2016/2017 KAN-CCMVV2401U Econometric Analysis of Firm Data
English Title | |
Econometric Analysis of Firm Data |
Course information |
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Language | English |
Course ECTS | 7.5 ECTS |
Type | Elective |
Level | Full Degree Master |
Duration | One Semester |
Start time of the course | Autumn |
Timetable | Course schedule will be posted at calendar.cbs.dk |
Max. participants | 80 |
Study board |
Study Board for MSc in Economics and Business
Administration
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Course coordinator | |
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Kontaktinformation: https://e-campus.dk/studium/kontakt eller Contact information: https://e-campus.dk/studium/kontakt | |
Main academic disciplines | |
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Last updated on 18-02-2016 |
Learning objectives | |||||||||||||||||||||||||
To achieve the grade 12, students
should meet the following learning objectives with no or only minor
mistakes or errors: After completing this course, the students
should be able to:
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Course prerequisites | |||||||||||||||||||||||||
The course is a progressive course, i.e. it presupposes that the students possess a thorough knowledge of "Applied Econometrics" corresponding to what has been taught during the 1 year of cand.merc.eba AEF concentration. Knowledge of the linear regression model and its estimation by ordinary least squares (OLS) is required. | |||||||||||||||||||||||||
Examination | |||||||||||||||||||||||||
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Course content and structure | |||||||||||||||||||||||||
With advances in computer technology, electronic systems have replaced paper files to a large extent in most firms. A wealth of data is being produced in operations by all sorts of business units. This includes internal pay roll and personal records in Human Resources and Finance, production data on the amount of in- and output of machines and customer data, including prices and quantity sold. All these data have in common that they are typically large enough in terms of number of observations and number of variables to conduct multivariate statistical analysis. While these data are increasingly available as a side product of operations, their use in firms is often limited because of a lack of quantitative data analytics skills. As a matter of fact the demand of leading international firms for graduates with profound skills in quantitative methods normally exceeds the supply. The goal of this course is to provide students with skills to analyse these data by means of modern econometric techniques. Thus, it will enable them to use these data in practise in order to move towards evidence based decision making within firms. An integral component of the course is therefore hands-on practical work with statistical software and effective presentation of statistical results to a general audience without background in quantitative methods. However, the main goal of the course is to provide a deeper understanding of the underlying econometrics using important subject content topics as motivating examples. These may include:
The course will first deepen the understanding of estimation of the linear regression model by Ordinary Least Squares. It will then cover methods which can be used if the key variables of interest are not exogenous, such as instrumental variable techniques or panel data techniques. This is followed by extending the linear model to a model with a limited dependent variable, which is estimated by Maximum Likelihood. It may also cover topics such as decomposition techniques or estimation of systems of equations. The course will use the statistical software STATA. By doing the course a student will
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Teaching methods | |||||||||||||||||||||||||
The course is composed of 12 two-hour lectures and 6 computer classes with one introductory computer class. The following classes will cover each one problem set with hands-on practical work on the computer. | |||||||||||||||||||||||||
Student workload | |||||||||||||||||||||||||
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Expected literature | |||||||||||||||||||||||||
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