Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Net Food Importing Developing Countries (NFIDCs)
Net Food Importing Developing Countries (NFIDCs): Consumption of Fixed Capital (Agriculture, Forestry and Fishing) was 24,769 million USD in 2023. ▲ Rising
Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Net Food Importing Developing Countries (NFIDCs), 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million USD.
Analysis
In 2023, consumption of fixed capital (agriculture, forestry and fishing) in Net Food Importing Developing Countries (NFIDCs) stood at 24,769 million USD. That is the highest value across all 29 years on record.
The figure is up 6.0% on the previous year and up 41.2% over ten years.
Over the whole period, consumption of fixed capital (agriculture, forestry and fishing) in Net Food Importing Developing Countries (NFIDCs) peaked at 24,769 million USD in 2023 and was at its lowest, 6,746 million USD, in 2001.
That places Net Food Importing Developing Countries (NFIDCs) 14th out of 29 groups with data for 2023, putting it 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 Net Food Importing Developing Countries (NFIDCs), year by year
| Year | million USD | Change |
|---|---|---|
| 1995 | 6,860 million USD | — |
| 1996 | 6,914 million USD | +0.8% |
| 1997 | 6,948 million USD | +0.5% |
| 1998 | 6,996 million USD | +0.7% |
| 1999 | 6,933 million USD | -0.9% |
| 2000 | 7,687 million USD | +10.9% |
| 2001 | 6,746 million USD | -12.2% |
| 2002 | 7,024 million USD | +4.1% |
| 2003 | 7,632 million USD | +8.7% |
| 2004 | 9,102 million USD | +19.3% |
| 2005 | 9,994 million USD | +9.8% |
| 2006 | 11,097 million USD | +11.0% |
| 2007 | 12,145 million USD | +9.4% |
| 2008 | 13,030 million USD | +7.3% |
| 2009 | 12,432 million USD | -4.6% |
| 2010 | 13,558 million USD | +9.1% |
| 2011 | 15,882 million USD | +17.1% |
| 2012 | 16,851 million USD | +6.1% |
| 2013 | 17,538 million USD | +4.1% |
| 2014 | 19,476 million USD | +11.0% |
| 2015 | 20,054 million USD | +3.0% |
| 2016 | 20,149 million USD | +0.5% |
| 2017 | 21,218 million USD | +5.3% |
| 2018 | 20,040 million USD | -5.6% |
| 2019 | 20,112 million USD | +0.4% |
| 2020 | 20,858 million USD | +3.7% |
| 2021 | 22,871 million USD | +9.7% |
| 2022 | 23,368 million USD | +2.2% |
| 2023 | 24,769 million USD | +6.0% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 6,930 million USD | 6,860 million USD | 6,996 million USD | 5 |
| 2000s | 9,689 million USD | 6,746 million USD | 13,030 million USD | 10 |
| 2010s | 18,488 million USD | 13,558 million USD | 21,218 million USD | 10 |
| 2020s | 22,967 million USD | 20,858 million USD | 24,769 million USD | 4 |
Countries ranked near Net Food Importing Developing Countries (NFIDCs)
- 11 Russian Federation 11,106 million USD compare
- 12 Spain 7,352 million USD compare
- 13 Democratic Republic of the Congo 66.03 million USD compare
- 13 Republic of Korea 6,736 million USD compare
- 14 Brazil 6,462 million USD compare
- 14 Timor-Leste 28.96 million USD compare
- 15 Netherlands (Kingdom of the) 6,382 million USD compare
- 16 Thailand 6,172 million USD compare
- 17 Pakistan 6,044 million USD compare
More environment data for Net Food Importing Developing Countries (NFIDCs)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.221 °C (2025)
- Temperature change 1.34 °C (2025)
- Nutrient potash K2O (total) — Import quantity 1.55 million t (2024)
- Nutrient phosphate P2O5 (total) — Use per value of agricultural 6.68 g/Int$ (2024)
- Nutrient potash K2O (total) — Agricultural Use 1.59 million t (2024)
- Nutrient potash K2O (total) — Use per area of cropland 4.9 kg/ha (2024)
- Country area — Area 3.02 million 1000 ha (2024)
- Land area — Area 2.95 million 1000 ha (2024)
- Nutrient potash K2O (total) — Use per capita 0.86 kg/cap (2024)
All data for Net Food Importing Developing Countries (NFIDCs) →
Frequently asked questions
- What is consumption of fixed capital (agriculture, forestry and fishing) in Net Food Importing Developing Countries (NFIDCs)?
- Consumption of fixed capital (agriculture, forestry and fishing) in Net Food Importing Developing Countries (NFIDCs) was 24,769 million USD 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 Net Food Importing Developing Countries (NFIDCs)?
- The highest recorded value was 24,769 million USD in 2023.
- What is the lowest consumption of fixed capital (agriculture, forestry and fishing) recorded in Net Food Importing Developing Countries (NFIDCs)?
- The lowest recorded value was 6,746 million USD in 2001.
- How does Net Food Importing Developing Countries (NFIDCs) rank for consumption of fixed capital (agriculture, forestry and fishing)?
- Net Food Importing Developing Countries (NFIDCs) ranks 14th out of 29 groups with data for 2023.
- Is consumption of fixed capital (agriculture, forestry and fishing) rising or falling in Net Food Importing Developing Countries (NFIDCs)?
- Over the last ten years it is up 41.2%. The long-run trend across the full record is rising.
- Where does this Net Food Importing Developing Countries (NFIDCs) 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 US$. 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.