Course Description
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Course Name
Empirical Marketing
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Host University
Vrije Universiteit Amsterdam
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Location
Amsterdam, The Netherlands
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Area of Study
Marketing
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Language Level
Taught In English
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ECTS Credits
6 -
Recommended U.S. Semester Credits3
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Recommended U.S. Quarter Units4
Hours & Credits
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Overview
COURSE OBJECTIVE
The objective is to show how econometrics can be applied to empirical questions in marketing and consumer behaviour. In particular, how to build models to support marketing decisions. Given the current big data revolution, models from which useful information about market behaviour and their sensitivity to marketing activities such as advertising, pricing, promotions and distribution are routinely used by managers (from leading organisations worldwide) for analyzing marketing programs that can improve brand performance. This course will introduce models and methods, together with their use in empirical marketing studies.COURSE CONTENT
This course focusses on quantitative methods for empirical research in marketing and consumer behaviour. In particular, we discuss how to build models to support marketing decisions and how to adopt data science methods to investigate market behaviour and the impact of marketing instruments such as advertising, pricing, promotions and distribution. The econometric methods that are employed include regression, multivariate statistical analysis, limited dependent variable models, panel data models, pooled regressions, forecasting methods, and trend extraction.TEACHING METHODS
Lectures and classes. During classes time will be made for discussing exercises and for supporting empirical work. Computer classes are also organisedTYPE OF ASSESSMENT
Final exam – Individual assessmentsENTRY REQUIREMENTS
None, but an introductory course in econometrics is highly recommended, see below.RECOMMENDED BACKGROUND KNOWLEDGE
Introductory courses in econometrics and time series, similar to the courses "Introduction to Econometrics" and "Introduction to Time Series" from our Minor program "Applied Econometrics: A Big Data Experience For All".
Course Disclaimer
Courses and course hours of instruction are subject to change.
Some courses may require additional fees.