Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Botswana
Botswana: Consumption of Fixed Capital (Agriculture, Forestry and Fishing) was 198.81 million SLC in 2023. ▲ Rising
Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Botswana, 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.
Analysis
In 2023, consumption of fixed capital (agriculture, forestry and fishing) in Botswana stood at 198.81 million SLC. That is the highest value across all 29 years on record.
Compared with earlier readings it is up 15.1% on the previous year and up 72.6% over ten years.
Over the whole period, consumption of fixed capital (agriculture, forestry and fishing) in Botswana peaked at 198.81 million SLC in 2023 and was at its lowest, 62.52 million SLC, in 1995.
Botswana ranks 134th of 181 countries on this measure, 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 Botswana, year by year
| Year | million SLC | Change |
|---|---|---|
| 1995 | 62.52 million SLC | — |
| 1996 | 65.42 million SLC | +4.6% |
| 1997 | 72.72 million SLC | +11.1% |
| 1998 | 77.31 million SLC | +6.3% |
| 1999 | 79.99 million SLC | +3.5% |
| 2000 | 78.58 million SLC | -1.8% |
| 2001 | 83.78 million SLC | +6.6% |
| 2002 | 87.67 million SLC | +4.6% |
| 2003 | 87.38 million SLC | -0.3% |
| 2004 | 84.19 million SLC | -3.7% |
| 2005 | 84.48 million SLC | +0.3% |
| 2006 | 85.59 million SLC | +1.3% |
| 2007 | 88.69 million SLC | +3.6% |
| 2008 | 93.23 million SLC | +5.1% |
| 2009 | 97.06 million SLC | +4.1% |
| 2010 | 99.98 million SLC | +3.0% |
| 2011 | 103.16 million SLC | +3.2% |
| 2012 | 108.32 million SLC | +5.0% |
| 2013 | 115.18 million SLC | +6.3% |
| 2014 | 121.55 million SLC | +5.5% |
| 2015 | 127.23 million SLC | +4.7% |
| 2016 | 133.56 million SLC | +5.0% |
| 2017 | 140.43 million SLC | +5.1% |
| 2018 | 147.52 million SLC | +5.0% |
| 2019 | 154.88 million SLC | +5.0% |
| 2020 | 162.18 million SLC | +4.7% |
| 2021 | 168.01 million SLC | +3.6% |
| 2022 | 172.72 million SLC | +2.8% |
| 2023 | 198.81 million SLC | +15.1% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 71.59 million SLC | 62.52 million SLC | 79.99 million SLC | 5 |
| 2000s | 87.07 million SLC | 78.58 million SLC | 97.06 million SLC | 10 |
| 2010s | 125.18 million SLC | 99.98 million SLC | 154.88 million SLC | 10 |
| 2020s | 175.43 million SLC | 162.18 million SLC | 198.81 million SLC | 4 |
Countries ranked near Botswana
- 131 Estonia 253.33 million SLC compare
- 132 Sierra Leone 239.77 million SLC compare
- 133 El Salvador 217.06 million SLC compare
- 135 Papua New Guinea 185.53 million SLC compare
- 136 Bosnia and Herzegovina 177.21 million SLC compare
- 137 Suriname 159.04 million SLC compare
More environment data for Botswana
- Historical exposure to drought — Land soil moisture anomaly 6.04 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly 6.49 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.381 °C (2025)
- Temperature change 0.443 °C (2025)
- Sawnwood, non-coniferous — Production, per unit of GDP 0 m3 per US$ of GDP (2024)
- Sawnwood, non-coniferous — Production, per capita 0 m3 per person (2024)
- Sawnwood, non-coniferous — Import quantity, annual growth rate -43.96 % change on previous year (2024)
- Sawnwood, non-coniferous — Import quantity, per unit of GDP 0 m3 per US$ of GDP (2024)
- Sawnwood, non-coniferous — Import quantity, per capita 0.0233 m3 per person (2024)
Frequently asked questions
- What is consumption of fixed capital (agriculture, forestry and fishing) in Botswana?
- Consumption of fixed capital (agriculture, forestry and fishing) in Botswana was 198.81 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 Botswana?
- The highest recorded value was 198.81 million SLC in 2023.
- What is the lowest consumption of fixed capital (agriculture, forestry and fishing) recorded in Botswana?
- The lowest recorded value was 62.52 million SLC in 1995.
- How does Botswana rank for consumption of fixed capital (agriculture, forestry and fishing)?
- Botswana ranks 134th out of 181 countries with data for 2023.
- Is consumption of fixed capital (agriculture, forestry and fishing) rising or falling in Botswana?
- Over the last ten years it is up 72.6%. The long-run trend across the full record is rising.
- Where does this Botswana 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, 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.