Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Mauritania
Mauritania: Consumption of Fixed Capital (Agriculture, Forestry and Fishing) was 4,653 million SLC in 2023. ◆ Volatile
Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Mauritania, 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.
Analysis
Mauritania recorded 4,653 million SLC for consumption of fixed capital (agriculture, forestry and fishing) in 2023. That is the highest value across all 29 years on record.
Compared with earlier readings it is up 18.2% on the previous year and up 126.4% over ten years.
Over the whole period, consumption of fixed capital (agriculture, forestry and fishing) in Mauritania peaked at 4,653 million SLC in 2023 and was at its lowest, 605.65 million SLC, in 1996.
Mauritania ranks 90th of 181 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.
Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Mauritania, year by year
| Year | million SLC | Change |
|---|---|---|
| 1995 | 618.8 million SLC | — |
| 1996 | 605.65 million SLC | -2.1% |
| 1997 | 685.45 million SLC | +13.2% |
| 1998 | 724.31 million SLC | +5.7% |
| 1999 | 841.27 million SLC | +16.1% |
| 2000 | 840.31 million SLC | -0.1% |
| 2001 | 860.69 million SLC | +2.4% |
| 2002 | 881.67 million SLC | +2.4% |
| 2003 | 902.91 million SLC | +2.4% |
| 2004 | 1,021 million SLC | +13.0% |
| 2005 | 1,070 million SLC | +4.9% |
| 2006 | 1,178 million SLC | +10.0% |
| 2007 | 1,289 million SLC | +9.4% |
| 2008 | 1,481 million SLC | +14.9% |
| 2009 | 1,485 million SLC | +0.3% |
| 2010 | 1,669 million SLC | +12.4% |
| 2011 | 1,781 million SLC | +6.7% |
| 2012 | 1,930 million SLC | +8.4% |
| 2013 | 2,055 million SLC | +6.5% |
| 2014 | 2,196 million SLC | +6.8% |
| 2015 | 2,261 million SLC | +3.0% |
| 2016 | 2,390 million SLC | +5.7% |
| 2017 | 2,517 million SLC | +5.3% |
| 2018 | 2,688 million SLC | +6.8% |
| 2019 | 2,900 million SLC | +7.9% |
| 2020 | 3,065 million SLC | +5.7% |
| 2021 | 3,520 million SLC | +14.8% |
| 2022 | 3,937 million SLC | +11.8% |
| 2023 | 4,653 million SLC | +18.2% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 695.1 million SLC | 605.65 million SLC | 841.27 million SLC | 5 |
| 2000s | 1,101 million SLC | 840.31 million SLC | 1,485 million SLC | 10 |
| 2010s | 2,239 million SLC | 1,669 million SLC | 2,900 million SLC | 10 |
| 2020s | 3,794 million SLC | 3,065 million SLC | 4,653 million SLC | 4 |
Countries ranked near Mauritania
- 87 Netherlands (Kingdom of the) 5,902 million SLC compare
- 88 Jamaica 4,995 million SLC compare
- 89 North Macedonia 4,797 million SLC compare
- 91 Peru 4,652 million SLC compare
- 92 Israel 4,617 million SLC compare
- 93 Kyrgyzstan 4,318 million SLC compare
More environment data for Mauritania
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.465 °C (2025)
- Temperature change 1.85 °C (2025)
- Roundwood, non-coniferous — Production, annual growth rate 1.86 % change on previous year (2024)
- Wood fuel — Production, annual growth rate 1.88 % change on previous year (2024)
- Wood fuel, non-coniferous — Production, annual growth rate 1.88 % change on previous year (2024)
- Industrial roundwood — Production, annual growth rate 0 % change on previous year (2024)
- Industrial roundwood — Import quantity, per unit of GDP 0 m3 per US$ of GDP (2024)
- Industrial roundwood — Import quantity, per capita 0.0042 m3 per person (2024)
- Industrial roundwood — Import value, per unit of GDP 0 1000 USD per US$ of GDP (2024)
Frequently asked questions
- What is consumption of fixed capital (agriculture, forestry and fishing) in Mauritania?
- Consumption of fixed capital (agriculture, forestry and fishing) in Mauritania was 4,653 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 Mauritania?
- The highest recorded value was 4,653 million SLC in 2023.
- What is the lowest consumption of fixed capital (agriculture, forestry and fishing) recorded in Mauritania?
- The lowest recorded value was 605.65 million SLC in 1996.
- How does Mauritania rank for consumption of fixed capital (agriculture, forestry and fishing)?
- Mauritania ranks 90th out of 181 countries with data for 2023.
- Is consumption of fixed capital (agriculture, forestry and fishing) rising or falling in Mauritania?
- Over the last ten years it is up 126.4%. The long-run trend across the full record is volatile.
- Where does this Mauritania 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.