Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Bolivia (Plurinational State of)
Bolivia (Plurinational State of): Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 4,824 million SLC in 2023. ▲ Rising
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Bolivia (Plurinational State of), 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.
Analysis
In 2023, gross fixed capital formation (agriculture, forestry and fishing) in Bolivia (Plurinational State of) stood at 4,824 million SLC. That is the highest value across all 29 years on record.
That represents a change of up 6.3% on the previous year and up 83.7% over ten years.
Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Bolivia (Plurinational State of) peaked at 4,824 million SLC in 2023 and was at its lowest, 1,248 million SLC, in 1995.
The long-run direction has been consistently rising across the 29 years of available data.
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Bolivia (Plurinational State of), year by year
| Year | million SLC | Change |
|---|---|---|
| 1995 | 1,248 million SLC | — |
| 1996 | 1,286 million SLC | +3.0% |
| 1997 | 1,552 million SLC | +20.7% |
| 1998 | 1,494 million SLC | -3.8% |
| 1999 | 1,578 million SLC | +5.6% |
| 2000 | 1,527 million SLC | -3.2% |
| 2001 | 1,493 million SLC | -2.2% |
| 2002 | 1,589 million SLC | +6.4% |
| 2003 | 1,762 million SLC | +10.9% |
| 2004 | 1,820 million SLC | +3.3% |
| 2005 | 1,600 million SLC | -12.1% |
| 2006 | 1,529 million SLC | -4.4% |
| 2007 | 1,473 million SLC | -3.7% |
| 2008 | 1,743 million SLC | +18.3% |
| 2009 | 1,996 million SLC | +14.5% |
| 2010 | 2,010 million SLC | +0.7% |
| 2011 | 2,176 million SLC | +8.3% |
| 2012 | 2,316 million SLC | +6.4% |
| 2013 | 2,625 million SLC | +13.3% |
| 2014 | 2,711 million SLC | +3.3% |
| 2015 | 2,967 million SLC | +9.4% |
| 2016 | 3,549 million SLC | +19.6% |
| 2017 | 4,110 million SLC | +15.8% |
| 2018 | 4,385 million SLC | +6.7% |
| 2019 | 4,755 million SLC | +8.4% |
| 2020 | 4,504 million SLC | -5.3% |
| 2021 | 4,474 million SLC | -0.7% |
| 2022 | 4,539 million SLC | +1.4% |
| 2023 | 4,824 million SLC | +6.3% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 1,432 million SLC | 1,248 million SLC | 1,578 million SLC | 5 |
| 2000s | 1,653 million SLC | 1,473 million SLC | 1,996 million SLC | 10 |
| 2010s | 3,160 million SLC | 2,010 million SLC | 4,755 million SLC | 10 |
| 2020s | 4,585 million SLC | 4,474 million SLC | 4,824 million SLC | 4 |
Countries ranked near Bolivia (Plurinational State of)
- 5 Democratic Republic of the Congo 1.77 million million SLC compare
- 5 Republic of Korea 5.32 million million SLC compare
- 6 India 4.98 million million SLC compare
- 6 Syrian Arab Republic 457,122 million SLC compare
- 7 Guinea 4.43 million million SLC compare
- 7 Türkiye 28,352 million SLC compare
- 8 Uganda 3.79 million million SLC compare
- 9 Paraguay 2.67 million million SLC compare
- 9 Timor-Leste 24.48 million SLC compare
- 10 Cambodia 2.11 million million SLC compare
- 10 Micronesia (Federated States of) 6.46 million SLC compare
- 11 Nigeria 1.86 million million SLC compare
More environment data for Bolivia (Plurinational State of)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.304 °C (2025)
- Temperature change 0.644 °C (2025)
- Nutrient phosphate P2O5 (total) — Use per area of cropland 4.28 kg/ha (2024)
- Inland waters — Area 1,062 1000 ha (2024)
- Nutrient potash K2O (total) — Import quantity 4,486 t (2024)
- Nutrient phosphate P2O5 (total) — Use per value of agricultural 3.39 g/Int$ (2024)
- Nutrient phosphate P2O5 (total) — Agricultural Use 27,016 t (2024)
- Permanent meadows and pastures — Share in Land area 30.33 % (2024)
- Nutrient phosphate P2O5 (total) — Import quantity 27,016 t (2024)
Frequently asked questions
- What is gross fixed capital formation (agriculture, forestry and fishing) in Bolivia (Plurinational State of)?
- Gross fixed capital formation (agriculture, forestry and fishing) in Bolivia (Plurinational State of) was 4,824 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 Bolivia (Plurinational State of)?
- The highest recorded value was 4,824 million SLC in 2023.
- What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Bolivia (Plurinational State of)?
- The lowest recorded value was 1,248 million SLC in 1995.
- How does Bolivia (Plurinational State of) rank for gross fixed capital formation (agriculture, forestry and fishing)?
- Bolivia (Plurinational State of) ranks 8th out of 10 countries with data for 2023.
- Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Bolivia (Plurinational State of)?
- Over the last ten years it is up 83.7%. The long-run trend across the full record is rising.
- Where does this Bolivia (Plurinational State of) 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
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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.