Supply and use tables — build_supply

Create a table with processes, their inputs (use) and their outputs (supply).

Usage

build_supply_use(
  cbs_version = NULL,
  feed_intake_version = NULL,
  primary_prod_version = NULL,
  primary_residues_version = NULL,
  processing_coefs_version = NULL
)

Arguments

cbs_version: File version passed to get_wide_cbs() call.
feed_intake_version: File version passed to get_feed_intake() call.
primary_prod_version: File version passed to get_primary_production() call.
primary_residues_version: File version passed to get_primary_residues() call.
processing_coefs_version: File version passed to get_processing_coefs() call.

Value

A tibble with the supply and use data for processes. It contains the following columns:

year: The year in which the recorded event occurred.
area_code: The code of the country where the data is from. For code details see e.g. add_area_name().
proc_group: The type of process taking place. It can be one of:
- crop_production: Production of crops and their residues, e.g. rice production, coconut production, etc.
- husbandry: Animal husbandry, e.g. dairy cattle husbandry, non-dairy cattle husbandry, layers chickens farming, etc.
- processing: Derived subproducts obtained from processing other items. The items used as inputs are those that have a non-zero processing use in the commodity balance sheet. See get_wide_cbs() for more details. In each process there is a single input. In some processes like olive oil extraction or soyabean oil extraction this might make sense. Others like alcohol production need multiple inputs (e.g. multiple crops work), so in this data there would not be a process like alcohol production but rather a virtual process like 'Wheat and products processing', giving all its possible outputs. This is a constraint because of how the data was obtained and might be improved in the future. See get_processing_coefs() for more details.
proc_cbs_code: The code of the main item in the process taking place. Together with proc_group, these two columns uniquely represent a process. The main item is predictable depending on the value of proc_group:
- crop_production: The code is from the item for which seed usage (if any) is reported in the commodity balance sheet (see get_wide_cbs() for more). For example, the rice code for a rice production process or the cottonseed code for the cotton production one.
- husbandry: The code of the farmed animal, e.g. bees for beekeeping, non-dairy cattle for non-dairy cattle husbandry, etc.
- processing: The code of the item that is used as input, i.e., the one that is processed to get other derived products. This uniquely defines a process within the group because of the nature of the data that was used, which you can see in get_processing_coefs().
For code details see e.g. add_item_cbs_name().
item_cbs_code: The code of the item produced or used in the process. Note that this might be the same value as proc_cbs_code, e.g., in rice production process for the row defining the amount of rice produced or the amount of rice seed as input, but it might also have a different value, e.g. for the row defining the amount of straw residue from rice production. For code details see e.g. add_item_cbs_name().
type: Can have two values:
- use: The given item is an input of the process.
- supply: The given item is an output of the process.
value: Quantity in tonnes.

Examples

# Note: These are smaller samples to show outputs, not the real data.
# For all data, call the function with default versions (i.e. no arguments).
build_supply_use(
  cbs_version = "20250721T132006Z-8ea47",
  feed_intake_version = "20250721T143825Z-c1313",
  primary_prod_version = "20250721T145805Z-8e12a",
  primary_residues_version = "20250721T150132Z-dfd94",
  processing_coefs_version = "20250721T143403Z-216d7"
)
#> ℹ Fetching files for primary_prod...
#> ℹ Fetching files for crop_residues...
#> ℹ Fetching files for commodity_balance_sheet...
#> ℹ Fetching files for feed_intake...
#> ℹ Fetching files for processing_coefs...
#> # A tibble: 27,914 × 7
#>     year area_code proc_group      proc_cbs_code item_cbs_code type       value
#>    <dbl>     <dbl> <chr>                   <dbl>         <dbl> <chr>      <dbl>
#>  1  1965        38 crop_production          2645          2645 supply     4460 
#>  2  1984        50 crop_production          2625          2625 supply       45 
#>  3  2003       131 crop_production          2577          2577 supply 13354800 
#>  4  1996       235 crop_production          2517          2517 supply     1600 
#>  5  2021        10 crop_production          2511          2511 supply 31922555.
#>  6  1970        41 crop_production          2605          2605 supply     7000 
#>  7  1997       222 crop_production          2605          2605 supply    12000 
#>  8  2003        59 crop_production          2662          2662 supply     2049.
#>  9  1966       236 crop_production          2549          2549 supply     5891 
#> 10  1976       105 crop_production          2533          2533 supply      800 
#> # ℹ 27,904 more rows