Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Land Locked Developing Countries (LLDCs)
Land Locked Developing Countries (LLDCs): Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 15,620 million USD in 2023. ◆ Volatile
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Land Locked Developing Countries (LLDCs), 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million USD.
Analysis
In 2023, gross fixed capital formation (agriculture, forestry and fishing) in Land Locked Developing Countries (LLDCs) stood at 15,620 million USD. That is the highest value across all 29 years on record.
That represents a change of up 13.0% on the previous year and up 88.2% over ten years.
Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Land Locked Developing Countries (LLDCs) peaked at 15,620 million USD in 2023 and was at its lowest, 2,658 million USD, in 1995.
Land Locked Developing Countries (LLDCs) ranks 21st 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 Land Locked Developing Countries (LLDCs), year by year
| Year | million USD | Change |
|---|---|---|
| 1995 | 2,658 million USD | — |
| 1996 | 2,731 million USD | +2.7% |
| 1997 | 2,777 million USD | +1.7% |
| 1998 | 2,990 million USD | +7.7% |
| 1999 | 3,098 million USD | +3.6% |
| 2000 | 3,566 million USD | +15.1% |
| 2001 | 3,774 million USD | +5.9% |
| 2002 | 3,884 million USD | +2.9% |
| 2003 | 3,992 million USD | +2.8% |
| 2004 | 4,163 million USD | +4.3% |
| 2005 | 6,536 million USD | +57.0% |
| 2006 | 4,748 million USD | -27.4% |
| 2007 | 5,057 million USD | +6.5% |
| 2008 | 5,310 million USD | +5.0% |
| 2009 | 6,108 million USD | +15.0% |
| 2010 | 6,526 million USD | +6.8% |
| 2011 | 7,166 million USD | +9.8% |
| 2012 | 7,769 million USD | +8.4% |
| 2013 | 8,298 million USD | +6.8% |
| 2014 | 8,247 million USD | -0.6% |
| 2015 | 9,163 million USD | +11.1% |
| 2016 | 9,639 million USD | +5.2% |
| 2017 | 10,408 million USD | +8.0% |
| 2018 | 10,480 million USD | +0.7% |
| 2019 | 11,957 million USD | +14.1% |
| 2020 | 12,526 million USD | +4.8% |
| 2021 | 13,348 million USD | +6.6% |
| 2022 | 13,826 million USD | +3.6% |
| 2023 | 15,620 million USD | +13.0% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 2,851 million USD | 2,658 million USD | 3,098 million USD | 5 |
| 2000s | 4,714 million USD | 3,566 million USD | 6,536 million USD | 10 |
| 2010s | 8,965 million USD | 6,526 million USD | 11,957 million USD | 10 |
| 2020s | 13,830 million USD | 12,526 million USD | 15,620 million USD | 4 |
Countries ranked near Land Locked Developing Countries (LLDCs)
- 18 Philippines 6,271 million USD compare
- 19 Mexico 5,582 million USD compare
- 20 Bangladesh 5,443 million USD compare
- 21 Netherlands (Kingdom of the) 4,831 million USD compare
- 22 Poland 4,828 million USD compare
- 23 Republic of Korea 4,705 million USD compare
- 24 Argentina 4,195 million USD compare
More environment data for Land Locked Developing Countries (LLDCs)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Temperature change 1.74 °C (2025)
- Standard Deviation 0.243 °C (2025)
- Nutrient phosphate P2O5 (total) — Use per capita 1.56 kg/cap (2024)
- Permanent crops — Share in Agricultural land 1.3 % (2024)
- Nutrient phosphate P2O5 (total) — Import quantity 835,204 t (2024)
- Nutrient phosphate P2O5 (total) — Agricultural Use 923,654 t (2024)
- Nutrient phosphate P2O5 (total) — Use per value of agricultural 4.32 g/Int$ (2024)
- Permanent crops — Area 10,963 1000 ha (2024)
- Nutrient phosphate P2O5 (total) — Use per area of cropland 5.4 kg/ha (2024)
Frequently asked questions
- What is gross fixed capital formation (agriculture, forestry and fishing) in Land Locked Developing Countries (LLDCs)?
- Gross fixed capital formation (agriculture, forestry and fishing) in Land Locked Developing Countries (LLDCs) was 15,620 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 Land Locked Developing Countries (LLDCs)?
- The highest recorded value was 15,620 million USD in 2023.
- What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Land Locked Developing Countries (LLDCs)?
- The lowest recorded value was 2,658 million USD in 1995.
- How does Land Locked Developing Countries (LLDCs) rank for gross fixed capital formation (agriculture, forestry and fishing)?
- Land Locked Developing Countries (LLDCs) ranks 21st out of 29 groups with data for 2023.
- Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Land Locked Developing Countries (LLDCs)?
- Over the last ten years it is up 88.2%. The long-run trend across the full record is volatile.
- Where does this Land Locked Developing Countries (LLDCs) 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$, 2015 prices. 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.