Introduction
The preliminary econometric package for Time Series and Panel Data Methods has been updated and functionality has been expanded in this release of TSPDLIB 2.0.0.
The TSPDLIB 2.0.0 package includes expanded functions for time series and panel data testing both with and without structural breaks and causality testing. In addition, TSPDLIB 2.0.0 is easier than ever to use with new implementation of default parameter settings, updated output printing, and automatic data type detection.
Changelog 2.0.0:
- Added response surface critical values in ADF, GLS, LM, and KPSS tests.
- Added innovational outlier and additive outlier options for Zivot & Andrews unit root tests.
- Bug Fix: Optimal lag selection in adf_1br, adf_2br, lm_1br, fourier_adf, fourier_lm, and fourier_gls.
- Add standardized output printing.
- New procedures:
- gls_1br - GLS unit root test with one break.
- gls_2br - GLS unit root tests with two breaks.
- RALSLM_breaks - RALS-LM unit root tests with one and two breaks.
- fixed_T_panel - Fixed T unit root tests.
- _get_cd_error - Error-cross section dependence tests.
- granger - Granger causality function with optional arguments.
- pdlm - PD level and trend break test with optional arguments.
- quantileADF - quantile ADF procedure with optional arguments.
- Update ADF_1br.e to accommodate new outlier model input.
- Update all procedure to use optional arguments for parameters and set defaults for all optional arguments.
- Add new dataframe datasets with date types.
- Update all structural break accommodating tests to be compatible with date types.
- Add automatic date type detection.
- Add printing of test details.
- Add printing of test conclusions.
- New examples:
- gls_1br.e
- gls_2br.e
- pdlm.e
- granger.e
- quantileADF.e
Citation
If using this library please include the following citation:
Nazlioglu, S (2018) TSPDLIB: GAUSS Time Series and Panel Data Methods (Version 2.0). Source Code. https://github.com/aptech/tspdlib
Getting Started
Prerequisites
The program files require a working copy of GAUSS 21+.
Installing
The GAUSS Time Series and Panel data tests library can be installed and updated directly in GAUSS using the GAUSS package manager.
Before using the functions created by tspdlib
you will need to load the newly created tspdlib
library. This can be done in a number of ways:
- Navigate to the library tool view window and click the small wrench located next to the
tspdlib
library. Select Load Library. - Enter
library tspdlib
in the program input/output window. - Put the line
library tspdlib;
at the beginning of your program files.
Examples
After installing the library, examples for all available procedures can be found in your GAUSS home directory in the directory pkgs > tspdlib >examples. The example uses GAUSS and .csv datasets which are included in the pkgs > tspdlib >examples directory.
Using GAUSS Packages
For more information on how to make the best use of the TSPDLIB, please see our blog, Using GAUSS Package; Complete Guide.
Example Applications
- A Guide to Conducting Cointegration Tests
- How to Conduct Unit Root Tests in GAUSS
- Panel data, structural breaks, and unit root testing
- Unit Root Tests with Structural Breaks
Eric has been working to build, distribute, and strengthen the GAUSS universe since 2012. He is an economist skilled in data analysis and software development. He has earned a B.A. and MSc in economics and engineering and has over 18 years of combined industry and academic experience in data analysis and research.