Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Equatorial Guinea
Equatorial Guinea: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value was 204,406 million SLC in 2023. ◆ Volatile
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Equatorial Guinea, 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.
Analysis
The most recent figure for net capital stocks (agriculture, forestry and fishing) — value in Equatorial Guinea is 204,406 million SLC, measured in 2023. That is the highest value across all 29 years on record.
That represents a change of up 1.2% on the previous year and up 39.5% over ten years.
Over the whole period, net capital stocks (agriculture, forestry and fishing) — value in Equatorial Guinea peaked at 204,406 million SLC in 2023 and was at its lowest, 5,261 million SLC, in 1995.
Equatorial Guinea ranks 66th of 179 countries on this measure, 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 in Equatorial Guinea, year by year
| Year | million SLC | Change |
|---|---|---|
| 1995 | 5,261 million SLC | — |
| 1996 | 6,121 million SLC | +16.3% |
| 1997 | 7,627 million SLC | +24.6% |
| 1998 | 8,840 million SLC | +15.9% |
| 1999 | 11,048 million SLC | +25.0% |
| 2000 | 17,170 million SLC | +55.4% |
| 2001 | 26,723 million SLC | +55.6% |
| 2002 | 33,627 million SLC | +25.8% |
| 2003 | 44,126 million SLC | +31.2% |
| 2004 | 58,716 million SLC | +33.1% |
| 2005 | 71,416 million SLC | +21.6% |
| 2006 | 81,270 million SLC | +13.8% |
| 2007 | 91,652 million SLC | +12.8% |
| 2008 | 102,993 million SLC | +12.4% |
| 2009 | 111,141 million SLC | +7.9% |
| 2010 | 118,066 million SLC | +6.2% |
| 2011 | 127,153 million SLC | +7.7% |
| 2012 | 137,075 million SLC | +7.8% |
| 2013 | 146,524 million SLC | +6.9% |
| 2014 | 155,309 million SLC | +6.0% |
| 2015 | 162,827 million SLC | +4.8% |
| 2016 | 169,489 million SLC | +4.1% |
| 2017 | 176,380 million SLC | +4.1% |
| 2018 | 182,266 million SLC | +3.3% |
| 2019 | 187,498 million SLC | +2.9% |
| 2020 | 192,625 million SLC | +2.7% |
| 2021 | 197,934 million SLC | +2.8% |
| 2022 | 201,918 million SLC | +2.0% |
| 2023 | 204,406 million SLC | +1.2% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 7,779 million SLC | 5,261 million SLC | 11,048 million SLC | 5 |
| 2000s | 63,883 million SLC | 17,170 million SLC | 111,141 million SLC | 10 |
| 2010s | 156,259 million SLC | 118,066 million SLC | 187,498 million SLC | 10 |
| 2020s | 199,221 million SLC | 192,625 million SLC | 204,406 million SLC | 4 |
Countries ranked near Equatorial Guinea
More environment data for Equatorial Guinea
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.21 °C (2025)
- Temperature change 1.27 °C (2025)
- Value Added (Agriculture, Forestry and Fishing) — Value US$, 2015 2.87 % change on previous year (2024)
- Value Added (Agriculture, Forestry and Fishing) — Value US$, 2015 0 million USD per US$ of GDP (2024)
- Value Added (Agriculture, Forestry and Fishing) — Value US$, 2015 0.0001 million USD per person (2024)
- Primary wood and paper products (export/import) — Import value -20 % change on previous year (2024)
- Primary wood and paper products (export/import) — Import value, per 0 1000 USD per US$ of GDP (2024)
- Primary wood and paper products (export/import) — Import value, per 0.0029 1000 USD per person (2024)
- Primary wood and paper products (export/import) — Export value -14.69 % change on previous year (2024)
Frequently asked questions
- What is net capital stocks (agriculture, forestry and fishing) — value in Equatorial Guinea?
- Net capital stocks (agriculture, forestry and fishing) — value in Equatorial Guinea was 204,406 million SLC in 2023, according to Food and Agriculture Organization of the United Nations.
- What is the highest net capital stocks (agriculture, forestry and fishing) — value recorded in Equatorial Guinea?
- The highest recorded value was 204,406 million SLC in 2023.
- What is the lowest net capital stocks (agriculture, forestry and fishing) — value recorded in Equatorial Guinea?
- The lowest recorded value was 5,261 million SLC in 1995.
- How does Equatorial Guinea rank for net capital stocks (agriculture, forestry and fishing) — value?
- Equatorial Guinea ranks 66th out of 179 countries with data for 2023.
- Is net capital stocks (agriculture, forestry and fishing) — value rising or falling in Equatorial Guinea?
- Over the last ten years it is up 39.5%. The long-run trend across the full record is volatile.
- Where does this Equatorial Guinea 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 Standard Local Currency, 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.