Compute Lenghty contracts indicator

The indicator reveals whether the (average) contract duration of a contracting authority/company is significantly longer than the overall (average) contract duration, with reference to post-emergency contracts belonging to relevant economic market.

Motivation

The red flag considers at risk contracting authorities/companies with post-emergency contracts whose excessive duration is not justified by the nature of the crisis, that is, contracts longer than the overall average duration of contracts won after the emergency outbreak.

Scoring rule

The computation procedure returns 1 - p-value of the involved test - Wilcoxon test in this case - (so that high values of the indicator correspond to high levels of corruption risk). When computing the composite, it will be dichotomised to 1 if statistical test is significant, and 0 otherwise (see normalise()).

Main target unit

This indicator targets companies and contracting authorities.

Usage

ind_9(
  data,
  publication_date,
  stat_unit,
  eff_start,
  eff_end,
  emergency_name,
  ...
)

Arguments

data

a dataframe containing the data to use for computing the indicator.

publication_date

name of the variable in data containing the publication date of each contract.

stat_unit

name of the variable in data containing the target unit ID (in this case, company or contracting authority).

eff_start

name of the variable in data containing the effective start date of each contract.

eff_end

name of the variable in data containing the contract execution effective end date.

emergency_name

string specifying the name of the emergency to consider. Examples could include "Coronavirus" or "Terremoto Centro Italia 2016-2017".

...

other parameters to pass to generate_indicator_schema(), such as country_name (default: Italy).

Value

indicator schema as from generate_indicator_schema().

See also

mutate, if_else, filter, pull, group_by, summarise, context, rename ymd as_factor str_sub as_string

Examples

if (FALSE) {
if (interactive()) {
  ind_9(
    data = mock_data_core,
    publication_date = data_pubblicazione,
    stat_unit = cf_amministrazione_appaltante,
    eff_start = data_inizio_effettiva,
    eff_end = data_effettiva_ultimazione,
    emergency_name = "coronavirus"
  )
}
}