residcov—421

Residual correlation matrix.

Displays the correlations of the residuals from each equation in the system, sspace, or var object, or the residuals from each pool cross-section equation. The sspace object residuals used in the calculation are the standardized, one-step ahead signal forecast errors.

Syntax

Options

Examples

sys1.residcor

displays the residual correlation matrix of SYS1.

Cross-references

See also residcov (p. 421) and makeresids (p. 359).

Residual covariance matrix.

Displays the covariances of the residuals from each equation in the system, sspace, or var object, or the residuals from each pool cross-section equation. The sspace object residuals used in the calculation are the standardized, one-step ahead signal forecast errors.

Syntax

Options

422—Appendix B. Command Reference

Examples

var1.residcov

displays the residual covariance matrix of VAR1.

Cross-references

See also residcor (p. 421) and makeresids (p. 359).

Display residuals.

For equation and pool objects, resids allows you to display the actual, fitted values and residuals in either tabular or graphical form.

For sspace objects, resids allows you to display the actual-fitted-residual graph.

For system, var or pool objects, resids displays multiple graphs of the residuals. Each graph will contain the residuals for each equation in the system or VAR, or for each crosssection in the pool.

Syntax

Examples

equation eq1.ls m1 c inc tb3 ar(1)

eq1.resids

regresses M1 on a constant, INC, and TB3, correcting for first order serial correlation, and displays a table of actual, fitted, and residual series.

eq1.resids(g)

displays a graph of the actual, fitted, and residual series.

rls—423

Cross-references

See also makeresids (p. 359).

Displays the results view of objects containing estimation output.

Syntax

Options

Examples

equation eq1.ls m1 c inc tb3 ar(1)

eq1.results(p)

estimates an equation using least squares, and displays and prints the results.

var mvar.ls 1 4 8 8 m1 gdp tb3 @ @trend(70.4)

mvar.results(p)

prints the estimation results from the estimated VAR.

Recursive least squares regression.

The rls view of an equation displays the results of recursive least squares (rolling) regression. This view is only available for (non-panel) equations estimated by ordinary least squares without ARMA terms.

You may plot various statistics from rls by choosing an option.

Syntax

424—Appendix B. Command Reference

Options

rPlot the recursive residuals about the zero line with plus and minus two standard errors.

cPlot the recursive coefficient estimates with two standard error bands.

oPlot the p-values of recursive one-step Chow forecast tests.

nPlot the p-values of recursive n-step Chow forecast tests.

qPlot the CUSUM (standardized cumulative recursive residual) and 5 percent critical lines.

vPlot the CUSUMSQ (CUSUM of squares) statistic and 5 percent critical lines.

Examples

equation eq1.ls m1 c tb3 gdp

eq1.rls(r,s)

eq1.rls(c) c(2) c(3)

plots and saves the recursive residual series from EQ1 and their standard errors as R_RES and R_RESSE. The third line plots the recursive slope coefficients of EQ1.

equation eq2.ls m1 c pdl(tb3,12,3) pdl(gdp,12,3)

eq2.rls(c) c(3)

eq2.rls(q)

The second command plots the recursive coefficient estimates of PDL02, the linear term in the polynomial of TB3 coefficients. The third line plots the CUSUM test statistic and the 5% critical lines.