target_market_share: Add targets for production, using the market share approach

View source: R/target_market_share.R

target_market_shareR Documentation

Add targets for production, using the market share approach

Description

This function calculates the portfolio-level production targets, as calculated using the market share approach applied to each relevant climate production forecast.

Usage

target_market_share(
  data,
  abcd,
  scenario,
  region_isos = r2dii.data::region_isos,
  use_credit_limit = FALSE,
  by_company = FALSE,
  weight_production = TRUE,
  ald = deprecated()
)

Arguments

data

A "data.frame" like the output of r2dii.match::prioritize.

abcd

An asset level data frame like r2dii.data::abcd_demo.

scenario

A scenario data frame like r2dii.data::scenario_demo_2020.

region_isos

A data frame like r2dii.data::region_isos (default).

use_credit_limit

Logical vector of length 1. FALSE defaults to using the column loan_size_outstanding. Set to TRUE to use the column loan_size_credit_limit instead.

by_company

Logical vector of length 1. FALSE defaults to outputting production_value at the portfolio-level. Set to TRUE to output production_value at the company-level.

weight_production

Logical vector of length 1. TRUE defaults to outputting production, weighted by relative loan-size. Set to FALSE to output the unweighted production values.

ald

[Superseded] ald has been superseded by abcd.

Value

A tibble including the summarized columns metric, production, technology_share, percentage_of_initial_production_by_scope and scope. If by_company = TRUE, the output will also have the column name_abcd.

Handling grouped data

This function ignores existing groups and outputs ungrouped data.

See Also

Other functions to calculate scenario targets: target_sda()

Examples

installed <- requireNamespace("r2dii.data", quietly = TRUE) &&
  requireNamespace("r2dii.match", quietly = TRUE) &&
  packageVersion("r2dii.match") >= "0.1.0"

if (installed) {
  library(r2dii.data)
  library(r2dii.match)

  loanbook <- head(loanbook_demo, 100)
  abcd <- head(abcd_demo, 100)

  matched <- loanbook %>%
    match_name(abcd) %>%
    prioritize()

  # Calculate targets at portfolio level
  matched %>%
    target_market_share(
      abcd = abcd,
      scenario = scenario_demo_2020,
      region_isos = region_isos_demo
    )

  # Calculate targets at company level
  matched %>%
    target_market_share(
      abcd = abcd,
      scenario = scenario_demo_2020,
      region_isos = region_isos_demo,
      by_company = TRUE
    )

  matched %>%
    target_market_share(
      abcd = abcd,
      scenario = scenario_demo_2020,
      region_isos = region_isos_demo,
      # Calculate unweighted targets
      weight_production = FALSE
    )
}

r2dii.analysis documentation built on Nov. 3, 2022, 5:06 p.m.