*! version 1.0.0 28may2026
help xtcsnardl_graphalso see: xtcsnardl xtcsnardl_methodology xtcsnardl_examples xtcsnardl_postestimation

Publication-quality CS-NARDL graphs

Syntax

Invoked automatically by xtcsnardl, graph. Can also be called explicitly after
xtcsnardl (advanced):

xtcsnardl_graph
,
ec(name)
ivar(panelvar)
asymvars(varlist)
posvars(varlist)
negvars(varlist)
[periods(#) depvar(varname)]

Description

xtcsnardl_graph produces five publication-quality plots, each saved as a Stata graph
under a stable name() so you can graph export, graph combine, or restyle
them later.

Author names are deliberately omitted from titles, subtitles and notes - the plots are
intended to be dropped directly into a paper without further redaction.

Plots produced

Plot Name

1. ECT speed of adjustment csn_ect

2. LR asymmetry (beta+/-) csn_lr_asym

3. Dynamic multipliers csn_multip_1, csn_multip_2, ...

4. Asymmetric IRF csn_irf_1, csn_irf_2, ...

5. CSA loadings csn_csa

Plot 1. ECT speed of adjustment per panel (csn_ect)

Vertical bar chart of {&phi}i across panels, coloured by convergence class (strong
< -0.5, moderate, weak, non-convergent). 95% confidence whiskers are added via rcap.
The cross-section mean of {&phi} is overlaid as a dashed reference line.

Use for: showing heterogeneity in adjustment speed across panels and supporting the
choice of MG vs PMG.

Top-journal styling: white plot region, dotted gridlines, no chartjunk. Legend
position 6 (below), single row.

Plot 2. Long-run asymmetric coefficients (csn_lr_asym)

Grouped vertical bar chart of {&beta}+ and {&beta}- for every variable in
asymmetric(), with 95% CI whiskers. Variables are labelled on the x-axis.

Use for: visual evidence of long-run asymmetry. When the CIs of {&beta}+ and
{&beta}- do not overlap, the asymmetry test (Table 5) rejects symmetry.

Plot 3. Cumulative dynamic multipliers (csn_multip_<idx>)

For each asymmetric variable, plots m+(h), m-(h), the asymmetry curve
m+ - m- with a 95% confidence band, and the long-run targets {&beta}+ and
{&beta}- as dashed reference lines.

Use for: showing the speed of adjustment to asymmetric long-run targets and any
overshooting. This is the canonical CS-NARDL figure (see Mehta & Derbeneva 2024 Fig. 3).

Reading the asymmetry band: if the 95% CI on m+ - m- excludes zero from
some horizon onward, asymmetry is statistically significant at that horizon.

Plot 4. Asymmetric impulse responses (csn_irf_<idx>)

For each asymmetric variable, plots the response of y to a unit positive shock and to a unit
negative shock, with horizontal dashed reference lines at the long-run targets {&beta}+
and {&beta}-.

Use for: contrasting the trajectory (not just the cumulative effect) of positive
vs negative shocks.

Plot 5. CSA loadings (csn_csa)

Horizontal bar chart of the loadings on each CSA proxy, with 95% CI whiskers. Variables are
labelled csa(varname), L1.csa(varname), ... .

Use for: showing that CSA augmentation is "doing work" -- significant loadings
on CSA confirm the presence of common factors that the augmentation absorbs.

If most loadings are insignificant: consider reducing cr_lags() to save degrees
of freedom.

Restyling and exporting

All graphs use name(..., replace) so subsequent xtcsnardl calls overwrite them.
Export to PDF / EPS / PNG:

. graph export csn_ect.pdf, name(csn_ect) replace

. graph export csn_multip_1.png, name(csn_multip_1) width(1200) replace

Combine in a 2x2 panel:

. graph combine csn_ect csn_lr_asym csn_multip_1 csn_csa, cols(2) ///

title("CS-NARDL diagnostic dashboard") name(csn_combined, replace)

Restyle interactively:

. graph edit csn_multip_1

Customising the palette

The default palette is colour-blind safe (Tableau 10). To restyle for B&W printing, edit the
ado at the lcolor() / color() options. Example - replace the dynamic-multiplier
colours with greyscale:

.do c:\ado\plus\x\xtcsnardl_graph.ado

and search/replace:

"31 119 180" -> gs4 (positive series)

"214 39 40" -> gs10 (negative series)

Author

Dr Merwan Roudane

merwanroudane920@gmail.com

xtcsnardl v1.0.0, 28 May 2026

Also see

Online: xtcsnardl, xtcsnardl_methodology, xtcsnardl_examples, xtcsnardl_postestimation

Stata graphics: twoway, graph combine, graph export, palettes