Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Eastern Europe
Eastern Europe: Consumption of Fixed Capital (Agriculture, Forestry and Fishing) was 25,854 million USD in 2023. ▲ Rising
Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Eastern Europe, 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million USD.
Analysis
Eastern Europe recorded 25,854 million USD for consumption of fixed capital (agriculture, forestry and fishing) in 2023. That is the highest value across all 29 years on record.
The figure is up 5.6% on the previous year and up 19.6% over ten years.
Over the whole period, consumption of fixed capital (agriculture, forestry and fishing) in Eastern Europe peaked at 25,854 million USD in 2023 and was at its lowest, 5,119 million USD, in 1999.
That places Eastern Europe 13th 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 Eastern Europe, year by year
| Year | million USD | Change |
|---|---|---|
| 1995 | 6,411 million USD | — |
| 1996 | 6,690 million USD | +4.4% |
| 1997 | 6,735 million USD | +0.7% |
| 1998 | 6,032 million USD | -10.4% |
| 1999 | 5,119 million USD | -15.1% |
| 2000 | 6,272 million USD | +22.5% |
| 2001 | 6,957 million USD | +10.9% |
| 2002 | 7,130 million USD | +2.5% |
| 2003 | 8,169 million USD | +14.6% |
| 2004 | 9,485 million USD | +16.1% |
| 2005 | 10,396 million USD | +9.6% |
| 2006 | 11,618 million USD | +11.7% |
| 2007 | 14,283 million USD | +22.9% |
| 2008 | 17,420 million USD | +22.0% |
| 2009 | 15,290 million USD | -12.2% |
| 2010 | 16,966 million USD | +11.0% |
| 2011 | 18,960 million USD | +11.8% |
| 2012 | 19,686 million USD | +3.8% |
| 2013 | 21,621 million USD | +9.8% |
| 2014 | 21,113 million USD | -2.4% |
| 2015 | 16,480 million USD | -21.9% |
| 2016 | 16,355 million USD | -0.8% |
| 2017 | 18,995 million USD | +16.1% |
| 2018 | 20,244 million USD | +6.6% |
| 2019 | 20,482 million USD | +1.2% |
| 2020 | 20,860 million USD | +1.8% |
| 2021 | 22,656 million USD | +8.6% |
| 2022 | 24,475 million USD | +8.0% |
| 2023 | 25,854 million USD | +5.6% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 6,198 million USD | 5,119 million USD | 6,735 million USD | 5 |
| 2000s | 10,702 million USD | 6,272 million USD | 17,420 million USD | 10 |
| 2010s | 19,090 million USD | 16,355 million USD | 21,621 million USD | 10 |
| 2020s | 23,461 million USD | 20,860 million USD | 25,854 million USD | 4 |
Countries ranked near Eastern Europe
- 10 Japan 13,058 million USD compare
- 10 Melanesia 174.88 million USD compare
- 11 Russian Federation 11,106 million USD compare
- 11 Syrian Arab Republic 140.53 million USD compare
- 12 Lao People's Democratic Republic 130.01 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
- 15 Polynesia 16.73 million USD compare
- 16 Thailand 6,172 million USD compare
- 16 Micronesia 15.34 million USD compare
More environment data for Eastern Europe
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Historical exposure to drought — Land soil moisture anomaly -2.03 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly -4.01 Percentage change (2025)
- Standard Deviation 0.483 °C (2025)
- Temperature change 2.81 °C (2025)
- Roundwood — Production 339.05 million m3 (2024)
- Roundwood, non-coniferous — Production 89.12 million m3 (2024)
- Roundwood, coniferous — Production 249.93 million m3 (2024)
- Roundwood — Export value 1.44 million 1000 USD (2024)
- Roundwood — Export quantity 13.20 million m3 (2024)
Frequently asked questions
- What is consumption of fixed capital (agriculture, forestry and fishing) in Eastern Europe?
- Consumption of fixed capital (agriculture, forestry and fishing) in Eastern Europe was 25,854 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 Eastern Europe?
- The highest recorded value was 25,854 million USD in 2023.
- What is the lowest consumption of fixed capital (agriculture, forestry and fishing) recorded in Eastern Europe?
- The lowest recorded value was 5,119 million USD in 1999.
- How does Eastern Europe rank for consumption of fixed capital (agriculture, forestry and fishing)?
- Eastern Europe ranks 13th out of 29 groups with data for 2023.
- Is consumption of fixed capital (agriculture, forestry and fishing) rising or falling in Eastern Europe?
- Over the last ten years it is up 19.6%. The long-run trend across the full record is rising.
- Where does this Eastern Europe 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.