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Metodo Kuantitatiboak eta Denborazko Serieen Analisia

Gaiari buruzko datu orokorrak

Modalitatea
Ikasgelakoa
Hizkuntza
Ingelesa

Irakasgaiaren azalpena eta testuingurua

This course offers a brief introduction to time series analysis, STATA and R.

Irakasleak

IzenaErakundeaKategoriaDoktoreaIrakaskuntza-profilaArloaHelbide elektronikoa
GARDEAZABAL MATIAS, FRANCISCO JAVIEREuskal Herriko UnibertsitateaUnibertsitateko KatedradunaDoktoreaElebakarraEkonomia Analisiaren Oinarriakjavier.gardeazabal@ehu.eus
UGIDOS OLAZABAL, ARANTZAEuskal Herriko UnibertsitateaUnibertsitateko Irakaslego TitularraDoktoreaElebakarraEkonomia Analisiaren Oinarriakarantza.ugidos@ehu.eus
VEGA BAYO, AINHOAEuskal Herriko UnibertsitateaIrakaslego AgregatuaDoktoreaElebidunaEkonomia Analisiaren Oinarriakainhoa.vega@ehu.eus

Gaitasunak

IzenaPisua
Conocer y aplicar las técnicas de computación simbólicas y numéricas de manera que se puedan resolver y simular modelos económicos dinámicos50.0 %
Conocer y aplicar las técnicas que permitan el análisis de series temporales de indicadores económicos50.0 %

Irakaskuntza motak

MotaIkasgelako orduakIkasgelaz kanpoko orduakOrduak guztira
Magistrala304575
Ordenagailuko p.203050

Irakaskuntza motak

IzenaOrduakIkasgelako orduen ehunekoa
Ariketak10.0100 %
Azalpenezko eskolak20.0100 %
Irakurketa eta analisi praktikoak75.00 %
Tutoretzak20.0100 %

Ebaluazio-sistemak

IzenaGutxieneko ponderazioaGehieneko ponderazioa
Idatzizko azterketa60.0 % 80.0 %
Lan praktikoak20.0 % 40.0 %

Ohiko deialdia: orientazioak eta uko egitea

The evaluation system of the Time Series part has four steps:

1. A homework on chapters 2 and 3. The weight of this task is 10%.

2. A homework on chapter 4. This second task also weighs 10% in the final grade.

3. A homework on chapter 5. The weight of this task is 10%.

4. An exam at the end of the course representing 70% of the Time Series final mark.

Irakasgai-zerrenda

TIME SERIES

a) Non-technical introduction: Stylized empirical regularities.

b) Linear difference equations.

c) Impulse Response Function.

d) Lag operator. e) Stationary ARMA processes.

f) Granger causality.

g) Vector autoregression (VAR).

h) Structural VAR.

i) Variance decomposition

j) Unit roots versus deterministic trends.

k) Structural change - Trend breaks.

l) Trend-cycle decompositions.

m) Error correction models and co-integration.

n) Stochastic volatility



STATA

a) General aspects.

b) Data handling.

c) Data management.

d) Reshaping data.

e) Joining together files.

f) Looping commands. g) Graphs.



R

a) The R Language.

b) RStudio

c) Basic syntax.

d) Reading data.

e) Data manipulation.

f) Graphs.

g) Descriptive statistical analysis.

h) Loops and functions.



SOFTWARE



TIME SERIES: You may use whatever software you fill more comfortable with. As an option, you could use GRETL. http://gretl.sourceforge.net/||gretl. Gnu Regression, Econometrics and Time-series Library. GRETL is a cross-platform, free and open source software. GRETL has a very friendly interface for interactive use, a console for batch jobs and it allows the user to make computations in R, Octave and Ox languages. GRETL is capable of doing all the necessary econometrics for this course.



STATA: You have to use the software Stata that is available in the Computer Rooms of the University.



R: You have to use the free software R available for download at: https://www.r-project.org. It is also recommended that you use the (also free) software RStudio because it makes using R a lot easier.

Bibliografia

Nahitaez erabili beharreko materiala

SOFTWARE FOR TIME SERIES



In the time series part we will be using GRETL. http://gretl.sourceforge.net/||gretl. Gnu Regression, Econometrics and Time-series Library. retl is a cross-platform, free and open source software. gretl has a very friendly interface for interactive use, a console for batch jobs and it allows the user to make computations in R, Octave and Ox languages. gretl is capable of doing all the necessary econometrics for this course. I strongly recommend this software. However, you may use whatever software you fill more comfortable with.

Oinarrizko bibliografia

TIME SERIES

- Enders, Walter, (2004), Applied Econometric Time Series. Wiley Series in Probability and Statistics.

- Hamilton, James D., (1994), Time Series Analysis. Princeton University Press.

- Lütkepohl, Helmut, (2005), New introduction to Multiple Time Series Analysis. Springer Verlag



STATA

- Acock, Alan C. (2016). A gentle introduction to Stata, Fifth Edition. Stata Press.

- Cameron, Trivedi (2010) Microeconomics using Stata. Stata Press.



R

- W. N. Venables, D. M. Smith and the R Core Team. An Introduction to R (Version 3.4.0, 2017-04-21).

- Zuur, A., Ieno, E. N., & Meesters, E. (2009). A Beginner's Guide to R. Springer Science & Business Media.

Gehiago sakontzeko bibliografia

- Perron, P., & T. Wada (2009) "Let's Take a Break: Trends and Cycles in US Real GDP," Journal of Monetary Economics 56 (6), 749-765.



- Schmitt-Grohe, S, & M. Uribe (2004), "Solving Dynamic General Equilibrium Models Using a Second-Order Approximation to the Policy Function," Journal of Economics Dynamics and Control 28, 755-775

Estekak

- ARIMA and Multivariate time series.Available at http://www.springer.com/statistics/statistical+theory+and+methods/book/978-0-387-95351-9-3



- Examples written in R. Available at http://dx.doi.org/10.1007/978-0-387-75959-3



- Guides to Matlab: http://www.mathworks.es/es/help/?s_cid=HP_FF_S_Doc y http://www.mathworks.com/moler/intro.pdf



- Econometric Toolbox for Matlab by James P. LeSage. http://www.spatial-econometrics.com/



- Bayesian Econometric for by Gary Koop. http://www.wiley.com/legacy/wileychi/koopbayesian/



- Bruce Hansen¿s paper and Program. http://www.ssc.wisc.edu/~bhansen/progs/progs_paper.htm



- McCallum¿s package for Rational Expectation Calculation. http://www.tepper.cmu.edu/faculty-research/faculty-directory/bennett-mccallum/matlab-files-for-re-calculations/index.aspx



- Martin Uribe¿s paper and program (first and second order solutions to DSGE models). http://www.columbia.edu/~mu2166/

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