AØKA08007U Econometrics C
Volume 2013/2014
Education
BSc in Economics - compulsory
MSc in Economics
MSc in Economics
Content
Econometrics C is the
final course in the compulsory BSc. course sequence in statistics
and econometrics. The course Econometrics B focuses on linear
regression and instrumental variables estimation of the linear
regression model for cross‐sectional data. The current course goes
into more details with the estimation principles and presents the
generalized method of moments and the likelihood analysis.
Econometrics C also discusses dependent observations and gives a
detailed account of the econometric analysis of time series data.
As an integral part of the course, students are introduced to
statistical tools for analysing time series and panel
data.
Learning Outcome
Give an account for the
motivation and intuition for different principles for estimation
and inference ‐ specifically the method of ordinary least squares
(OLS), method of moments (MM), and maximum likelihood (ML) ‐ and
discuss relative advantages and drawbacks. ∙ Give an account for
the sufficient conditions for consistent estimation and valid
inference and apply the estimation principles to derive MM and ML
estimators in statistical models. ∙ Give an account for the
important differences between (independent) cross‐sectional data,
analyzed in detail in Econometrics B, and time series data.
Precisely describe the conditions under which the results from the
linear regression analysis for cross‐sectional data can be used
also on time series data. ∙ Explain the consequences of unit roots
in economic data and interpret statistical models for stationary
and non‐stationary time series. Construct and interpret statistical
tests for unit roots in economic time series. ∙ Interpret
statistical models based on cointegration and error correction and
perform empirical analyses based on these ideas. ∙ Give an account
for autoregressive conditional heteroscedasticity (ARCH) in
financial time series, and perform empirical ARCH analyses. ∙ Give
an account for models involving both a cross‐sectional dimension
and a time dimension (panel data) and perform empirical analyses
based on these models. ∙ Choose the relevant tools for a given
problem and apply the tools to new problems and new data sets. More
specifically to identify the characteristic properties of a given
data set, suggest and construct relevant statistical models,
analyze to what extend the statistical model is congruent with the
38 data, estimate and interpret the parameters of the model,
formulate economic questions as hypotheses on the parameters of the
model, and test these hypotheses. ∙ Use statistic and econometric
software. Give statistically sound and economically relevant
interpretations of statistical results. ∙ Use statistic and
econometric terms in a correct way and be able to present
econometric results in a clear and concise way.
Literature
Syllabus:
- Textbook: Marno Verbeek: A Guide to Modern Econometrics, 4th Ed., Wiley.
- Chapter 1-3 (cursory reading) p. 1-93 (93*)
- Section 4.1-4.5 (cursory reading) 94-112 (18*)
- Section 4.6-4.11: p. 112-136 (25)
- Chapter 5-6 p. 137-205 (69)
- Section 7.1.1-7.1.6 p. 206-217 (12)
- Section 7.3 p. 231-238 (8)
- Chapter 8 p. 278-337 (59)
- Section 9.1-9.3 p. 338-350 (13)
- Section 9.4-9.7 (cursory reading) p. 350-371 (22*)
- Section 10.1-10.2.4 p. 372-387 (15)
- Section 10.3 p. 394-396 (3)
Lecture notes:
- [1] Introduction to Time Series (13)
- [2] Linear Regression with Time Series Data (22)
- [3] Introduction to Vector and Matrix Differentiation (cursory reading) (6*)
- [4] Dynamic Models for Stationary Time Series (28)
- [5] Non-Stationary Time Series and Unit Root Testing (21)
- [6] Cointegration and Common Trends (31)
- [7] Modeling Volatility in Financial Time Series: An introduction to ARCH (16)
- [8] Generalized Method of Moments Estimation (31)
Location:
Check the location of the lecturing and classes at
the
locationplan for the spring semester.
Academic qualifications
Econometrics A and
B
Teaching and learning methods
4 hours of lecturing and 2
hours of excercises per week for 14 weeks
Various software packages will be introduced and applied
Various software packages will be introduced and applied
Workload
- Category
- Hours
- Class Exercises
- 28
- Exam
- 1
- Lectures
- 56
- Preparation
- 121
- Total
- 206
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Exam (Oral)
- Credit
- 7,5 ECTS
- Type of assessment
- Oral examination, 25 minutes under invigilationOral examination with preparation
- Exam registration requirements
- As a part of the course, three written assignments should be completed and accepted.
- Aid
- Written aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
100 % external censorship
- Exam period
- Will be published before the start of the semester
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
- AØKA08007U
- Credit
- 7,5 ECTS
- Level
- BachelorFull Degree Master
- Duration
- 1 semester
- Placement
- Autumn And Spring
- Schedule
- Autumn (week 36-50)
Spring (week 6-21) - Course capacity
- No limits
- 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 (18-6c696d72733266736c7232726d69707769724469677372326f7932686f)
- Rémi Piatek (11-7568706c31736c6477686e4368667271316e7831676e)
Lecturers
Autumn 2013:
Teacher: Rémi Piatek og Heino Bohn Nielsen
Classteachers:
Hold 1 Jeppe Madsen
Hold 2 Jeppe Madsen
Hold 3 Rasmus Bjerre
Hold 4 Sigrid Koob
Hold 5 Martin Oksbjerg
Spring 2014:
Teacher: Rémi Piatek
Classteachers:
Class 1: Philipp Kless
Hold 2: Jeppe Madsen
Hold 3: Rasmus Bjerre
Hold 4: Jesper Schultz Petersen
hold 5: Jeppe Madsen
Saved on the
24-01-2014