Summarize a panselect fit
Usage
# S3 method for class 'panselect'
summary(object, ...)Value
an object of class "summary.panselect": a list with the
coefficient table (coefficients: estimate, standard error, z value
and p-value, using the default covariance of the fit), the selection
test (selection_test), the probit coefficients (probit) and the
fit information.
See also
Other panselect methods:
plot.pangmm(),
predict.panselect(),
vcov.panselect()
Examples
set.seed(3)
d <- data.frame(id = rep(1:100, each = 3), t = rep(1:3, 100))
d$x <- rnorm(300); d$z <- rnorm(300); v <- rnorm(300)
d$s <- as.numeric(0.5 + d$x + d$z + v > 0)
d$y <- ifelse(d$s == 1, 1 + d$x + 0.5 * v + rnorm(300), NA)
summary(panselect(s ~ x + z, y ~ x, data = d, index = c("id", "t"),
boot = 29, seed = 1))
#>
#> Call:
#> panselect(selection = s ~ x + z, outcome = y ~ x, data = d, index = c("id",
#> "t"), boot = 29, seed = 1)
#>
#> Wooldridge (1995) panel selection correction: fixed effects with Mundlak means, inverse Mills ratio by period
#> Selection sample: n = 300 groups = 100
#> Outcome sample: n = 193 groups = 94
#> Probits fitted for periods: 1, 2, 3
#>
#> Outcome equation (vcov: panel bootstrap, 29 replicates):
#> Estimate Std. Error z value Pr(>|z|)
#> x 0.9704 0.1243 7.809 5.78e-15 ***
#> lambda:1 0.3577 0.5316 0.673 0.501
#> lambda:2 0.1731 0.5164 0.335 0.737
#> lambda:3 0.5822 0.4667 1.247 0.212
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Test of selection bias (H0: all inverse Mills ratio coefficients are zero):
#> cluster-robust Wald chi2(3) = 1.473, p = 0.6885
#> bootstrap Wald chi2(3) = 1.621, p = 0.6545
#> Residual df: 95
#>