Moon and Perron Panel Unit Root Test
res = Moon_Perron(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:
. 'criteria=x' with x = Criteria used to estimate the number of common factors
= 'IC1', 'IC2', 'IC3', 'PC1', 'PC2', 'PC3', 'AIC3', 'BIC3' (see Bai and Ng (2002))
. 'kmax=x' with x=maximum number of common factors used to compute the criterion functions for the estimation of r, the number of common factors. If it is not specified it is set to min(N,T)
. '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
. 'bandwidth=n' with:
n = 'C' (Default) common lag troncature for the Bartlett kernel (Levin and Lin 2003)
n = 'N' for the Newey West (1994)'s non parametric bandwidth parameter
n = 'A' for the Andrews (1991) automatic bandwidth parameter selection with AR(1) structure
. 'kernel=n' with:
n = 'b' for Bartlett (Default)
n= 'qs' for Quadratic Spectral (not possible when bandwitch = 'C')
. '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 to be able to perform a panel unit root test)
res = a results tlist with:
- res('meth') = 'Moon Perron'
- 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('ta_star') = Statistic ta_star
- res('tb_star') = Statistic tb_star
- res('ta_pvalue') = Pvalue for the statistics ta_star
- res('tb_pvalue') = Pvalue for the statistics tb_star
- res('critical') = Normal Critical Values for the statistics ta_star and tb_star at 1%, 5% and 10%
- res('rho_pool') = Pooled OLS estimator on initial series
- res('rho_star') = Modified pooled OLS estimator using de-factored data
- res('khat') = Estimated numbers of Factor with IC1, IC2, IC3, PC1, PC2, PC3, AIC3 and BIC3
- res('criteria') = Criteria used to estimate the number of common factors. Default value = 1 (IC1)
- res('IC') = IC1, IC2 and IC3 Information criteriums for r=1,...,rmax
- res('PC') = PC1, PC2 and PC3 Information criteriums for r=1,...,rmax
- res('BIC3') = BIC3 Information criterium for k=1,...,kmax (only BIC criteria function of N and T)
- res('AIC3') = AIC3 Information criterium (only AIC criteria function of N and T): it tends to overestimate k
- res('kmax') = Maximum number of common factors authorized
- res('h') = Values of individual bandwitch parameters
- res('LRV') = Estimated of Individual Long Run Variances
- res('TLRV') = Estimated of Individual Temporal Long Run Variances
- res('kernel') = kern function used
- res('bandwidth') = Method to fix the bandwitch parameter
- 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+'/macros/grocer/db/gdpan_oecd.dat'); // retrieve the names of all variables in database listvar=dblist(GROCERDIR+'/macros/grocer/db/gdpan_oecd.dat') res = Moon_Perron('log('+listvar+')','kmax=5','t_order=0','kernel=qs','bandwidth=n','criteria=BIC3') // This example (taken from Moon_Perron_d()) provides the Moon and Perron test for the log of gdp of 25 OECD countries, // with individual constants but no trends ('t_order=0'), the maximum # of factors allowed set to 5 ('kmax=5'), // the number of factors determined by the criteria 'AIC1' proposed by Bai an Ng ('criteria=AIC1'), // the Newey-West bandwidth ('bandwidth=n') and the Quadratic Spectral kernel ('kernel=b'). res = Moon_Perron('log('+listvar+')','kmax=5','t_order=0','kernel=b','bandwidth=n','criteria=AIC1') // This Example does the same but with the criteria 'AIC1' proposed by Bai an Ng ('criteria=AIC1') and the Barlett kernel ('kernel=b'). | ![]() | ![]() |