Africa’s Agricultural R&D  Funding RollercoasterAn Analysis of the Elements of Funding Volatility                   Gert-J...
Background: Trends in Agricultural R&D       Investment in Sub-Saharan AfricaSource: Beintema and Stads 2011 Investments ...
Investment challenge: Underinvestment Source: Beintema and Stads 2011 NEPAD target: Allocation of at least 1 % of GDP to ...
Trends in Agricultural R&D spending                            in the “Big Eight” since 2008                       30Chang...
Investment challenge: Volatility FASTEN YOUR SEAT       BELTKeep arms and legs inside vehicle at            all times
Severe fluctuations in annual agricultural   R&D investment levels, 1981–2008                                             ...
Economic Theory on Volatility Increased macroeconomic volatility has a negative impact oneconomic growth, or is at least ...
Why is Stable Agricultural             R&D Funding Important? Agricultural R&D investment is positively associated with h...
Volatility coefficient of                   agricultural R&D spendingGrowth in agricultural R&D spending (gs) was expresse...
Volatility in African           agricultural RD spending                          0.12                          (Asia–Paci...
Volatility coefficient                                                            0.0                                     ...
Volatility and Country Groupings   Agricultural RD spending in low-income countries    (0.23) is on average more volatile...
Volatility of agricultural RD           spending across cost categories           Salaries   Operating costsCapital invest...
Funding sources for agricultural RD National government funding: either through direct allocationsor competitive funding ...
Benin (INRAB)                  Botswana (DAR)Burkina Faso (INERA, IRSAT, CNSF)                                    Governme...
Drivers of Funding Volatility                in African Agricultural RD                  Government     Sale of goods and ...
Donor dependency and funding volatility                                         Average and spreadShare of funding as a % ...
Funding sources and cost categories for DRD(Tanzania) and INERA (Burkina Faso), 2001–08                            40     ...
Concluding Remarks:                Putting a Halt to Volatility Agricultural RD spending in SSA has been far from stable ...
Thank you    Will Africa’s bumpyrollercoaster ride end here?           2013           2012         2011
Africa’s Agricultural R&D Funding Rollercoaster: An Analysis of the Elements of Funding Volatility
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Africa’s Agricultural R&D Funding Rollercoaster: An Analysis of the Elements of Funding Volatility

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By Gert-Jan Stads. Presented at the ASTI-FARA conference Agricultural R&D: Investing in Africa's Future: Analyzing Trends, Challenges, and Opportunities - Accra, Ghana on December 5-7, 2011. http://www.asti.cgiar.org/2011conf

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  • Besides severe underinvestment, African AgR&D is also characterized by severe fluctuations in annual AgR&D investments. Before we start analyzing the elements that cause volatility in year-to-year AgR&D spending in Africa, I wanted to show you the following short clip first. This clip is representative of what many African agricultural R&D have gone through over the past 20 years. So, are you ready? Here we go….
  • Although this clip may look like an exaggeration, it is actually not so far off the truth when it comes to long-term AgR&D trends in Africa. Many African countries have had extremely volatile agricultural R&D funding levels over the past decades as these figures show. If Africa were a theme park full of country rollercoasters, true thrill seekers would ride the Burkina Faso or Gabon rollercoasters; the South African roller coaster would be for small children or less adventurous people, and the Niger rollercoaster would really be for the die-hards. All jokes aside, what these figures reveal is a very worrisome trend. Many African countries are characterized by extreme fluctuations in their agricultural R&D spending levels from one year to the next.
  • A wide body of literature exists on the impact of macroeconomic volatility on economic growth and performance in developing countries. This literature has focused primarily on volatility across countries, thereby setting the issue within an international context. (bullet point 1)This is unsurprising given the broad consensus that high macroeconomic volatility likely slows down investment (because investment flows depend on expected rewards and risks), as well as biasing investments toward short-term returns. High macroeconomic volatility has also been associated with lower investment in human capital, for similar reasons.In addition, a vast amount of literature has focused on the volatility of aid flows to developing countries. (bullet point 2)The findings on macroeconomic volatility and aid volatility suggest that extreme volatility in agricultural R&D funding is similarly harmful to the institutional stability and long-term outputs of agricultural R&D. This is supported by substantial anecdotal evidence. Numerous examples across Africa indicate that, upon the completion of multimillion dollar projects, agricultural R&D agencies have been plunged into financial hardship and an uncertain future, forcing them to cut research programs and lay off staff. Large fluctuations in yearly investment levels are therefore thought to have a detrimental impact on the release of new varieties and technologies in the long run, which in turn can have a negative impact on agricultural productivity growth and poverty reduction.
  • In order to measure the degree of volatility in yearly agricultural R&D spending levels across SSA countries, a commonly used method of calculating price volatility in finance and output volatility in macroeconomics was applied to ASTI’s agricultural R&D spending data. The so-called volatility coefficient quantifies volatility in agricultural R&D spending by applying the standard deviation formula to average one-year logarithmic growth of agricultural R&D spending over a certain period
  • In order to analyze the main causes of volatility in yearly agricultural R&D investment levels, it is important to gain insight into how agricultural R&D is funded across SSA
  • In order to reduce future volatility, it is important to identify the main drivers of funding volatility in agricultural R&D across countries over the past decade. The volatility coefficient, introduced earlier, is a useful tool for comparing the relative stability of different funding sources over time and across countries. It is important to note, however, that not all volatility is bad per se. A sudden injection of government or donor funding to rehabilitate R&D infrastructure after a civil war, for example, is of course a positive thing. Based on sample of 49 large government agencies from 22 countriesThe fact that donor and development bank funding for agricultural R&D shows a much higher degree of volatility than other funding sources is worrying, given that many national agricultural R&D institutes in SSA, particularly those in low-income countries, derive a significant share of their total funding from donors, development banks, and SROs. In many countries, the bulk of government appropriations is spent on salaries, which leaves the costs of operating research programs and investing in necessary infrastructure largely dependent on volatile funding from donors, competitive grants, or the private sector. Although competitive salaries are crucial to maintaining a critical mass of qualified researchers, it is equally important to provide these scientists with well-funded research programs and well-equipped research laboratories, which requires long-term, sustainable investment in nonsalary expenditures.
  • The dots in this figure indicate the average share of donor funding in total agricultural R&D funding for the main agencies in each country during 2001–08. The lines intersecting the dots range from the highest share of donor funding in total agricultural R&D funding during 2001–08 to the lowest share. The shorter the line, the lower the spread in the share of donor funding over time.AgR&D in middle-income countries is much less dependent on donor funding and has shown a considerably lower degree of volatility
  • Africa’s Agricultural R&D Funding Rollercoaster: An Analysis of the Elements of Funding Volatility

    1. 1. Africa’s Agricultural R&D Funding RollercoasterAn Analysis of the Elements of Funding Volatility Gert-Jan Stads 5–7 December 2011, Accra, Ghana
    2. 2. Background: Trends in Agricultural R&D Investment in Sub-Saharan AfricaSource: Beintema and Stads 2011 Investments (and human capacity) in agricultural R&D increased bymore than 20% during 2000–08. Most of this growth was driven by just a handful of countries (mainlyfollowing boosts in salaries and rehabilitation of infrastructure). In many other countries (particularly in francophone West Africa),investments have declined since 2000.
    3. 3. Investment challenge: Underinvestment Source: Beintema and Stads 2011 NEPAD target: Allocation of at least 1 % of GDP to R&D In 2008, Africa spent $0.61 for every $100 of AgGDP on agricultural R&D. Despite an overall increase in recent years, Africa is widely underinvestingin agricultural R&D.
    4. 4. Trends in Agricultural R&D spending in the “Big Eight” since 2008 30Change 2008-2010 (%) 20 10 0 -10 -20 -30
    5. 5. Investment challenge: Volatility FASTEN YOUR SEAT BELTKeep arms and legs inside vehicle at all times
    6. 6. Severe fluctuations in annual agricultural R&D investment levels, 1981–2008 Burkina Faso Niger 8 40 8 35Billion 2005 CFA francs Billion 2005 CFA francs Million 2005 PPP dollars Million 2005 PPP dollars 6 30 6 26 4 20 4 18 2 10 2 9 0 0 0 0 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 1.5 South Africa 415 1.0 Gabon 3.9 Billion 2005 CFA francs Million 2005 PPP dollars Million 2005 PPP dollarsBillion 2005 rand 1.2 332 0.8 3.1 0.9 249 0.6 2.3 0.6 166 0.4 1.5 0.3 83 0.2 0.8 0.0 0 0.0 0.0 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 1991 1993 1995 1997 1999 2001 2003 2005 2007
    7. 7. Economic Theory on Volatility Increased macroeconomic volatility has a negative impact oneconomic growth, or is at least closely associated with slowergrowth (Aghion et al. 2005; Fatás and Mihov 2006; Hnatkovskaand Loayza 2004; Perry 2009). Aid flows in developing countries are more volatile thangovernment revenues, household consumption, or gross domesticproduct (GDP), and aid volatility tends to reinforcemacroeconomic instability and slow down economic growth (Bulířand Hamann 2003; Desai and Kharas 2010; Fielding and Mavrotas2008). No literature was found on R&D funding volatility in developingcountries.
    8. 8. Why is Stable Agricultural R&D Funding Important? Agricultural R&D investment is positively associated with highreturns, but these returns take time—commonly decades—todevelop. Consequently, the inherent lag from the inception of research tothe adoption of a new technology or the introduction of a newvariety calls for sustained and stable R&D funding. Severe fluctuations in annual agricultural R&D fundingexacerbate uncertainty at the institute level and renders long-term R&D budget, staffing, and planning decisions more difficult. Therefore, the continuity of research programs is imperiled inthe short run, as is the release of new varieties and technologiesin the long run.
    9. 9. Volatility coefficient of agricultural R&D spendingGrowth in agricultural R&D spending (gs) was expressed as follows: = ln −1 s=1,…, N,where s is agricultural RD spending (in constant prices), and t represents the year.A country’s volatility coefficient (V) of agricultural RD expenditureswas calculated by taking the standard deviation of growth in annualagricultural RD spending: 1 2, 1 V= =1 − where = =1 .
    10. 10. Volatility in African agricultural RD spending 0.12 (Asia–Pacific 1992–2002)0.21 (SSA 2001–2008) 0.14 (Latin America 2004–2006) 0.09 (SSA agricultural output, 2001–2008)
    11. 11. Volatility coefficient 0.0 0.1 0.2 0.3 0.4 0.5 Mauritania Gabon Tanzania Burkina Faso very high Ethiopia Namibia Gambia, The Mali Côte dIvoire highCalculated from Beintema and Stads (2011) Sierra Leone Eritrea Guinea Sudan Togo Nigeria Burundi Botswana Benin Senegal Zambia Uganda moderate Kenya Cross-Country Variation Ghana Niger Volatility Coefficients 2001–08 Mauritius Madagascar South Africa Malawi low Congo, Rep.
    12. 12. Volatility and Country Groupings Agricultural RD spending in low-income countries (0.23) is on average more volatile than spending in middle-income countries (0.16) Average volatility was higher in West (0.23) and East (0.22) Africa than in Southern Africa (0.14) Spending at NARS with less than 100 FTEs (0.24) is on average more volatile than spending at NARS with more than 100 FTEs (0.19) AgRD expenditures in countries spending less than 0.5% of AgGDP on AgRD (0.23) are on average more volatile than those in countries spending more than 1.0% of AgGDP on AgRD (0.16)
    13. 13. Volatility of agricultural RD spending across cost categories Salaries Operating costsCapital investments 0.0 0.2 0.4 0.6 0.8 1.0 1.2 Volatility coefficient
    14. 14. Funding sources for agricultural RD National government funding: either through direct allocationsor competitive funding schemes Donors and development banks: high donor dependency inlow-income countries worldwide Production or export levies (mostly on export crops):e.g. cocoa in Ghana; tea in Tanzania and Kenya; sugarcane in Mauritius, etc. Sale of goods and services: e.g. on-demand research for privatecompanies
    15. 15. Benin (INRAB) Botswana (DAR)Burkina Faso (INERA, IRSAT, CNSF) Government Burundi (ISABU) Donors Côte dIvoire (CNRA) Producer organizations Eritrea (NARI) Own income Gambia, The (NARI) Guinea (IRAG) Other Kenya (see footnote) Madagascar (FOFIFA) Source: Beintema and Stads (2011) Mali (IER) Mauritania (CNERV, CNRADA) Mauritius (FARC, MSIRI) Mozambique (IIAM, IIP) Namibia (DRT) Niger (INRAN) Rwanda (ISAR) Senegal (ISRA, ITA) Sierra Leone (SLARI) South Africa (ARC) Sudan (ARC) Tanzania (DRD) Togo (ITRA) Uganda (NARO) Zambia (ZARI) 0 20 40 60 80 100 Share of total funding (%)
    16. 16. Drivers of Funding Volatility in African Agricultural RD Government Sale of goods and servicesDonors and development banks TotalIndicates that in manycases shocks in one 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9funding source are to Volatility coefficientsome extent absorbedby reverse shocks inother funding sources
    17. 17. Donor dependency and funding volatility Average and spreadShare of funding as a % of of donor Volatility 100 total agriculturaldonorfunding, 2001–08 RD funding coefficient 10% 0.19 80 10% 0.28 40% 0.31Share of donor funding intotal annual funding (%) 60 40 20 0
    18. 18. Funding sources and cost categories for DRD(Tanzania) and INERA (Burkina Faso), 2001–08 40 40 DRD – cost categories DRD – funding sources Million 2005 PPP dollars Million 2005 PPP dollars 30 30 20 20 10 10 0 0 2001 2002 2003 2004 2005 2006 2007 2008 2001 2002 2003 2004 2005 2006 2007 2008 Salaries Operational Capital Government Donors, development banks, SROs Producer organizations Sales of goods and services 30 30 INERA – cost categories INERA – funding sources Million 2005 PPP dollarsMillion 2005 PPP dollars 20 20 10 10 0 0 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Salaries Operational Capital Government Donors, development banks, SROs Sales of goods and services
    19. 19. Concluding Remarks: Putting a Halt to Volatility Agricultural RD spending in SSA has been far from stable in recent years. Problem is more pronounced in donor-dependent low-income countries. Halting excessive volatility in yearly agricultural RD investment levelsrequires a long-term commitment from national governments, donors anddevelopment banks, as well as the private sector. Stable and sustainable levels of government funding are key, not just tosecure salaries (which are fundamentally important), but also to enablenecessary nonsalary expenditures. Donor and development bank funding needs to be better aligned withnational priorities, and consistency and complementarities among donorprograms need to be assured. Mitigating the effects of any single donor’s abrupt change in aiddisbursement is crucial. Need for greater funding diversification (e.g. throughthe sale of goods and services or private sector funding).
    20. 20. Thank you Will Africa’s bumpyrollercoaster ride end here? 2013 2012 2011

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