Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ in South America
South America: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ was 255,063 million USD in 2023. ▲ Rising
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ in South America, 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million USD.
Analysis
The most recent figure for net capital stocks (agriculture, forestry and fishing) — value us$ in South America is 255,063 million USD, measured in 2023. That is the highest value across all 29 years on record.
That represents a change of up 3.5% on the previous year and up 24.2% over ten years.
Over the whole period, net capital stocks (agriculture, forestry and fishing) — value us$ in South America peaked at 255,063 million USD in 2023 and was at its lowest, 165,527 million USD, in 2001.
That places South America 15th out of 29 groups with data for 2023, putting it in the middle of the range.
The long-run direction has been consistently rising across the 29 years of available data.
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ in South America, year by year
| Year | million USD | Change |
|---|---|---|
| 1995 | 167,297 million USD | — |
| 1996 | 166,861 million USD | -0.3% |
| 1997 | 167,185 million USD | +0.2% |
| 1998 | 167,485 million USD | +0.2% |
| 1999 | 166,718 million USD | -0.5% |
| 2000 | 166,069 million USD | -0.4% |
| 2001 | 165,527 million USD | -0.3% |
| 2002 | 166,460 million USD | +0.6% |
| 2003 | 168,725 million USD | +1.4% |
| 2004 | 171,352 million USD | +1.6% |
| 2005 | 172,881 million USD | +0.9% |
| 2006 | 174,930 million USD | +1.2% |
| 2007 | 178,221 million USD | +1.9% |
| 2008 | 182,216 million USD | +2.2% |
| 2009 | 184,232 million USD | +1.1% |
| 2010 | 188,865 million USD | +2.5% |
| 2011 | 195,367 million USD | +3.4% |
| 2012 | 200,014 million USD | +2.4% |
| 2013 | 205,438 million USD | +2.7% |
| 2014 | 210,056 million USD | +2.2% |
| 2015 | 212,407 million USD | +1.1% |
| 2016 | 217,303 million USD | +2.3% |
| 2017 | 221,622 million USD | +2.0% |
| 2018 | 224,717 million USD | +1.4% |
| 2019 | 227,505 million USD | +1.2% |
| 2020 | 231,220 million USD | +1.6% |
| 2021 | 238,900 million USD | +3.3% |
| 2022 | 246,433 million USD | +3.2% |
| 2023 | 255,063 million USD | +3.5% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 167,109 million USD | 166,718 million USD | 167,485 million USD | 5 |
| 2000s | 173,061 million USD | 165,527 million USD | 184,232 million USD | 10 |
| 2010s | 210,329 million USD | 188,865 million USD | 227,505 million USD | 10 |
| 2020s | 242,904 million USD | 231,220 million USD | 255,063 million USD | 4 |
Countries ranked near South America
- 12 Australia 110,662 million USD compare
- 12 Bolivia (Plurinational State of) 6,461 million USD compare
- 13 Lao People's Democratic Republic 3,599 million USD compare
- 13 Thailand 89,792 million USD compare
- 14 Timor-Leste 431.78 million USD compare
- 14 United Kingdom of Great Britain and Northern Ireland 88,207 million USD compare
- 15 Brazil 84,760 million USD compare
- 15 Polynesia 222.17 million USD compare
- 16 Argentina 77,308 million USD compare
- 16 Micronesia 184.73 million USD compare
- 17 Micronesia (Federated States of) 104.55 million USD compare
- 17 Spain 69,098 million USD compare
- 18 Austria 60,401 million USD compare
More environment data for South America
- Historical exposure to drought — Cropland soil moisture anomaly -6.52 Percentage change (2025)
- Historical exposure to drought — Land soil moisture anomaly -4.98 Percentage change (2025)
- Standard Deviation 0.218 °C (2025)
- Temperature change 1.23 °C (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Other paper and paperboard, not elsewhere specified — Import value -5.13 % change on previous year (2024)
- Total fibre furnish — Production, annual growth rate 4.24 % change on previous year (2024)
- Other industrial roundwood, non-coniferous (production) — Production 7.42 % change on previous year (2024)
- Sawnwood — Export quantity, annual growth rate -2.5 % change on previous year (2024)
- Sawnwood — Import value, annual growth rate -13.02 % change on previous year (2024)
Frequently asked questions
- What is net capital stocks (agriculture, forestry and fishing) — value us$ in South America?
- Net capital stocks (agriculture, forestry and fishing) — value us$ in South America was 255,063 million USD in 2023, according to Food and Agriculture Organization of the United Nations.
- What is the highest net capital stocks (agriculture, forestry and fishing) — value us$ recorded in South America?
- The highest recorded value was 255,063 million USD in 2023.
- What is the lowest net capital stocks (agriculture, forestry and fishing) — value us$ recorded in South America?
- The lowest recorded value was 165,527 million USD in 2001.
- How does South America rank for net capital stocks (agriculture, forestry and fishing) — value us$?
- South America ranks 15th out of 29 groups with data for 2023.
- Is net capital stocks (agriculture, forestry and fishing) — value us$ rising or falling in South America?
- Over the last ten years it is up 24.2%. The long-run trend across the full record is rising.
- Where does this South America data come from?
- The figures come from Food and Agriculture Organization of the United Nations, published as part of Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$, 2015 prices. Statizoid updates them automatically from the source API.
Download this data
CSV · JSON — 29 observations, free to reuse under CC BY-NC-SA 3.0 IGO (FAO).
About this data
As part of the FAO Agriculture Capital Stock (ACS) database, the Statistics Division of FAO publishes country-by-country data on physical investment in agriculture, forestry and fishing as measured by the System of National Accounts (SNA) concept of Gross Fixed Capital Formation (GFCF). Additional variables included in the ACS are Net and Gross Capital Stock, Consumption of Fixed Capital, the Agriculture Investment ratio, and the Gross Fixed Capital Formation Agriculture Orientation Index. The FAO Agriculture Capital Stock Database is an analytical database: whenever available, the database integrates official National Accounts data harvested from the UNSD National Accounts Main Aggregates Database (UNSD AMA) and the OECD Annual National Accounts Database (OECD ANA). The database is further supplemented by OECD Structural Analysis database (OECD STAN) and, in a few cases, data from country’s statistics websites. If the full set of official data is not available for any specific country, imputation methods are applied to obtain estimates over the complete time series. Many data points in ACS are estimated and are flagged as such; they do not represent official submissions by Member Countries. With a view of producing internationally comparable net capital stock estimates, the Perpetual Inventory Method (PIM) with a constant geometric depreciation rate is employed to impute missing data. The Perpetual Inventory Method is a well-established economic model to calculate Net Capital Stocks (NCS) and Consumption of Fixed Capital (CFC) from time series of Gross Fixed Capital Formation (GFCF). Specifically, annual measures of the NCS are obtained from cumulating historical series on physical investment flows and deducting the part of assets that are depreciated (the Consumption of Fixed Capital that occurs in every period). In order to implement the PIM, long time series on aggregate GFCF in agriculture, forestry and fishing is required.An attempt is made to rely as much as possible on National Accounts data published by the OECD and UNSD. When country data are partially or fully missing, econometric techniques to impute missing observations are employed. Depending on the pattern of data missingness for the countries, different imputation methods are applied (from among the ARIMAX, PANEL regression, and OLS approaches) for the data series from 1995 to 2022. The values of Agriculture Capital Stock related indicators for 2023, including Agriculture Investment Ratio, Agriculture Orientation Index, Net Capital Stock, Gross Fixed Capital Formation and Consumption of Fixed Capital, are estimated using the Holt-Winters (HW) method (Cipra et al., 1995). The HW method is an exponential smoothing method for forecasting the annual values of economic variables. In this context, the HW method relies on existing (historical) values of the Agriculture Capital Stock. The predicted value is an extrapolation of the historical values to the specified target date, which extends the timeline without considering seasonality in the annual series.All data series in the database are provided both in national currencies and in US dollars as well as in current prices and constant prices with base year 2015.