Two decades after Maputo, What’s in the CAADP ten percent? Determinants and effects of the composition of government agriculture expenditure in Africa

Benin, Samuel. 2024. Two decades after Maputo, What’s in the CAADP ten percent? Determinants and effects of the composition of government agriculture expenditure in Africa. Discussion Paper 2260. Washington, DC: International Food Policy Research Institute. https://hdl.handle.net/10568/148782

This paper analyzes the determinants of the composition of government agriculture expenditure (GAE) in Africa and estimates the effect of the composition on agricultural productivity using cross-country annual data from 2014 to 2020 and structural equations modeling methods. It includes different specifications of the explanatory variables to assess the sensitivity of the results to different assumptions of the conceptual variables that are hypothesized to affect the composition and pathways of impact of government expenditure. The results show that there is a wide variation in GAE across African countries, and few have achieved the 10 percent CAADP agriculture expenditure target. Most African countries spend much smaller proportions of the national budget on agriculture than the sector’s share in the economy, and total agriculture expenditure seems to be allocated across subsectors according to their relative contribution to the sector’s output, with forestry and fisheries being slightly favored compared with crops and livestock, which dominate the sector. The allocation is also affected by several factors, such as past output and size of the subsector, official development assistance, education, irrigation, and state of agricultural transformation, although there are cross-subsector differences in their influence. There are also subsector differences in the estimated effect of GAE on land productivity: 0.06 to 0.08 for expenditure on the total sector, 0.02 for research, 0 to 0.09 for crops, 0 to 0.08 for livestock, and 0 to 0.07 for fisheries. The lower bound of zero means that the estimated effect is not statistically significant in some of the model specifications, such as whether cross-subsector expenditure effects are considered. We discuss implications of the results and suggestions for future research.