plotIrf#

Purpose#

Plot impulse response functions in an m × m grid. Each cell shows the response of one variable to a one-standard-deviation shock to another.

Format#

plotIrf(irf)#

Parameters:: irf (struct irfResult) – IRF result from irfCompute() or girfCompute().

Examples#

Cholesky IRF Grid#

library timeseries;

fname = getGAUSSHome("pkgs/timeseries/examples/data/us_macro_quarterly.csv");
data = loadd(fname, "gdp_growth + cpi_inflation + fed_funds");

ctl = varControlCreate();
ctl.p = 4;
ctl.quiet = 1;

rv = varFit(data, ctl);
irf = irfCompute(rv, 20);

// 3×3 grid of impulse responses
plotIrf(irf);

Save to File#

plotIrf(irf);
plotSave("irf_grid.png", "px", 900 | 900);

Remarks#

Grid layout: Row i, column j shows the response of variable i to a shock to variable j. Each cell is titled “response ← shock” using the variable names from the estimation result.

Zero line: A horizontal dashed gray line at zero is drawn in every cell. If the IRF stays above (or below) zero at all horizons, the effect is consistently positive (or negative).

Diagonal cells: These show each variable’s response to its own shock. For Cholesky identification, the impact response (h=0) on the diagonal equals the Cholesky factor of \(\Sigma\).

For credible bands: Use plotSvIrf() with an svIrfResult from irfSvCompute(). The point-estimate plotIrf() does not show bands.