Ch00 Syllabus
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Time Series Analysis
Christian Kleiber
Universitat Basel
HS 2011
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Instructor
Christian KleiberWWZ, Quantitative Methods Unit
Universitat BaselE-mail: [email protected]: http://wwz.unibas.ch/kleiber
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mailto:[email protected]://wwz.unibas.ch/kleiberhttp://wwz.unibas.ch/kleibermailto:[email protected] -
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Overview
Introduction
Smoothing and decomposition methods
Stationary stochastic processes
ARIMA models
Nonstationarity: Unit roots and cointegration (some of)
Time series regression and structural change (if time permits)
GARCH models
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Time series decomposition
7.0
7.4
7.8
observe
d
7.2
7.4
7.6
trend
0.1
0.1
season
0.1
5
0.0
0
0.1
5
1970 1975 1980 1985
remaind
er
Time
UK driver deaths (in logs)
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ARIMA modelsConsumption of NonDurables in the UK
Time
log(Consum
ption)
1955 1960 1965 1970 1975 1980 1985 1990
10.2
10.6
11.0
0 1 2 3 4 5
0.5
0.0
0.5
1.0
Lag
ACF of returns
1 2 3 4 5
0.5
0.0
0.5
Lag
Partial ACF of returns
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Time series regression
1000
3000
5000
Fittedvalues
1950 1960 1970 1980 1990 2000
Time
200
0
100
300
Residuals
US consumption function
ObservedDistributed lagAutoregressive distributed lag
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CointegrationEuropean pepper prices
Time
Averagemonthlyspotprice
1975 1980 1985 1990 1995
1000
3000
5000
7000
whiteblack
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Structural change analysisChange in seatbelt legislation in the UK
Time
UKd
riverdeaths
1970 1975 1980 1985
7.0
7.2
7.4
7.6
7.8
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GARCH models
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Required background
Linear regression:
Ordinary/weighted/generalized least squares estimation(OLS, WLS, GLS)
Gauss-Markov theorem
Inference (t and F tests) for linear hypotheses
Robust standard errors
Factors and interactions
Model selection
R basics (see material for Introductory Econometrics)
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Books
Primary reference:
Cryer JD, Chan KS (2008). Time Series Analysis WithApplications in R, 2nd ed. New York: Springer-Verlag.
Econometrics with R:
Kleiber C, Zeileis A (2008). Applied Econometrics with R. New
York: Springer-Verlag.
Further references:
Brockwell PJ, Davis RA (2002). Introduction to Time Series and
Forecasting, 2nd ed. New York: SpringerVerlag.Tsay RS (2010). Analysis of Financial Time Series, 3rd ed.Hoboken, NJ: John Wiley & Sons.
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Books
Cochrane JH (2005). Time Series for Macroeconomics andFinance. Lecture Notes, Graduate School of Business, University
of Chicago.Franke J, Hardle W, Hafner C (2011). Statistics of FinancialMarkets, 3rd ed. New York: Springer-Verlag.[earlier editions in German]
Hamilton JD (1994). Time Series Analysis. Princeton:Princeton University Press.
Neusser K (2009). Zeitreihenanalyse in denWirtschaftswissenschaften, 2nd ed. Wiesbaden:Vieweg+Teubner Verlag.
Shumway RH, Stoffer DS (2011). Time Series Analysis and ItsApplications, 3rd ed. New York: Springer-Verlag.
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R
Open-source software, freely available under GPL
Current version: 2.13.1
Homepagehttp://www.R-project.org/
Comprehensive R Archive Networkhttp://CRAN.R-project.org/
Windows setup program (
39 MB)../bin/windows/base/R-2.13.1-win32.exe
Econometrics task view:http://CRAN.R-project.org/view=Econometrics
Time series task view:
http://CRAN.R-project.org/view=TimeSeriesExtension package AER for Applied Econometrics with Rhttp://CRAN.R-project.org/package=AER
Extension package TSA forTime Series Analysishttp://CRAN.R-project.org/package=TSA
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http://www.r-project.org/http://cran.r-project.org/http://cran.r-project.org/bin/windows/base/R-2.13.1-win32.exehttp://cran.r-project.org/view=Econometricshttp://cran.r-project.org/view=TimeSerieshttp://cran.r-project.org/package=AERhttp://cran.r-project.org/package=TSAhttp://cran.r-project.org/package=TSAhttp://cran.r-project.org/package=AERhttp://cran.r-project.org/view=TimeSerieshttp://cran.r-project.org/view=Econometricshttp://cran.r-project.org/bin/windows/base/R-2.13.1-win32.exehttp://cran.r-project.org/http://www.r-project.org/ -
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Format
Credit hoursLecture: 2
Time/placeThu 10:1512:00, JBH (WWZ) HG S13,possibly including lab sessions
Exam
Written exam, 90 min.Possibly extra homework, accounts for 20%.
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