Dynamic Econometrics

Uitgebreide vaknaam	Dynamic Econometrics
Leerdoelen	Upon completion of the course the student is able to: 1. create an original research question which involves the analysis of time series data; 2. describe the statistical properties of linear auto-regressive moving average processes of any order, in both the univariate and multivariate cases (ARMA and VARMA models); 3. estimate ARMA/VARMA process and select the most appropriate process to model and forecast time series data; 4. test for time series data nonstationarity due to time trends and unit roots, and account for these characteristics of the data in parameter estimation and hypothesis testing; 5. study quantitatively the behavior of multiple nonstationary time series by cointegration analysis techniques; 6. choose an appropriate linear model to analyze time series data, and use the results of estimation and testing to answer a research question; 7. write a scientific paper following the standards in econometric literature.
Omschrijving	Analysis of univariate and multivariate linear time series models
Uren per week	4
Onderwijsvorm	hoorcolleges
Toetsvorm	opdracht(en), schriftelijk tentamen (Final exam and group assignments (exercises and a research paper))
Vaksoort	bachelor
Coördinator	dr. T. Boot
Docent(en)	dr. T. Boot
Verplichte literatuur	Titel Auteur ISBN Prijs Econometrics Hayashi, F. 9780691010182 ca. €  48,00 Lecture slides
Entreevoorwaarden	Notions of econometrics, statistics and mathematics considered in previous courses of the BSc EOR Programme, in particular the courses Probability Theory for EOR, Probability Distributions, Estimation and Testing, Statistical Modelling for EOR, Statistical Inference, Linear Models in Statistics, Introduction to Econometrics. Participants in the course need to know (a) matrix algebra, determinants, convergence of deterministic sequences, difference equations; (b) the topics considered in chapters 1.1-2.9 of the book Econometrics by F. Hayashi; (c) standard theory on estimation and hypothesis testing for models of independent and identically distributed random variables (including asymptotic results involving LLN, CLT, CMT and stochastic convergence modes). In addition, the course requires familiarity with some softwares to perform statistical data analysis (e.g., Stata, R, EViews, Matlab, S-Plus, Gauss, GNU-Octave, etc.).
Opmerkingen	Secretary: Martine Geerlings-Koolman, phone +31(0)50 36 37018, e-mail m.a.koolman@rug.nl
Opgenomen in	Opleiding Jaar Periode Type BSc Econometrics and Operations Research/EOR 2 semester II b verplicht BSc Mathematics: Probability and Statistics 2 semester II b keuzegroep Courses open to Exchange Students (BSc)  ( Courses open to Exchange Students (BSc) without limited access) 2 semester II b keuze