plot.scm_frontier: Plot a Balance Possibility Frontier

In coresynth: Fast and Unified Synthetic Control Methods

Plot a Balance Possibility Frontier

Description

Draws the trade-off traced by scm_balance_frontier(): the imbalance of the treated average, which the aggregate ATT rests on, against the root mean square of the per-block imbalances, which the block-level effects rest on. Separate SCM sits at one end of the curve and fully pooled SCM at the other, with the heuristic the fit used marked along it.

Usage

## S3 method for class 'scm_frontier'
plot(x, relative = TRUE, label_nu = TRUE, colors = NULL, ...)

Arguments

x	An scm_frontier object from scm_balance_frontier().
relative	Plot the imbalances normalised by the separate solution (default), which puts both axes on comparable scales, rather than in the outcome's own units.
label_nu	Annotate the drawn points with their nu.
colors	Optional named overrides for the "frontier" line and the "heuristic" marker.
...	Ignored.

Details

The curve is normally strongly convex, which is the point of looking at it: a small move away from either end usually buys a large reduction in the other imbalance for very little, so the interesting values of nu are the ones near the bend.

Value

A ggplot2 plot object.

See Also

scm_balance_frontier()

Examples

set.seed(1)
panel <- expand.grid(unit = 1:15, year = 1:20)
adopt <- c(`1` = 12, `2` = 15, `3` = 17)
panel$treated <- as.integer(!is.na(adopt[as.character(panel$unit)]) &
  panel$year >= adopt[as.character(panel$unit)])
panel$treated[is.na(panel$treated)] <- 0L
panel$gdp <- panel$unit + 0.4 * panel$year +
  rnorm(nrow(panel)) + 2 * panel$treated
fit <- scm_fit(gdp ~ treated | unit + year, data = panel, method = "scm")
plot(scm_balance_frontier(fit, nu_grid = c(0, 0.25, 0.5, 0.75, 1)))

coresynth documentation built on Oct. 11, 2026, 5:07 p.m.