Applied Econometrics with R
Lecture/Practicals
| Instructor: | Oleg Nenadić |
| Time: | Mondays, 12 - 14 |
| Venue: | MZG 8.163 |
| Sundry: | Course No. 800847, Module No. M.WIWI-QMW.0008, Credits: 6 CP (Master/PhD) The course language is English. |
Course Overview
This course covers the econometric models discussed in the lectures "Econometrics I" and "Econometrics II". Within this course R (http://www.r-project.org) is presented as an alternative and freely available (Open Source) software for empirical analyses by means of selected case studies.
Contents:
- Introduction:
- Getting started & working with R
- R basics:
- R as a calculator; matrix operations; R as a programming language; data management; graphics; exploratory data analysis.
- Linear Regression:
- Simple/multiple linear regression; factors/interactions and weights; linear regression with time series data and with panel data.
- Diagnostics and alternative methods of regression:
- Diagnostic tests; testing for heteroskedasticity/functional form/autocorrelation; robust standard errors & tests; HC/HAC estimators; resistant/quantile regression.
- Models of Microeconometrics:
- Generalized linear models / binary dependent variables / models for count data; censored dependent variables.
- Time Series Analysis:
- Classical decomposition / filtering / exponential smoothing; stationarity, unit roots and cointegration; time series regression; ARIMA models / extensions.
Literature
- Kleiber, C. & Zeileis, A. (2008), "Applied Econometrics with R", Springer, Heidelberg.
Further Information
Updated: March 13 2012