Forestry, Capital (central government expenditure) — Value Standard Local Currency by country
The Statistics Division of FAO collects annually data on Government Expenditure on Agriculture through a questionnaire, which was developed in partnership with the International Monetary Fund (IMF). The IMF is the responsible institution for the Government Finance Statistics (GFS) methodology and annually collects...
What the numbers show
Forestry, Capital (central government expenditure) — Value Standard Local Currency is currently reported for 43 countries. The highest value is 230,000 million SLC in Viet Nam; the lowest is -14 million SLC in Australia.
The median across all reporting countries is 35 million SLC, and the mean is 6,388 million SLC.
The gap between the highest and lowest reporting country is a factor of about 16,429.
Over the past decade 17 countries rose and 18 fell. The largest increase was in Peru (up 26,600.0%), and the largest decrease in Australia (down 1,500.0%).
Forestry, Capital (central government expenditure) — Value Standard: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Viet Nam | 230,000 million SLC | 2022 | down 33.9% | volatile |
| 1 | Guinea | 15,700 million SLC | 2020 | — | rising |
| 2 | Bangladesh | 11,390 million SLC | 2024 | up 3,574.2% | volatile |
| 2 | Republic of Moldova | 259 million SLC | 2024 | up 1,469.7% | volatile |
| 3 | Togo | 3,685 million SLC | 2018 | up 152.5% | volatile |
| 3 | United Republic of Tanzania | 35 million SLC | 2024 | down 94.3% | volatile |
| 4 | Senegal | 3,109 million SLC | 2024 | down 29.9% | volatile |
| 5 | Kenya | 2,998 million SLC | 2024 | up 362.8% | volatile |
| 6 | Chile | 2,058 million SLC | 2024 | down 13.9% | volatile |
| 7 | Mali | 1,694 million SLC | 2013 | up 163.0% | volatile |
| 8 | Israel | 1,017 million SLC | 2024 | up 90.8% | rising |
| 9 | Kazakhstan | 647.62 million SLC | 2015 | up 284.4% | volatile |
| 10 | Chad | 605 million SLC | 2020 | down 13.8% | volatile |
| 11 | Armenia | 534.19 million SLC | 2022 | — | volatile |
| 12 | Guinea-Bissau | 168.45 million SLC | 2015 | up 1.8% | volatile |
| 13 | Paraguay | 139 million SLC | 2024 | down 50.6% | volatile |
| 14 | Namibia | 125 million SLC | 2024 | down 17.8% | volatile |
| 15 | Peru | 120.15 million SLC | 2024 | up 26,600.0% | volatile |
| 16 | Cuba | 118.58 million SLC | 2019 | — | falling |
| 17 | Albania | 92.92 million SLC | 2022 | up 90.4% | rising |
| 18 | Guyana | 52.6 million SLC | 2023 | up 22.4% | rising |
| 19 | Slovakia | 39.51 million SLC | 2011 | up 2,916.0% | volatile |
| 20 | South Africa | 30 million SLC | 2023 | down 62.0% | volatile |
| 21 | Kyrgyzstan | 27.6 million SLC | 2024 | up 43.0% | volatile |
| 22 | Brazil | 14.98 million SLC | 2024 | down 59.2% | volatile |
| 23 | Sweden | 12 million SLC | 2024 | down 52.0% | volatile |
| 24 | Lesotho | 9.9 million SLC | 2024 | down 92.4% | volatile |
| 25 | Nicaragua | 8 million SLC | 2023 | down 1.2% | volatile |
| 26 | Fiji | 4 million SLC | 2023 | up 566.7% | rising |
| 27 | Mauritius | 3.13 million SLC | 2024 | down 57.1% | volatile |
| 28 | Zambia | 0.84 million SLC | 2024 | up 133.3% | volatile |
| 29 | Saint Lucia | 0.62 million SLC | 2024 | up 121.4% | volatile |
| 30 | Guatemala | 0.35 million SLC | 2024 | — | volatile |
| 31 | Grenada | 0.13 million SLC | 2024 | down 74.0% | volatile |
| 32 | El Salvador | 0.1 million SLC | 2023 | — | volatile |
| 33 | Russian Federation | 0.09 million SLC | 2021 | — | volatile |
| 34 | Argentina | 0 million SLC | 2024 | down 100.0% | volatile |
| 34 | Angola | 0 million SLC | 2024 | — | volatile |
| 34 | Trinidad and Tobago | 0 million SLC | 2015 | down 100.0% | volatile |
| 34 | Eswatini | 0 million SLC | 2023 | — | volatile |
| 34 | Mexico | 0 million SLC | 2024 | down 100.0% | volatile |
| 46 | Poland | -5 million SLC | 2023 | up 70.6% | volatile |
| 47 | Australia | -14 million SLC | 2024 | down 1,500.0% | volatile |
About this data
The Statistics Division of FAO collects annually data on Government Expenditure on Agriculture through a questionnaire, which was developed in partnership with the International Monetary Fund (IMF). The IMF is the responsible institution for the Government Finance Statistics (GFS) methodology and annually collects GFS data, including Expenditure by Functions of Government (COFOG). The Classification of the Functions of Government (COFOG) is an international classification developed by Organisation for Economic Co-operation and Development (OECD) and published by the United Nations Statistical Division (UNSD), with the aim of categorise governments' functions according to their purposes. The FAO questionnaire aligns with Table 7 of the IMF GFS questionnaire, replicates the relevant aggregates and drills down to request additional detail related to Agriculture. The FAO dataset consists of a time series, from 2001 onwards, of Total Government Expenditure and expenditure in: Agriculture, Forestry, Fishing and Hunting, along with its three disaggregated subsectors of Agriculture, Forestry and Fishing; and Environmental Protection. In addition, expenditure in each detailed function are further disaggregated into Recurrent and Capital expenditure. Additional indicators include the Agriculture Share of Government Expenditure, and the Agriculture Orientation Index (ratio between the Agriculture Share of Government Expenditure and the Agriculture Value Added as Share of GDP). Data are reported for the highest level of government available (Consolidated general government, consolidated central government or budgetary central government) and are available for about 100 countries on a regular basis.