Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Philippines
Philippines: Consumption of Fixed Capital (Agriculture, Forestry and Fishing) was 3,950 million USD in 2023. ◆ Volatile
Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Philippines, 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million USD.
Analysis
In 2023, consumption of fixed capital (agriculture, forestry and fishing) in Philippines stood at 3,950 million USD. That is the highest value across all 29 years on record.
The figure is up 10.8% on the previous year and up 74.5% over ten years.
Over the whole period, consumption of fixed capital (agriculture, forestry and fishing) in Philippines peaked at 3,950 million USD in 2023 and was at its lowest, 785.22 million USD, in 2001.
That places Philippines 19th out of 182 countries with data for 2023, putting it in the top 10%.
The series is highly variable year to year, so single readings are best treated with caution.
Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Philippines, year by year
| Year | million USD | Change |
|---|---|---|
| 1995 | 1,015 million USD | — |
| 1996 | 960.11 million USD | -5.4% |
| 1997 | 913.75 million USD | -4.8% |
| 1998 | 825.84 million USD | -9.6% |
| 1999 | 852.82 million USD | +3.3% |
| 2000 | 800.68 million USD | -6.1% |
| 2001 | 785.22 million USD | -1.9% |
| 2002 | 810.55 million USD | +3.2% |
| 2003 | 849.7 million USD | +4.8% |
| 2004 | 928.07 million USD | +9.2% |
| 2005 | 925.77 million USD | -0.2% |
| 2006 | 935.56 million USD | +1.1% |
| 2007 | 1,017 million USD | +8.7% |
| 2008 | 1,128 million USD | +11.0% |
| 2009 | 2,090 million USD | +85.2% |
| 2010 | 2,183 million USD | +4.5% |
| 2011 | 2,246 million USD | +2.9% |
| 2012 | 2,250 million USD | +0.2% |
| 2013 | 2,264 million USD | +0.6% |
| 2014 | 2,685 million USD | +18.6% |
| 2015 | 2,649 million USD | -1.3% |
| 2016 | 2,844 million USD | +7.3% |
| 2017 | 3,152 million USD | +10.8% |
| 2018 | 3,357 million USD | +6.5% |
| 2019 | 3,330 million USD | -0.8% |
| 2020 | 3,131 million USD | -6.0% |
| 2021 | 3,402 million USD | +8.7% |
| 2022 | 3,564 million USD | +4.8% |
| 2023 | 3,950 million USD | +10.8% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 913.57 million USD | 825.84 million USD | 1,015 million USD | 5 |
| 2000s | 1,027 million USD | 785.22 million USD | 2,090 million USD | 10 |
| 2010s | 2,696 million USD | 2,183 million USD | 3,357 million USD | 10 |
| 2020s | 3,512 million USD | 3,131 million USD | 3,950 million USD | 4 |
Countries ranked near Philippines
- 16 Thailand 5,796 million USD compare
- 16 Micronesia 12.74 million USD compare
- 17 Micronesia (Federated States of) 6.95 million USD compare
- 17 Netherlands (Kingdom of the) 5,199 million USD compare
- 18 United Kingdom of Great Britain and Northern Ireland 4,832 million USD compare
- 20 Poland 3,758 million USD compare
- 21 Canada 3,368 million USD compare
- 22 Sweden 3,075 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 — Production, annual growth rate 0 % change on previous year (2024)
- Sawnwood — Production, per unit of GDP 0 m3 per US$ of GDP (2024)
- Sawnwood — Production, per capita 0.0042 m3 per person (2024)
- Sawnwood — Import quantity, annual growth rate -26.33 % change on previous year (2024)
- Sawnwood — Import quantity, per unit of GDP 0 m3 per US$ of GDP (2024)
Frequently asked questions
- What is consumption of fixed capital (agriculture, forestry and fishing) in Philippines?
- Consumption of fixed capital (agriculture, forestry and fishing) in Philippines was 3,950 million USD in 2023, according to Food and Agriculture Organization of the United Nations.
- What is the highest consumption of fixed capital (agriculture, forestry and fishing) recorded in Philippines?
- The highest recorded value was 3,950 million USD in 2023.
- What is the lowest consumption of fixed capital (agriculture, forestry and fishing) recorded in Philippines?
- The lowest recorded value was 785.22 million USD in 2001.
- How does Philippines rank for consumption of fixed capital (agriculture, forestry and fishing)?
- Philippines ranks 19th out of 182 countries with data for 2023.
- Is consumption of fixed capital (agriculture, forestry and fishing) rising or falling in Philippines?
- Over the last ten years it is up 74.5%. The long-run trend across the full record is volatile.
- Where does this Philippines data come from?
- The figures come from Food and Agriculture Organization of the United Nations, published as part of Consumption of Fixed Capital (Agriculture, Forestry and Fishing) — Value US$, 2015 prices. 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.