Time Series Modeling Tools in GAUSS
Overview
As a lead developer and educator for the Time Series Modeling Tools (TSMT) library in GAUSS, I played a central role in both extending and refining GAUSS’s capabilities for time series econometrics. My contributions spanned new model development, API design and optimization, and user-focused documentation and training.
These tools serve researchers, analysts, and students applying sophisticated econometric techniques in fields such as macroeconomic forecasting, financial modeling, and structural policy evaluation.
My Role
Core Responsibilities
- Built new functionality from the ground up for advanced time series estimation models.
- Refactored and modernized existing code to improve usability, consistency, and performance.
- Designed a streamlined API using optional arguments and output structures for greater flexibility.
- Wrote a comprehensive documentation suite and authored over 30 educational blog posts and tutorials.
- Collaborated on product planning, helping define scope, prioritize features, and respond to customer needs.
New Features Developed
-
State-Space Estimation for ARIMA and SARIMA Models
Added Kalman-filter-based likelihood estimation for models with latent components and seasonal structure. -
Structural VAR (SVAR) Models with Sign Restrictions
Implemented identification via long-run restrictions, short-run restriction, and sign restrictions. -
Nonlinear Time Series Tools
Developed and tested procedures for:- Markov-Switching Autoregressive (MSAR) models
- Threshold Autoregression (TAR)
- Structural Break models
These features expanded GAUSS’s modeling suite to support a broader class of nonlinear and regime-switching dynamics.
Improvements & Enhancements
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API Simplification with Optional Arguments
Enabled users to specify only what they need — reducing learning curve and boilerplate code. -
Modular Output & Control Structures
Unified input/output structure across all time series functions for easier integration into workflows. -
Performance Optimization
Rewrote estimation routines and diagnostic tools for greater computational efficiency, especially for large datasets or multi-equation systems.
Documentation & Educational Content
- Created a complete online documentation suite for the TSMT library, with examples, inline usage tips, and links to source code.
- Authored 30+ blog tutorials on time series modeling topics including:
- Forecasting with ARIMA and VARIMA
- Impulse response analysis
- Unit root and cointegration testing
- Markov-switching model interpretation
- Structural decomposition in SVAR models
These resources help bridge the gap between theory and application, serving both new and experienced users.
Technical Stack
- Language: GAUSS matrix language
- Model Types: ARIMA, SARIMA, VAR, VARIMA, VECM, SVAR, MSAR, TAR
- Tools: Kalman Filter, Sign Restrictions, IRF Analysis, Model Selection, Forecasting
- Design Focus: Extensibility, backward compatibility, ease of use, reproducibility
Example Resources
- Estimating SVAR Models with GAUSS
- Easier ARIMA Modeling with State Space
- SVAR with Sign Restrictions
- Unit Root Testing
- GAUSS TSMT Documentation