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Learning Objectives
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The skills developed are valuable and necessary for handling of data and understanding empirical results related to most of the other courses of the concentration.
After this course it is the aim that the students can:
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Demonstrate knowledge of the concepts, models, methods and tools of econometrics as discussed during the course (when to apply what and why).
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Perform a fairly simple econometric analysis in practice:
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1) Identify the problem and phrase the purpose of the analysis.
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2) Formulate the theoretical background for solving the problem.
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3) Specify a suitable econometric model including the assumptions of the model.
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4) Estimate the model using an appropriate method.
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5) Discuss and solve any important problems encountered in relation to the analysis (e.g. heteroscedasticity for a cross-sectional data set).
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6) Perform hypotheses testing of both simple and more composite hypotheses.
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7) Apply the model for the purpose it was constructed for (e.g. testing a theory or making forecasts).
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8) Report the results of the analysis both if the reader of the report is an econometrician and if the reader is a non-econometrician (e.g. the CEO).
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9) Conclude upon the analysis.
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Evaluate an empirical study conducted by another person/researcher and read and interprete output from the SAS computer programme.
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Examination
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Applied Econometrics
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Applied Econometrics:
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Assessment
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Written Exam
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Marking Scale
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7-step scale
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Censorship
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No censorship
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Exam Period
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December/January and February
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Aids
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Please, see the detailed regulations below
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Duration
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4 Hours
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The exam has the form of an individual 4-hour written, open book exam (all written materials and calculators, but no computers, are allowed at the exam) with a preparatory data analysis starting three days before the exam date. The 4-hour written regular exam takes place in November. Make-up /re-exam takes place in January. Case for the data analyses will be handed out three days before the exam date |
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Course Content
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Some of the main tools of econometrics that are standard when analyzing data from fields such as industrial organization, economics and finance at the graduate level are introduced. Emphasis will be on analysis of economic data by means of statistical models, i.e. regression models and time series models. Some relevant software will be used in handling data introduced for computer based exercises and illustrations. Integration with the other courses at the line will take place via the selection of material for illustrations and exercises.
Some of the topics covered are:
The simple and multiple regression models and their interpretation.
Basic time series models (ARIMA), identification, estimation, testing and forecasting
Time series econometrics. More advanced topics (e.g. ARCH) only at the introductory level. |
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Teaching Methods
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Lectures with PC-based exercises.
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Literature
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Preliminary literature.
Gujarati, D.N. (2003). Basic Econometrics, 5th ed. McGraw-Hill (or latest edition on the market, please check the Syllabus) |
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