Course Coordinator: Professor Peter Bogetoft, Department of Economics (ECON)

Faculty
Professor Peter Bogetoft
Department of Economics, CBS

Prerequisites
A basic knowledge of quantitative methods and statistics is required; however, the course will revisit and refresh participants’ prior knowledge as needed. The focus will be on practical applications in research and consultancy, with training in the use of open-source software such as R. Participants are expected to bring their own laptops to fully benefit from the hands-on activities.

Aim of the Course
The aim of this course is to introduce the participants to the theory and practice of performance evaluations and their usages in research, policy analyses, incentive schemes and regulation.

Specifically, the objectives are
1. To provide a basic understanding of state-of-the-art benchmarking, efficiency, and productivity analysis methods using Data Envelopment Analysis (DEA), Stochastic Frontier Analysis (SFA), and related approaches.

2. To offer training in the practical application of these methods and associated software across various use cases.

3. To discuss the use of performance evaluations for assessing economic systems and designing decision support tools, reallocation mechanisms, and incentive systems.

Background:
Productivity and efficiency analysis is a rapidly growing interdisciplinary field that spans economics, management sciences, and statistics. Beyond conducting empirical research on the magnitude, direction, and sources of productivity growth, this field has developed quantitative methods such as Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA). These methods, once primarily applied to production settings, have now expanded to a wide range of applications, including environmental studies, development research, education, finance, healthcare, natural resource management, public economics, and sports, among others. 

The tools and approaches of productivity analysis are equally suited for micro-level studies of firms and decision-making units, as well as macro-level cross-country and longitudinal comparisons. Furthermore, their integration with incentive theory, mechanism design, and decision support systems enhances their relevance for normative applications.

Preliminary Lecture Plan
Monday
D1 1. Course Introduction
D1 2. Introduction to Benchmarking - From Academic Studies to Managerial Advice
D1 3. Regulatory Benchmarking
D1 4. Efficiency Concepts
D1 5. Getting started with R

In addition, there will be four two-hour Zoom events following the in-class course, during which we will discuss challenging topics, explore new methods, and provide participants with the opportunity to present work-in-progress on efficiency and productivity projects.

Lecture Plan
A preliminary plan is provided above. Some adjustments and the inclusion of specific applications will be determined, in part, based on the interests of the participants.

Assessment
A course certificate for the course is granted based on attendance and active participation.

Course Literature
The course will draw of original literature (articles) supplemented by text-book treatments like in

• Bogetoft, P. and L. Otto, Benchmarking with DEA, SFA, and R, Springer New York, 2011
• Bogetoft, P, Performance Benchmarking: Measuring and Managing Performance, Springer New York 2012