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Evaluate an explicit elasticity specification grid

Source: R/robustness.R
lamp_elasticity_robustness.Rd

Runs every requested outcome, lag window and family, retaining failures and optional leave-one-area-out estimates. Register the primary outcome and specification before examining the grid. These are dependent, exploratory checks; selecting a favourable row does not establish a cause. The OLS and Poisson rows target different quantities and should not be interpreted as estimates of one common elasticity.

Usage

lamp_elasticity_robustness(
  panel,
  outcomes = "crime_total",
  lags = list(current = 0L, short = 0:1, distributed = 0:3),
  families = c("poisson", "ols_log"),
  cluster = c("area", "force"),
  leave_one_out = FALSE
)

Arguments

panel

A lamp_panel.

outcomes

Outcome column names.

lags

A named list of non-negative integer lag vectors.

families

Character vector containing "poisson", "ols_log", or both.

cluster

"area" or "force".

leave_one_out

Also fit each specification after omitting each area. This can be expensive on large panels.

Value

A tibble with every requested specification, omitted area, status, error message, lag-sum estimate and interval, and observed sample sizes.

See also

Other diagnostics: lamp_design_audit(), lamp_effect_summary(), lamp_placebo(), lamp_pretrends(), lamp_trend_sensitivity()

Examples

sim <- lamp_simulate(design = "continuous", n_areas = 12, seed = 1)
lamp_elasticity_robustness(sim, lags = list(current = 0, short = 0:1))
#> # A tibble: 4 × 14
#>   outcome    lag_specification lags  family omitted_area status message estimate
#>   <chr>      <chr>             <chr> <chr>  <chr>        <chr>  <chr>      <dbl>
#> 1 crime_tot… current           0     poiss… NA           ok     NA       -0.0519
#> 2 crime_tot… current           0     ols_l… NA           ok     NA       -0.0417
#> 3 crime_tot… short             0,1   poiss… NA           ok     NA        0.150 
#> 4 crime_tot… short             0,1   ols_l… NA           ok     NA        0.147 
#> # ℹ 6 more variables: std_error <dbl>, conf_low <dbl>, conf_high <dbl>,
#> #   n_rows <int>, n_areas <int>, n_clusters <int>