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GAUSS times series and panel unit root tests compiled by Saban Nazlioglu
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GAUSS Time Series and Panel data tests

Econometric package for Time Series and Panel Data Methods covering unit root, co-integration & causality tests. Extensive coverage of testing in the presence of structural breaks.

The tspdlib library is written for GAUSS by Saban Nazlioglu, Department of International Trade & Finance, Pamukkale University-Türkiye.

Getting Started


The program files require a working copy of GAUSS 19+. Many tests can be run on earlier versions with some small revisions and users should contact for a modified library for earlier GAUSS versions.


The GAUSS Time Series and Panel data tests can be easily installed using the GAUSS Application Installer, as shown below:

  1. Download the zipped folder
  2. Select Tools > Install Application from the main GAUSS menu.
    install wizard
  3. Follow the installer prompts, making sure to navigate to the downloaded
  4. 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.
    load library
  • Enter library tspdlib in the program input/output window.
  • Put the line library tspdlib; at the beginning of your program files.

Note: I have provided the individual files found in for examination and review. However, installation should always be done using the folder and the GAUSS Application Installer.


After installing the library the example files examples > PDuroot.e and examples > TSuroot.e will be found in your GAUSS home directory in the directory pkgs > tspdlib >examples. The example uses GAUSS datasets included in the pkgs > tspdlib >examples directory.


We have not yet developed detailed documentation about the library. However, you can find more information about the functions by looking at the function headers in the src codes.

accessing GAUSS source files

You can access these source codes through the library tool by expanding the tspdlib.lcg menu and clicking on the file name. The file will open in the program editor and you will be able to view the headers for each specific function.


The author makes no performance guarantees. The tspdlib is available for public non-commercial use only.


For any bugs, please send e-mail to Saban Nazlioglu or Erica Clower.


Time Series Unit Root Tests

src file Reference
zandrews Zivot, E. & Andrews, W.K. (1992). Further evidence on the great crash, the oil-price shock, and the unit root hypothesis. Journal of Business and Economic Statistics 10(3), 251-270.
npopp Narayan, P.K. & Popp, S. (2010). A new unit root test with two structural breaks in level and slope at unknown time. Journal of Applied Statistics, 37:9, 1425-1438.
lstrazicich1 Lee, J. & Strazicich, Mark C. (2013). Minimum LM unit root test with one structural break. Economics Bulletin 33(4), 2483-2492.
lstrazicich2 Lee, J. & Strazicich, M.C. (2003). Minimum Lagrange Multiplier unit toot test with two structural breaks. Review of Economics and Statistics 85(4), 1082-1089.
kurozumi Kurozumi, E. (2002). Testing for stationarity with a break. Journal of Econometrics, 108(1), 63-99.
cissanso Carrion-i-Silvestre, J. Ll. & Sansó, A. (2007). The KPSS test with two structural breaks. Spanish Economic Review, 9, 2, 105-127.
eleeFadf Enders, W. & Lee, J. (2012). The flexible Fourier form and Dickey-Fuller type unit root tests. Economics Letters, 117, 196-199.
eleeFlm Enders, W., and Lee, J. (2012). A Unit Root Test Using a Fourier Series to Approximate Smooth Breaks. Oxford Bulletin of Economics and Statistics,74,4(2012),574-599.
belFkpss Becker, R., Enders, W., Lee, J. (2006). A stationarity test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381-409.
rtaylorFgls Rodrigues, P. & Taylor, A.M.R. (2012). The flexible Fourier form and local GLS de-trending unit root tests. Oxford Bulletin of Economics and Statistics, 74(5), 736-759.
rals_adf Im, K. S., Lee, J., & Tieslau, M. A. (2014). More powerful unit root tests with non-normal errors. In Festschrift in Honor of Peter Schmidt (pp. 315-342). Springer New York.
rals_lm Meng, M., Im, K. S., Lee, J., & Tieslau, M. A. (2014). More powerful LM unit root tests with non-normal errors. In Festschrift in Honor of Peter Schmidt (pp. 343-357). Springer New York.
qradf Koenker, R. & Xiao, Z. (2004). Unit root quantile autoregression inference, Journal of the American Statistical Association, 99(467), 775-787.

Panel Data Unit Root Tests

src file Reference
pd_panic Bai, J. & Ng, S. (2004). A PANIC attack on unit roots and cointegration. Econometrica, 72, 1127–78.
pd_panic Westerlund, J., & Larsson, R. (2009). A note on the pooling of individual PANIC unit root tests. Econometric Theory, 25(6), 1851-1868.
pd_panic Bai, J., & Ng, S. (2010). Panel unit root tests with cross-section dependence: a further investigation. Econometric Theory, 26(4), 1088-1114.
pd_panic Reese, S., & Westerlund, J. (2016). PANICCA: PANIC on Cross‐Section Averages. Journal of Applied Econometrics, 31(6), 961-981.
pd_panic Bai, J., & Ng, S. (2002). Determining the number of factors in approximate factor models. Econometrica, 70(1), 191-221.
pd_iltlevel Im, K., Lee, J., Tieslau, M. (2005). Panel LM Unit-root Tests with Level Shifts, Oxford Bulletin of Economics and Statistics 67, 393–419.
pd_lttrend Lee, J., & Tieslau, M. (2017). Panel LM unit root tests with level and trend shifts. Economic Modelling.
pd_nkarul Nazlioglu, S., & Karul, C. (2017). A panel stationarity test with gradual structural shifts: Re-investigate the international commodity price shocks. Economic Modelling, 61, 181-192.

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