Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ in South-Eastern Asia
South-Eastern Asia: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ was 528,950 million USD in 2023. ◆ Volatile
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ in South-Eastern Asia, 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million USD.
Analysis
In 2023, net capital stocks (agriculture, forestry and fishing) — value us$ in South-Eastern Asia stood at 528,950 million USD. That is the highest value across all 29 years on record.
That represents a change of up 3.9% on the previous year and up 42.5% over ten years.
Over the whole period, net capital stocks (agriculture, forestry and fishing) — value us$ in South-Eastern Asia peaked at 528,950 million USD in 2023 and was at its lowest, 79,762 million USD, in 1998.
That places South-Eastern Asia 11th out of 29 groups with data for 2023, putting it in the middle of the range.
The series is highly variable year to year, so single readings are best treated with caution.
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ in South-Eastern Asia, year by year
| Year | million USD | Change |
|---|---|---|
| 1995 | 107,240 million USD | — |
| 1996 | 115,158 million USD | +7.4% |
| 1997 | 105,359 million USD | -8.5% |
| 1998 | 79,762 million USD | -24.3% |
| 1999 | 94,713 million USD | +18.7% |
| 2000 | 96,956 million USD | +2.4% |
| 2001 | 93,389 million USD | -3.7% |
| 2002 | 102,568 million USD | +9.8% |
| 2003 | 114,823 million USD | +11.9% |
| 2004 | 125,981 million USD | +9.7% |
| 2005 | 139,447 million USD | +10.7% |
| 2006 | 168,259 million USD | +20.7% |
| 2007 | 193,542 million USD | +15.0% |
| 2008 | 229,628 million USD | +18.6% |
| 2009 | 249,656 million USD | +8.7% |
| 2010 | 305,218 million USD | +22.3% |
| 2011 | 351,296 million USD | +15.1% |
| 2012 | 368,141 million USD | +4.8% |
| 2013 | 371,314 million USD | +0.9% |
| 2014 | 373,664 million USD | +0.6% |
| 2015 | 364,386 million USD | -2.5% |
| 2016 | 379,222 million USD | +4.1% |
| 2017 | 400,422 million USD | +5.6% |
| 2018 | 417,268 million USD | +4.2% |
| 2019 | 446,340 million USD | +7.0% |
| 2020 | 460,508 million USD | +3.2% |
| 2021 | 494,072 million USD | +7.3% |
| 2022 | 509,064 million USD | +3.0% |
| 2023 | 528,950 million USD | +3.9% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 100,446 million USD | 79,762 million USD | 115,158 million USD | 5 |
| 2000s | 151,425 million USD | 93,389 million USD | 249,656 million USD | 10 |
| 2010s | 377,727 million USD | 305,218 million USD | 446,340 million USD | 10 |
| 2020s | 498,148 million USD | 460,508 million USD | 528,950 million USD | 4 |
Countries ranked near South-Eastern Asia
- 8 United Republic of Tanzania 12,576 million USD compare
- 8 Australia and New Zealand 153,605 million USD compare
- 9 France 141,023 million USD compare
- 9 Melanesia 9,308 million USD compare
- 10 Bolivia (Plurinational State of) 6,735 million USD compare
- 10 Japan 129,982 million USD compare
- 11 Australia 126,064 million USD compare
- 11 Syrian Arab Republic 4,565 million USD compare
- 12 Democratic Republic of the Congo 2,953 million USD compare
- 12 Pakistan 109,361 million USD compare
- 13 Lao People's Democratic Republic 2,515 million USD compare
- 13 Thailand 94,816 million USD compare
- 14 Brazil 88,219 million USD compare
- 14 Timor-Leste 449.49 million USD compare
More environment data for South-Eastern Asia
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Historical exposure to drought — Land soil moisture anomaly 1.01 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly 1.59 Percentage change (2025)
- Temperature change 1.1 °C (2025)
- Standard Deviation 0.195 °C (2025)
- Recovered paper — Production 10.49 million t (2024)
- Total fibre furnish — Production 22.16 million t (2024)
- Agricultural land — Value of agricultural production (Int. $) per Area 2,246 USD_PPP/ha (2024)
- Nutrient potash K2O (total) — Use per capita 6.08 kg/cap (2024)
- Nutrient potash K2O (total) — Use per value of agricultural production 14.29 g/Int$ (2024)
Frequently asked questions
- What is net capital stocks (agriculture, forestry and fishing) — value us$ in South-Eastern Asia?
- Net capital stocks (agriculture, forestry and fishing) — value us$ in South-Eastern Asia was 528,950 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-Eastern Asia?
- The highest recorded value was 528,950 million USD in 2023.
- What is the lowest net capital stocks (agriculture, forestry and fishing) — value us$ recorded in South-Eastern Asia?
- The lowest recorded value was 79,762 million USD in 1998.
- How does South-Eastern Asia rank for net capital stocks (agriculture, forestry and fishing) — value us$?
- South-Eastern Asia ranks 11th out of 29 groups with data for 2023.
- Is net capital stocks (agriculture, forestry and fishing) — value us$ rising or falling in South-Eastern Asia?
- Over the last ten years it is up 42.5%. The long-run trend across the full record is volatile.
- Where does this South-Eastern Asia 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$. 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.