Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Sao Tome and Principe
Sao Tome and Principe: Consumption of Fixed Capital (Agriculture, Forestry and Fishing) was 60.55 million SLC in 2023. ◆ Volatile
Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Sao Tome and Principe, 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.
Analysis
In 2023, consumption of fixed capital (agriculture, forestry and fishing) in Sao Tome and Principe stood at 60.55 million SLC. That is the highest value across all 29 years on record.
Compared with earlier readings it is up 27.3% on the previous year and up 214.4% over ten years.
Over the whole period, consumption of fixed capital (agriculture, forestry and fishing) in Sao Tome and Principe peaked at 60.55 million SLC in 2023 and was at its lowest, 1.02 million SLC, in 1995.
That places Sao Tome and Principe 149th out of 181 countries with data for 2023, putting it in the bottom quarter.
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 Sao Tome and Principe, year by year
| Year | million SLC | Change |
|---|---|---|
| 1995 | 1.02 million SLC | — |
| 1996 | 2.01 million SLC | +97.6% |
| 1997 | 2.78 million SLC | +38.0% |
| 1998 | 3.19 million SLC | +14.9% |
| 1999 | 3.43 million SLC | +7.3% |
| 2000 | 3.61 million SLC | +5.5% |
| 2001 | 2.55 million SLC | -29.5% |
| 2002 | 2.96 million SLC | +16.2% |
| 2003 | 3.5 million SLC | +18.2% |
| 2004 | 4.05 million SLC | +15.7% |
| 2005 | 5.01 million SLC | +23.5% |
| 2006 | 6 million SLC | +19.9% |
| 2007 | 7.2 million SLC | +19.9% |
| 2008 | 9.55 million SLC | +32.7% |
| 2009 | 10.34 million SLC | +8.3% |
| 2010 | 18.72 million SLC | +81.0% |
| 2011 | 20.05 million SLC | +7.1% |
| 2012 | 21.6 million SLC | +7.7% |
| 2013 | 19.26 million SLC | -10.8% |
| 2014 | 19.21 million SLC | -0.3% |
| 2015 | 26.64 million SLC | +38.7% |
| 2016 | 29.03 million SLC | +9.0% |
| 2017 | 30.2 million SLC | +4.0% |
| 2018 | 25.52 million SLC | -15.5% |
| 2019 | 29.51 million SLC | +15.6% |
| 2020 | 29.94 million SLC | +1.4% |
| 2021 | 38.99 million SLC | +30.3% |
| 2022 | 47.56 million SLC | +22.0% |
| 2023 | 60.55 million SLC | +27.3% |
Sao Tome and Principe compared with similar countries
- Sao Tome and Principe's 60.55 million SLC is below the median for lower middle income countries, which is 8,061 million SLC, 1% of the median. (41 countries reporting)
- Sao Tome and Principe's 60.55 million SLC is below the median for Sub-Saharan Africa, which is 21,362 million SLC, 0% of the median. (43 countries reporting)
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 2.49 million SLC | 1.02 million SLC | 3.43 million SLC | 5 |
| 2000s | 5.48 million SLC | 2.55 million SLC | 10.34 million SLC | 10 |
| 2010s | 23.98 million SLC | 18.72 million SLC | 30.2 million SLC | 10 |
| 2020s | 44.26 million SLC | 29.94 million SLC | 60.55 million SLC | 4 |
Countries ranked near Sao Tome and Principe
More environment data for Sao Tome and Principe
- Historical exposure to drought — Land soil moisture anomaly -16.99 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly -12.85 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.214 °C (2025)
- Temperature change 1.16 °C (2025)
- Nutrient potash K2O (total) — Agricultural Use, gaps filled 58 t (2024)
- Nutrient potash K2O (total) — Agricultural Use, annual growth rate -32.56 % change on previous year (2024)
- Country area — Area, annual growth rate 0 % change on previous year (2024)
- Country area — Area, per unit of GDP 0 1000 ha per US$ of GDP (2024)
- Country area — Area, per capita 0.0004 1000 ha per person (2024)
Frequently asked questions
- What is consumption of fixed capital (agriculture, forestry and fishing) in Sao Tome and Principe?
- Consumption of fixed capital (agriculture, forestry and fishing) in Sao Tome and Principe was 60.55 million SLC 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 Sao Tome and Principe?
- The highest recorded value was 60.55 million SLC in 2023.
- What is the lowest consumption of fixed capital (agriculture, forestry and fishing) recorded in Sao Tome and Principe?
- The lowest recorded value was 1.02 million SLC in 1995.
- How does Sao Tome and Principe rank for consumption of fixed capital (agriculture, forestry and fishing)?
- Sao Tome and Principe ranks 149th out of 181 countries with data for 2023.
- Is consumption of fixed capital (agriculture, forestry and fishing) rising or falling in Sao Tome and Principe?
- Over the last ten years it is up 214.4%. The long-run trend across the full record is volatile.
- Where does this Sao Tome and Principe 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 Standard Local Currency. 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.