Applied Quantitative Methods – Introduction to Basic Econometric Techniques (November 2009)

Faculty
Keld Laursen, Professor, Department of Innovation and Organizational Economics, CBS; Toke Reichstein, Associate Professor, Department of Innovation and Organizational Economics, CBS; Francesco Rullani, Assistant Professor, Department of Innovation and Organizational Economics, CBS; Larissa Rabbiosi, Assistant Professor, Center for Strategic Management and Globalization, CBS

Course Coordinator
Keld Laursen, Professor, Department of Innovation and Organizational Economics, CBS

Prerequisite
The course requires that the students have very basic qualifications in statistics. We only assume the students know how to calculate mean values and standard deviations and how to interpret these. Knowledge of any particular programming language or estimation procedures is not required.
Aim of the course

The overall aim of the course is to provide basic econometric analytical tools to PhD students with limited prior econometric experience. Student will learn how to find and quantify economic relationships as well as basic econometrics models with focus on linear regression models (OLS). Subsequent attending this course, the student should feel substantially better equipped to tackle econometric challenges and to discuss and comment on econometric work of others.

The course's development of personal competences

The course teaches the students:

How to obtain basic descriptive statistics, use them for data inspection, understand their values, and which and how to report these in an article.
How to distinguish between different types of variables and what implications this classification has for further statistical analysis.
To evaluate the sampling and the representativeness of a dataset.
How to carry out an Ordinary Least Square (OLS) regression and what to be careful about when applying this particular type of regression technique to a dataset
To know what options they have when having categorical explanatory variables or when the theoretical framework argues a relationship to be non-linear.
How to calculate and interpret moderation effects
What a latent variable is, how to create them using factor analysis, and why they are useful.

Lecture plan

Time/period	Faculty	Title
25 November		Welcome – details of the course
		What to report in Academic Papers
		Types of data and data variables
		Standard Descriptive Statistics
		Means, Standard Deviations, Distributions
		Mean comparisons and chi-square tests
		Sampling and data representativeness
26 November		Ordinary Least Squares
		Hypothesis testing
		Specification test, multicollinearity, heteroscedasticity, normality, structural stability
		Efficiency and Consistency
		Dummy Variables in OLS (constants and slopes)
		Tobit Estimations
27 November		Non-linear Functional Forms with OLS
		Moderation effects
		Predictions and size effects
		Factor analysis and latent constructs
		Training the learnt methods through practice

Teaching methods

Lectures, discussion and exercise.

The course employs STATA throughout the sessions furnishing students with examples and assignments for illustration. The methods taught will hence be displayed and demonstrated in STATA. Participants can bring own laptops with STATA installed and use these throughout the course. However, there will be desktop computers with STATA installed available. We encourage students to bring a memory stick or external hard drive so that they can work directly on these and bring all files used and programs written with them home after the course.

Course literature

Students attending the course will receive a more detailed recommended reading list assisting them in preparing for the course and pointing to readings that may prove helpful as a follow up after attending a session.

Recommended literature

Wooldridge, J. M. (2006), “Introductory Econometrics – A Modern Approach”, 3rd edition, Thomson South-Western, International Edition.
Hamilton, L. C. (2006), “Statistics with Stata”, Brooks/Cole, Belmont, CA.

Enrolment

Applications should be sent to:

The Doctoral School in Economics and Management, Copenhagen Business School
Attn: Shi Hua Chen Kold
Department of Innovation and Organizational Economics
Kilevej 15, 3rd. floor
2000 Frederiksberg
Denmark

E-mail: shc.ino@cbs.dk

Other

Location:

Copenhagen Business School
Address/room: Solbjerg Plads 3, room SP108

Fee:

525 Euro

Not to be paid by PhD students enroled at a Danish University

Sidst opdateret af Kristine Olsen 27.10.2009