Value Added (Agriculture, Forestry and Fishing) — Value Standard in Zimbabwe
Zimbabwe: Value Added (Agriculture, Forestry and Fishing) — Value Standard was 20,101 million SLC in 2024. ◆ Volatile
Value Added (Agriculture, Forestry and Fishing) — Value Standard in Zimbabwe, 1970–2024
Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.
Analysis
In 2024, value added (agriculture, forestry and fishing) — value standard in Zimbabwe stood at 20,101 million SLC. That is the highest value across all 55 years on record.
The figure is up 1,511.2% on the previous year and up 1,079.0% over ten years.
Over the whole period, value added (agriculture, forestry and fishing) — value standard in Zimbabwe peaked at 20,101 million SLC in 2024 and was at its lowest, 270.56 million SLC, in 1970.
Zimbabwe ranks 109th of 199 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.
Value Added (Agriculture, Forestry and Fishing) — Value Standard in Zimbabwe, year by year
| Year | million SLC | Change |
|---|---|---|
| 1970 | 270.56 million SLC | — |
| 1971 | 354.72 million SLC | +31.1% |
| 1972 | 449.31 million SLC | +26.7% |
| 1973 | 463.96 million SLC | +3.3% |
| 1974 | 682.58 million SLC | +47.1% |
| 1975 | 715.63 million SLC | +4.8% |
| 1976 | 706.94 million SLC | -1.2% |
| 1977 | 671.42 million SLC | -5.0% |
| 1978 | 541.57 million SLC | -19.3% |
| 1979 | 596.52 million SLC | +10.1% |
| 1980 | 883.82 million SLC | +48.2% |
| 1981 | 1,171 million SLC | +32.5% |
| 1982 | 1,113 million SLC | -5.0% |
| 1983 | 678.27 million SLC | -39.1% |
| 1984 | 751.35 million SLC | +10.8% |
| 1985 | 1,476 million SLC | +96.4% |
| 1986 | 1,267 million SLC | -14.1% |
| 1987 | 1,118 million SLC | -11.8% |
| 1988 | 1,463 million SLC | +31.0% |
| 1989 | 1,398 million SLC | -4.4% |
| 1990 | 1,642 million SLC | +17.4% |
| 1991 | 1,400 million SLC | -14.8% |
| 1992 | 575.27 million SLC | -58.9% |
| 1993 | 1,137 million SLC | +97.7% |
| 1994 | 1,486 million SLC | +30.7% |
| 1995 | 1,210 million SLC | -18.6% |
| 1996 | 2,239 million SLC | +85.1% |
| 1997 | 2,318 million SLC | +3.5% |
| 1998 | 1,504 million SLC | -35.1% |
| 1999 | 1,788 million SLC | +18.9% |
| 2000 | 1,686 million SLC | -5.7% |
| 2001 | 2,122 million SLC | +25.8% |
| 2002 | 2,039 million SLC | -3.9% |
| 2003 | 1,519 million SLC | -25.5% |
| 2004 | 695.99 million SLC | -54.2% |
| 2005 | 683.95 million SLC | -1.7% |
| 2006 | 1,114 million SLC | +62.9% |
| 2007 | 1,558 million SLC | +39.8% |
| 2008 | 1,117 million SLC | -28.3% |
| 2009 | 1,038 million SLC | -7.1% |
| 2010 | 1,157 million SLC | +11.4% |
| 2011 | 1,222 million SLC | +5.6% |
| 2012 | 1,377 million SLC | +12.7% |
| 2013 | 1,364 million SLC | -0.9% |
| 2014 | 1,705 million SLC | +25.0% |
| 2015 | 1,654 million SLC | -3.0% |
| 2016 | 1,618 million SLC | -2.2% |
| 2017 | 1,597 million SLC | -1.3% |
| 2018 | 1,731 million SLC | +8.3% |
| 2019 | 2,219 million SLC | +28.2% |
| 2020 | 1,901 million SLC | -14.3% |
| 2021 | 2,134 million SLC | +12.3% |
| 2022 | 1,894 million SLC | -11.3% |
| 2023 | 1,248 million SLC | -34.1% |
| 2024 | 20,101 million SLC | +1511.2% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1970s | 545.32 million SLC | 270.56 million SLC | 715.63 million SLC | 10 |
| 1980s | 1,132 million SLC | 678.27 million SLC | 1,476 million SLC | 10 |
| 1990s | 1,530 million SLC | 575.27 million SLC | 2,318 million SLC | 10 |
| 2000s | 1,357 million SLC | 683.95 million SLC | 2,122 million SLC | 10 |
| 2010s | 1,564 million SLC | 1,157 million SLC | 2,219 million SLC | 10 |
| 2020s | 5,455 million SLC | 1,248 million SLC | 20,101 million SLC | 5 |
Countries ranked near Zimbabwe
- 106 Papua New Guinea 22,683 million SLC compare
- 107 Denmark 21,983 million SLC compare
- 108 Israel 21,006 million SLC compare
- 110 Netherlands (Kingdom of the) 19,053 million SLC compare
- 111 French Polynesia 18,689 million SLC compare
- 112 Namibia 17,882 million SLC compare
More environment data for Zimbabwe
- Historical exposure to drought — Land soil moisture anomaly 2.93 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly 3.29 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.311 °C (2025)
- Temperature change 1.06 °C (2025)
- Printing and writing papers — Import quantity, annual growth rate 7.86 % change on previous year (2024)
- Printing and writing papers — Import quantity, per capita 0.0008 t per person (2024)
- Printing and writing papers — Import value, annual growth rate 0.9808 % change on previous year (2024)
- Printing and writing papers — Import value, per capita 0.0011 1000 USD per person (2024)
- Other paper and paperboard — Import quantity, annual growth rate -10.86 % change on previous year (2024)
Frequently asked questions
- What is value added (agriculture, forestry and fishing) — value standard in Zimbabwe?
- Value added (agriculture, forestry and fishing) — value standard in Zimbabwe was 20,101 million SLC in 2024, according to Food and Agriculture Organization of the United Nations.
- What is the highest value added (agriculture, forestry and fishing) — value standard recorded in Zimbabwe?
- The highest recorded value was 20,101 million SLC in 2024.
- What is the lowest value added (agriculture, forestry and fishing) — value standard recorded in Zimbabwe?
- The lowest recorded value was 270.56 million SLC in 1970.
- How does Zimbabwe rank for value added (agriculture, forestry and fishing) — value standard?
- Zimbabwe ranks 109th out of 199 countries with data for 2024.
- Is value added (agriculture, forestry and fishing) — value standard rising or falling in Zimbabwe?
- Over the last ten years it is up 1,079.0%. The long-run trend across the full record is volatile.
- Where does this Zimbabwe data come from?
- The figures come from Food and Agriculture Organization of the United Nations, published as part of Value Added (Agriculture, Forestry and Fishing) — Value Standard Local Currency. Statizoid updates them automatically from the source API.
Download this data
CSV · JSON — 55 observations, free to reuse under CC BY-NC-SA 3.0 IGO (FAO).
About this data
The FAOSTAT Macro Indicators database provides a selection of country-level macro indicators relating to total economy (Gross Domestic Product, Gross Fixed Capital Formation); agriculture activity; agriculture, forestry and fishing activity; total manufacturing activity; manufacturing of food products and beverages activity; manufacturing activity of tobacco products; and manufacturing activity of food, beverage and tobacco products.It releases time series for a selection of National Accounts variables, including gross domestic product, gross fixed capital formation, industry-level value added and gross output. The database also proposes additional indicators such as gross domestic product per capita, year-on-year growth rates and measures of industry contribution to gross domestic product. All data relating to Gross Domestic Product, Gross Fixed Capital Formation, agriculture, forestry and fishing activity, and to total manufacturing activity originates from the United Nations Statistics Division (UNSD) National Accounts Estimates of Main Aggregates database, which consists of a complete and consistent set of time series of the main National Accounts aggregates of all UN Members States and other territories in the world for which National Accounts information is available. The UNSD database's content is based on the countries' official National Accounts data reported to UNSD through the annual National Accounts Questionnaire, supplemented with data estimates for any years and countries with incomplete or inconsistent information (See http://unstats.un.org/unsd/snaama/Introduction.asp). Data series relating to the sub-industry Agriculture activity are obtained from the UNSD national accounts Official Country Data databases while series on the Manufacturing activity of food and beverages products, manufacturing activity of tobacco products and manufacturing activity of food, beverages and tobacco products originates from the United Nations Industrial Development Organization (UNIDO) INDSTAT2 database. In order to ensure that sub-industry series are consistent in levels with National Accounts based series, which is needed to support comparability across industries (agriculture vs. agro-industry and sub-industries), UNIDO originating series are rescaled on UNSD National Accounts Estimates of Main Aggregates data series (See Section 17.5 for a more detailed description of the data processing steps).