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This file contains instructions for installation and use of the procedures adecm.g and jmle.g for
use in estimating the error correction matrix and cointegrating matrix in an Error Correction
Model.
Authors: Douglas Hodgson and Keith Vorkink, University of Rochester
Installation:
Copy the two .g files into the /gauss/src directory. They will be directly available by calling
into your program. There is no need to edit/add libraries.
Purpose:
The procedure adecm.g is the main procedure to call to estimate an Error Correction Model.
Within this procedure jmle.g is called to obtain johansen's MLE preliminary estimators
which are used to obtain the adaptive estimators. We note that jmle.g can be called independently
to estimate the cointegrating basis and error correction matrix. The main reference for this
procedure is Douglas Hodgson, (95), "Adaptive Estimation of Error Correction Models" RCER working
paper #410. The reader is also referred to James Hamilton's Time Series Analysis book for
Error Correction Representation and Johansen's MLE.
Format:
{b,vb} = adecm(y,k);
Inputs:
y nxr matrix, series where cointegration is assumed present
x nx(q-r) matrix, series assumed to have unit roots
Outputs:
b vector or coefficients of A, PSI, B (see Hodgson for representation)
vb covariance matrix of parameter estimates
Remarks:
The models assumes the distribution is symmetric and proceeds to estimate
the residual distribution nonparametrically. This requres trimming and smoothing
parameters that can be set to default values or specified by the user. Addititionally
the model can be estimated with or without a constant, this is chosen interactively
in the inputs procedure which also determines the lags to include in the model, the
trimming parameter, and the smoothing parameter.
Example:
loadm dat[658,5] = c:\gauss\data\cdxr1.txt;
fxr = ln(dat[1:658,2]);
sxr = ln(dat[1:658,5]);
y = sxr;
x = fxr;
{v,b} = adecm(y,x);
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