Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in South America
South America: Consumption of Fixed Capital (Agriculture, Forestry and Fishing) was 15,106 million USD in 2023. ▲ Rising
Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in South America, 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million USD.
Analysis
In 2023, consumption of fixed capital (agriculture, forestry and fishing) in South America stood at 15,106 million USD. That is the highest value across all 29 years on record.
Compared with earlier readings it is up 2.5% on the previous year and up 7.2% over ten years.
Over the whole period, consumption of fixed capital (agriculture, forestry and fishing) in South America peaked at 15,106 million USD in 2023 and was at its lowest, 4,524 million USD, in 2002.
South America ranks 18th of 29 groups on this measure, in the middle of the range.
The long-run direction has been consistently rising across the 29 years of available data.
Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in South America, year by year
| Year | million USD | Change |
|---|---|---|
| 1995 | 7,353 million USD | — |
| 1996 | 7,910 million USD | +7.6% |
| 1997 | 7,856 million USD | -0.7% |
| 1998 | 7,488 million USD | -4.7% |
| 1999 | 6,142 million USD | -18.0% |
| 2000 | 6,290 million USD | +2.4% |
| 2001 | 5,719 million USD | -9.1% |
| 2002 | 4,524 million USD | -20.9% |
| 2003 | 4,806 million USD | +6.2% |
| 2004 | 5,559 million USD | +15.7% |
| 2005 | 6,764 million USD | +21.7% |
| 2006 | 7,656 million USD | +13.2% |
| 2007 | 8,808 million USD | +15.0% |
| 2008 | 10,227 million USD | +16.1% |
| 2009 | 10,123 million USD | -1.0% |
| 2010 | 11,808 million USD | +16.6% |
| 2011 | 13,324 million USD | +12.8% |
| 2012 | 13,836 million USD | +3.8% |
| 2013 | 14,097 million USD | +1.9% |
| 2014 | 14,125 million USD | +0.2% |
| 2015 | 12,672 million USD | -10.3% |
| 2016 | 12,101 million USD | -4.5% |
| 2017 | 13,410 million USD | +10.8% |
| 2018 | 12,744 million USD | -5.0% |
| 2019 | 13,071 million USD | +2.6% |
| 2020 | 11,376 million USD | -13.0% |
| 2021 | 12,786 million USD | +12.4% |
| 2022 | 14,731 million USD | +15.2% |
| 2023 | 15,106 million USD | +2.5% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 7,350 million USD | 6,142 million USD | 7,910 million USD | 5 |
| 2000s | 7,048 million USD | 4,524 million USD | 10,227 million USD | 10 |
| 2010s | 13,119 million USD | 11,808 million USD | 14,125 million USD | 10 |
| 2020s | 13,500 million USD | 11,376 million USD | 15,106 million USD | 4 |
Countries ranked near South America
- 15 Netherlands (Kingdom of the) 6,382 million USD compare
- 15 Polynesia 16.73 million USD compare
- 16 Thailand 6,172 million USD compare
- 16 Micronesia 15.34 million USD compare
- 17 Micronesia (Federated States of) 9.5 million USD compare
- 17 Pakistan 6,044 million USD compare
- 18 United Kingdom of Great Britain and Northern Ireland 4,820 million USD compare
- 19 Canada 4,392 million USD compare
- 20 Poland 4,263 million USD compare
- 21 Philippines 4,029 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)
- Sawnwood — Production, annual growth rate 1.3 % change on previous year (2024)
- Plywood and LVL — Import quantity, annual growth rate -11.07 % change on previous year (2024)
- Plywood and LVL — Import value, annual growth rate -29.58 % change on previous year (2024)
Frequently asked questions
- What is consumption of fixed capital (agriculture, forestry and fishing) in South America?
- Consumption of fixed capital (agriculture, forestry and fishing) in South America was 15,106 million USD in 2023, according to Food and Agriculture Organization of the United Nations.
- What is the highest consumption of fixed capital (agriculture, forestry and fishing) recorded in South America?
- The highest recorded value was 15,106 million USD in 2023.
- What is the lowest consumption of fixed capital (agriculture, forestry and fishing) recorded in South America?
- The lowest recorded value was 4,524 million USD in 2002.
- How does South America rank for consumption of fixed capital (agriculture, forestry and fishing)?
- South America ranks 18th out of 29 groups with data for 2023.
- Is consumption of fixed capital (agriculture, forestry and fishing) rising or falling in South America?
- Over the last ten years it is up 7.2%. 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 Consumption of Fixed Capital (Agriculture, Forestry and Fishing) — Value US$. 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.