diff --git a/etl/steps/data/garden/faostat/2024-03-14/additional_variables.meta.yml b/etl/steps/data/garden/faostat/2024-03-14/additional_variables.meta.yml
index e8d7eb60289..c00bd9a7392 100644
--- a/etl/steps/data/garden/faostat/2024-03-14/additional_variables.meta.yml
+++ b/etl/steps/data/garden/faostat/2024-03-14/additional_variables.meta.yml
@@ -670,3 +670,14 @@ tables:
   # All metadata for maize_and_wheat and fertilizer_exports is prepared via script.
   # maize_and_wheat:
   # fertilizer_exports:
+  net_exports_as_share_of_supply:
+    variables:
+      net_exports_as_share_of_supply:
+        title: Net food trade as a share of domestic supply
+        unit: "%"
+        short_unit: "%"
+        description_short: |
+          Net exports of all agricultural products expressed as a share of domestic supply. This includes food for human consumption, animal feed, and other products.
+        description_processing: |
+          - This indicator is calculated as 100 x (exports - imports) / domestic supply.
+          - Imports, exports, and domestic supply encompass the total of all items across the following groups: cereals and grains, pulses, starchy roots, fruits and vegetables, oils and fats, sugar, meat, dairy and eggs, alcoholic beverages, and an other products. The latter group includes miscellaneous items such as spices, offals, and other minor commodities.
diff --git a/etl/steps/data/garden/faostat/2024-03-14/additional_variables.py b/etl/steps/data/garden/faostat/2024-03-14/additional_variables.py
index 5bd97b9f6df..d322901ab69 100644
--- a/etl/steps/data/garden/faostat/2024-03-14/additional_variables.py
+++ b/etl/steps/data/garden/faostat/2024-03-14/additional_variables.py
@@ -11,6 +11,183 @@
 # Get paths and naming conventions for current step.
 paths = PathFinder(__file__)
 
+# List of food groups created by OWID for FBSC (combination of FBS and FBSH).
+# Each food group contains one or more "item groups", defined in dataset by FAOSTAT.
+# Each item group contains one or more "item", defined by FAOSTAT.
+# The complete list of items coincides exactly with the complete list of items of FAOSTAT item group "Grand Total"
+# (with item group code 2901).
+# So all existing food items in FBSC are contained here, and there are no repetitions.
+# Notes:
+# * There are a few item groups that are not included here, namely "Vegetal Products" (item group code 2903),
+#   and "Animal Products" (item group code 2941). But their items are contained in other item groups, so including
+#   them would cause unnecessary repetition of items.
+# * To check for the components of an individual item group:
+# from etl.paths import DATA_DIR
+# metadata = Dataset(DATA_DIR / "meadow/faostat/2023-02-22/faostat_metadata")
+# item_groups = metadata["faostat_fbs_item_group"]
+# set(item_groups.loc[2941]["item"])
+FOOD_GROUPS_FBSC = {
+    "Cereals and grains": [
+        "00002905",  # Cereals, Excluding Beer
+        # Item group contains:
+        # 'Barley and products',
+        # 'Cereals, Other',
+        # 'Maize and products',
+        # 'Millet and products',
+        # 'Oats',
+        # 'Rice and products',
+        # 'Rye and products',
+        # 'Sorghum and products',
+        # 'Wheat and products',
+    ],
+    "Pulses": [
+        "00002911",  # Pulses
+        # Item group contains:
+        # 'Beans',
+        # 'Peas',
+        # 'Pulses, Other and products',
+    ],
+    "Starchy roots": [
+        "00002907",  # Starchy Roots
+        # Item group contains:
+        # 'Cassava and products',
+        # 'Potatoes and products',
+        # 'Roots, Other',
+        # 'Sweet potatoes',
+        # 'Yams',
+    ],
+    "Fruits and vegetables": [
+        "00002919",  # Fruits - Excluding Wine
+        # Item group contains:
+        # 'Apples and products',
+        # 'Bananas',
+        # 'Citrus, Other',
+        # 'Dates',
+        # 'Fruits, other',
+        # 'Grapefruit and products',
+        # 'Grapes and products (excl wine)',
+        # 'Lemons, Limes and products',
+        # 'Oranges, Mandarines',
+        # 'Pineapples and products',
+        # 'Plantains',
+        "00002918",  # Vegetables
+        # Item group contains:
+        # 'Onions',
+        # 'Tomatoes and products',
+        # 'Vegetables, other',
+    ],
+    "Oils and fats": [
+        "00002914",  # Vegetable Oils
+        # Item group contains:
+        # 'Coconut Oil',
+        # 'Cottonseed Oil',
+        # 'Groundnut Oil',
+        # 'Maize Germ Oil',
+        # 'Oilcrops Oil, Other',
+        # 'Olive Oil',
+        # 'Palm Oil',
+        # 'Palmkernel Oil',
+        # 'Rape and Mustard Oil',
+        # 'Ricebran Oil',
+        # 'Sesameseed Oil',
+        # 'Soyabean Oil',
+        # 'Sunflowerseed Oil'
+        "00002946",  # Animal fats group
+        # Item group contains:
+        # 'Butter, Ghee',
+        # 'Cream',
+        # 'Fats, Animals, Raw',
+        # 'Fish, Body Oil',
+        # 'Fish, Liver Oil'
+        "00002913",  # Oilcrops
+        # Item group contains:
+        # 'Coconuts - Incl Copra',
+        # 'Cottonseed',
+        # 'Groundnuts',
+        # 'Oilcrops, Other',
+        # 'Olives (including preserved)',
+        # 'Palm kernels',
+        # 'Rape and Mustardseed',
+        # 'Sesame seed',
+        # 'Soyabeans',
+        # 'Sunflower seed'
+        "00002912",  # Treenuts
+        # Item group contains:
+        # 'Nuts and products',
+    ],
+    "Sugar": [
+        "00002909",  # Sugar & Sweeteners
+        # Item group contains:
+        # 'Honey',
+        # 'Sugar (Raw Equivalent)',
+        # 'Sugar non-centrifugal',
+        # 'Sweeteners, Other',
+        "00002908",  # Sugar crops
+        # Item group contains:
+        # 'Sugar beet',
+        # 'Sugar cane',
+    ],
+    "Meat": [
+        "00002960",  # Fish and seafood
+        # Item group contains:
+        # 'Aquatic Animals, Others',
+        # 'Cephalopods',
+        # 'Crustaceans',
+        # 'Demersal Fish',
+        # 'Freshwater Fish',
+        # 'Marine Fish, Other',
+        # 'Molluscs, Other',
+        # 'Pelagic Fish',
+        "00002943",  # Meat, total
+        # Item group contains:
+        # 'Bovine Meat',
+        # 'Meat, Other',
+        # 'Mutton & Goat Meat',
+        # 'Pigmeat',
+        # 'Poultry Meat',
+    ],
+    "Dairy and eggs": [
+        "00002948",  # Milk - Excluding Butter
+        # Item group contains:
+        # 'Milk - Excluding Butter',
+        "00002949",  # Eggs
+        # Item group contains:
+        # 'Eggs',
+    ],
+    "Alcoholic beverages": [
+        "00002924",  # Alcoholic Beverages
+        # Item group contains:
+        # 'Alcohol, Non-Food',
+        # 'Beer',
+        # 'Beverages, Alcoholic',
+        # 'Beverages, Fermented',
+        # 'Wine',
+    ],
+    "Other": [
+        "00002928",  # Miscellaneous
+        # Item group contains:
+        # 'Infant food',
+        # 'Miscellaneous',
+        "00002923",  # Spices
+        # Item group contains:
+        # 'Cloves',
+        # 'Pepper',
+        # 'Pimento',
+        # 'Spices, Other',
+        "00002922",  # Stimulants
+        # Item group contains:
+        # 'Cocoa Beans and products',
+        # 'Coffee and products',
+        # 'Tea (including mate)',
+        "00002945",  # Offals
+        # Item group contains:
+        # 'Offals, Edible',
+        "00002961",  # Aquatic Products, Other
+        # 'Aquatic Plants',
+        # 'Meat, Aquatic Mammals',
+    ],
+}
+
 
 def generate_arable_land_per_crop_output(tb_rl: Table, tb_qi: Table) -> Table:
     # Item code for item "Arable land" of faostat_rl dataset.
@@ -280,194 +457,19 @@ def generate_food_available_for_consumption(tb_fbsc: Table) -> Table:
     error = "Units for food available for consumption have changed."
     assert list(tb_fbsc["unit"].unique()) == [CONSUMPTION_UNIT], error
 
-    # List of food groups created by OWID.
-    # Each food group contains one or more "item groups", defined by FAOSTAT.
-    # Each item group contains one or more "item", defined by FAOSTAT.
-    # The complete list of items coincides exactly with the complete list of items of FAOSTAT item group "Grand Total"
-    # (with item group code 2901).
-    # So all existing food items in FBSC are contained here, and there are no repetitions.
-    # Notes:
-    # * There are a few item groups that are not included here, namely "Vegetal Products" (item group code 2903),
-    #   and "Animal Products" (item group code 2941). But their items are contained in other item groups, so including
-    #   them would cause unnecessary repetition of items.
-    # * To check for the components of an individual item group:
-    # from etl.paths import DATA_DIR
-    # metadata = Dataset(DATA_DIR / "meadow/faostat/2023-02-22/faostat_metadata")
-    # item_groups = metadata["faostat_fbs_item_group"]
-    # set(item_groups.loc[2941]["item"])
-    FOOD_GROUPS = {
-        "Cereals and grains": [
-            "00002905",  # Cereals, Excluding Beer
-            # Item group contains:
-            # 'Barley and products',
-            # 'Cereals, Other',
-            # 'Maize and products',
-            # 'Millet and products',
-            # 'Oats',
-            # 'Rice and products',
-            # 'Rye and products',
-            # 'Sorghum and products',
-            # 'Wheat and products',
-        ],
-        "Pulses": [
-            "00002911",  # Pulses
-            # Item group contains:
-            # 'Beans',
-            # 'Peas',
-            # 'Pulses, Other and products',
-        ],
-        "Starchy roots": [
-            "00002907",  # Starchy Roots
-            # Item group contains:
-            # 'Cassava and products',
-            # 'Potatoes and products',
-            # 'Roots, Other',
-            # 'Sweet potatoes',
-            # 'Yams',
-        ],
-        "Fruits and vegetables": [
-            "00002919",  # Fruits - Excluding Wine
-            # Item group contains:
-            # 'Apples and products',
-            # 'Bananas',
-            # 'Citrus, Other',
-            # 'Dates',
-            # 'Fruits, other',
-            # 'Grapefruit and products',
-            # 'Grapes and products (excl wine)',
-            # 'Lemons, Limes and products',
-            # 'Oranges, Mandarines',
-            # 'Pineapples and products',
-            # 'Plantains',
-            "00002918",  # Vegetables
-            # Item group contains:
-            # 'Onions',
-            # 'Tomatoes and products',
-            # 'Vegetables, other',
-        ],
-        "Oils and fats": [
-            "00002914",  # Vegetable Oils
-            # Item group contains:
-            # 'Coconut Oil',
-            # 'Cottonseed Oil',
-            # 'Groundnut Oil',
-            # 'Maize Germ Oil',
-            # 'Oilcrops Oil, Other',
-            # 'Olive Oil',
-            # 'Palm Oil',
-            # 'Palmkernel Oil',
-            # 'Rape and Mustard Oil',
-            # 'Ricebran Oil',
-            # 'Sesameseed Oil',
-            # 'Soyabean Oil',
-            # 'Sunflowerseed Oil'
-            "00002946",  # Animal fats group
-            # Item group contains:
-            # 'Butter, Ghee',
-            # 'Cream',
-            # 'Fats, Animals, Raw',
-            # 'Fish, Body Oil',
-            # 'Fish, Liver Oil'
-            "00002913",  # Oilcrops
-            # Item group contains:
-            # 'Coconuts - Incl Copra',
-            # 'Cottonseed',
-            # 'Groundnuts',
-            # 'Oilcrops, Other',
-            # 'Olives (including preserved)',
-            # 'Palm kernels',
-            # 'Rape and Mustardseed',
-            # 'Sesame seed',
-            # 'Soyabeans',
-            # 'Sunflower seed'
-            "00002912",  # Treenuts
-            # Item group contains:
-            # 'Nuts and products',
-        ],
-        "Sugar": [
-            "00002909",  # Sugar & Sweeteners
-            # Item group contains:
-            # 'Honey',
-            # 'Sugar (Raw Equivalent)',
-            # 'Sugar non-centrifugal',
-            # 'Sweeteners, Other',
-            "00002908",  # Sugar crops
-            # Item group contains:
-            # 'Sugar beet',
-            # 'Sugar cane',
-        ],
-        "Meat": [
-            "00002960",  # Fish and seafood
-            # Item group contains:
-            # 'Aquatic Animals, Others',
-            # 'Cephalopods',
-            # 'Crustaceans',
-            # 'Demersal Fish',
-            # 'Freshwater Fish',
-            # 'Marine Fish, Other',
-            # 'Molluscs, Other',
-            # 'Pelagic Fish',
-            "00002943",  # Meat, total
-            # Item group contains:
-            # 'Bovine Meat',
-            # 'Meat, Other',
-            # 'Mutton & Goat Meat',
-            # 'Pigmeat',
-            # 'Poultry Meat',
-        ],
-        "Dairy and eggs": [
-            "00002948",  # Milk - Excluding Butter
-            # Item group contains:
-            # 'Milk - Excluding Butter',
-            "00002949",  # Eggs
-            # Item group contains:
-            # 'Eggs',
-        ],
-        "Alcoholic beverages": [
-            "00002924",  # Alcoholic Beverages
-            # Item group contains:
-            # 'Alcohol, Non-Food',
-            # 'Beer',
-            # 'Beverages, Alcoholic',
-            # 'Beverages, Fermented',
-            # 'Wine',
-        ],
-        "Other": [
-            "00002928",  # Miscellaneous
-            # Item group contains:
-            # 'Infant food',
-            # 'Miscellaneous',
-            "00002923",  # Spices
-            # Item group contains:
-            # 'Cloves',
-            # 'Pepper',
-            # 'Pimento',
-            # 'Spices, Other',
-            "00002922",  # Stimulants
-            # Item group contains:
-            # 'Cocoa Beans and products',
-            # 'Coffee and products',
-            # 'Tea (including mate)',
-            "00002945",  # Offals
-            # Item group contains:
-            # 'Offals, Edible',
-            "00002961",  # Aquatic Products, Other
-            # 'Aquatic Plants',
-            # 'Meat, Aquatic Mammals',
-        ],
-    }
-
     # Sanity check.
     error = "Not all expected item codes are found in the data."
-    assert set([item_code for group in FOOD_GROUPS.values() for item_code in group]) <= set(tb_fbsc["item_code"]), error
+    assert set([item_code for group in FOOD_GROUPS_FBSC.values() for item_code in group]) <= set(
+        tb_fbsc["item_code"]
+    ), error
 
     # Create a list of tables, one for each food group.
     tables = [
-        tb_fbsc[tb_fbsc["item_code"].isin(FOOD_GROUPS[group])]
+        tb_fbsc[tb_fbsc["item_code"].isin(FOOD_GROUPS_FBSC[group])]
         .groupby(["country", "year"], as_index=False, observed=True)
         .agg({"value": "sum"})
         .rename(columns={"value": group}, errors="raise")
-        for group in FOOD_GROUPS
+        for group in FOOD_GROUPS_FBSC
     ]
     combined = pr.multi_merge(tables=tables, on=["country", "year"], how="outer")
 
@@ -484,8 +486,8 @@ def generate_food_available_for_consumption(tb_fbsc: Table) -> Table:
         "household or consumption level, so they may not directly reflect the quantity of food finally consumed by a "
         "given individual.\n\nSpecific food commodities have been grouped into higher-level categories."
     )
-    for group in FOOD_GROUPS:
-        item_names = list(tb_fbsc[tb_fbsc["item_code"].isin(FOOD_GROUPS[group])]["item"].unique())
+    for group in FOOD_GROUPS_FBSC:
+        item_names = list(tb_fbsc[tb_fbsc["item_code"].isin(FOOD_GROUPS_FBSC[group])]["item"].unique())
         description = (
             common_description
             + f" Food group '{group}' includes the FAO item groups: '"
@@ -1175,6 +1177,63 @@ def generate_fertilizer_exports(tb_rfn: Table) -> Table:
     return tb_fertilizer_exports
 
 
+def generate_net_exports_as_share_of_supply(tb_fbsc: Table) -> Table:
+    # I want to create a new indicator for the net trade balance as a share of consumption (or rather, domestic supply).
+    # In other words, I want to calculate (Exports - Imports) / Domestic supply.
+    # Here, note that we don't use "Food", since imports and exports include all agricultural products (including e.g. feed), whereas "Food" includes only food allocated for human consumption.
+    # "Domesetic supply" is the total supply of an item (including food, feed, and other uses) available for consumption.
+    # However, I want to have this indicator for a global total, not for each item.
+    # There is a grand total in the data, but only for "Fat supply quantity (t)", "Food available for consumption", "Food supply (kcal)", and "Protein supply quantity (t)".
+    # We would need to create this total for Imports, Exports, and Domestic supply.
+    # To do that, I can simply sum those elements over all items in FOOD_GROUPS.
+
+    # Element code for "Exports".
+    ELEMENT_CODE_FOR_EXPORTS = "005911"
+    # Element code for "Imports".
+    ELEMENT_CODE_FOR_IMPORTS = "005611"
+    # Element code for "Domestic supply quantity".
+    ELEMENT_CODE_FOR_DOMESTIC_SUPPLY = "005301"
+    # Gather the items that make up all foods.
+    all_items = sum(FOOD_GROUPS_FBSC.values(), [])
+
+    # Select the relevant items/elements.
+    tb = tb_fbsc[
+        (tb_fbsc["item_code"].isin(all_items))
+        & (
+            tb_fbsc["element_code"].isin(
+                [ELEMENT_CODE_FOR_EXPORTS, ELEMENT_CODE_FOR_IMPORTS, ELEMENT_CODE_FOR_DOMESTIC_SUPPLY]
+            )
+        )
+    ][["country", "year", "item", "element", "value", "unit"]].reset_index(drop=True)
+
+    # Sanity check.
+    error = "Units have changed."
+    assert list(tb["unit"].unique()) == ["tonnes"], error
+    tb = tb.drop(columns="unit", errors="raise")
+
+    # Visually inspect how many item groups are informed for each element.
+    # tb.groupby(["element", "item"], observed=True, as_index=False).size().sort_values(["item", "element"])
+    # I see that, for all item groups, there is roughly a similar number of imports, exports, and food.
+    # It is possible that supply is better informed that imports and exports, but if so, it's not by a significant percentage.
+
+    # Add up the total of imports, exports and food for each country and year.
+    tb = tb.groupby(["country", "year", "element"], observed=True, as_index=False).agg({"value": "sum"})
+
+    # Transpose data and rename columns conveniently.
+    tb = tb.pivot(index=["country", "year"], columns="element", values="value", join_column_levels_with="_")
+
+    # Create a new column for food trade balance relative to domestic supply, defined as net exports as a share of domestic supply.
+    tb["net_exports_as_share_of_supply"] = 100 * (tb["Exports"] - tb["Imports"]) / tb["Domestic supply"]
+
+    # Remove unnecessary columns.
+    tb = tb.drop(columns=["Exports", "Imports", "Domestic supply"], errors="raise")
+
+    # Improve table format.
+    tb = tb.format(short_name="net_exports_as_share_of_supply")
+
+    return tb
+
+
 def run(dest_dir: str) -> None:
     #
     # Load inputs.
@@ -1245,6 +1304,9 @@ def run(dest_dir: str) -> None:
     # Create table for fertilizer exports (used in the context of the Ukraine war).
     tb_fertilizer_exports = generate_fertilizer_exports(tb_rfn=tb_rfn)
 
+    # Create table for food trade as a share of consumption.
+    tb_net_exports_as_share_of_supply = generate_net_exports_as_share_of_supply(tb_fbsc=tb_fbsc)
+
     #
     # Save outputs.
     #
@@ -1265,6 +1327,7 @@ def run(dest_dir: str) -> None:
             tb_cereal_allocation,
             tb_maize_and_wheat,
             tb_fertilizer_exports,
+            tb_net_exports_as_share_of_supply,
         ],
         check_variables_metadata=True,
     )
diff --git a/etl/steps/data/grapher/faostat/2024-03-14/additional_variables.py b/etl/steps/data/grapher/faostat/2024-03-14/additional_variables.py
index fe862342b8d..98421c76303 100644
--- a/etl/steps/data/grapher/faostat/2024-03-14/additional_variables.py
+++ b/etl/steps/data/grapher/faostat/2024-03-14/additional_variables.py
@@ -151,6 +151,7 @@ def run(dest_dir: str) -> None:
     tb_cereal_allocation = ds_garden["cereal_allocation"]
     tb_maize_and_wheat = ds_garden["maize_and_wheat"].reset_index()
     tb_fertilizer_exports = ds_garden["fertilizer_exports"]
+    tb_net_exports_as_share_of_supply = ds_garden["net_exports_as_share_of_supply"]
 
     #
     # Process data.
@@ -204,6 +205,7 @@ def run(dest_dir: str) -> None:
             tb_cereal_allocation,
             tb_maize_and_wheat_in_the_context_of_the_ukraine_war,
             tb_fertilizer_exports_in_the_context_of_the_ukraine_war,
+            tb_net_exports_as_share_of_supply,
         ],
         default_metadata=ds_garden.metadata,
         check_variables_metadata=True,