Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Eastern Africa
Eastern Africa: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 9,362 million USD in 2023. ◆ Volatile
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Eastern Africa, 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 Eastern Africa stood at 9,362 million USD. That is the highest value across all 29 years on record.
Compared with earlier readings it is up 15.9% on the previous year and up 106.0% over ten years.
Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Eastern Africa peaked at 9,362 million USD in 2023 and was at its lowest, 965.01 million USD, in 1995.
Eastern Africa ranks 23rd of 29 groups on this measure, in the bottom quarter.
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 Eastern Africa, year by year
| Year | million USD | Change |
|---|---|---|
| 1995 | 965.01 million USD | — |
| 1996 | 1,078 million USD | +11.7% |
| 1997 | 1,119 million USD | +3.8% |
| 1998 | 1,187 million USD | +6.0% |
| 1999 | 1,167 million USD | -1.7% |
| 2000 | 1,122 million USD | -3.8% |
| 2001 | 1,116 million USD | -0.6% |
| 2002 | 1,131 million USD | +1.3% |
| 2003 | 1,234 million USD | +9.1% |
| 2004 | 1,302 million USD | +5.5% |
| 2005 | 1,565 million USD | +20.2% |
| 2006 | 1,842 million USD | +17.7% |
| 2007 | 2,049 million USD | +11.2% |
| 2008 | 2,618 million USD | +27.8% |
| 2009 | 3,116 million USD | +19.0% |
| 2010 | 3,143 million USD | +0.9% |
| 2011 | 3,532 million USD | +12.4% |
| 2012 | 4,262 million USD | +20.6% |
| 2013 | 4,546 million USD | +6.7% |
| 2014 | 4,889 million USD | +7.5% |
| 2015 | 4,901 million USD | +0.3% |
| 2016 | 5,260 million USD | +7.3% |
| 2017 | 5,830 million USD | +10.8% |
| 2018 | 5,670 million USD | -2.8% |
| 2019 | 6,547 million USD | +15.5% |
| 2020 | 6,580 million USD | +0.5% |
| 2021 | 7,264 million USD | +10.4% |
| 2022 | 8,077 million USD | +11.2% |
| 2023 | 9,362 million USD | +15.9% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 1,103 million USD | 965.01 million USD | 1,187 million USD | 5 |
| 2000s | 1,709 million USD | 1,116 million USD | 3,116 million USD | 10 |
| 2010s | 4,858 million USD | 3,143 million USD | 6,547 million USD | 10 |
| 2020s | 7,821 million USD | 6,580 million USD | 9,362 million USD | 4 |
Countries ranked near Eastern Africa
- 20 Netherlands (Kingdom of the) 5,931 million USD compare
- 21 Bangladesh 5,718 million USD compare
- 22 Poland 5,477 million USD compare
- 23 Romania 5,180 million USD compare
- 24 Republic of Korea 5,054 million USD compare
- 25 Argentina 4,668 million USD compare
- 26 Austria 3,566 million USD compare
More environment data for Eastern Africa
- Historical exposure to drought — Land soil moisture anomaly -7.18 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly -5.98 Percentage change (2025)
- Temperature change 1.28 °C (2025)
- Standard Deviation 0.229 °C (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Exposure to drought — Land soil moisture anomaly -5.99 Percentage change (2024)
- Exposure to drought — Cropland soil moisture anomaly -5.69 Percentage change (2024)
- Other paper and paperboard, not elsewhere specified — Import value -0.3367 % change on previous year (2024)
- Total fibre furnish — Production, annual growth rate 0 % change on previous year (2024)
- Newsprint — Import quantity, annual growth rate -3.02 % change on previous year (2024)
Frequently asked questions
- What is gross fixed capital formation (agriculture, forestry and fishing) in Eastern Africa?
- Gross fixed capital formation (agriculture, forestry and fishing) in Eastern Africa was 9,362 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 Eastern Africa?
- The highest recorded value was 9,362 million USD in 2023.
- What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Eastern Africa?
- The lowest recorded value was 965.01 million USD in 1995.
- How does Eastern Africa rank for gross fixed capital formation (agriculture, forestry and fishing)?
- Eastern Africa ranks 23rd out of 29 groups with data for 2023.
- Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Eastern Africa?
- Over the last ten years it is up 106.0%. The long-run trend across the full record is volatile.
- Where does this Eastern Africa 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
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.