Description and contextualization of the subject

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

Ordinary call: orientations and renunciation

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.



The final exam will be at the classroom unless special circunstances require an alternative form of exam. This alternative exam will be announced in due time.

Temary

TIME SERIES

1. Introduction

2. Linear difference equations

3. Lag operators

4. Stationary ARMA process

5. Vector autoregression

6. Examples of Time Series

7. Modeling 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.

Bibliography

Compulsory materials

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. 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. I strongly recommend this software. However, you may use whatever software you fill more comfortable with.

Basic bibliography

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.

In-depth bibliography

- 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

Links

- 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/