Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ in Thailand
Thailand: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ was 89,792 million USD in 2023. ▲ Rising
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ in Thailand, 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 Thailand stood at 89,792 million USD. That is the highest value across all 29 years on record.
Compared with earlier readings it is up 2.1% on the previous year and up 21.8% over ten years.
Over the whole period, net capital stocks (agriculture, forestry and fishing) — value us$ in Thailand peaked at 89,792 million USD in 2023 and was at its lowest, 50,425 million USD, in 1995.
Thailand ranks 13th of 180 countries on this measure, in the top 10%.
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 Thailand, year by year
| Year | million USD | Change |
|---|---|---|
| 1995 | 50,425 million USD | — |
| 1996 | 52,261 million USD | +3.6% |
| 1997 | 53,403 million USD | +2.2% |
| 1998 | 53,887 million USD | +0.9% |
| 1999 | 53,895 million USD | +0.0% |
| 2000 | 53,709 million USD | -0.3% |
| 2001 | 53,523 million USD | -0.3% |
| 2002 | 53,662 million USD | +0.3% |
| 2003 | 54,351 million USD | +1.3% |
| 2004 | 55,338 million USD | +1.8% |
| 2005 | 56,484 million USD | +2.1% |
| 2006 | 57,885 million USD | +2.5% |
| 2007 | 59,458 million USD | +2.7% |
| 2008 | 61,293 million USD | +3.1% |
| 2009 | 62,781 million USD | +2.4% |
| 2010 | 65,092 million USD | +3.7% |
| 2011 | 67,785 million USD | +4.1% |
| 2012 | 70,764 million USD | +4.4% |
| 2013 | 73,705 million USD | +4.2% |
| 2014 | 75,692 million USD | +2.7% |
| 2015 | 77,144 million USD | +1.9% |
| 2016 | 78,592 million USD | +1.9% |
| 2017 | 80,108 million USD | +1.9% |
| 2018 | 81,649 million USD | +1.9% |
| 2019 | 83,237 million USD | +1.9% |
| 2020 | 84,720 million USD | +1.8% |
| 2021 | 86,236 million USD | +1.8% |
| 2022 | 87,918 million USD | +2.0% |
| 2023 | 89,792 million USD | +2.1% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 52,774 million USD | 50,425 million USD | 53,895 million USD | 5 |
| 2000s | 56,848 million USD | 53,523 million USD | 62,781 million USD | 10 |
| 2010s | 75,377 million USD | 65,092 million USD | 83,237 million USD | 10 |
| 2020s | 87,167 million USD | 84,720 million USD | 89,792 million USD | 4 |
Countries ranked near Thailand
- 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
- 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
More environment data for Thailand
- Historical exposure to drought — Land soil moisture anomaly 1.44 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly 1.54 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.306 °C (2025)
- Temperature change 1.01 °C (2025)
- Sawlogs and veneer logs — Production, annual growth rate 0 % change on previous year (2024)
- Sawlogs and veneer logs, non-coniferous — Production, annual growth 0 % change on previous year (2024)
- Other industrial roundwood — Production, annual growth rate 0 % change on previous year (2024)
- Other industrial roundwood, non-coniferous (production) — Production 0 % change on previous year (2024)
- Wood charcoal — Production, annual growth rate 1.19 % change on previous year (2024)
Frequently asked questions
- What is net capital stocks (agriculture, forestry and fishing) — value us$ in Thailand?
- Net capital stocks (agriculture, forestry and fishing) — value us$ in Thailand was 89,792 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 Thailand?
- The highest recorded value was 89,792 million USD in 2023.
- What is the lowest net capital stocks (agriculture, forestry and fishing) — value us$ recorded in Thailand?
- The lowest recorded value was 50,425 million USD in 1995.
- How does Thailand rank for net capital stocks (agriculture, forestry and fishing) — value us$?
- Thailand ranks 13th out of 180 countries with data for 2023.
- Is net capital stocks (agriculture, forestry and fishing) — value us$ rising or falling in Thailand?
- Over the last ten years it is up 21.8%. The long-run trend across the full record is rising.
- Where does this Thailand 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.