Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Belarus
Belarus: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 3,742 million SLC in 2023. ◆ Volatile
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Belarus, 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.
Analysis
The most recent figure for gross fixed capital formation (agriculture, forestry and fishing) in Belarus is 3,742 million SLC, measured in 2023.
That represents a change of up 12.9% on the previous year and down 10.7% over ten years.
Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Belarus peaked at 4,907 million SLC in 2010 and was at its lowest, 270.66 million SLC, in 1996.
Belarus ranks 96th of 181 countries 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 Belarus, year by year
| Year | million SLC | Change |
|---|---|---|
| 1995 | 363.01 million SLC | — |
| 1996 | 270.66 million SLC | -25.4% |
| 1997 | 349.26 million SLC | +29.0% |
| 1998 | 461.16 million SLC | +32.0% |
| 1999 | 373.04 million SLC | -19.1% |
| 2000 | 432.63 million SLC | +16.0% |
| 2001 | 308.62 million SLC | -28.7% |
| 2002 | 353.87 million SLC | +14.7% |
| 2003 | 468.85 million SLC | +32.5% |
| 2004 | 855.98 million SLC | +82.6% |
| 2005 | 1,559 million SLC | +82.1% |
| 2006 | 2,633 million SLC | +68.9% |
| 2007 | 2,695 million SLC | +2.3% |
| 2008 | 3,495 million SLC | +29.7% |
| 2009 | 4,476 million SLC | +28.1% |
| 2010 | 4,907 million SLC | +9.6% |
| 2011 | 4,106 million SLC | -16.3% |
| 2012 | 4,463 million SLC | +8.7% |
| 2013 | 4,192 million SLC | -6.1% |
| 2014 | 2,855 million SLC | -31.9% |
| 2015 | 2,582 million SLC | -9.6% |
| 2016 | 2,084 million SLC | -19.3% |
| 2017 | 2,520 million SLC | +20.9% |
| 2018 | 2,492 million SLC | -1.1% |
| 2019 | 2,854 million SLC | +14.5% |
| 2020 | 3,050 million SLC | +6.9% |
| 2021 | 2,990 million SLC | -2.0% |
| 2022 | 3,315 million SLC | +10.8% |
| 2023 | 3,742 million SLC | +12.9% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 363.43 million SLC | 270.66 million SLC | 461.16 million SLC | 5 |
| 2000s | 1,728 million SLC | 308.62 million SLC | 4,476 million SLC | 10 |
| 2010s | 3,305 million SLC | 2,084 million SLC | 4,907 million SLC | 10 |
| 2020s | 3,274 million SLC | 2,990 million SLC | 3,742 million SLC | 4 |
Countries ranked near Belarus
- 93 New Zealand 4,204 million SLC compare
- 94 Bhutan 4,183 million SLC compare
- 95 Turkmenistan 3,871 million SLC compare
- 97 Jamaica 3,575 million SLC compare
- 98 Israel 3,548 million SLC compare
- 99 Kyrgyzstan 3,345 million SLC compare
More environment data for Belarus
- Historical exposure to drought — Land soil moisture anomaly -0.1734 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly -0.1993 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.869 °C (2025)
- Temperature change 2.57 °C (2025)
- Paper and paperboard — Import quantity, annual growth rate -58.58 % change on previous year (2024)
- Paper and paperboard — Import quantity, per unit of GDP 0 t per US$ of GDP (2024)
- Paper and paperboard — Import quantity, per capita 0.0044 t per person (2024)
- Paper and paperboard — Import value, annual growth rate -34.3 % change on previous year (2024)
- Paper and paperboard — Import value, per unit of GDP 0 1000 USD per US$ of GDP (2024)
Frequently asked questions
- What is gross fixed capital formation (agriculture, forestry and fishing) in Belarus?
- Gross fixed capital formation (agriculture, forestry and fishing) in Belarus was 3,742 million SLC 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 Belarus?
- The highest recorded value was 4,907 million SLC in 2010.
- What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Belarus?
- The lowest recorded value was 270.66 million SLC in 1996.
- How does Belarus rank for gross fixed capital formation (agriculture, forestry and fishing)?
- Belarus ranks 96th out of 181 countries with data for 2023.
- Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Belarus?
- Over the last ten years it is down 10.7%. The long-run trend across the full record is volatile.
- Where does this Belarus 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 Standard Local Currency, 2015 prices. 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.