knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

The goal of this article is to define the market-share-approach for allocating scenario efforts and to show how to calculate the market-share target for a given scenario.

Scenario market-shares

Say that you want to study how a portfolio would perform in a specific climate scenario. How can you allocate scenario efforts to the production profile of your portfolio? You can do that in two ways -- by technology, or by sector.

1. Market-share by technology

We define the market-share by technology as:

$$p_{i}^{tmsr}(t) = p_{i}(t_{0}) + p_{i}(t_{0}) * \frac{s_i(t) - s_{i}(t_0)}{s_i(t_0)}$$

We can see that this reduces to:

$$p_{i}^{tmsr}(t) = p_{i}(t_{0}) \left(1 + \frac{s_i(t) - s_{i}(t_0)}{s_i(t_0)} \right) \ p_{i}^{tmsr}(t) = p_{i}(t_{0}) \left(1 + \frac{s_i(t)}{s_i(t_0)} -1 \right) \ p_{i}^{tmsr}(t) = p_{i}(t_{0}) * \frac{s_i(t)}{s_i(t_0)}$$

where:

We define the "Technology Market Share Ratio" as:

$$\dfrac{s_i(t)}{s_i(t_0)}$$ This method is used to set targets for "decreasing" (ie. brown) technologies.

2. Market-share by sector

To calculate the market-share by sector, we use the initial production of both the portfolio and scenario at the sector-level instead. $$p_{i}^{smsp}(t) = p_{i}(t_0) +P(t_0) * \left( \dfrac{s_i(t)-s_i(t_0)}{S(t_0)}\right)$$ where:

We define the "Sector Market Share Percentage" as:

$$\dfrac{s_i(t)-s_i(t_0)}{S(t_0)}$$ This method is used to calculate targets for "increasing" (ie. green) technologies.

How to calculate market-share targets for a given scenario

To calculate market-share targets, you need to use the package r2dii.analysis and a number of datasets. One of those datasets is a "matched" dataset (loanbook + asset-level data) that you can get with the package r2dii.match. The datasets I use here come from the package r2dii.data; they are fake but show how you should structure your own data.

library(r2dii.data)
library(r2dii.match)
library(r2dii.analysis)
loanbook <- r2dii.data::loanbook_demo
abcd <- r2dii.data::abcd_demo

matched <- match_name(loanbook, abcd) %>%
  # WARNING: Remember to validate the output of match_name() before prioritize()
  prioritize()

matched
# portfolio level targets
scenario <- r2dii.data::scenario_demo_2020
regions <- r2dii.data::region_isos_demo


matched %>% target_market_share(abcd, scenario, regions)
matched %>% target_market_share(abcd, scenario, regions, by_company = TRUE)


2DegreesInvesting/r2dii.analysis documentation built on May 18, 2022, 2:48 a.m.