Syllabus

Title
4084 Macro Econometrics
Instructors
ao.Univ.Prof. Dr. Michael Hauser, Mag.Dr. Thomas Url
Contact details
thomas.url@wifo.ac.at, michael.hauser@wu.ac.at
Type
PI SE
Weekly hours
2
Language of instruction
Englisch
Registration
02/06/14 to 02/26/14
Registration via LPIS
Notes to the course
Subject(s) Doctoral/PhD Programs
Advanced Course Research Methods of Social and Economic Sciences
Dates
Day Date Time Room
Monday 03/03/14 05:00 PM - 06:30 PM TC.4.13
Monday 03/10/14 05:00 PM - 06:30 PM D2.0.025 Workstation-Raum
Monday 03/17/14 05:00 PM - 06:30 PM TC.4.13
Monday 03/24/14 05:00 PM - 06:30 PM TC.4.13
Monday 03/31/14 05:00 PM - 06:30 PM TC.4.13
Monday 04/07/14 05:00 PM - 06:30 PM TC.4.13
Monday 04/28/14 05:00 PM - 06:30 PM D2.-1.019 Workstation-Raum
Monday 05/05/14 05:00 PM - 06:30 PM TC.4.13
Monday 05/12/14 05:00 PM - 06:30 PM TC.4.13
Monday 05/19/14 05:00 PM - 06:30 PM TC.4.13
Monday 05/26/14 05:00 PM - 06:30 PM TC.4.13
Monday 06/02/14 05:30 PM - 07:00 PM D2.-1.019 Workstation-Raum
Monday 06/16/14 05:00 PM - 06:30 PM TC.4.13
Monday 06/23/14 05:00 PM - 06:30 PM TC.4.13

On this page:

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Contents
  • Univariate time series procedures for seasonal adjustent.
  • Methods for extracting cyclical componentsDetection of outliers, calender effects.
  • Autoregressive moving average models: modeling, estimation, forecasting Overview of macroeconometric modelingVector autoregressive models.
  • Bayesian Vector Autoregression Models.
  • Forecasting with Large Scale Macroeconometric Models: US and Austria.
  • Specification and solving Dynamic General Equilibrium Models.
  • Modeling and forecasting with New Keynesian Real Business Cycle Models.
  • Modeling and forecasting with Vector Cointegrated Autoregressive Models (A Long-run Structural Model of the UK).

Articles, book chapters, data, and software are provided.

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Learning outcomes

The students will be able to give an overview of and evaluate the different statistical and econometric techniques used for current macroeconomic modeling as summarized largely e.g. in Diebold(1998), Journal of Economic Perspectives. Among others, we will discuss the conceptual differences of DSGE and CVAR approaches.

The students will also be able to apply most of the methods by means of provided software to some data sets.

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Teaching/learning method(s)
The course will be held in English if at least one only English speaking student participates, otherwise it will be held in German. Students have to prepare presentations of some book chapters and/or papers, present and discuss the methods and/or models. Software and/or the models themselves including data and equations are partly provided. Reestimation, simulations and forecasting are then possible.
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Assessment
Both the presentations as well as a written paper (15 to 20 pages) are evaluated.
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Prerequisites for participation and waiting lists
Sound knowledge of basic econometrics and intermediate macroeconomics.
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Availability of lecturer(s)
For more information write to either michael.hauser@wu.ac.at or thomas.url@wu.ac.at or call 01 31336 4759, or see http://statmath.wu.ac.at/~hauser/
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Unit details
Unit Date Contents
1

Discussion of organizational issues: Short presentation of the themes of the course.

Students choose their topics for the presentations. Making the schedule for the course.
Last edited: 2013-10-28



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