Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Central African Republic
Central African Republic: Consumption of Fixed Capital (Agriculture, Forestry and Fishing) was 17,390 million SLC in 2023. ▲ Rising
Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Central African Republic, 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 Central African Republic stood at 17,390 million SLC.
Compared with earlier readings it is up 0.3% on the previous year and down 21.6% over ten years.
Over the whole period, consumption of fixed capital (agriculture, forestry and fishing) in Central African Republic peaked at 24,040 million SLC in 2014 and was at its lowest, 7,983 million SLC, in 1995.
Central African Republic ranks 66th of 181 countries on this measure, in the middle of the range.
The long-run direction has been consistently rising across the 29 years of available data.
Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Central African Republic, year by year
| Year | million SLC | Change |
|---|---|---|
| 1995 | 7,983 million SLC | — |
| 1996 | 10,845 million SLC | +35.9% |
| 1997 | 10,739 million SLC | -1.0% |
| 1998 | 10,655 million SLC | -0.8% |
| 1999 | 10,818 million SLC | +1.5% |
| 2000 | 11,221 million SLC | +3.7% |
| 2001 | 11,716 million SLC | +4.4% |
| 2002 | 11,941 million SLC | +1.9% |
| 2003 | 12,294 million SLC | +3.0% |
| 2004 | 12,078 million SLC | -1.8% |
| 2005 | 12,183 million SLC | +0.9% |
| 2006 | 12,710 million SLC | +4.3% |
| 2007 | 13,344 million SLC | +5.0% |
| 2008 | 14,913 million SLC | +11.8% |
| 2009 | 15,823 million SLC | +6.1% |
| 2010 | 18,678 million SLC | +18.0% |
| 2011 | 19,274 million SLC | +3.2% |
| 2012 | 20,156 million SLC | +4.6% |
| 2013 | 22,193 million SLC | +10.1% |
| 2014 | 24,040 million SLC | +8.3% |
| 2015 | 23,101 million SLC | -3.9% |
| 2016 | 22,869 million SLC | -1.0% |
| 2017 | 23,806 million SLC | +4.1% |
| 2018 | 23,477 million SLC | -1.4% |
| 2019 | 15,547 million SLC | -33.8% |
| 2020 | 15,804 million SLC | +1.7% |
| 2021 | 16,296 million SLC | +3.1% |
| 2022 | 17,339 million SLC | +6.4% |
| 2023 | 17,390 million SLC | +0.3% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 10,208 million SLC | 7,983 million SLC | 10,845 million SLC | 5 |
| 2000s | 12,822 million SLC | 11,221 million SLC | 15,823 million SLC | 10 |
| 2010s | 21,314 million SLC | 15,547 million SLC | 24,040 million SLC | 10 |
| 2020s | 16,707 million SLC | 15,804 million SLC | 17,390 million SLC | 4 |
Countries ranked near Central African Republic
More environment data for Central African Republic
- Historical exposure to drought — Land soil moisture anomaly -17.69 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly -17.75 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.218 °C (2025)
- Temperature change 1.3 °C (2025)
- Value Added (Agriculture, Forestry and Fishing) — Value US$, 2015 16.99 % change on previous year (2024)
- Value Added (Agriculture, Forestry and Fishing) — Value US$, 2015 0 million USD per US$ of GDP (2024)
- Value Added (Agriculture, Forestry and Fishing) — Value US$, 2015 0.0002 million USD per person (2024)
- Primary wood and paper products (export/import) — Import value -24.99 % change on previous year (2024)
- Primary wood and paper products (export/import) — Import value, per 0 1000 USD per US$ of GDP (2024)
Frequently asked questions
- What is consumption of fixed capital (agriculture, forestry and fishing) in Central African Republic?
- Consumption of fixed capital (agriculture, forestry and fishing) in Central African Republic was 17,390 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 Central African Republic?
- The highest recorded value was 24,040 million SLC in 2014.
- What is the lowest consumption of fixed capital (agriculture, forestry and fishing) recorded in Central African Republic?
- The lowest recorded value was 7,983 million SLC in 1995.
- How does Central African Republic rank for consumption of fixed capital (agriculture, forestry and fishing)?
- Central African Republic ranks 66th out of 181 countries with data for 2023.
- Is consumption of fixed capital (agriculture, forestry and fishing) rising or falling in Central African Republic?
- Over the last ten years it is down 21.6%. The long-run trend across the full record is rising.
- Where does this Central African Republic 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.