Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ in Philippines
Philippines: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ was 60,199 million USD in 2023. ▲ Rising
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$ in Philippines, 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 Philippines stood at 60,199 million USD. That is the highest value across all 29 years on record.
Compared with earlier readings it is up 4.0% on the previous year and up 44.9% over ten years.
Over the whole period, net capital stocks (agriculture, forestry and fishing) — value us$ in Philippines peaked at 60,199 million USD in 2023 and was at its lowest, 21,240 million USD, in 1995.
That places Philippines 19th out of 180 countries with data for 2023, putting it in the top quarter.
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 Philippines, year by year
| Year | million USD | Change |
|---|---|---|
| 1995 | 21,240 million USD | — |
| 1996 | 22,143 million USD | +4.2% |
| 1997 | 23,098 million USD | +4.3% |
| 1998 | 23,950 million USD | +3.7% |
| 1999 | 24,829 million USD | +3.7% |
| 2000 | 25,745 million USD | +3.7% |
| 2001 | 26,596 million USD | +3.3% |
| 2002 | 27,535 million USD | +3.5% |
| 2003 | 28,543 million USD | +3.7% |
| 2004 | 29,723 million USD | +4.1% |
| 2005 | 30,897 million USD | +4.0% |
| 2006 | 32,143 million USD | +4.0% |
| 2007 | 33,616 million USD | +4.6% |
| 2008 | 35,389 million USD | +5.3% |
| 2009 | 36,348 million USD | +2.7% |
| 2010 | 37,470 million USD | +3.1% |
| 2011 | 38,695 million USD | +3.3% |
| 2012 | 40,034 million USD | +3.5% |
| 2013 | 41,532 million USD | +3.7% |
| 2014 | 43,014 million USD | +3.6% |
| 2015 | 44,529 million USD | +3.5% |
| 2016 | 46,190 million USD | +3.7% |
| 2017 | 48,057 million USD | +4.0% |
| 2018 | 50,042 million USD | +4.1% |
| 2019 | 51,968 million USD | +3.8% |
| 2020 | 53,795 million USD | +3.5% |
| 2021 | 55,789 million USD | +3.7% |
| 2022 | 57,878 million USD | +3.7% |
| 2023 | 60,199 million USD | +4.0% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 23,052 million USD | 21,240 million USD | 24,829 million USD | 5 |
| 2000s | 30,654 million USD | 25,745 million USD | 36,348 million USD | 10 |
| 2010s | 44,153 million USD | 37,470 million USD | 51,968 million USD | 10 |
| 2020s | 56,915 million USD | 53,795 million USD | 60,199 million USD | 4 |
Countries ranked near Philippines
- 16 Argentina 77,308 million USD compare
- 17 Spain 69,098 million USD compare
- 18 Austria 60,401 million USD compare
- 20 Republic of Korea 58,769 million USD compare
- 21 Netherlands (Kingdom of the) 58,655 million USD compare
- 22 Switzerland 53,222 million USD compare
More environment data for Philippines
- Historical exposure to drought — Land soil moisture anomaly 6.85 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly 7.07 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.177 °C (2025)
- Temperature change 0.905 °C (2025)
- Sawnwood, non-coniferous — Production, annual growth rate 0 % change on previous year (2024)
- Sawnwood, non-coniferous — Production, per unit of GDP 0 m3 per US$ of GDP (2024)
- Sawnwood, non-coniferous — Production, per capita 0.0042 m3 per person (2024)
- Sawnwood, non-coniferous — Import quantity, annual growth rate -70.52 % change on previous year (2024)
- Sawnwood, non-coniferous — Import quantity, per unit of GDP 0 m3 per US$ of GDP (2024)
Frequently asked questions
- What is net capital stocks (agriculture, forestry and fishing) — value us$ in Philippines?
- Net capital stocks (agriculture, forestry and fishing) — value us$ in Philippines was 60,199 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 Philippines?
- The highest recorded value was 60,199 million USD in 2023.
- What is the lowest net capital stocks (agriculture, forestry and fishing) — value us$ recorded in Philippines?
- The lowest recorded value was 21,240 million USD in 1995.
- How does Philippines rank for net capital stocks (agriculture, forestry and fishing) — value us$?
- Philippines ranks 19th out of 180 countries with data for 2023.
- Is net capital stocks (agriculture, forestry and fishing) — value us$ rising or falling in Philippines?
- Over the last ten years it is up 44.9%. The long-run trend across the full record is rising.
- Where does this Philippines 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.