Pesaran Panel Unit Root Test
res = Pesaran(arg1,...,argn)
* arg1,..., argn = arguments that can be:
-a panel data tlist (in that case there must be an argument 'namevar= xxx' to indicate the name of the variable in the panel, see below)
-the strings:
. 'lagorders=x' with x=%nan (if the lags for the ADF test are to be determined automatically) or a (N x 1) or (1 x N) vector of lags for the ADF test
. 'pmax=x' with x=%nan or a number if for the maximal # of lags for the ADF test
. 'signif=x' with x the significance level for the individual ADF tests (0.05, 0.01 or 0.1)
. 't_order=x' for the trend order with x:
-1: no constant, no trend
0: a constant, no trend (default)
1: a constant and a trend
. 'noprint' if the user does not want to print the results of the test
. 'namevar=xx' where xx is the name of the variable in the panel (only if the data are in a 'panel data' tlist, see help paneldb)
- a time series
- a real (n x p) matrix
- a string equal to the name of a time series or a (n x p) real matrix between quotes (note that there must be several variables of this type tos be able to perform a panel unit root test)
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
- res('prests') = boolean indicating the presence or absence of a time series in the regression
- res('namey') = name of the y variable
- res('dropna') = boolean indicating if NAs have been dropped
- res('bounds') = if there is a timeseries in the regression, the bounds of the regression
- res('nonna') = vector indicating position of non-NAs
// load the database containing the GDP for 25 countries in the OECD over the period 1963-2003 load(GROCERDIR+'/data/gdpan_oecd.dat'); // retrieve the names of all variables in database listvar=dblist(GROCERDIR+'/macros/grocer/db/gdpan_oecd.dat') res = Pesaran('log('+listvar+')','pmax=4','t_order=0') // Provides the Pesaran test for all variables in the database, taken in logarithm, // with a constant but not trend ('t_order=0'), the Lag order to be determined by the programm, // the maximum number of lags set to 4 (arg 'pmax=4'). | ![]() | ![]() |