Extensive/intensive first-difference decomposition for a hurdle- or ZI-CPB

The effect of moving variable from one value to another, decomposed into the change in the participation (extensive) margin, the intensity (intensive) margin, and the marginal expected count, holding other covariates at their means. This is the quantity the single-equation defaults cannot separate.

Usage

# S3 method for class 'hurdle_cpb'
first_difference(
  object,
  variable,
  from,
  to,
  B = 0,
  level = 0.95,
  data = NULL,
  stage = c("both", "participation", "intensity", "zero", "count"),
  cores = 1L,
  ...
)

# S3 method for class 'zi_cpb'
first_difference(
  object,
  variable,
  from,
  to,
  B = 0,
  level = 0.95,
  data = NULL,
  stage = c("both", "participation", "intensity", "zero", "count"),
  cores = 1L,
  ...
)

Arguments

object

A "hurdle_cpb" or "zi_cpb" object.

variable

Name of a model-matrix column to vary (in either margin).

from, to

The two values to contrast.

B

Bootstrap replicates for percentile intervals; 0 (default) returns point estimates only. For zi_cpb the bootstrap is slow (each replicate refits the mixture).

level

Confidence level.

data

The original data frame; required when B > 0.

stage

Which equation(s) the covariate moves in: "both" (default), the binary stage only ("participation"/"zero"), or the count stage only ("intensity"/"count"), holding the covariate at its reference in the other equation. All three component rows are always returned.

cores

Worker processes for the bootstrap refits (default 1); see cpb().

...

Unused; unknown arguments error.

Value

A "ud_fd" data frame (the package-wide first-difference contract): columns component, from, to, diff, lower, upper, method, one row per margin level.