HarvestChoice keeps catalogs of both raster and vector maps of sub-Saharan Africa (downloadable in either ASCII or ESRI Shapefile formats) along with their associated datasets. We also provide access to over 400 articles, survey and census reports on agriculture-related topics in support of investment targeting and prioritization decisions.

Yield Target and Poverty Reduction Model for Sub-Saharan Africa

This comparative static model estimates potential yield increases and poverty reduction effects based on user-selected yield closure gap assumptions. A poverty-productivity elasticity (extracted from the relevant literature) and crop-specific adjustments are used to link productivity gains to a lowering of poverty prevalence rates and poverty headcounts compounded over a 20 year period.

Region Dashboard

HarvestChoice region dashboard provides a one-page view of national time-series and sub-national statistics for 52 countries in sub-Saharan Africa.

Yield Target and Poverty Reduction Model for South Asia

Yield Target and Poverty Reduction Model for South Asia

Comparative static model used to estimate long-term aggregate potential yield gains and aggregate potential poverty reduction effects from narrowing yield gaps for selected commodities in selected regions. The model allows for differentiated yield gap closure and technology adoption scenarios in focus and non-focus countries and for focus and non-focus crops. The model also accounts for varying "poverty-productivity" elasticities across commodities (a synthetic measure linking productivity gains and poverty reduction).

The Changing Pattern and Sources of Agricultural Growth in India

[South Africa] Census of Commercial Agriculture, 2007: Financial and Production Statistics

This publication updates Statistical Release P1101, Census of commercial agriculture 2007, and in many respects can be compared with Report 11-02-01, Census of commercial agriculture 2002.

Generating Plausible Crop Distribution Maps for Sub-Saharan Africa Using a Spatially Disagreggated Data Fusion and Optimization Approach

Large gaps exist in our knowledge of the current geographic distribution and spatial patterns of performance of crops, and these gaps are unlikely to be filled.

Crop Production: SPAM

Dragging and dropping the red marker (Droppr) to any location in SSA provides information on:
• Country name
• District name
• Average cropping intensity (SPAM)
• Crop name (SPAM)

[Tanzania] National Sample Census of Agriculture 2002/2003, Volume 5b (5a): Regional Report, Arusha Region

At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar... conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania...

[Tanzania] National Sample Census of Agriculture 2002/2003, Volume 5c: Regional Report, Kilimanjaro Region

At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar... conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania...

[Tanzania] National Sample Census of Agriculture 2002/2003, Volume 5e: Regional Report, Morogoro Region

At the end of the 2002/03 Agriculture Year, the National Bureau of Statistics and the Office of the Chief Government Statistician in Zanzibar... conducted the Agriculture Sample Census. This is the third Agriculture Census to be carried out in Tanzania...

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