Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Bolivia (Plurinational State of)
Bolivia (Plurinational State of): Consumption of Fixed Capital (Agriculture, Forestry and Fishing) was 3,107 million SLC in 2023. ◆ Volatile
Consumption of Fixed Capital (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
Bolivia (Plurinational State of) recorded 3,107 million SLC for consumption of fixed capital (agriculture, forestry and fishing) in 2023. That is the highest value across all 29 years on record.
That represents a change of up 15.3% on the previous year and up 111.9% over ten years.
Over the whole period, consumption of fixed capital (agriculture, forestry and fishing) in Bolivia (Plurinational State of) peaked at 3,107 million SLC in 2023 and was at its lowest, 330.61 million SLC, in 1995.
The series is highly variable year to year, so single readings are best treated with caution.
Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Bolivia (Plurinational State of), year by year
| Year | million SLC | Change |
|---|---|---|
| 1995 | 330.61 million SLC | — |
| 1996 | 364.99 million SLC | +10.4% |
| 1997 | 383.94 million SLC | +5.2% |
| 1998 | 419.59 million SLC | +9.3% |
| 1999 | 431.56 million SLC | +2.9% |
| 2000 | 490.82 million SLC | +13.7% |
| 2001 | 514.71 million SLC | +4.9% |
| 2002 | 525.25 million SLC | +2.0% |
| 2003 | 534.49 million SLC | +1.8% |
| 2004 | 577.97 million SLC | +8.1% |
| 2005 | 681.96 million SLC | +18.0% |
| 2006 | 829.94 million SLC | +21.7% |
| 2007 | 943.74 million SLC | +13.7% |
| 2008 | 1,011 million SLC | +7.1% |
| 2009 | 970.77 million SLC | -3.9% |
| 2010 | 1,059 million SLC | +9.1% |
| 2011 | 1,218 million SLC | +15.0% |
| 2012 | 1,340 million SLC | +10.0% |
| 2013 | 1,466 million SLC | +9.4% |
| 2014 | 1,651 million SLC | +12.6% |
| 2015 | 1,676 million SLC | +1.5% |
| 2016 | 1,703 million SLC | +1.6% |
| 2017 | 1,854 million SLC | +8.8% |
| 2018 | 1,965 million SLC | +6.0% |
| 2019 | 2,090 million SLC | +6.3% |
| 2020 | 2,212 million SLC | +5.9% |
| 2021 | 2,458 million SLC | +11.1% |
| 2022 | 2,695 million SLC | +9.7% |
| 2023 | 3,107 million SLC | +15.3% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 386.14 million SLC | 330.61 million SLC | 431.56 million SLC | 5 |
| 2000s | 708.02 million SLC | 490.82 million SLC | 1,011 million SLC | 10 |
| 2010s | 1,602 million SLC | 1,059 million SLC | 2,090 million SLC | 10 |
| 2020s | 2,618 million SLC | 2,212 million SLC | 3,107 million SLC | 4 |
Countries ranked near Bolivia (Plurinational State of)
- 5 Somalia 5.64 million million SLC compare
- 5 Syrian Arab Republic 1.04 million million SLC compare
- 6 Lebanon 5.51 million million SLC compare
- 6 Türkiye 191,619 million SLC compare
- 7 Colombia 5.48 million million SLC compare
- 7 Democratic Republic of the Congo 154,505 million SLC compare
- 8 Guinea 3.24 million million SLC compare
- 9 India 2.29 million million SLC compare
- 9 Timor-Leste 28.96 million SLC compare
- 10 Micronesia (Federated States of) 9.5 million SLC compare
- 10 Uganda 2.21 million million SLC compare
- 11 Japan 1.83 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 consumption of fixed capital (agriculture, forestry and fishing) in Bolivia (Plurinational State of)?
- Consumption of fixed capital (agriculture, forestry and fishing) in Bolivia (Plurinational State of) was 3,107 million SLC 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 Bolivia (Plurinational State of)?
- The highest recorded value was 3,107 million SLC in 2023.
- What is the lowest consumption of fixed capital (agriculture, forestry and fishing) recorded in Bolivia (Plurinational State of)?
- The lowest recorded value was 330.61 million SLC in 1995.
- How does Bolivia (Plurinational State of) rank for consumption of fixed capital (agriculture, forestry and fishing)?
- Bolivia (Plurinational State of) ranks 8th out of 10 countries with data for 2023.
- Is consumption of fixed capital (agriculture, forestry and fishing) rising or falling in Bolivia (Plurinational State of)?
- Over the last ten years it is up 111.9%. The long-run trend across the full record is volatile.
- 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 Consumption of Fixed Capital (Agriculture, Forestry and Fishing) — Value Standard Local Currency. 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.