University of Bergamo
Managerial Economics
Course Syllabus 2014
Faculty’s Tutor: Andrea Salanti
Email: andrea.salanti@unibg.it
The Course is divided in three parts: (1) Empirical applications in Managerial Economics (Instructor Prof.
Francesco Moscone), (2) Productivity Management (Instructor Prof. Nicole Adler), (3) Economics and
Business studies (Instructor Prof. Andrea Salanti).
(1) Empirical applications in Managerial Economics
Instructor: Francesco Moscone, Professor of Business Economics, Business School, Brunel University,
London, UK
Email: francesco.moscone@brunel.ac.uk
Texts:
• An Introduction to Econometrics, by Gary Koop, Wiley (GK)
• Managerial Economics, 6th ed., by Paul Keat, Philip K. Young, Prentice Hall (ME)
See also: Managerial Economics, Applications, Strategy and Tactics, 12th Edition. McGuigan, Moyer and Harris,
Thompson, Southwestern Press.
Description:
In this course we analyse qualitative and quantitative information using a variety of tools and techniques
statistically, econometrically, and heuristically based. The idea is to prepare students to be able to critically
analyse business and economic data, and make informed business decisions, ultimately enhancing their
employability and competitiveness in the labour market. More in detail, in this course we use microeconomic
theory, and various applied tools, particularly quantitative techniques that are used in modern managerial
decision-making. Thus, the student should revise before and during the course microeconomic theory, basic
calculus, statistics, and elementary econometrics. The main aim is to provide the students a basic problem
solving skill that is used in modern managerial decision making. In an environment where also SMEs tend to
go global, CEOs and managers, need to constantly update and upgrade their tools of analysis in order to
better tackle business the uncretenity across different dimensions . Indeed, economic and business decisions
that were profitable a few years ago may not be so in this new hisorical moment. New decision making
theory, mehtods and tools need to be applied.
Method:
Both graphical and mathematical methods, especially statistical techniques (descriptive statistics and
inferential statistics) will be used. The student will learn how to chose and adopt methods and techniques to
estimate the demand function, tackle business and economic forecasting, and estimate the production
function and costs function. Theory will be supported via spreadsheet like Excel and software like STATA,
with applications to industry and management evaluation.
Prerequisite:
Students are expected to have some basic knowledge of algebra, calculus, and some statistics.
Course Content/Outline:
March, 31, 2014:
• Supply and demand (Ch. 4, 6 of ME)
• Non-technical introduction to regression analysis (Ch. 1-2 of GK)
1 April, 07, 2014:
• The econometrics of the simple regression analysis (Ch. 3 of GK)
• Estimating the demand for healthcare (please see Newhouse, J. P. (1977). Medical care
expenditure: A cross-national survey. Journal of Human Resources 12, 115-125)
• Investigating the production of health (please see Skinner, J. S. and Staiger D. (2005)
Technology Adoption from Hybrid Corn to Beta Blockers, NBER Working Paper No. W1125)
April, 14, 2014:
• The econometrics of the multiple regression analysis (Ch. 4 of GK)
• An application to the real estate market
• The multiple regression model, freeing up the classical assumptions (Ch. 5 of GK): theory
and applications
April, 28, 2014:
•
•
•
•
Time series models (Ch. 6 of GK): theory and applications
Forecasting techniques (Ch. 5 of ME)
Regression with time series variables (Ch. 7 of GK)
Revision of the material covered in the course.
Grading: Students will prepare a project. The project is worth 50% of the overall mark of the course. The maximum number of words to be written is 2000. The project must be structured (title, abstract, introduction, literature review, business/economic framework, exploratory data analysis, empirical model, conclusion, references, and appendix – when appropriate). The student, when performing the statistical analysis, must use a log file in Stata that will have to be sent by 30th August 2014, along with the project, to the email address Francesco.Moscone@brunel.ac.uk. The topic of the project, and all information related to the data set (where to download it, etc.) will be provided on the last lecture to be held on the 28th April 2014. (2) Productivity management
Instructor: Nicole Adler, Professor of Operation Management, School of Business Administration, Hebrew
University of Jerusalem
Email: msnic@huji.ac.il
Description:
Benchmarking, productivity analysis and performance measurement can be used to improve an
organization's products and processes. The practice of benchmarking - the global search for industry's
best practices - is becoming widespread even though it suffers from a lack of support tools and
methodologies. Robust frontier estimation techniques will be presented within the framework of process
improvement to provide economic and mathematical underpinnings for benchmarking. Analytical models
will be developed for reasonable identification of best-practice units from within a group and metrics
for evaluating both the degree of leadership of these best-practice units and the degree of
inefficiency of under-performing units. This quantitative approach has proven to yield exceptional insight
and substantial results in practice both in the public and private sectors.
Objective: To understand the problems inherent in performance measurement and master several
state-of-the-art techniques and their use in quality management and continuous improvement.
Grading: The final grade in the course will be determined by a written exam where there will be an open
question covering the contents. I twill account for 35% of the final grade.
Subject
Chapter
Date
2 Introduction
Introduction to benchmarking productivity
1
10/4
2, 3
10/4
Deterministic Frontier Analysis
7
10/4
Stochastic Frontier Analysis
7
10/4
Stochastic Distance Functions
8
15/4
Panel Data
8
15/4
Efficiency measures, production models & technology
Stochastic
Frontier
Analysis
Applications
15/4
Airport Case Study
Mergers, Regulation and Efficiency Measurement
9, 10
15/4
Course Textbook:
Benchmarking with DEA, SFA, and R., by Bogetoft, Peter, Otto, Lars
Published
Springer, New York, 2010.
Additional Relevant Literature:
An Introduction to Efficiency and Productivity Analysis, by Coelli T, Prasada Rao DS, Battese G.
Published
Kluwer Academic Publishers, New York, 2005.
Performance Benchmarking: Measuring and Managing Performance., by Bogetoft, Peter
Springer, New York, 2012.
Published
Measuring and Managing Performance
., by Coelli, Prasada-Rao, O’Donnel, Battese
Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References, and DEASolver Software (Second Edition), by W. W. Cooper, Lawrence M. Seiford and Kaoru Tone,
Springer, New York, 2006.
Published
Handbook on data envelopment analysis / edited by William W. Cooper, Lawrence M. Seiford, Joe
Zhu.
Boston : Kluwer Academic, c2004.
Published
Introduction to the theory and application of data envelopment analysis: a foundation text with
integrated software / by Emmanuel Thanassoulis.
Published
Norwell, Mass: Kluwer Academic Publishers, 2001.
Data envelopment analysis: theory, methodology, and application / [edited by] Abraham Charnes ...
[et al.].
Published
Boston : Kluwer Academic, 1994.
Modeling data irregularities and structural complexities in data envelopment analysis / [edited by]
Joe Zhu, Wade D. Cook.
Published
New York: Springer, 2007.
3 (3) Rigor vs. Relevance in Economics and Business Studies
Instructor: Andrea Salanti, Professor of Economics, Università degli Studi di Bergamo
Room 404, C building - Dalmine
Email: andrea.salanti@unibg.it
Objective: To present the main features of the above referred debate and encourage students to elaborate
some personal reflections on this issue, to be condensed in a short paper (max. 1500 words).
Grading: The short paper will account for 15% of the final grade.
1st meeting (May 6, 2014 – 9.00-13.00): Introductory lecture on the methodology of economics.
Relevant Literature: slides to be circulated
2nd meeting (May 13, 2014 – 9.00-12.00): Seminar on Rigor vs. Relevance in Economics
Relevant Literature:
§
§
§
Gordon, R. A. (1976), “Rigor and Relevance in a Changing Institutional Setting”. American Economic
Review, 66 (1), 1-14.
Blaug, M. (2009), “The Trade-Off between Rigor and Relevance: Sraffian Economics as a Case in
Point”. History of Political Economy, 41 (2), 219-247.
Salanti, A. (2014), “Rigor Vs. Relevance in Economic Theory: A Plea for a Different Methodological
Perspective”. History of Political Economy, 46(1), 149-166.
Timetable
3rd meeting (May 276, 2014 – 9.00-12.00): Seminar on Rigor vs. Relevance in Business Studies.
Relevant Literature:
§
§
§
§
§
Eisenhardt K.M. (1989), “Building theories from case study research”. Academy of Management
Review, 14 (4), 532-550.
Numagami T. (1998), “The infeasibility of invariant laws in management studies: A reflective
dialogue in defense of case studies”. Organization Science, 9 (1), 1-15.
Scandura T.A. and E.A. Williams (2000), “Research methodology in management: Current practices,
trends, and implications for future research”. Academy of Management Journal, 43(6), 1248-1264.
Eisenhardt K.M. and M.E. Graeber (2007), “Theory building from cases: Opportunities and
challenges”. Academy of Management Journal, 50 (1), 25–32.
Gibbert M., W. Ruigrock and B. Wicki (2008), “What passes as a rigorous case study?”. Strategic
Management Journal, 29 (13), 1465–1474.
Exams
June, 17th 2014, July, 4th, September, 5th, always at 1430.
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