Abstract

PurposeAgriculture is the major source of livelihood for the majority of population in Sub-Saharan Africa but its productivity is not only low it has started showing signs of decline since 2012. The purpose of this paper is to find out whether official development assistance for agriculture is effective.Design/methodology/approachThe data for development assistance for agriculture are broken down into the major agricultural sectors in receiving countries. The empirical evidence is based on the two-step system, i.e. generalized method of moments, to assess the degree of responsiveness of agricultural productivity to development assistance.FindingsThere is a positive relationship between development assistance and agricultural productivity in general. However, when broken down into the major agricultural recipient sectors, there is a substitution effect between food crop production and industrial crop production. Better institutions and economic freedom are found to enable agricultural productivity growth, and to increase the effectiveness of development assistance. The structural economic transformation associated with agricultural development assistance is also found to be weak.Practical implicationsAllocation of development assistance for agriculture is primarily determined by need, although expected effectiveness also increases the assistance receipts. Agricultural assistance policies could focus more on building productive capacity to reduce the need while boosting effectiveness.Originality/valueBreaking down data into agricultural recipient sectors and controlling for the potential spurious correlation under the assumption that more development assistance could be allocated, where agricultural productivity is already increasing due to some other factors.

Highlights

  • Previous research shows that agriculture plays a pivotal role in the development of the SubSaharan Africa (SSA) as the major source of income, food, employment, and in its effectiveness in reducing poverty

  • The African Development Bank Group (AfDB) Feed Africa Strategy (2016) disclosed that in 2014 over 60 percent of the people in Africa lived in rural areas and relied on agriculture for their livelihoods, and that women in Africa made up at least half of the agricultural labor force (Dao, 2009)

  • We find that agriculture value-added percent of GDP is inversely related to increases in official development assistance (ODA) for agriculture per worker. This is a natural result because structural transformation in developing countries often begins with an increase in agricultural output per worker creating a surplus in the rural economy, which is progressively transferred into the nonagricultural sectors

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Summary

Introduction

Previous research shows that agriculture plays a pivotal role in the development of the SubSaharan Africa (SSA) as the major source of income, food, employment, and in its effectiveness in reducing poverty. ODA allocation to areas in need has a strong marginal impact on agricultural value added per worker that falls between 4.55 and 9.01 percentage points, and capable of increasing by approximately 6 percentage points under better government effectiveness. The unexplained effects (constant terms) are significant but small, implying that the volatility of agricultural output (need) and government institutions are the key determinants of how much ODA a country receives We end this part of result discussion upholding that ODA does affect agricultural productivity. We find that agriculture value-added percent of GDP is inversely related to increases in ODA for agriculture per worker This is a natural result because structural transformation in developing countries often begins with an increase in agricultural output per worker creating a surplus in the rural economy, which is progressively transferred into the nonagricultural sectors. Future studies should focus on the extent to which different components of ODA can be correlated and how the established findings withstand empirical scrutiny when ODA from other sectors are added to the regressions

Discussion
Findings
Control of corruption
Government effectiveness
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