AØKK08204U Adv. Macroeconometrics
The focus of this course is on likelihood based analysis of the
cointegrated VAR model with an emphasis on applicability,
particularly in the field of macroeconomics and international
finance. Cointegration analysis is a means to uncover, estimate and
test stationary relations among non-stationary variables. The
reason why this is interesting is that such stationary relations
often can be interpreted as equilibrium relations between economic
variables. Within the cointegrated VAR model it is possible to
investigate dynamic interaction and feed-back effects, in
particular how deviations from a steady-state relation affect the
economic system. Furthermore, it is also possible to make inference
on the common driving trends which have generated the
non-stationarity of the data. The reason why this is interesting is
that these common trends can be interpreted in terms of
unanticipated shocks to the variables of the system. In short the
cointegrated VAR model allows us to investigate the economic
reality as a system of pulling forces (the equilibrium correction
forces) and the pushing forces (the common stochastic trends). The
course includes the topics:
(i) Introduction to central concepts: vector autoregressive
processes, error-correction models, non-stationary processes and
cointegration. (ii) Representation of cointegrated processes. (iii)
Estimation and testing in the cointegrated VAR model. (iv)
Identification and estimation of structural econometric models and
common trends models. (iv) Introduction to processes integrated of
order 2.
The aim of this course is to provide the students with a
profound theoretical and practical knowledge of the econometric
analysis of non-stationary time-series using multivariate dynamic
models. At the end of the course students should be able to perform
cointegration analyses based on a given set of data and critically
assess empirical analyses of macroeconomic time series.
The overall goal is that the students - after having completed the
course - should be able to:
- Formulate a vector autoregressive (VAR) model for a given set of
data and test whether it is a congruent representation of the
information in the data.
-Formulate the hypotheses of unit roots and cointegration as
restrictions on the VAR model. Test for the cointegration rank of
the VAR model.
- Explain the role of constants, trend terms, and dummy variables
in the cointegrated VAR model.
- Estimate the parameters of the cointegrated VAR model using
maximum likelihood. Interpret the results in terms of equilibrium
relationships and driving common trends.
- Formulate and test hypotheses on the cointegrating relationships
and the equilibrium adjustments. -Analyze whether the VAR model has
constant parameters.
- Explain when a structure is exact-, under- or overidentified.
- Impose identifying restrictions on the long-run and short-run
structure of the model.
- Impose identifying restrictions on the common trends of the model
and perform a structural VAR analysis.
- Understand the basics of the cointegration model for variables
integrated of order two and perform a nominal-to-real
transformation.
- Apply the theory to perform and interpret an empirical
cointegration analysis.
Main textbooks:
[1] Juselius, K. (2007): The Cointegrated VAR Model: Methodology
and Applications, Oxford University Press.
Additional Material:
[2] Johansen, S. (1996): Likelihood Based Inference in Cointegrated
Vector Autoregressive Models, Oxford University
Press.
2 hours of class for 14 weeks.
- Category
- Hours
- Class Instruction
- 28
- Lectures
- 42
- Preparation
- 161
- Total
- 231
- Credit
- 7,5 ECTS
- Type of assessment
- Written assignmentThe final assessment is a 48 hours individual take-home exam. The exam paper may be written in Danish or English.
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
- Exam period
- Will be updated during the semester
- Re-exam
- Oral with the non-passed take-home assessment handed in again.
Criteria for exam assesment
The Student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.
Course information
- Language
- English
- Course code
- AØKK08204U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 semester
- Placement
- Autumn
- Schedule
- Autumn (week 36-50)
- Continuing and further education
- Price
320 DKK. per ECTS
- Study board
- Department of Economics, Study Council
Contracting department
- Department of Economics
Course responsibles
- Heino Bohn Nielsen (18-7774787d7e3d717e777d3d7d78747b82747d4f74727e7d3d7a843d737a)
Lecturers
Heino Bohn Nielsen