and Lovell, C.A.K. (1994) Production Frontiers, Cambridge University Press, Cambridge.
Greene, W. H. (2007) The Econometric Approach to Efficiency Measurement. In: Fried, H., Lovell, C.A.K. and Schmidt, S., editors, The Measurement of Productive Efficiency. Oxford University Press, Oxford.
Kuosmanen, T. (2012): Stochastic semi-nonparametric frontier estimation of electricity distribution networks: Application of the StoNED method in the Finnish regulatory model. Energy Economics, in press.
Kuosmanen, T., and Kortelainen, M. (2012): Stochastic non-smooth envelopment of data: Semi-parametric frontier estimation subject to shape constraints. Journal of Productivity Analysis Vol. 38 (1), 11-28.
Simar, L. and Wilson, P. (2007) Statistical Inference in Nonparametric Frontier Models: Recent Developments and Perspectives. In: Fried, H., Lovell, C.A.K. and Schmidt, S., editors, The Measurement of Productive Efficiency. Oxford University Press, Oxford.

Module examiner

Prüfungsberechtigte Personen im WS 2019/20: 1

Herr Christian Hirschhausen

Assigned Degree Programs

Zur Zeit wird die Datenstruktur umgestellt. Aus technischen Gründen wird die Verwendung des Moduls während des Umstellungsprozesses in zwei Listen angezeigt.

This module is used in the following modulelists:

Students of other degrees can participate in this module without capacity testing.

This module is used in the following Degree Programs (new System):

    Students of other degrees can participate in this module without capacity testing.


    No information