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
