Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ in Africa
Africa: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ was 482,032 million USD in 2023. ▲ Rising
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ in Africa, 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 Africa is 482,032 million USD, measured in 2023. That is the highest value across all 29 years on record.
Compared with earlier readings it is up 3.3% on the previous year and up 41.5% over ten years.
Over the whole period, net capital stocks (agriculture, forestry and fishing) — value us$ in Africa peaked at 482,032 million USD in 2023 and was at its lowest, 161,869 million USD, in 1995.
Africa ranks 12th 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.
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ in Africa, year by year
| Year | million USD | Change |
|---|---|---|
| 1995 | 161,869 million USD | — |
| 1996 | 168,585 million USD | +4.1% |
| 1997 | 175,841 million USD | +4.3% |
| 1998 | 183,498 million USD | +4.4% |
| 1999 | 190,383 million USD | +3.8% |
| 2000 | 207,859 million USD | +9.2% |
| 2001 | 213,522 million USD | +2.7% |
| 2002 | 224,000 million USD | +4.9% |
| 2003 | 234,867 million USD | +4.9% |
| 2004 | 240,528 million USD | +2.4% |
| 2005 | 248,139 million USD | +3.2% |
| 2006 | 256,929 million USD | +3.5% |
| 2007 | 265,146 million USD | +3.2% |
| 2008 | 274,549 million USD | +3.5% |
| 2009 | 285,534 million USD | +4.0% |
| 2010 | 298,174 million USD | +4.4% |
| 2011 | 309,974 million USD | +4.0% |
| 2012 | 324,936 million USD | +4.8% |
| 2013 | 340,624 million USD | +4.8% |
| 2014 | 355,841 million USD | +4.5% |
| 2015 | 373,049 million USD | +4.8% |
| 2016 | 389,255 million USD | +4.3% |
| 2017 | 404,650 million USD | +4.0% |
| 2018 | 418,470 million USD | +3.4% |
| 2019 | 430,612 million USD | +2.9% |
| 2020 | 441,589 million USD | +2.5% |
| 2021 | 452,503 million USD | +2.5% |
| 2022 | 466,725 million USD | +3.1% |
| 2023 | 482,032 million USD | +3.3% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 176,035 million USD | 161,869 million USD | 190,383 million USD | 5 |
| 2000s | 245,107 million USD | 207,859 million USD | 285,534 million USD | 10 |
| 2010s | 364,558 million USD | 298,174 million USD | 430,612 million USD | 10 |
| 2020s | 460,712 million USD | 441,589 million USD | 482,032 million USD | 4 |
Countries ranked near Africa
- 9 Democratic Republic of the Congo 12,728 million USD compare
- 9 Japan 129,050 million USD compare
- 10 France 127,890 million USD compare
- 10 United Republic of Tanzania 12,682 million USD compare
- 11 Pakistan 121,223 million USD compare
- 11 Melanesia 8,211 million USD compare
- 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
More environment data for Africa
- Historical exposure to drought — Land soil moisture anomaly -7.93 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly -7.12 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Temperature change 1.32 °C (2025)
- Standard Deviation 0.213 °C (2025)
- Sawlogs and veneer logs, non-coniferous — Production 29.81 million m3 (2024)
- Industrial roundwood — Export value 652,409 1000 USD (2024)
- Industrial roundwood, non-coniferous — Production 66.41 million m3 (2024)
- Wood charcoal — Production 38.75 million t (2024)
- Other industrial roundwood, non-coniferous (production) — Production 26.92 million m3 (2024)
Frequently asked questions
- What is net capital stocks (agriculture, forestry and fishing) — value us$ in Africa?
- Net capital stocks (agriculture, forestry and fishing) — value us$ in Africa was 482,032 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 Africa?
- The highest recorded value was 482,032 million USD in 2023.
- What is the lowest net capital stocks (agriculture, forestry and fishing) — value us$ recorded in Africa?
- The lowest recorded value was 161,869 million USD in 1995.
- How does Africa rank for net capital stocks (agriculture, forestry and fishing) — value us$?
- Africa ranks 12th out of 29 groups with data for 2023.
- Is net capital stocks (agriculture, forestry and fishing) — value us$ rising or falling in Africa?
- Over the last ten years it is up 41.5%. The long-run trend across the full record is rising.
- Where does this Africa 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.