This article shows how to calculate the descriptive analysis of
coefficient of variation for emission profile, sector profile, and
transition risk profile.
Example company-level output of transition risk profile for
cov_emission_rank
comp_1 |
all |
10 |
comp_1 |
isic_4digit |
15 |
comp_1 |
tilt_subsector |
20 |
comp_1 |
unit |
25 |
comp_1 |
unit_isic_4digit |
30 |
comp_1 |
unit_tilt_subsector |
35 |
comp_2 |
all |
45 |
comp_2 |
isic_4digit |
50 |
comp_2 |
tilt_subsector |
55 |
comp_2 |
unit |
60 |
comp_2 |
unit_isic_4digit |
65 |
comp_2 |
unit_tilt_subsector |
70 |
Average cov_emission_rank
per company for emission
profile benchmarks
avg_cov_emission_rank_per_benchmark <- emission_product_example |>
select(all_of(c("companies_id", "grouping_emission", "cov_emission_rank"))) |>
filter(!is.na(cov_emission_rank)) |>
distinct() |>
mutate(sum_cov_emission_rank = sum(.data$cov_emission_rank, na.rm = TRUE), .by = "grouping_emission") |>
mutate(distinct_companies_per_benchmark = n_distinct(.data$companies_id, na.rm = TRUE), .by = "grouping_emission") |>
mutate("Average COV of emission rank for all firms" = sum_cov_emission_rank/distinct_companies_per_benchmark) |>
select(-all_of(c("sum_cov_emission_rank", "distinct_companies_per_benchmark", "cov_emission_rank", "companies_id"))) |>
distinct() |>
filter(grouping_emission %in% c("all", "tilt_subsector")) |>
rename("group" = "grouping_emission")
Average COV of emission rank for all firms per group
group
|
Average COV of emission rank for all firms
|
all
|
27.5
|
tilt_subsector
|
37.5
|
Example company-level output of transition risk profile for
cov_sector_target
comp_1 |
1.5C RPS |
2030 |
10 |
comp_1 |
1.5C RPS |
2050 |
15 |
comp_1 |
NZ 2050 |
2030 |
20 |
comp_1 |
NZ 2050 |
2050 |
25 |
comp_2 |
1.5C RPS |
2030 |
45 |
comp_2 |
1.5C RPS |
2050 |
50 |
comp_2 |
NZ 2050 |
2030 |
55 |
comp_2 |
NZ 2050 |
2050 |
60 |
Average cov_sector_target
per company for
grouping_sector
Average COV of sector target for all firms per scenario
scenario
|
Average COV of sector target for all firms
|
1.5C RPS_2030
|
27.5
|
1.5C RPS_2050
|
32.5
|
NZ 2050_2030
|
37.5
|
NZ 2050_2050
|
42.5
|
Example company-level output of transition risk profile for
cov_transition_risk
comp_1 |
1.5C RPS_2030_tilt_subsector |
10 |
comp_1 |
1.5C RPS_2050_tilt_subsector |
15 |
comp_1 |
NZ 2050_2030_tilt_subsector |
20 |
comp_1 |
NZ 2050_2050_tilt_subsector |
25 |
comp_2 |
1.5C RPS_2030_tilt_subsector |
45 |
comp_2 |
1.5C RPS_2050_tilt_subsector |
50 |
comp_2 |
NZ 2050_2030_tilt_subsector |
55 |
comp_2 |
NZ 2050_2050_tilt_subsector |
60 |
Average cov_transition_risk
per company for
tilt_subsector benchmarks of grouping_transition_risk
Average COV of transition risk for all firms per scenario of
tilt_subsector
group
group
|
scenario
|
Average COV of transition risk for all firms
|
tilt_subsector
|
1.5C RPS_2030
|
27.5
|
1.5C RPS_2050
|
32.5
|
NZ 2050
|
37.5
|
NZ 2050
|
42.5
|