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Pesaran1

Pesaran Panel Unit Root Test

CALLING SEQUENCE

res = Pesaran1(Y,t_order,LagOrders,pmax,signif)

PARAMETERS

Input

* Y = matrix (T,N) of observations

  The data matrix may be unbalanced.

  Missing Values must be specified as %nan

* t_order = -1 : no individual effect

      0 : individual effects (Default)

      1 : individual effects and time trends

* LagOrders =

  - %nan if the user wants the program to determine the optimal lag order for each country (pmax=12 or T/4)

  - a vector (N x 1) or (1 x N) of optimal lags for all the individuals of the panel

* pmax = Maximum of the lag order authorized

* signif = significance level for the individual ADF tests (0.05, 0.01 or 0.1)

 

Output

res = a results tlist with:

  - res('meth') = 'Pesaran'

  - res('y') = (T x k) matrix of data

  - res('t_order') = the trend order (-1, 0 or 1)

  - res('t_orderlit') = the trend order in plain english

  - res('CIPS') = CIPS statistic

  - res('CIPS_star') = Truncated CIPS : CIPS* statistic

  - res('CIPS_pvalue') = Pvalue of the CIPS statistic

  - res('CIPS_star_pvalue') = Pvalue of the truncated CIPS* statistic

  - res('CIPS_critical') = Critical Values of the CIPS distribution at 1%, 5% and 10% for T and N sample

  - res('CADF') = Individual CADF statistics

  - res('CADF_pvalue') = Pvalues of the individual CADF statistics (based on the CADF distribution)

  - res('CADF_critical') = Critical Values of the CADF distribution at 1%, 5% and 10% for T and N sample

  - res('CADF_star') = Truncated individual CADF statistics

  - res('CADF_star_critical') = Critical Values of the CADF distribution at 1%, 5% and 10% for T and N sample

  - res('CADF_star_pvalue') = Pvalues of the individual truncated CADF_star statistics (based on the CADF distribution)

  - res('p') = Lag order in the CADF regressions (common for all individuals)

  - res('CP') = Chi-Squared test statistic CP

  - res('CZ') = Inverse normal test statistic CZ

DESCRIPTION

Pesaran (2007) unit root test (ref: "A simple panel unit root test in the presence of cross-section dependence", Journal of Applied Econometrics, John Wiley and Sons, Ltd., vol. 22(2), pages 265-312).

EXAMPLE

load(GROCERDIR+'/data/gdpan_oecd.dat');
Y=explone(dblist(GROCERDIR+'/data/gdpan_oecd.dat'));
// extract matrix of data present in database
 
res=Pesaran1(log(Y),0,%nan,5,0.05)
// Provides the Pesaran test for all Y columns, with a constant but not trend (arg # 2 = 0),
// the Lag order to be determined by the program (arg # 3 = %nan),
// the maximum number of lags set to 5 (arg # 4 = 5) at a 5% significance level (arg # 5 = 0.05).

AUTHOR

Christophe Hurlin 2004 / Eric Dubois 2008

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