Value Added (Agriculture, Forestry and Fishing) — Value Standard in Zimbabwe
Zimbabwe: Value Added (Agriculture, Forestry and Fishing) — Value Standard was 2,176 million SLC in 2024. ▲ Rising
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
Zimbabwe recorded 2,176 million SLC for value added (agriculture, forestry and fishing) — value standard in 2024.
Compared with earlier readings it is down 15.0% on the previous year and up 24.8% over ten years.
Over the whole period, value added (agriculture, forestry and fishing) — value standard in Zimbabwe peaked at 2,561 million SLC in 2023 and was at its lowest, 882.52 million SLC, in 2008.
Zimbabwe ranks 130th of 191 countries on this measure, in the middle of the range.
The long-run direction has been consistently rising across the 55 years of available data.
Value Added (Agriculture, Forestry and Fishing) — Value Standard in Zimbabwe, year by year
| Year | million SLC | Change |
|---|---|---|
| 1970 | 892.48 million SLC | — |
| 1971 | 1,132 million SLC | +26.9% |
| 1972 | 1,280 million SLC | +13.0% |
| 1973 | 1,035 million SLC | -19.1% |
| 1974 | 1,222 million SLC | +18.1% |
| 1975 | 1,150 million SLC | -5.9% |
| 1976 | 1,280 million SLC | +11.3% |
| 1977 | 1,007 million SLC | -21.3% |
| 1978 | 1,110 million SLC | +10.2% |
| 1979 | 1,110 million SLC | +0.0% |
| 1980 | 1,127 million SLC | +1.6% |
| 1981 | 1,287 million SLC | +14.2% |
| 1982 | 1,195 million SLC | -7.2% |
| 1983 | 1,007 million SLC | -15.7% |
| 1984 | 1,240 million SLC | +23.1% |
| 1985 | 1,535 million SLC | +23.8% |
| 1986 | 1,409 million SLC | -8.2% |
| 1987 | 1,349 million SLC | -4.3% |
| 1988 | 1,392 million SLC | +3.2% |
| 1989 | 1,440 million SLC | +3.5% |
| 1990 | 1,614 million SLC | +12.1% |
| 1991 | 1,631 million SLC | +1.0% |
| 1992 | 1,253 million SLC | -23.2% |
| 1993 | 1,593 million SLC | +27.1% |
| 1994 | 1,709 million SLC | +7.3% |
| 1995 | 1,580 million SLC | -7.6% |
| 1996 | 1,893 million SLC | +19.8% |
| 1997 | 1,954 million SLC | +3.2% |
| 1998 | 1,998 million SLC | +2.3% |
| 1999 | 2,071 million SLC | +3.6% |
| 2000 | 2,074 million SLC | +0.1% |
| 2001 | 2,338 million SLC | +12.7% |
| 2002 | 1,844 million SLC | -21.1% |
| 2003 | 1,676 million SLC | -9.1% |
| 2004 | 1,548 million SLC | -7.6% |
| 2005 | 1,453 million SLC | -6.1% |
| 2006 | 1,391 million SLC | -4.3% |
| 2007 | 1,293 million SLC | -7.1% |
| 2008 | 882.52 million SLC | -31.7% |
| 2009 | 1,242 million SLC | +40.7% |
| 2010 | 1,331 million SLC | +7.2% |
| 2011 | 1,350 million SLC | +1.4% |
| 2012 | 1,456 million SLC | +7.8% |
| 2013 | 1,418 million SLC | -2.6% |
| 2014 | 1,745 million SLC | +23.0% |
| 2015 | 1,654 million SLC | -5.2% |
| 2016 | 1,590 million SLC | -3.9% |
| 2017 | 1,749 million SLC | +10.0% |
| 2018 | 2,070 million SLC | +18.4% |
| 2019 | 1,855 million SLC | -10.4% |
| 2020 | 1,932 million SLC | +4.1% |
| 2021 | 2,270 million SLC | +17.5% |
| 2022 | 2,409 million SLC | +6.2% |
| 2023 | 2,561 million SLC | +6.3% |
| 2024 | 2,176 million SLC | -15.0% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1970s | 1,122 million SLC | 892.48 million SLC | 1,280 million SLC | 10 |
| 1980s | 1,298 million SLC | 1,007 million SLC | 1,535 million SLC | 10 |
| 1990s | 1,730 million SLC | 1,253 million SLC | 2,071 million SLC | 10 |
| 2000s | 1,574 million SLC | 882.52 million SLC | 2,338 million SLC | 10 |
| 2010s | 1,622 million SLC | 1,331 million SLC | 2,070 million SLC | 10 |
| 2020s | 2,270 million SLC | 1,932 million SLC | 2,561 million SLC | 5 |
Countries ranked near Zimbabwe
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)
- Wood-based panels — Import quantity, annual growth rate 6.7 % change on previous year (2024)
- Wood-based panels — Import quantity, per unit of GDP 0 m3 per US$ of GDP (2024)
- Wood-based panels — Import quantity, per capita 0.0057 m3 per person (2024)
- Wood-based panels — Import value, annual growth rate 15.38 % change on previous year (2024)
- Wood-based panels — Import value, per unit of GDP 0 1000 USD per US$ of GDP (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 2,176 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 2,561 million SLC in 2023.
- What is the lowest value added (agriculture, forestry and fishing) — value standard recorded in Zimbabwe?
- The lowest recorded value was 882.52 million SLC in 2008.
- How does Zimbabwe rank for value added (agriculture, forestry and fishing) — value standard?
- Zimbabwe ranks 130th out of 191 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 24.8%. The long-run trend across the full record is rising.
- 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, 2015 prices. Statizoid updates them automatically from the source API.
Download this data
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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).