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Build a semi-synthetic panel from real data

Source: R/sim.R
sim_semisynthetic.Rd

Takes a real long panel, uses its outcomes (optionally smoothed through a low-rank-plus-two-way-fixed-effects fit) as the untreated potential outcomes Y(0), and imposes a known treatment effect on a chosen block of units and periods. Because the baseline is real data but the effect is known, the result is a ground-truth benchmark that "closely matches" the real setting – the style of semi-synthetic experiment used to evaluate panel estimators in Athey, Imbens, Qu & Viviano (2026). Pair it with panel_compare() or panel_rmse() to score estimators against the truth.

Usage

sim_semisynthetic(
  data,
  outcome,
  unit,
  time,
  n_treated,
  t0 = NULL,
  att = 1,
  effect = NULL,
  baseline = c("observed", "lowrank"),
  lambda_nn = NULL,
  noise = 0,
  seed = NULL
)

Arguments

data

A real long data.frame, one row per unit-time.

outcome, unit, time

Column names (strings).

n_treated

Number of units to assign to the placebo treated group (sampled at random from all units).

t0

First treated period (block design). Defaults to about three quarters of the way through the panel.

att

Constant additive treatment effect imposed on treated cells. Ignored if effect is supplied.

effect

Optional per-treated-period effect: a single number, or a numeric vector of length T - t0 + 1 giving a dynamic effect path.

baseline

"observed" uses the real outcomes directly as Y(0); "lowrank" replaces them with a low-rank + two-way-FE fit (optionally plus resampled residuals scaled by noise) for a smoother synthetic baseline.

lambda_nn

Nuclear-norm penalty for the "lowrank" baseline fit.

noise

For "lowrank", standard-deviation multiplier on resampled residuals added back to the fit (0 = noiseless baseline).

seed

Optional RNG seed.

Value

A long data.frame with columns id, t, y, w, y0 (the imposed untreated potential outcome) and tau (the true effect, 0 off treatment).

See also

sim_panel(), panel_compare(), panel_rmse()

Examples

real <- sim_panel(N = 16, T = 10, n_treated = 0L, att = 0, seed = 1)
ss <- sim_semisynthetic(real, "y", "id", "t",
                        n_treated = 6, t0 = 8, att = 3, seed = 2)
mean(ss$tau[ss$w == 1])   # true ATT = 3
#> [1] 3