Time Series Modeling with GAUSS
Date: June 03-05, 2013
Location: Singapore
Course Program
This is a 3-day intensive course at the intermediate-advanced level on modeling macroeconomic and financial variables using the econometric software GAUSS, a highly flexible and powerful programming language for statistical computation.
The workshop begins with a session on the basics of GAUSS programming. This is followed by extensive treatment of univariate and multivariate time series models using both simulated and real data in economics and finance. The workshop also tackles some advanced methods including VAR, VECM, Markov-switching, and Kalman filters. Participants
are welcomed to bring your own datasets.
Day 1: Introduction to GAUSS
Morning Session
- Data types, reading data into GAUSS
- Vectors and matrices, arrays
- Matrix, relational, and logical operators
- Conditional statements and loops
- Procedures, functions, and keywords
- Case studies
Afternoon Session
- Regression Basics: OLS, GLS, MLE, GMM, Bayesian methods
- Basic Time Series Concepts: Stationarity, Non-stationarity, Unit-root tests
- Case studies
Day 2: Modeling Stationary Time Series
Morning Session
- Univariate Modeling: Simulation, ARIMA(p,d,q), estimation and forecasting
- Modeling Volatility: ARCH, GARCH, GARCH-m, EGARCH etc.
- Case studies
Afternoon Session
- Multivariate Modeling: ADL(p,q) models
- Markov-switching Models
- Case studies
Day 3: Modeling Non-stationary Time Series
Morning Session
- Co-Integration and Error Correction Models: Single and multiple equations
- Vector Autoregressive (VAR) and Vector-Error Correction (VEC) Models
- Case studies
Afternoon Session
- Kalman filters and Time-varying Parameters
- Basics of Bayesian Computation: MCMC, Gibbs sampling
- Case studies
For more information and registration details click here.
