Introduction
The following is an example of implementing the lsdvFit
procedure for estimating least squares dummy variable models given by
$$Y = X_{1} + X_{2} + X_{3}$$
Estimate the model
This example uses previously simulated data stored in the GAUSS dataset "lsdv.dat". The model can be estimated in a single line using the GAUSS formula string syntax.
new;
library tsmt;
// Get file name with full path
dataset = getGAUSSHome() $+ "pkgs/tsmt/examples/lsdv.dat";
// Estimate the model
call lsdvFIT(dataset, "Y ~ X1 + X2 + X3", 50, 2);
Output
The output reads:
Bias Corrected Auto-regression Coefficients coeff std err t-stat prob Y-1 0.29891 0.00490 61.00745 0.01043 Y-2 0.00099 0.00496 0.19860 0.87519 Bias Corrected Regression Coefficients coeff std err t-stat prob X1 0.50511 0.00694 72.80321 0.00874 X2 0.50107 0.00689 72.73983 0.00875 X3 0.49650 0.00692 71.74688 0.00887 Total SS 7845.7652634122 Explained SS 4950.6572554781 Residual SS 2890.4866068818 Pooled SS 4.6214010523
Number of cases 500
Number of periods 50
Number of Degrees of Freedom 17433
Number of observations 25000
Number of missings 6567
lower upper bound bound Constraint Lagrangean = 0.0000 0.0000