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Average treatment effects on the treated from an ETWFE fit

Source: R/etwfe.R
summary.panglm_etwfe.Rd

Averages, over the treated observations, the difference between the predicted mean with and without the observation's cohort by period effect (on the response scale). The averages are taken over all treated observations ("simple"), by cohort ("group"), by calendar period ("calendar") or by time since treatment ("event"), with delta-method standard errors. With sampling weights in etwfe(), the averages are weighted. They correspond to etwfe::emfx(). With control = "never", the event study also reports the pre-treatment placebo effects, with event time -1 as the reference (zero).

Usage

# S3 method for class 'panglm_etwfe'
summary(
  object,
  type = c("simple", "group", "calendar", "event"),
  level = object$level,
  byxvar = !is.null(object$xvar),
  ...
)

Arguments

object

a "panglm_etwfe" fit from etwfe()

type

"simple", "group", "calendar" or "event"

level

confidence level; defaults to that of the fit

byxvar

logical; for a fit with xvar, report the ATTs separately for each value of the covariate (by aggregation level and value). The default is TRUE for such fits; overall is always the ATT over all treated observations.

...

unused

Value

an object of class "summary.panglm_etwfe": a list with overall (the simple ATT: estimate, se, statistic, p.value, lower, upper), estimates (the same columns by level of the aggregation, and by value of the xvar covariate in a column named after it when byxvar = TRUE; NULL for "simple" without byxvar), cells and the fit information.

See also

Other etwfe methods: plot.panglm_etwfe()

Examples

set.seed(2)
d <- expand.grid(id = 1:150, t = 1:8)
d$first <- rep(c(4, 6, NA), each = 50)[d$id]
d$y <- rbinom(nrow(d), 1, plogis(-1 + 0.1 * d$t +
  0.8 * (!is.na(d$first) & d$t >= d$first)))
fit <- etwfe(y ~ 1, d, index = c("id", "t"), treat = "first", family = "binomial")
summary(fit, type = "event")
#> 
#> Extended TWFE (Wooldridge), logit model, control group: not yet treated
#> Observations: 1200  Individuals: 150  vcov: cluster 
#> Fixed effects: cohort and period
#> 
#> ATT (response scale): 0.2108 (SE 0.06119, 95% CI 0.09088 to 0.3308, p = 0.0005711)
#> 
#>  event estimate      se statistic  p.value    lower  upper
#>      0   0.2275 0.07474     3.044 0.002335  0.08102 0.3740
#>      1   0.1772 0.07631     2.322 0.020212  0.02766 0.3268
#>      2   0.2018 0.08722     2.314 0.020657  0.03090 0.3728
#>      3   0.1862 0.12379     1.504 0.132495 -0.05640 0.4288
#>      4   0.2871 0.10781     2.663 0.007735  0.07584 0.4985
#>