Calculates the shares of imports to total consumption by product, for each country and year.

The function calculates the shares of imports to total consumption by product, for each country and year.

calc_share_imports_by_products(
  .tidy_iea_df,
  flow = IEATools::iea_cols$flow,
  country = IEATools::iea_cols$country,
  method = IEATools::iea_cols$method,
  energy_type = IEATools::iea_cols$energy_type,
  last_stage = IEATools::iea_cols$last_stage,
  ledger_side = IEATools::iea_cols$ledger_side,
  flow_aggregation_point = IEATools::iea_cols$flow_aggregation_point,
  year = IEATools::iea_cols$year,
  product = IEATools::iea_cols$product,
  unit = IEATools::iea_cols$unit,
  e_dot = IEATools::iea_cols$e_dot,
  imports = IEATools::interface_industries$imports,
  matnames = "matnames",
  Total_Consumption_By_Product = "Total_Consumption_By_Product",
  Share_Imports_By_Product = "Share_Imports_By_Product"
)

Arguments

.tidy_iea_df

The .tidy_iea_df for which the shares of imports over final consumption, by product, need to be calculated.

flow, country, method, energy_type, last_stage, ledger_side, flow_aggregation_point, year, product, unit, e_dot

See IEATools::iea_cols.

imports

The name of the column containing the quantity (in energy terms) of imported products. Default is IEATools::interface_industries$imports.

matnames

The column name for matrices names. Default is IEATools::mat_meta_cols$matnames.

Total_Consumption_By_Product

The name of the new column returning total consumption by product.

Share_Imports_By_Product

The name of the new column returning the share of imports over total consumption.

Value

A data frame returning the share of imports over final consumption, for each product.

Details

Total consumption is calculated using the calc_total_consumption_by_product() function.

Note: the function needs to have a column indicating matrix names added first, most likely using the IEATools::add_psut_matnames() function.

Examples

tidy_AB_data %>%
IEATools::add_psut_matnames() %>%
calc_share_imports_by_products() %>%
print()
#> # A tibble: 21 × 9
#> # Groups:   Country, Method, Energy.type, Last.stage, Year, Product [21]
#>    Country Method Energy.type Last.stage  Year Product    Total_Consumption_By…¹
#>    <chr>   <chr>  <chr>       <chr>      <dbl> <chr>                       <dbl>
#>  1 A       PCM    E           Final       2018 Blast fur…                    850
#>  2 A       PCM    E           Final       2018 Coke oven…                   1000
#>  3 A       PCM    E           Final       2018 Coking co…                   3000
#>  4 A       PCM    E           Final       2018 Coking co…                   5000
#>  5 A       PCM    E           Final       2018 Crude oil                    5000
#>  6 A       PCM    E           Final       2018 Crude oil…                   8500
#>  7 A       PCM    E           Final       2018 Electrici…                   3200
#>  8 A       PCM    E           Final       2018 Heat                          250
#>  9 A       PCM    E           Final       2018 Kerosene …                   1750
#> 10 A       PCM    E           Final       2018 Motor gas…                   2400
#> # ℹ 11 more rows
#> # ℹ abbreviated name: ¹​Total_Consumption_By_Product
#> # ℹ 2 more variables: Imports <dbl>, Share_Imports_By_Product <dbl>