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Agricultural R&D Expenditure in Africa: An Analysis of Growth and Volatility

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Abstract

Agricultural research and development (R&D) investment is positively associated with high returns, but these returns take time – often decades – to develop. Consequently, the inherent lag from the inception of research to the adoption of new technologies calls for sustained and stable R&D funding. This article introduces a quantitative measure to assess volatility in agricultural R&D spending. It reveals that agricultural R&D spending in Sub-Saharan Africa (SSA) has been substantially more volatile than in other developing regions, which is the consequence of low levels of government funding, coupled with a high dependence on short-term and ad hoc donor and development bank funding. Rather than relying too much on external funding, SSA governments need to clearly identify long-term priorities, design focused and coherent agricultural R&D programmes accordingly, and commit sufficient funding for their implementation, while donor funding needs to be better aligned with national priorities. Moreover, diversification of funding sources is needed to better absorb funding shocks.

Abstract

L’investissement en R&D agricole est positivement associé à des rendements élevés, mais ces rendements prennent du temps, souvent plusieurs décennies, à se développer. Par conséquent, le décalage inhérent entre le début de la recherche et l’adoption de nouvelles technologies rappelle le besoin de financements soutenus et stables pour la R& D. Cet article introduit une mesure quantitative pour évaluer la volatilité des dépenses en R&D. Il révèle que les dépenses en R&D agricole en Afrique sub-saharienne (ASS) sont beaucoup plus volatiles que dans d’autres régions en développement, ce qui est la conséquence du faible niveau de financement du gouvernement, allié à une forte dépendance sur les financements à court terme et ad hoc des bailleurs de fonds et des banques de développement. Plutôt que de trop compter sur un financement externe, les gouvernements d’Afrique subsaharienne doivent définir clairement leurs priorités à long terme, concevoir en conséquence des programmes de R&D agricole ciblés et cohérents, et engager des fonds suffisants pour leur mise en œuvre, tandis que le financement des bailleurs de fonds doit être mieux aligné sur les priorités nationales. En outre, la diversification des sources de financement est nécessaire pour mieux absorber les chocs de financement.

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Notes

  1. For more information on ASTI methodology, visit www.asti.cgiar.org/methodology.

  2. Cariolle (2012) identifies three main measures to quantify volatility: volatility as the standard deviation of the growth rate of a variable, volatility as the standard deviation of the residual of an econometric regression and volatility as the standard deviation of the cycle isolated by a statistical filter. These techniques vary in terms of the choice of reference value and the way in which deviations from the reference value are calculated. We recognize some of the limitations of calculating volatility based on the standard deviation of the growth rate, but given the relatively small sample of just 31 SSA countries, we believe the method is sufficient to highlight cross-country differences in volatility in agricultural R&D spending.

  3. This is an unweighted average. Country-level agricultural R&D expenditure data for 2009–2011 were unavailable for Asia-Pacific and Latin America.

  4. Agricultural GDP data were taken from World Bank (2013).

  5. The sample includes 82 large agricultural research agencies in Benin, Botswana, Burkina Faso, Burundi, Republic of Congo, Côte d’Ivoire, Eritrea, Ethiopia, Gabon, The Gambia, Ghana, Guinea, Kenya, Madagascar, Mali, Mauritania, Mauritius, Namibia, Nigeria, Senegal, Sudan, Tanzania, Togo, Uganda and Zambia. Combined, these agencies accounted for 31 per cent of total agricultural R&D spending in SSA in 2011. Given that log transform can only be applied to non-zero values, a value of 0.001 was added to each agency’s salary, operating and capital investments. This had a negligible impact on the individual institutes’ and overall volatility coefficients, and allowed for the calculation of volatility coefficients of institutes without capital spending during a certain year.

  6. Although the data allowed for the calculation of a volatility coefficient for funding derived from commodity levies and producer organizations, this coefficient was irrelevant at the SSA level as only a handful of countries generate funding for agricultural R&D this way and therefore the mean would be skewed.

References

  • Agion, P., Angeletos, G.M., Banerjee, A. and Manova, K. (2005) Volatility and Growth: Credit Constraints and Productivity-Enhancing Investment. Cambridge, MA: National Bureau of Economic Research. NBER Working Paper 11349.

  • Alene, A.D. and Coulibaly, O. (2009) The impact of agricultural research on productivity and poverty in Sub-Saharan Africa. Food Policy 34 (2): 198–209.

    Article  Google Scholar 

  • Alene, A.D., Manyong, V.M., Abele, S. and Sanyogo, D. (eds.) (2006) Assessing the Impacts of Agricultural Research on Rural Livelihoods: Achievements, Gaps, and Options. Ibadan, Nigeria: International Institute for Tropical Agriculture.

    Google Scholar 

  • Alston, J.M., Chan-Kang, C., Marra, M.C., Pardey, P.G. and Wyatt, T.J. (2000) A Meta-analysis of Rates of Return to Agricultural R&D: Ex Pede Herculem? Washington DC: International Food Policy Research Institute. IFPRI Research Report 113.

  • Alston, J.M., Pardey, P.G. and Piggott, R.R. (eds.) (2006) Synthesis of themes and policy issues. In: Agricultural R&D in the Developing World: Too Little, Too Late?. Washington DC: International Food Policy Research Institute, pp. 361–372.

    Google Scholar 

  • ASTI (Agricultural Science and Technology Indicators) (2001–2014) ASTI database, http://asti.cgiar.org/data/.

  • Beintema, N.M. and Stads, G.J. (2011) African Agricultural R&D in the New Millennium: Progress for Some, Challenges for Many. Washington DC: International Food Policy Research Institute. IFPRI Food Policy Report.

  • Beintema, N.M. and Stads, G.J. (2014) Agricultural R&D: Is Africa investing enough? In: A. Marble and H. Fritschel (eds.) 2013 Global Food Policy Report. Washington DC: International Food Policy Research Institute, pp. 53–62.

    Google Scholar 

  • Beintema, N.M., Stads, G.J., Fuglie, K.O. and Heisey, P. (2012) ASTI Global Assessment of Agricultural R&D Spending: Developing Countries Accelerate Investment. Washington DC; Rome, Italy: International Food Policy Research Institute and Global Forum on Agricultural Research.

    Google Scholar 

  • Bulíř, A. and Hamann, A.J. (2003) Aid Volatility: An Empirical Assessment. Washington DC: International Monetary Fund. IMF staff papers 50 (1).

  • Cariolle, J. (2012) Measuring Macroeconomic Volatility: Applications to Export Revenue Data, 1970–2005. Clermont-Ferrand, France: Fondation pour les études et recherches sur le développement international. Working Paper I14.

  • Cullen, G., Gasbarro, D., Ruan, W. and Xiang, E. (2014) R&D expenditure volatility and stock return: Earnings management, adjustment costs or overinvestment? http://ssrn.com/abstract=2482827.

  • Desai, R.M. and Kharas, H. (2010) The Determinants of Aid Volatility. Washington DC: Brookings Institution. Global Economy and Development Working Paper 42.

  • Durlauf, S.N., Johnson, J.A. and Temple, P.R.W. (2005) Growth econometrics. In: P. Agion and S.N. Durlauf (eds.) Handbook of Economic Growth. Amsterdam, The Netherlands: Elsevier, pp. 555–677.

    Google Scholar 

  • Evenson, R.E. and Gollin, D. (eds.) (2003) Crop Variety Improvement and Its Effect on Productivity: The Impact of International Agricultural Research. Oxon, UK: Cabi Publishing.

    Book  Google Scholar 

  • Fan, S., Mogues, T. and Benin, S. (2009) Setting Priorities for Public Spending for Agricultural and Rural Development in Africa. Washington DC: International Food Policy Research Institute. IFPRI Policy Brief 12.

  • Fatás, A. and Mihov, I. (2006) Fiscal Discipline, Volatility and Growth. Paris, France; London: Institut européen d’administration des affaires and Centre for Economic Policy Research.

    Google Scholar 

  • Fielding, D. and Mavrotas, G. (2008) Aid volatility and donor-recipient characteristics in difficult partnership countries. Economica 75 (299): 481–494.

    Article  Google Scholar 

  • Guellec, D. and Ioannidis, E. (1997) Causes of Fluctuations in R&D Expenditures: A Quantitative Analysis. Paris, France: Organisation for Economic Co-operation and Development. OECD Economics Studies No. 29, 1997/II.

  • Hnatkovska, V. and Loayza, N. (2004) Volatility and Growth. Washington DC: World Bank. Policy Research Working Paper 3184.

  • IAASTD (International Assessment of Agricultural Knowledge, Science and Technology for Development) (2008) Synthesis Report. Washington DC: Island Press.

  • Johnson, D.K.N. and Evenson, R.E. (2000) How Far Away is Africa? Technological Spillovers to Agriculture and Productivity. Wellesley, MA: Wellesley College. Working Paper 2000–01.

  • Johnstone, N., Haščič, I. and Kalamova, M. (2011) Environmental policy design characteristics and innovation. In: OECD Studies on Environmental Innovation: Invention and Transfer of Environmental Technologies. Paris, France: Organisation for Economic Cooperation and Development, pp. 19–46.

    Chapter  Google Scholar 

  • Kharas, H. (2008) Measuring the Cost of Aid Volatility. Washington DC: Brookings Institution. Wolfensohn Center for Development Working Paper 3.

  • Krebs, T., Krishna, P. and Maloney, W. (2005) Income Risk and Human Capital in LDCs. Unpublished paper. Washington DC: World Bank.

  • NEPAD (New Partnership for Africa’s Development, Office of Science and Technology) (2006) Africa’s Science and Technology Consolidated Plan of Action. Pretoria, South Africa.

  • Perry, G. (2009) Beyond Lending: How Multilateral Banks Can Help Developing Countries Manage Volatility. Washington DC: Center for Global Development.

    Google Scholar 

  • Servén, L. (1997) Uncertainty, Instability, and Irreversible Investment: Theory, Evidence, and Lessons for Africa. Washington DC: World Bank. Policy Research Working Paper 1722.

  • Stads, G.J. (2011) Africa’s Agricultural R&D Funding Rollercoaster: An Analysis of the Elements of Funding Volatility. Washington DC and Accra, Ghana: International Food Policy Research Institute and Forum for Agricultural Research in Africa. ASTI/IFPRI-FARA Conference Working Paper 2.

  • Stads, G.J., Issoufou, M. and Massou, A.M. (2010) Niger: Recent Developments in Agricultural Research. Washington DC; Niamey, Niger: International Food Policy Research Institute and Niger National Institute of Agricultural Research. ASTI Country Note.

  • Swift, T.J. (2008) Creative destruction in R&D: On the relationship between R&D expenditure volatility and firm performance. Doctoral Dissertation, Temple University, Philadelphia, PA.

  • UNSDN (United Nations Sustainable Development Network) (2013) Solutions for Sustainable Agriculture and Food Systems. New York. Technical Report for the Post-2015 Development Agenda.

  • Wälde, K. and Woitek, U. (2004) R&D expenditure in G7 countries and the implications for endogenous fluctuations and growth. Economics Letters 82 (1): 91–97.

    Article  Google Scholar 

  • World Bank (2007) World Development Report 2008: Agriculture for Development. Washington DC: World Bank.

  • World Bank (2013) World development indicators, http://databank.worldbank.org/data/views/variableSelection/selectvariables.aspx?source=world-development-indicators, accessed 19 September 2013.

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Stads, GJ., Beintema, N. Agricultural R&D Expenditure in Africa: An Analysis of Growth and Volatility. Eur J Dev Res 27, 391–406 (2015). https://doi.org/10.1057/ejdr.2015.25

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