A conference paper presentation in IPAR's Annual research conference 201

Bizoza, Alfred R.

English

IDS OpenDocs

Role of Agricultural Research and 
Development in the MDGs – Post 2015 in 
Sub-Saharan Africa
Alfred R. Bizoza (PhD)
Director of Research, IPAR-Rwanda
1
4th Annual Research Conference
Outline of the presentation
1. Introduction
2. Research Methods and Materials 
3. Public Spending in Agricultural R&D in SSA 
4. Economic and Poverty Impacts of Agricultural R&D in SSA
5. Some Challenges of Ag R&D in SSA 
6. Some Concluding remarks 
2
1. Introduction  
Two major question in our literature review :
• The extent to which the Millennium Development Goals (MDGs) have
been achieved and avenues for future orientation to achieve
Sustainable Development Goals ( SDGs)
• Another question is what is the expected role of Research and
Development in reducing extreme poverty – one of both MDGs and
SDGs targets.
3
2. Introduction  
o The aim of this article is to call upon more reflection on
the questions raised above as we try to understand
further what would be the role of research and
Development (R&D) in post 2015 –MDGs in Sub Saharan
Africa.
o The focus in this paper is on Agricultural Research and
Development (Ag R&D) to assess the economic and
poverty impacts of Ag R&D in the Sub Saharan African
Countries.
4
3. Research Methods and Materials
• Data used for this paper were obtained from secondary
sources. These includes: ASTI led by IFPRI, CGIAR
research program on policies, institutions, and markets;
the FAOSTAT, others.
• Data collected is mostly regarding public spending in Ag
R&D, Agricultural GDP, Total GDP for SSA countries.
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3. Research Methods and Materials
• The analysis used both descriptive and inferential
procedures.
• A recursive simultaneous equations system was
estimated to test the expected relationships.
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Recursive relationship between Ag. R&D, Ag.GDP, and Total GDP
Ag. GDP
Ag. R&D Total GDP
Recursive 
Relationship 
7ii uDAgRxAgGdP 1211
' &  
ii uAgGDPxGDP 2112
,
2  
itti uGDPAgGDPxDAgR 31123
,
3&   
(1)
(2) 
(3)
Where Ag. GDP , GDP, and Ag. GDP: endogenous variables (parameters to
be estimated);
: vector of conditioning variables for the ith individual SSA country
: captures all unobservable factors that affect the dependent variables
ix
iu
3. Research Methods and Materials
4. Public Spending in Agricultural R&D in SSA 
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• AgR&D can be measured by:
– The weight given to Ag. R&D in the budgeting process
– The total agriculture spending on R&D as % of Agricultural Gross
Domestic Product
• There is a guidance from NEPAD that SSA countries low and middle-
income countries need to increase their spending on Ag. R&D by 5%
per year and allocate at least 1% of their GDP for the public Ag. R&D
during 2015-2025.
4. Public Spending in Agricultural R&D in SSA 
o Estimates from IFPRI (2014) show that overall investment levels in 
most countries are still well below the levels required to sustain 
agricultural R&D needs.
o For instance, in 2011, SSA as whole invested 0.51percentage of Ag.GDP 
on average. 
o Only 10 countries met the investment target of 1% of the total Ag.GDP 
set by NEPAD. These include:  Mauritius, Namibia, Botswana, South 
Africa, Swaziland, Uganda, Kenya, Cape Verbe, Malawi, and Gambia.  
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4.Public Spending in Agricultural R&D in SSA 
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SUB-SAHARAN AFRICA
Agriculture Defense
Mining Trans_Com
Education Health
Soc_Protection Other
Agriculture Spending in Developed Countries and SSA
4.Public Spending in Agricultural R&D in SSA 
Economic and poverty impacts of Agricultural 
R&D in SSA
• Ending extreme poverty remains one of the 2015 
development agenda for all regions. 
• Since 1990, the number of extreme poor has fallen in all 
regions expect Sub-Saharan Africa, where population 
growth exceeded the rate of poverty reduction , increasing 
the number of extremely poor people from 287 million in 
1990 to 415 million in 2011 (GMR, 2015).
12
13
5. Economic and poverty impacts of Agricultural R&D 
in SSA 
Regional poverty rates, Source (GMR, 2015).
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5. Economic and poverty impacts of Agricultural 
R&D in SSA 
MDGs Progress status (GMR,2013)
5. Economic and poverty impacts of 
Agricultural R&D in SSA 
o A lot of empirical research has documented the effects of Ag. 
R&D  on productivity growth and poverty reduction in 
developing countries including SSA (e.g. Alene et al. 2009, 
Thritle et al., 2003).  
o In SSA, despite low levels of investments, Ag. R&D reduces 
poverty by an annual rate of 0.8% (Alene and Coulibaly, 
2009).   
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5. Economic and poverty impacts of 
Agricultural R&D in SSA
During the discussion  of the post 2015 sustainable 
development agenda, the  academics and scientists 
recommended:
o the adoption of a science –based and action –
oriented  agenda, 
o integrating four interdependent dimensions of 
sustainable development (economic, social, 
environmental and governance)
16
Economic and poverty impacts of Agricultural 
R&D in SSA
• The Ag. R&D can reduce poverty in a number of different 
ways as already indicated such as:
– A direct raise of income or home consumption, 
– The effects of agricultural technology adoption, 
– Lowering food prices,
– Increased employment and wage effects in agriculture and other 
sectors of economic activity through production, consumption, and 
savings
17
18
5. Economic and poverty impacts of Agricultural 
R&D in SSA (Cont’d)
Region % in $1
Poverty
Number in $1
poverty, Millions
Reduction in $1
per day poverty,
millions
Cost per person
($)
East Asia 15.32 278.32 1.34 179
South Asia 39.99 522.00 2.51 179
Sub-Saharan Africa 46.30 290.87 2.09 144
Middle East and North
Africa
7.32 20.85 0.12 NA
Latin America 15.57 78.16 0.08 11.397
East Europe and Central
Asia
5.14 23.98 0.12 NA
Total 24.27 1244.18 6.24 NA
Source: Thirtle et al. 2003
For SSA, a 1% increase in yield is likely to reduce the number of people
living in under $1 per day by about 2.1 millions. The increase of crop yield
is also a result of the uptake of improved technologies by farmers- effect of
R&D
Economic and poverty impacts of Agricultural 
R&D in SSA (Cont’d)
• Preliminary results 
19
                                                                                 
          _cons    -1.594281   .8144183    -1.96   0.059    -3.249378    .0608164
expensesinagrrd     .4521961   .0660128     6.85   0.000      .318042    .5863503
                                                                                 
          aggdp        Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
                                Robust
                                                                                 
                                                       Root MSE      =  5.6417
                                                       R-squared     =  0.8695
                                                       Prob > F      =  0.0000
                                                       F(  1,    34) =   46.92
Linear regression                                      Number of obs =      36
. regress aggdp expensesinagrrd,robust
Economic and poverty impacts of Agricultural 
R&D in SSA (Cont’d)
20
                                                                              
       _cons     9.292868   6.886196     1.35   0.184    -4.576642    23.16238
       aggdp     4.594432   .3042762    15.10   0.000     3.981588    5.207275
                                                                              
gdpbillion~d        Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
                             Robust
                                                                              
                                                       Root MSE      =  54.272
                                                       R-squared     =  0.5752
                                                       Prob > F      =  0.0000
                                                       F(  1,    45) =  228.00
Linear regression                                      Number of obs =      47
. regress gdpbillionusd aggdp,robust
Economic and poverty impacts of Agricultural 
R&D in SSA (Cont’d)
21
                                                                              
       _cons     .5985654   3.191145     0.19   0.852    -5.886621    7.083752
      aggdp1     4.390102   .7376921     5.95   0.000     2.890931    5.889272
                                                                              
gdpbillion~d        Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
                             Robust
                                                                              
                                                       Root MSE      =  25.644
                                                       R-squared     =  0.8614
                                                       Prob > F      =  0.0000
                                                       F(  1,    34) =   35.42
Linear regression                                      Number of obs =      36
. regress gdpbillionusd aggdp1,robust
(11 missing values generated)
(option xb assumed; fitted values)
. predict aggdp1
Economic and poverty impacts of Agricultural 
R&D in SSA (Cont’d)
22
                                                                              
Exogenous variables:   lagagdp laggdp 
Endogenous variables:  aggdp gdpbillionusd expensesinagrrd 
                                                                                 
          _cons     4.938342   2.010062     2.46   0.014     .9986928    8.877991
         laggdp     .2576729   .0211208    12.20   0.000      .216277    .2990688
        lagagdp      .947445   .0857141    11.05   0.000     .7794484    1.115442
expensesinagrrd  
                                                                                 
          _cons     .7050135   1.688578     0.42   0.676    -2.604539    4.014566
          aggdp     4.370183   .1049866    41.63   0.000     4.164413    4.575953
gdpbillionusd    
                                                                                 
          _cons    -2.638547   1.104853    -2.39   0.017     -4.80402   -.4730751
expensesinagrrd     .5202536   .0335277    15.52   0.000     .4545405    .5859667
aggdp            
                                                                                 
                       Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
                                                                                 
                                                                      
expensesin~d       36      2    11.36293    0.8682     238.85   0.0000
gdpbillion~d       36      1     9.55588    0.9796    1732.73   0.0000
aggdp              36      1    5.881988    0.8498     240.78   0.0000
                                                                      
Equation          Obs  Parms        RMSE    "R-sq"       chi2        P
                                                                      
Three-stage least-squares regression
. reg3 (aggdp = expensesinagrrd) (gdpbillionusd = aggdp) (expensesinagrrd = lagagdp laggdp)
Some Challenges of Ag R&D in SSA
1. Limited funding and investment: Research agendas
with high donor funding help to achieve short term
research targets that are not necessarily customized to
national or regional research and development priorities.
2. Lack of coordinated research priority setting: no
adequate mechanisms from which both policy makers and
researchers identify R&D priorities.
3. Lack of sufficient research capacities: in terms of
qualified researchers, required research facilities,
opportunistic research, high turnover of researchers due
to unattractive remuneration package and benefits,
23
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Some Challenges of Ag R&D in SSA (Cont’d)
Category /Country Government Higher education Non-profit Total
Small NARSs
Guinea-Bissau 1 - - 1
Liberia 1 2 1 4
Mauritania 4 3 1 8
Swaziland 1 1 - 2
Medium Sized NARSs
Congo, Republic 12 2 2 16
Mali 2 2 - 4
Mauritius 10 2 1 13
Rwanda 1 6 - 7
Large NARSs
Ethiopia 8 8 - 18
Kenya 6 29 2 37
Sudan 4 28 - 32
Tanzania 6 5 3 14
Table : National Agricultural Research Institutes 
Source : IFPRI (2014). 
Concluding remarks 
o The paper adds a vote to the role of R&D in
reducing poverty and support the SDGs.
o The importance given to R&D will translate into
economic impacts and reduce poverty.
o If Sustainable Development Goals are to be
achieved post 2015- R&D needs the right place in
public and private investments in the SSA.
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Role of agricultural research and development in the MDGs – post 2015 in Sub-Saharan Africa

https://opendocs.ids.ac.uk/opendocs/bitstream/20.500.12413/10121/1/Role%20of%20Agricultural%20Research%20and%20Development%20in%20the%20MDGs.pdf

Role of agricultural research and development in the MDGs – post 2015 in Sub-Saharan Africa

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