Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Democratic Republic of the Congo
Democratic Republic of the Congo: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value was 11.79 million million SLC in 2023. ▼ Falling
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Democratic Republic of the Congo, 2000–2023
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 Democratic Republic of the Congo is 11.79 million million SLC, measured in 2023. That is the highest value across all 24 years on record.
Compared with earlier readings it is up 15.7% on the previous year and up 73.7% over ten years.
Over the whole period, net capital stocks (agriculture, forestry and fishing) — value in Democratic Republic of the Congo peaked at 11.79 million million SLC in 2023 and was at its lowest, 6.66 million million SLC, in 2015.
The long-run direction has been consistently falling across the 24 years of available data.
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Democratic Republic of the Congo, year by year
| Year | million SLC | Change |
|---|---|---|
| 2000 | 10.23 million million SLC | — |
| 2001 | 9.81 million million SLC | -4.1% |
| 2002 | 9.42 million million SLC | -3.9% |
| 2003 | 9.03 million million SLC | -4.2% |
| 2004 | 8.60 million million SLC | -4.7% |
| 2005 | 8.21 million million SLC | -4.5% |
| 2006 | 7.84 million million SLC | -4.5% |
| 2007 | 7.53 million million SLC | -4.1% |
| 2008 | 7.30 million million SLC | -3.1% |
| 2009 | 7.14 million million SLC | -2.1% |
| 2010 | 6.86 million million SLC | -3.9% |
| 2011 | 6.74 million million SLC | -1.8% |
| 2012 | 6.86 million million SLC | +1.8% |
| 2013 | 6.78 million million SLC | -1.2% |
| 2014 | 6.70 million million SLC | -1.2% |
| 2015 | 6.66 million million SLC | -0.7% |
| 2016 | 6.68 million million SLC | +0.3% |
| 2017 | 6.76 million million SLC | +1.2% |
| 2018 | 6.87 million million SLC | +1.6% |
| 2019 | 6.85 million million SLC | -0.4% |
| 2020 | 7.00 million million SLC | +2.2% |
| 2021 | 7.74 million million SLC | +10.6% |
| 2022 | 10.19 million million SLC | +31.5% |
| 2023 | 11.79 million million SLC | +15.7% |
Biggest year-on-year movements
Years where Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Democratic Republic of the Congo changed far more than this series normally does. A large move can be a real event or a change in how the figure was measured — the source note below says who published it.
| Year | Change | From | To |
|---|---|---|---|
| 2022 | +31.5% | 7.74 million million SLC | 10.19 million million SLC |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 2000s | 8.51 million million SLC | 7.14 million million SLC | 10.23 million million SLC | 10 |
| 2010s | 6.78 million million SLC | 6.66 million million SLC | 6.87 million million SLC | 10 |
| 2020s | 9.18 million million SLC | 7.00 million million SLC | 11.79 million million SLC | 4 |
Countries ranked near Democratic Republic of the Congo
- 2 Republic of Korea 66.48 million million SLC compare
- 2 Viet Nam 1.26 billion million SLC compare
- 3 Cabo Verde 17,574 million SLC compare
- 3 Lao People's Democratic Republic 29.32 million million SLC compare
- 3 Uzbekistan 59.43 million million SLC compare
- 4 Somalia 57.79 million million SLC compare
- 4 United Republic of Tanzania 25.25 million million SLC compare
- 5 Colombia 56.60 million million SLC compare
- 6 India 50.65 million million SLC compare
- 6 Syrian Arab Republic 5.00 million million SLC compare
- 7 Paraguay 44.22 million million SLC compare
- 7 Türkiye 375,176 million SLC compare
- 8 Bolivia (Plurinational State of) 44,643 million SLC compare
- 8 Nigeria 33.50 million million SLC compare
More environment data for Democratic Republic of the Congo
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Historical exposure to drought — Land soil moisture anomaly -10.22 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly -10.46 Percentage change (2025)
- Temperature change 1.17 °C (2025)
- Standard Deviation 0.193 °C (2025)
- Cropland — Area per capita 0.17 ha/cap (2024)
- Country area — Area 234,541 1000 ha (2024)
- Cropland — Share in Land area 8.16 % (2024)
- Cropland — Share in Agricultural land 50.42 % (2024)
- Cropland — Area 18,510 1000 ha (2024)
Frequently asked questions
- What is net capital stocks (agriculture, forestry and fishing) — value in Democratic Republic of the Congo?
- Net capital stocks (agriculture, forestry and fishing) — value in Democratic Republic of the Congo was 11.79 million 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 Democratic Republic of the Congo?
- The highest recorded value was 11.79 million million SLC in 2023.
- What is the lowest net capital stocks (agriculture, forestry and fishing) — value recorded in Democratic Republic of the Congo?
- The lowest recorded value was 6.66 million million SLC in 2015.
- How does Democratic Republic of the Congo rank for net capital stocks (agriculture, forestry and fishing) — value?
- Democratic Republic of the Congo ranks 5th out of 10 countries with data for 2023.
- Is net capital stocks (agriculture, forestry and fishing) — value rising or falling in Democratic Republic of the Congo?
- Over the last ten years it is up 73.7%. The long-run trend across the full record is falling.
- Where does this Democratic Republic of the Congo 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 — 24 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.