Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Bolivia (Plurinational State of)
Bolivia (Plurinational State of): Net Capital Stocks (Agriculture, Forestry and Fishing) — Value was 44,643 million SLC in 2023. ▲ Rising
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Bolivia (Plurinational State of), 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.
Analysis
Bolivia (Plurinational State of) recorded 44,643 million SLC for net capital stocks (agriculture, forestry and fishing) — value in 2023. That is the highest value across all 29 years on record.
Compared with earlier readings it is up 4.3% on the previous year and up 76.2% over ten years.
Over the whole period, net capital stocks (agriculture, forestry and fishing) — value in Bolivia (Plurinational State of) peaked at 44,643 million SLC in 2023 and was at its lowest, 16,056 million SLC, in 1995.
The long-run direction has been consistently rising across the 29 years of available data.
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Bolivia (Plurinational State of), year by year
| Year | million SLC | Change |
|---|---|---|
| 1995 | 16,056 million SLC | — |
| 1996 | 16,340 million SLC | +1.8% |
| 1997 | 16,866 million SLC | +3.2% |
| 1998 | 17,303 million SLC | +2.6% |
| 1999 | 17,795 million SLC | +2.8% |
| 2000 | 18,209 million SLC | +2.3% |
| 2001 | 18,565 million SLC | +2.0% |
| 2002 | 18,993 million SLC | +2.3% |
| 2003 | 19,562 million SLC | +3.0% |
| 2004 | 20,154 million SLC | +3.0% |
| 2005 | 20,497 million SLC | +1.7% |
| 2006 | 20,750 million SLC | +1.2% |
| 2007 | 20,934 million SLC | +0.9% |
| 2008 | 21,368 million SLC | +2.1% |
| 2009 | 22,022 million SLC | +3.1% |
| 2010 | 22,650 million SLC | +2.9% |
| 2011 | 23,402 million SLC | +3.3% |
| 2012 | 24,245 million SLC | +3.6% |
| 2013 | 25,337 million SLC | +4.5% |
| 2014 | 26,446 million SLC | +4.4% |
| 2015 | 27,738 million SLC | +4.9% |
| 2016 | 29,516 million SLC | +6.4% |
| 2017 | 31,732 million SLC | +7.5% |
| 2018 | 34,081 million SLC | +7.4% |
| 2019 | 36,649 million SLC | +7.5% |
| 2020 | 38,818 million SLC | +5.9% |
| 2021 | 40,830 million SLC | +5.2% |
| 2022 | 42,782 million SLC | +4.8% |
| 2023 | 44,643 million SLC | +4.3% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 16,872 million SLC | 16,056 million SLC | 17,795 million SLC | 5 |
| 2000s | 20,106 million SLC | 18,209 million SLC | 22,022 million SLC | 10 |
| 2010s | 28,180 million SLC | 22,650 million SLC | 36,649 million SLC | 10 |
| 2020s | 41,768 million SLC | 38,818 million SLC | 44,643 million SLC | 4 |
Countries ranked near Bolivia (Plurinational State of)
- 5 Colombia 56.60 million million SLC compare
- 5 Democratic Republic of the Congo 11.79 million million SLC compare
- 6 India 50.65 million million SLC compare
- 6 Syrian Arab Republic 5.00 million million SLC compare
- 7 Paraguay 44.22 million million SLC compare
- 7 Türkiye 375,176 million SLC compare
- 8 Nigeria 33.50 million million SLC compare
- 9 Timor-Leste 431.78 million SLC compare
- 9 Uganda 28.33 million million SLC compare
- 10 Guinea 26.97 million million SLC compare
- 10 Micronesia (Federated States of) 104.55 million SLC compare
- 11 Cambodia 18.01 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 net capital stocks (agriculture, forestry and fishing) — value in Bolivia (Plurinational State of)?
- Net capital stocks (agriculture, forestry and fishing) — value in Bolivia (Plurinational State of) was 44,643 million SLC in 2023, according to Food and Agriculture Organization of the United Nations.
- What is the highest net capital stocks (agriculture, forestry and fishing) — value recorded in Bolivia (Plurinational State of)?
- The highest recorded value was 44,643 million SLC in 2023.
- What is the lowest net capital stocks (agriculture, forestry and fishing) — value recorded in Bolivia (Plurinational State of)?
- The lowest recorded value was 16,056 million SLC in 1995.
- How does Bolivia (Plurinational State of) rank for net capital stocks (agriculture, forestry and fishing) — value?
- Bolivia (Plurinational State of) ranks 8th out of 10 countries with data for 2023.
- Is net capital stocks (agriculture, forestry and fishing) — value rising or falling in Bolivia (Plurinational State of)?
- Over the last ten years it is up 76.2%. 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 Net Capital Stocks (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.