Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Low Income Food Deficit Countries (LIFDCs)
Low Income Food Deficit Countries (LIFDCs): Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 19,474 million USD in 2023. ◆ Volatile
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Low Income Food Deficit Countries (LIFDCs), 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million USD.
Analysis
The most recent figure for gross fixed capital formation (agriculture, forestry and fishing) in Low Income Food Deficit Countries (LIFDCs) is 19,474 million USD, measured in 2023. That is the highest value across all 29 years on record.
That represents a change of up 9.0% on the previous year and up 50.3% over ten years.
Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Low Income Food Deficit Countries (LIFDCs) peaked at 19,474 million USD in 2023 and was at its lowest, 3,219 million USD, in 1995.
Low Income Food Deficit Countries (LIFDCs) ranks 19th of 29 groups 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.
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Low Income Food Deficit Countries (LIFDCs), year by year
| Year | million USD | Change |
|---|---|---|
| 1995 | 3,219 million USD | — |
| 1996 | 3,345 million USD | +3.9% |
| 1997 | 3,542 million USD | +5.9% |
| 1998 | 3,496 million USD | -1.3% |
| 1999 | 3,513 million USD | +0.5% |
| 2000 | 3,519 million USD | +0.2% |
| 2001 | 3,454 million USD | -1.8% |
| 2002 | 3,613 million USD | +4.6% |
| 2003 | 3,780 million USD | +4.6% |
| 2004 | 4,189 million USD | +10.8% |
| 2005 | 4,727 million USD | +12.9% |
| 2006 | 5,072 million USD | +7.3% |
| 2007 | 5,913 million USD | +16.6% |
| 2008 | 9,154 million USD | +54.8% |
| 2009 | 9,737 million USD | +6.4% |
| 2010 | 10,926 million USD | +12.2% |
| 2011 | 11,892 million USD | +8.8% |
| 2012 | 12,962 million USD | +9.0% |
| 2013 | 12,955 million USD | -0.1% |
| 2014 | 14,309 million USD | +10.5% |
| 2015 | 14,636 million USD | +2.3% |
| 2016 | 14,211 million USD | -2.9% |
| 2017 | 15,461 million USD | +8.8% |
| 2018 | 14,113 million USD | -8.7% |
| 2019 | 15,533 million USD | +10.1% |
| 2020 | 15,483 million USD | -0.3% |
| 2021 | 16,340 million USD | +5.5% |
| 2022 | 17,870 million USD | +9.4% |
| 2023 | 19,474 million USD | +9.0% |
Biggest year-on-year movements
Years where Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Low Income Food Deficit Countries (LIFDCs) 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 |
|---|---|---|---|
| 2008 | +54.8% | 5,913 million USD | 9,154 million USD |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 3,423 million USD | 3,219 million USD | 3,542 million USD | 5 |
| 2000s | 5,316 million USD | 3,454 million USD | 9,737 million USD | 10 |
| 2010s | 13,700 million USD | 10,926 million USD | 15,533 million USD | 10 |
| 2020s | 17,292 million USD | 15,483 million USD | 19,474 million USD | 4 |
Countries ranked near Low Income Food Deficit Countries (LIFDCs)
- 16 Pakistan 7,943 million USD compare
- 16 Micronesia 16.21 million USD compare
- 17 Mexico 7,727 million USD compare
- 17 Micronesia (Federated States of) 8.83 million USD compare
- 18 Spain 7,596 million USD compare
- 19 Philippines 6,395 million USD compare
- 20 Netherlands (Kingdom of the) 5,931 million USD compare
- 21 Bangladesh 5,718 million USD compare
- 22 Poland 5,477 million USD compare
More environment data for Low Income Food Deficit Countries (LIFDCs)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.238 °C (2025)
- Temperature change 1.36 °C (2025)
- Nutrient potash K2O (total) — Use per area of cropland 2.28 kg/ha (2024)
- Nutrient potash K2O (total) — Import quantity 327,977 t (2024)
- Nutrient potash K2O (total) — Agricultural Use 489,714 t (2024)
- Nutrient potash K2O (total) — Use per value of agricultural production 1.71 g/Int$ (2024)
- Land area — Area 2.01 million 1000 ha (2024)
- Country area — Area 2.05 million 1000 ha (2024)
- Nutrient phosphate P2O5 (total) — Use per value of agricultural 2.65 g/Int$ (2024)
Frequently asked questions
- What is gross fixed capital formation (agriculture, forestry and fishing) in Low Income Food Deficit Countries (LIFDCs)?
- Gross fixed capital formation (agriculture, forestry and fishing) in Low Income Food Deficit Countries (LIFDCs) was 19,474 million USD in 2023, according to Food and Agriculture Organization of the United Nations.
- What is the highest gross fixed capital formation (agriculture, forestry and fishing) recorded in Low Income Food Deficit Countries (LIFDCs)?
- The highest recorded value was 19,474 million USD in 2023.
- What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Low Income Food Deficit Countries (LIFDCs)?
- The lowest recorded value was 3,219 million USD in 1995.
- How does Low Income Food Deficit Countries (LIFDCs) rank for gross fixed capital formation (agriculture, forestry and fishing)?
- Low Income Food Deficit Countries (LIFDCs) ranks 19th out of 29 groups with data for 2023.
- Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Low Income Food Deficit Countries (LIFDCs)?
- Over the last ten years it is up 50.3%. The long-run trend across the full record is volatile.
- Where does this Low Income Food Deficit Countries (LIFDCs) data come from?
- The figures come from Food and Agriculture Organization of the United Nations, published as part of Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Value US$. Statizoid updates them automatically from the source API.
Download this data
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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.