Name

cadf — ADF statistic for residuals from a cointegrating regression

CALLING SEQUENCE

[rescadf]=cadf(p,l,namey,arg1,…,argn)

PARAMETERS

Input

• p: order of time polynomial in the null-hypothesis

 - p = -1, no deterministic part

 - p =  0, for constant term

 - p =  1, for constant plus time-trend

 - p >  1  returns no critical values

• l: # of lagged changes of the residuals to include in regression

• namey: a time series, a real (nx1) vector or a string equal to the name of a time series or a (nx1) real vector between quotes

• argi: arguments which can be:

 * a time series

 * a real (nx1) vector

 * a string equal to the name of a time series or a (nx1) real vector between quotes

 * the string 'noprint' if the user doesn't want to print the results of the regression

 * the string 'dropna' if the user wants to remove the NA values from the data

Output

• rcadf= a tlist with

  . all of the arguments of the second stage regression

• and

  . rcadf('cointrel') = tlist with all the arguments of the first stage regression (see ols() for a description of all these arguments)

DESCRIPTION

Computes augmented Dickey-Fuller statistic for residuals from a cointegrating regression, allowing for deterministic polynomial trends.

EXAMPLE


load(GROCERDIR+'/data/datajpl.dat')
r = cadf(0,6,'illinos','indiana')
// Example taken from function cadf_d. Illinos and indiania are the names of two variables taken from data base jpl.dat 
// and these names will be used for printings. First entry is set to 0, which means that no trend is imposed in the
// cointegrating regression. second entry is set to 6, which means that there are 6 lags to the residuals in the second 
// stage regression. 
r = cadf(1,4,illinos,indiana)
// Now, a trend is included in the cointegrating regression, 4 lags on residuals in the second stage 
// regression and the variables are named 'endogenous' and 'exogenous' respectively when the results are printed.

               

AUTHOR

Eric Dubois 2002-2007