Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in South-Eastern Asia
South-Eastern Asia: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 54,064 million USD in 2023. ◆ Volatile
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in South-Eastern Asia, 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million USD.
Analysis
In 2023, gross fixed capital formation (agriculture, forestry and fishing) in South-Eastern Asia stood at 54,064 million USD. That is the highest value across all 29 years on record.
The figure is up 8.6% on the previous year and up 38.9% over ten years.
Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in South-Eastern Asia peaked at 54,064 million USD in 2023 and was at its lowest, 6,503 million USD, in 1998.
That places South-Eastern Asia 9th 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.
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in South-Eastern Asia, year by year
| Year | million USD | Change |
|---|---|---|
| 1995 | 10,748 million USD | — |
| 1996 | 11,754 million USD | +9.4% |
| 1997 | 10,429 million USD | -11.3% |
| 1998 | 6,503 million USD | -37.6% |
| 1999 | 7,536 million USD | +15.9% |
| 2000 | 7,333 million USD | -2.7% |
| 2001 | 7,004 million USD | -4.5% |
| 2002 | 8,283 million USD | +18.3% |
| 2003 | 9,552 million USD | +15.3% |
| 2004 | 10,627 million USD | +11.2% |
| 2005 | 11,589 million USD | +9.1% |
| 2006 | 14,198 million USD | +22.5% |
| 2007 | 17,709 million USD | +24.7% |
| 2008 | 22,545 million USD | +27.3% |
| 2009 | 23,740 million USD | +5.3% |
| 2010 | 30,599 million USD | +28.9% |
| 2011 | 36,091 million USD | +17.9% |
| 2012 | 38,391 million USD | +6.4% |
| 2013 | 38,911 million USD | +1.4% |
| 2014 | 38,498 million USD | -1.1% |
| 2015 | 37,287 million USD | -3.1% |
| 2016 | 38,774 million USD | +4.0% |
| 2017 | 41,163 million USD | +6.2% |
| 2018 | 42,648 million USD | +3.6% |
| 2019 | 44,904 million USD | +5.3% |
| 2020 | 45,573 million USD | +1.5% |
| 2021 | 48,682 million USD | +6.8% |
| 2022 | 49,771 million USD | +2.2% |
| 2023 | 54,064 million USD | +8.6% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 9,394 million USD | 6,503 million USD | 11,754 million USD | 5 |
| 2000s | 13,258 million USD | 7,004 million USD | 23,740 million USD | 10 |
| 2010s | 38,727 million USD | 30,599 million USD | 44,904 million USD | 10 |
| 2020s | 49,522 million USD | 45,573 million USD | 54,064 million USD | 4 |
Countries ranked near South-Eastern Asia
- 6 Nigeria 16,517 million USD compare
- 7 Russian Federation 16,465 million USD compare
- 8 Italy 15,546 million USD compare
- 9 Germany 14,644 million USD compare
- 10 Australia 14,042 million USD compare
- 10 Democratic Republic of the Congo 704.24 million USD compare
- 11 United Kingdom of Great Britain and Northern Ireland 11,303 million USD compare
- 12 Japan 10,095 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 gross fixed capital formation (agriculture, forestry and fishing) in South-Eastern Asia?
- Gross fixed capital formation (agriculture, forestry and fishing) in South-Eastern Asia was 54,064 million USD in 2023, according to Food and Agriculture Organization of the United Nations.
- What is the highest gross fixed capital formation (agriculture, forestry and fishing) recorded in South-Eastern Asia?
- The highest recorded value was 54,064 million USD in 2023.
- What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in South-Eastern Asia?
- The lowest recorded value was 6,503 million USD in 1998.
- How does South-Eastern Asia rank for gross fixed capital formation (agriculture, forestry and fishing)?
- South-Eastern Asia ranks 9th out of 29 groups with data for 2023.
- Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in South-Eastern Asia?
- Over the last ten years it is up 38.9%. 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 Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Value US$. Statizoid updates them automatically from the source API.
Download this data
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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.