boot_tgr: Bootstrap Confidence Intervals for the Technology Gap Ratio

In metafrontier: Analysis of Metafrontier Models for Efficiency and Productivity

Bootstrap Confidence Intervals for the Technology Gap Ratio

Description

Computes bootstrap confidence intervals for TGR estimates from a fitted metafrontier model. Supports both parametric (residual resampling) and nonparametric (case resampling) bootstraps.

Usage

boot_tgr(
  object,
  R = 999,
  type = c("parametric", "nonparametric"),
  level = 0.95,
  ci_type = c("percentile", "bca"),
  seed = NULL,
  progress = TRUE,
  ncores = 1L,
  ...
)

Arguments

object	a "metafrontier" object.
R	integer. Number of bootstrap replications (default 999).
type	character. "parametric" resamples from estimated error distributions; "nonparametric" resamples rows within groups with replacement.
level	numeric. Confidence level (default 0.95).
ci_type	character. "percentile" (default) or "bca" (bias-corrected and accelerated).
seed	optional integer seed for reproducibility.
progress	logical. Show progress bar (default TRUE).
ncores	integer. Number of CPU cores for parallel bootstrap (default 1, sequential). Requires the parallel package.
...	additional arguments passed to metafrontier.

Value

An object of class "boot_tgr" containing:

tgr_boot

R x n matrix of bootstrapped TGR values

tgr_original

original TGR estimates

ci

n x 2 matrix of observation-level confidence intervals

ci_group

data frame of group-level mean TGR intervals

R_effective

number of successful replications

R

requested number of replications

type

bootstrap type used

ci_type

CI type used

level

confidence level

Examples

sim <- simulate_metafrontier(n_groups = 2, n_per_group = 100,
                             seed = 42)
fit <- metafrontier(log_y ~ log_x1 + log_x2,
                    data = sim$data, group = "group",
                    meta_type = "stochastic")
boot <- boot_tgr(fit, R = 50, seed = 1)
print(boot)
confint(boot)

metafrontier documentation built on Aug. 19, 2026, 5:08 p.m.