New Release TSPDLIB 3.0


The preliminary econometric package for Time Series and Panel Data Methods has been updated and functionality has been expanded with over 20 new functions in this release of TSPDLIB 3.0.

The TSPDLIB 3.0 package includes expanded functions for time series and panel data testing both with and without structural breaks and causality testing.

It requires a GAUSS 23+ for use.

Changelog 3.0:

  1. New functionality: Add metadata based variable names for improved printing.
  2. Improvement: Simplified data loading formulas using expanded GAUSS 23 .
  3. New unit root testing procedures:
    • fourier_kpss - KPSS stationarity testing with flexible Fourier form, smooth structural breaks.
    • fourier_kss - KSS unit root test with flexible Fourier form, smooth structural breaks.
    • fourier_wadf - Wavelet ADF unit root test with flexible Fourier form, smooth structural breaks.
    • fourier_wkss - Wavelet KSS unit root test with flexible Fourier form, smooth structural breaks.
    • kss - KSS unit root test.
    • qr_fourier_adf - Quantile ADF unit root test with flexible Fourier form, smooth structural breaks.
    • qr_fourier_kss - Quantile KSS unit root test with flexible Fourier form, smooth structural breaks.
    • qr_kss - Quantile KSS unit root test.
    • qks_tests - Quantile Kolmogorov-Smirnov (QKS) tests.
    • wkss - Wavelet KSS unit root test.
    • sbur_gls - Carrion-i-Silvestre, Kim, and Perron (2009) GLS-unit root tests with multiple structural breaks.
  4. New cointegration tests:
  5. New panel data unit root tests:
    • pd_kpss - Carrion-i-Silvestre, et al.(2005) panel data KPSS test with multiple structural breaks.
    • pd_stationary - Tests for unit roots in heterogeneous panel data including with or without cross-sectional averages, with or without flexible Fourier from structural breaks.
  6. New causality tests:
    • asymCause - Hatemi-J tests for asymmetric causality.
    • pd_cause - Tests for Granger causality in heterogenous panels including Fisher, Zhnc, and SUR Wald tests.
  7. Other new functions:
    • sbvar_icss - Sanso, Arag & Carrion (2002) ICSS test for changes in unconditional variance.
    • pd_getCDError - Tests for cross-sectional dependency.
  8. New examples:
    • actest.e
    • ascomp.e
    • fourier_kss.e
    • fourier_kpss.e
    • fourier_wadf.e
    • fourier_wkss.e
    • kss.e
    • pd_cause.e
    • pd_getcderror.e
    • pd_coint_wedgerton.e
    • pd_kpss.e
    • qr_fourier_adf.e
    • qr_fourier_kss.e
    • qr_kss.e
    • qr_qks.e
    • sbur.e
    • sbvar_icss.e
    • wkss.e


If using this library please include the following citation:

Nazlioglu, S (2018) TSPDLIB: GAUSS Time Series and Panel Data Methods (Version 3.0). Source Code.

Getting Started


The program files require a working copy of GAUSS 23+.


The GAUSS Time Series and Panel data tests library should only 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.


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 Packages Complete Guide.

Example Applications

  1. A Guide to Conducting Cointegration Tests
  2. How to Conduct Unit Root Tests in GAUSS
  3. Panel data, structural breaks, and unit root testing
  4. Unit Root Tests with Structural Breaks
  5. How to Run the Maki Cointegration Test (Video)
  6. How to Run the Fourier LM Test (Video)
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