## Energy Subsidy Template (dataset overview)

## Source details

**Canonical URL:** [Energy Subsidy Template (dataset overview)](https://www.imf.org/-/media/files/topics/energy-subsidies/externalfuelsubsidiestemplate2023new.xlsx)

## Other formats

- [Markdown version](/-/media/files/topics/energy-subsidies/externalfuelsubsidiestemplate2023new.xlsx.md)
- [Structured JSON version](/-/media/files/topics/energy-subsidies/externalfuelsubsidiestemplate2023new.xlsx.json)

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### Overview and purpose
- This spreadsheet contains FAD's fossil fuel subsidy estimates and associated externalities.
- Calculations follow two steps for each fuel source and end-user:
  - (i) estimation of country-level externalities based on associated air pollution, greenhouse gas emissions, road congestion, etc.
  - (ii) calculation of country-level subsidies based on support given to producers and the gap between retail prices and the efficient optimal price, with the efficient price being the monetary supply cost plus all externalities.
- Subsidies are disaggregated into explicit and implicit subsidies:
  - Explicit reflect subsidies due to supply costs being greater than the retail prices.
  - Implicit reflect subsidies due to the efficient price being greater than the retail price, exclusive of any explicit subsidy.
- Calculations are performed for all IMF member countries where data is available.
- Retail price data in the Single_Country_Fuel sheet may be missing if there are copyright related restrictions.
- All price and subsidy values are in 2021 constant prices.

### Sheets included (description excerpts from ReadMe)
- Single_Country_Fuel: Per-unit subsidies for a single country, without comparisons to other countries.
- Single_Country_Total: Total subsidies for a single country and comparisons to other countries and regions. Subsidies over time are shown at the bottom.
- Global_Regional_Total: Global and regional subsidies by component over time.
- Reform_Impacts: Information on the impacts of fossil fuel subsidy reform on welfare, emissions, revenue, and air pollution.
- All_Explicit: Explicit subsidies for all countries.
- All_Implicit: Implicit subsidies for all countries.
- variables: variable names and descriptions.
- lists: lookup lists for Countries, Regions, Years, Unit.
- data: the underlying dataset with 5,377 rows and 304 columns (column names enumerated in the data sheet header).

### Methodology and key definitions (from ReadMe / Cover Page notes)
- Externalities considered include air pollution, greenhouse gas emissions, road congestion, vehicle externalities, VAT effects, and global warming costs (labels such as mit.airpol.cost, mit.scc.cost, mit.ener, mit.vat.cost appear in summary rows).
- Efficient price per unit = supply cost + Global Warming + Local air pollution + Vehicle externalities* + VAT* (as shown in Single_Country_Fuel summary headings).
- Producer subsidy, Explicit subsidy, Implicit subsidy are presented at country level in monetary units (Billions USD or per-unit measures) and as % of GDP.
- Scenario coding: "U1 = full reform, U5 = partial reform" (variables sheet).

### Example country-level inputs and sample values (preserve exact numbers from sample rows)
- USA (selected in Single_Country_Fuel / Single_Country_Total sample inputs):
  - Population: 337.499 (Millions)
  - Select year: 2022
  - GDP: 23373.384 (Billions USD)
  - Exchange rate: 1 (LCU / USD)
  - Currency unit: Billions (scale result 1)
- Single_Country_Fuel summary headings include columns: Consumer Price (mit.rp), Supply Cost (mit.sup.cost), Global Warming (mit.scc.cost), Local air pollution (mit.airpol.cost), Vehicle externalities*, VAT*, Efficient price - per unit (mit.eff.price), Explicit subsidy - per unit (mit.sub.tpro.tot), Implicit subsidy - per unit (mit_preall / mit_potall), Consumption (millions)**.

### Sample explicit subsidy values (from All_Explicit sample rows, values in US$ billions unless otherwise labeled)
- Afghanistan: Explicit Subsidies total = 0.43590796478458227
- Albania: Explicit Subsidies total = 0.08934021699210039
- Algeria: Explicit Subsidies total = 45.20322334885715
- Angola: Explicit Subsidies total = 6.408994058930138
- Argentina: Explicit Subsidies total = 14.186585470869876
- Australia: Explicit Subsidies total = 7.856833560587999

### Sample implicit subsidy and total implicit values (from All_Implicit sample rows, values in US$ billions)
- Afghanistan: Implicit Subsidies total = 1.8480421882548532
- Albania: Implicit Subsidies total = 0.9985441768656834
- Algeria: Implicit Subsidies total = 30.077607980830763
- Angola: Implicit Subsidies total = 5.108118890770172
- Argentina: Implicit Subsidies total = 36.31138640991577
- Australia: Implicit Subsidies total = 39.56159533275485

### Reform impacts and scenarios (from Reform_Impacts sample rows)
- Scenario label mapping in the sheet: IF( F5 = "Full reform", "U1", "U5") — sample result "U5".
- Example Reform_Impacts sample values for 2030, scenario U5 (units "USD Billions"):
  - Environmental benefits (mit.wel.env.tot.usd) — sample results:
    - United States: 558.29449575
    - India: 242.84851525
    - Germany: 23.8845415
    - Japan: 99.99668825
    - China: 1547.72996425
    - Latin America & Caribbean: 169.11964924999998
    - North America: 574.6185055
    - World: 3906.343669749996
  - Economic costs (mit.wel.eco.tot.usd) — sample results:
    - United States: -75.22960575
    - India: -47.65178275
    - Germany: -7.8334165
    - Japan: -23.41134575
    - China: -281.36292925
    - Latin America & Caribbean: -28.49407925
    - North America: -79.3779805
    - World: -649.2083747500004
  - Welfare change (sum of environmental benefits and economic costs) — sample results:
    - United States: 483.06489
    - India: 195.1967325
    - Germany: 16.051125
    - Japan: 76.58534250000001
    - China: 1266.367035
    - Latin America & Caribbean: 140.62556999999998
    - North America: 495.24052499999993
    - World: 3257.1352949999955

### Variables and key column names (selected from variables and data sheet headers)
- Core identifiers and descriptors:
  - countryname, countrycode, region, incomelevel, scenario, year
- Macroeconomic/population:
  - mit.gdp.pre.lvl.1 (GDP in 2021 USD billions)
  - mit.pop.mn (Population in millions)
- Emissions and externality metrics:
  - mit.ghg.tot.exc.1 (Greenhouse gas emissions in million tons of CO2 eq, excluding LULUCF, no reform)
  - mit.co2.tot.1
  - mit.wel.env.tot.usd (environmental benefits)
  - mit.wel.eco.tot.usd (economic costs)
- Subsidy and price components (repeated by fuel and end-user):
  - mit.eff.price.* (efficient price)
  - mit.sup.cost.* (supply cost)
  - mit.scc.cost.* (social cost of carbon / global warming)
  - mit.airpol.cost.* (local air pollution costs)
  - mit.vat.cost.* (VAT effects)
  - mit.rp.* (retail/consumer price)
  - mit.sub.texp.* (consumer explicit subsidies)
  - mit.sub.tpro.* (producer subsidies)
  - mit.sub.timp.* (implicit subsidies)
  - mit.sub.tot.* (total subsidies)
- Fuel/end-user suffixes observed in column names:
  - gso (Gasoline), die (Diesel), lpg (LPG), ker (Kerosene), oop (Other oil products), nga (Natural gas), coa (Coal), ecy (Electricity)
- Units and conversion scale are controlled via the lists sheet: Unit (Thousands, Millions, Billions) with corresponding scale "#": 1000000, 1000, 1.

### Data scope and structure
- Data sheet contains 5,377 rows and 304 columns with time series and scenario entries by country.
- The lists sheet enumerates Countries, Regions, and Years (sample years 2015 through 2024 present in lists).
- variables sheet provides human-readable descriptions for the variable name codes used across sheets.

*Dataset: Energy Subsidy Template (IMF Fiscal Affairs Department). Canonical file: externalfuelsubsidiestemplate2023new (XLSX). All price and subsidy values are in 2021 constant prices.*

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_Source: https://www.imf.org/-/media/files/topics/energy-subsidies/externalfuelsubsidiestemplate2023new.xlsx_