Posting this on behalf of a friend.
Any clue what programming language this is? :-/
Code taken from : Journal of Applied Econometrics Data Archive: Data Directory
Any clue what programming language this is? :-/
Code:
@version 3, October 11, 2004.
These routines can be used by and distributed for non-profit academic purposes
without any royalty except that the users must cite:
Bai, Jushan and Pierre Perron (1996): "Estimating and Testing Linear
Models with Multiple Structural Changes," Econometrica, 1998, vol 66, 47-78
and
Bai, J. and P. Perron (2003): "Computation and Analysis of Multiple
Structural Change Models," Journal of Applied Econometrics, 18, 1-22.
For any other commercial use and/or comments, please contact
Pierre Perron at perron at bu.edu.
Even though we tried to make this program error-free we cannot be held
responsible for any consequences that could result from remaining errors.
Copyright, Pierre Perron (1999, 2004).
@
new;
format /ld 6,4;
output file = real.out reset; @select your output file@
load yyy[103,1] = real.dat; @read data@
bigt=103; @set effective sample size@
y=yyy[1:103,1]; @set up the data, y is the dependent variable
z is the matrix of regressors (bigt,q) whose
coefficients are allowed to change, x is a
(bigt,p) matrix of regressors with coefficients
fixed across regimes. Note: initialize x to
something, say 0, even if p = 0.@
z=ones(bigt,1);
x=0;
q=1; @number of regressors z@
p=0; @number of regressors x@
m=5; @maximum number of structural changes allowed@
eps1=.15; @Value of the trimming (in percentage) for the construction
and critical values of the supF ype tests (used in the
supF test, the Dmax, the supF(l+1|l) and the sequential
procedure). If these test are used, h below should be set
at int(eps1*bigt). But if the tests are not required, estimation
can be done with an arbitrary h.
There are five options: eps1 = .05, .10, .15, .20 or .25.
For each option, the maximal value of m above is: 10 for eps1 = .05;
8 for eps1 = .10, 5 for eps1 = .15, 3 for eps1 = .20 and 2 for eps1 = .25.@
h=int(eps1*bigt); @minimal length of a segment (h >= q). Note: If
robust=1, h should be set at a larger value.@
/* the following are options if p > 0.
----------------------------------- */
fixb=0; @set to 1 if use fixed initial values for beta@
betaini=0; @if fixb=1, load the initial value of beta.@
maxi=20; @maximum number of iterations for the nonlinear
procedure to obtain global minimizers.@
printd=1; @set to 1 if want the output from the iterations
to be printed.@
eps=0.0001; @criterion for the convergence.@
/*--------------------------------- */
robust=1; @set to 1 if want to allow for heterogeneity
and autocorrelation the in residuals, 0 otherwise.
The method used is Andrews(1991) automatic
bandwidth with AR(1) approximation and the
quadratic quernel. Note: Do not set to 1 if
lagged dependent variables are included as
regressors.@
prewhit=1; @set to 1 if want to apply AR(1) prewhitening
prior to estimating the long run covariance
matrix@
hetdat=1; @Option for the construction of the F-tests.
Set to 1 if want to allow different moment matrices of the
regressors accross segments. If hetdat = 0, the same
moment matrices are assumed for each segment and estimated
from the full sample. It is recommended to set hetdat=1. If p > 0
set hetdat = 1.@
hetvar=1; @Option for the construction of the F-tests.
Set to 1 if want to allow for the variance of the residuals
to be different across segments. If hetvar=0, the variance
of the residuals is assumed constant across segments
and constructed from the full sample. This option is not available
when robust = 1.@
hetomega=1; @Used in the construction of the confidence
intervals for the break dates. If hetomega=0,
the long run covariance matrix of zu is assumed
identical accross segments (the variance of the
errors u if robust = 0).@
hetq=1; @Used in the construction of the confidence
intervals for the break dates. If hetq=0,
the moment matrix of the data is assumed
identical accross segments.@
doglobal=1; @set to 1 if want to call the procedure
to obtain global minimizers.@
dotest=1; @set to 1 if want to construct the sup F,
UDmax and WDmax tests. doglobal must be set
to 1 to run this procedure.@
dospflp1=1; @set to 1 if want to construct the sup(l+1|l)
tests where under the null the l breaks are
obtained using global minimizers. doglobal
must be set to 1 to run this procedure.@
doorder=1; @set to 1 if want to call the procedure that
selects the number of breaks using information
criteria. doglobal must be set to 1 to run
this procedure.@
dosequa=1; @set to 1 if want to estimate the breaks
sequentially and estimate the number of
breaks using the supF(l+1|l) test.@
dorepart=1; @set to 1 if want to modify the
break dates obtained from the sequential
method using the repartition method of
Bai (1995), Estimating breaks one at a time.
This is needed for the confidence intervals
obtained with estim below to be valid.@
estimbic=1; @set to 1 if want to estimate the model with
the number of breaks selected by BIC.@
estimlwz=0; @set to 1 if want to estimate the model with
the number of breaks selected by LWZ.@
estimseq=1; @set to 1 if want to estimate the model with
the number of breaks selected using the
sequential procedure.@
estimrep=0; @set to 1 if want to esimate the model with
the breaks selected using the repartition
method.@
estimfix=0; @set to 1 if want to estimate the model with
a prespecified number of breaks equal to fixn
set below.@
fixn=0;
call pbreak(bigt,y,z,q,m,h,eps1,robust,prewhit,hetomega,
hetq,doglobal,dotest,dospflp1,doorder,dosequa,dorepart,estimbic,estimlwz,
estimseq,estimrep,estimfix,fixb,x,q,eps,maxi,fixb,betaini,printd,hetdat,hetvar,fixn);
#include brcode.src @set the path to where you store the file brcode.src@
end;Code taken from : Journal of Applied Econometrics Data Archive: Data Directory
