Impact of cowpea breeding and storage research in Cameroon - IITA
Impact of cowpea breeding and storage research in Cameroon - IITA
Impact of cowpea breeding and storage research in Cameroon - IITA
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<strong>Impact</strong> <strong>of</strong> <strong>cowpea</strong> <strong>breed<strong>in</strong>g</strong> <strong>and</strong> <strong>storage</strong> <strong>research</strong> <strong>in</strong> <strong>Cameroon</strong><br />
5.5<br />
<strong>Impact</strong> <strong>of</strong> <strong>cowpea</strong> <strong>breed<strong>in</strong>g</strong> <strong>and</strong> <strong>storage</strong><br />
<strong>research</strong> <strong>in</strong> <strong>Cameroon</strong><br />
F. Diaz-Hermelo, A. Langy<strong>in</strong>tuo, <strong>and</strong> J. Lowenberg-DeBoer 1<br />
Abstract<br />
The Bean–Cowpea Collaborative Research Support Program (CRSP) has <strong>research</strong><br />
programs focused on beans <strong>and</strong> <strong>cowpea</strong> that span the full range from producer to<br />
consumer. CRSP <strong>research</strong>ers work on postharvest technologies, such as improved<br />
<strong>storage</strong> <strong>and</strong> value-added process<strong>in</strong>g, as well as on genetic improvement, agronomic<br />
practices, <strong>and</strong> field <strong>in</strong>tegrated pest management. The methodologies for economic<br />
impact assessment <strong>of</strong> this <strong>research</strong> are well developed for either production-related<br />
work or postharvest technology, but a framework for an <strong>in</strong>tegrated assessment <strong>of</strong><br />
<strong>research</strong>, which <strong>in</strong>cludes both production <strong>and</strong> postharvest, is not available. The<br />
objective <strong>of</strong> this paper is to summarize the results from a theoretical model <strong>of</strong><br />
impact assessment with a comb<strong>in</strong>ed production <strong>and</strong> <strong>storage</strong> assessment <strong>and</strong> to apply<br />
that comb<strong>in</strong>ed model to an empirical example based on Bean–Cowpea CRSP<br />
<strong>breed<strong>in</strong>g</strong> <strong>and</strong> <strong>storage</strong> <strong>research</strong> on <strong>cowpea</strong> <strong>in</strong> northern <strong>Cameroon</strong>, West Africa. From<br />
a methodology perspective, this study has shown that the <strong>in</strong>teraction <strong>of</strong> production<br />
<strong>and</strong> <strong>storage</strong> technologies can have important consequences for impact assessment.<br />
Higher yields <strong>and</strong> reduced <strong>storage</strong> losses are two ways to have more usable products.<br />
The sum <strong>of</strong> their separate benefits is <strong>of</strong>ten greater than the estimate <strong>of</strong> comb<strong>in</strong>ed<br />
benefits. The bias <strong>in</strong>troduced by separate estimation is greatest when the<br />
dem<strong>and</strong> for the product <strong>in</strong> period two is elastic <strong>and</strong> when the <strong>storage</strong> loss reduction<br />
is large. Comb<strong>in</strong>ed estimation should be used when the bias is likely to be large,<br />
but simpler, separate estimates are still useful for other situations. For the <strong>Cameroon</strong><br />
<strong>cowpea</strong> example, separate estimation has little effect on impact estimates. With<br />
conservative estimates <strong>of</strong> <strong>cowpea</strong> area <strong>and</strong> new technology adoption, both comb<strong>in</strong>ed<br />
<strong>and</strong> separate estimates, the basel<strong>in</strong>e IRR is about 5% <strong>and</strong> the net present value<br />
(NPV) about US$200 000. With a real opportunity cost <strong>of</strong> capital <strong>of</strong> about 4%, the<br />
<strong>Cameroon</strong> project is about breakeven from just the adoption <strong>in</strong> <strong>Cameroon</strong> alone.<br />
The real ga<strong>in</strong>s from the <strong>research</strong> are com<strong>in</strong>g from extension <strong>of</strong> the <strong>cowpea</strong> <strong>storage</strong><br />
technologies <strong>in</strong>to other areas <strong>of</strong> West <strong>and</strong> Southern Africa.<br />
Introduction<br />
The Bean–Cowpea Collaborative Research Support Program (CRSP) has <strong>research</strong> programs<br />
focused on beans <strong>and</strong> <strong>cowpea</strong> that span the full range from producer to consumer.<br />
CRSP <strong>research</strong>ers work on postharvest technologies, such as improved <strong>storage</strong> <strong>and</strong> valueadded<br />
process<strong>in</strong>g, as well as on genetic improvement, agronomic practices, <strong>and</strong> field<br />
<strong>in</strong>tegrated pest management. The methodologies for economic impact assessment <strong>of</strong> this<br />
<strong>research</strong> are well developed for either production related work (Alston et al. 1995; Masters<br />
et al. 1996) or postharvest technology (Fuglie 1995), but a framework for an <strong>in</strong>tegrated<br />
assessment <strong>of</strong> <strong>research</strong> which <strong>in</strong>cludes both production <strong>and</strong> postharvest is not available.<br />
1. All authors are at Purdue University, West Lafayette, Indiana, USA.<br />
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Cowpea postharvest <strong>and</strong> socioeconomic studies<br />
One alternative would be to apply the production <strong>and</strong> postharvest impact assessment<br />
methods separately <strong>and</strong> sum the benefits. Unfortunately, this simple approach may lead<br />
to over- or underestimat<strong>in</strong>g benefits because production <strong>and</strong> postharvest technology may<br />
have complementary or <strong>of</strong>fsett<strong>in</strong>g effects. The objectives <strong>of</strong> this paper are to summarize<br />
the results <strong>of</strong> an <strong>in</strong>tegrated production <strong>and</strong> <strong>storage</strong> theoretical model <strong>and</strong> to apply that<br />
<strong>in</strong>tegrated model to Bean–Cowpea CRSP <strong>breed<strong>in</strong>g</strong> <strong>and</strong> <strong>storage</strong> <strong>research</strong> on <strong>cowpea</strong> <strong>in</strong><br />
northern <strong>Cameroon</strong>, West Africa.<br />
An example <strong>of</strong> the potential problem with separate impact assessments <strong>of</strong> production<br />
<strong>and</strong> postharvest <strong>research</strong> is provided by the CRSP work <strong>in</strong> <strong>Cameroon</strong> that focused<br />
on <strong>breed<strong>in</strong>g</strong> for higher yields <strong>and</strong> resistance to postharvest pests (Murdock et al. 1997).<br />
Both the higher yields <strong>and</strong> reduced <strong>storage</strong> losses could lead to <strong>in</strong>creases <strong>in</strong> the effective<br />
supply <strong>and</strong>, depend<strong>in</strong>g on elasticities, to lower producer <strong>and</strong> consumer prices. Separate<br />
assessment <strong>of</strong> impact for production <strong>and</strong> postharvest may tend to overestimate benefits,<br />
especially for producers. Typically, higher yields result <strong>in</strong> consumer ga<strong>in</strong>s through lower<br />
prices <strong>and</strong> producer ga<strong>in</strong>s from greater productivity, <strong>in</strong> spite <strong>of</strong> the lower prices. Reduction<br />
<strong>in</strong> <strong>storage</strong> losses ma<strong>in</strong>ly benefits consumers <strong>and</strong> may have negative results on producers<br />
because less needs to be produced to satisfy consumer dem<strong>and</strong> <strong>in</strong> subsequent periods.<br />
With comb<strong>in</strong>ed yield <strong>in</strong>creases <strong>and</strong> reduction <strong>in</strong> <strong>storage</strong> losses, the price effects are greater<br />
than with either effect alone. With reduced <strong>storage</strong> losses, the value <strong>of</strong> the extra gra<strong>in</strong><br />
produced through genetic improvement may be less than it would have been without the<br />
<strong>storage</strong> <strong>research</strong>.<br />
CRSPs are programs funded by the US Agency for International Development (USAID)<br />
to support <strong>research</strong> <strong>and</strong> technology transfer on specific agricultural problems through<br />
collaboration between the US <strong>and</strong> develop<strong>in</strong>g country <strong>in</strong>stitutions. CRSPs are organized<br />
to focus on a specific commodity or resource management problem <strong>and</strong> are among the<br />
longest runn<strong>in</strong>g USAID programs. The Bean–Cowpea CRSP was created <strong>in</strong> 1980 to work<br />
on beans <strong>and</strong> <strong>cowpea</strong> <strong>in</strong> Africa, Lat<strong>in</strong> America, <strong>and</strong> the US. The CRSP <strong>cowpea</strong> <strong>storage</strong><br />
project <strong>in</strong> northern <strong>Cameroon</strong> started <strong>in</strong> 1987 with a partnership between Purdue University<br />
<strong>and</strong> the Institute for Agricultural Research for Development (IRAD) <strong>of</strong> <strong>Cameroon</strong>.<br />
The <strong>Cameroon</strong> project <strong>in</strong>cludes both nonchemical <strong>storage</strong> technologies <strong>and</strong> <strong>breed<strong>in</strong>g</strong> for<br />
<strong>storage</strong> pest resistance.<br />
<strong>Impact</strong> assessment overview<br />
As <strong>research</strong> budgets shr<strong>in</strong>k, impact assessment has become more important for donors <strong>and</strong><br />
adm<strong>in</strong>istrators. Donors want to know if their resources are used effectively <strong>and</strong> adm<strong>in</strong>istrators<br />
want <strong>in</strong>formation that will help them guide allocation <strong>of</strong> <strong>research</strong> resources <strong>in</strong>to<br />
productive areas. Several methods have been used to assess the economic impact <strong>of</strong><br />
<strong>research</strong>, <strong>in</strong>clud<strong>in</strong>g economic surplus, econometric methods, <strong>and</strong> mathematical programm<strong>in</strong>g<br />
models (Alston et al. 1995). The economic surplus approach is most widely used<br />
because it is relatively simple to implement <strong>in</strong> spreadsheets <strong>and</strong> flexible <strong>in</strong> terms <strong>of</strong> data<br />
requirements. It is almost the only method used for assessment <strong>of</strong> the economic impact<br />
<strong>of</strong> agricultural <strong>research</strong> <strong>in</strong> develop<strong>in</strong>g countries where data are <strong>of</strong>ten <strong>in</strong>adequate for other<br />
approaches.<br />
Typically, f<strong>in</strong>ancial tools are borrowed to summarize net benefits over time. A time<br />
series <strong>of</strong> net benefits is created by subtract<strong>in</strong>g <strong>research</strong> <strong>and</strong> transfer costs from the benefits<br />
estimated us<strong>in</strong>g economic surplus techniques. From this time series an <strong>in</strong>ternal rate <strong>of</strong><br />
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<strong>Impact</strong> <strong>of</strong> <strong>cowpea</strong> <strong>breed<strong>in</strong>g</strong> <strong>and</strong> <strong>storage</strong> <strong>research</strong> <strong>in</strong> <strong>Cameroon</strong><br />
return (IRR) or net present value (NPV) is estimated to determ<strong>in</strong>e if the <strong>research</strong> is a good<br />
<strong>in</strong>vestment. Essentially, agricultural <strong>in</strong>vestment <strong>in</strong> <strong>research</strong> is treated just as any other<br />
<strong>in</strong>vestment. A positive NPV means that the <strong>in</strong>vestment returns more than the opportunity<br />
cost <strong>of</strong> capital. The IRR can be compared with returns to other <strong>research</strong> <strong>in</strong>vestments.<br />
Economic impacts are only one <strong>of</strong> the many types <strong>of</strong> <strong>research</strong> impact that might be<br />
tracked. Others <strong>in</strong>clude environmental, health, social, <strong>and</strong> nutritional impacts. Most projects<br />
<strong>in</strong>clude economic impact assessment <strong>in</strong> their plans because:<br />
• it is less costly than other types <strong>of</strong> impact assessment<br />
• economic measures (<strong>in</strong> particular IRR) are comparable across a wide variety <strong>of</strong> projects<br />
• use <strong>of</strong> f<strong>in</strong>ancial tools allows it to deal with a series <strong>of</strong> costs <strong>and</strong> benefits over time<br />
Most economic impact assessments have focused on production <strong>research</strong> (Echeverria<br />
1990; Alston 1991). Masters et al. (1996) provide a practical guide for do<strong>in</strong>g this k<strong>in</strong>d <strong>of</strong><br />
assessment <strong>in</strong> a spreadsheet format. The functional form <strong>of</strong> supply <strong>and</strong> dem<strong>and</strong> curves, the<br />
nature <strong>of</strong> the supply shift, has been the subject <strong>of</strong> considerable debate <strong>in</strong> academic circles.<br />
Most analyses use l<strong>in</strong>ear supply <strong>and</strong> dem<strong>and</strong> with parallel shifts as the simplest alternative.<br />
Ak<strong>in</strong>o <strong>and</strong> Hayami (1975) propose constant elasticity power functions <strong>and</strong> pivotal shifts.<br />
L<strong>in</strong>dner <strong>and</strong> Jarret (1978) <strong>and</strong> Rose (1980) showed that the type <strong>of</strong> shift has important<br />
consequences for the distribution <strong>of</strong> benefits between consumers <strong>and</strong> producers.<br />
Assessment <strong>of</strong> the benefits <strong>of</strong> postharvest <strong>research</strong> is a more recent phenomena. Fuglie<br />
(1995) used a framework developed by Muth (1964) <strong>and</strong> Alston (1991) to estimate the<br />
benefits from potato <strong>storage</strong> <strong>research</strong> <strong>in</strong> Tunisia. Fuglie specified a two-period model with<br />
l<strong>in</strong>ear supply <strong>and</strong> dem<strong>and</strong>, <strong>and</strong> changes <strong>in</strong> <strong>storage</strong> costs <strong>and</strong> <strong>storage</strong> losses. Production<br />
occurs <strong>in</strong> period one; consumption occurs <strong>in</strong> both periods. The model could be easily<br />
modified to accommodate more than two periods. Process<strong>in</strong>g technology can use a similar<br />
model that is specified <strong>in</strong> terms <strong>of</strong> multiple markets. Instead <strong>of</strong> the <strong>storage</strong> costs <strong>and</strong><br />
losses, the process<strong>in</strong>g model parameters would <strong>in</strong>clude process<strong>in</strong>g cost <strong>and</strong> efficiency. The<br />
authors are not aware <strong>of</strong> any model that comb<strong>in</strong>es production <strong>and</strong> postharvest impacts <strong>of</strong><br />
<strong>research</strong> <strong>in</strong> a common framework.<br />
Integrated model<br />
In a two-period l<strong>in</strong>ear model based on the work <strong>of</strong> Fuglie (1995), Diaz-Hermelo <strong>and</strong><br />
Lowenberg-DeBoer (1999) show that the potential bias <strong>in</strong> the economic surplus estimate<br />
due to separate estimation <strong>of</strong> the impact <strong>of</strong> production <strong>and</strong> <strong>storage</strong> <strong>in</strong>novations is related<br />
to the changed weighted sum <strong>of</strong> the dem<strong>and</strong> <strong>and</strong> supply elasticities:<br />
1 –∆E/EE’ = – (E’–E)/EE’<br />
where:<br />
E = –η 1<br />
q 1<br />
– η 2<br />
q s<br />
(P 1<br />
/P 2<br />
)ρφ + ε = the weighted sum <strong>of</strong> supply <strong>and</strong> dem<strong>and</strong><br />
elasticities, E > 0<br />
E’ = –η 1<br />
q 1<br />
– η 2<br />
q 2<br />
(P 1<br />
/P 2<br />
) ρ (φ – α) 2 + ε = weighted sum <strong>of</strong> supply <strong>and</strong> dem<strong>and</strong><br />
elasticities when <strong>in</strong>novations reduce <strong>storage</strong> losses, E’ > 0<br />
P i<br />
= price <strong>of</strong> product for period i<br />
ρ = (1 + r) = opportunity cost <strong>of</strong> capital factor<br />
r = six months opportunity cost <strong>of</strong> capital, r > 0<br />
φ = 1/(1–δ) = <strong>storage</strong> loss factor<br />
409
Cowpea postharvest <strong>and</strong> socioeconomic studies<br />
δ = proportional <strong>storage</strong> losses, 0 δ 1<br />
η 1<br />
= elasticity <strong>of</strong> dem<strong>and</strong> period 1, η 1<br />
< 0<br />
η 2<br />
= elasticity <strong>of</strong> dem<strong>and</strong> period 2, η 2<br />
< 0<br />
ε = elasticity <strong>of</strong> supply, ε > 0<br />
q 1<br />
= proportion <strong>of</strong> total quantity consumed <strong>in</strong> period 1, q 1<br />
, = 0<br />
q 2<br />
= proportion <strong>of</strong> total quantity consumer <strong>in</strong> period 2, q 2<br />
, = 0<br />
q s<br />
= proportion <strong>of</strong> total quantity stored <strong>in</strong> period 1, qs = 0<br />
α = <strong>storage</strong> loss reduction with <strong>in</strong>novation, α, = 0<br />
Dias-Hermelo <strong>and</strong> Lowenberg-DeBoer call this (–∆E/EE’) the bias factor. The<br />
importance <strong>of</strong> the weighted elasticity term (E) can be better understood by not<strong>in</strong>g that<br />
it is the denom<strong>in</strong>ator <strong>of</strong> the economic surplus estimation formula. The bias factor is<br />
always non-negative <strong>and</strong> it is largest when first period elasticity <strong>of</strong> dem<strong>and</strong> <strong>and</strong> supply<br />
elasticity are small relative to the second period dem<strong>and</strong> elasticity term. When supply<br />
or first period dem<strong>and</strong> is very elastic, the bias factor dw<strong>in</strong>dles to <strong>in</strong>significance. For<br />
example, with the basel<strong>in</strong>e parameters <strong>in</strong> Table 1, if the <strong>storage</strong> loss reduction almost<br />
elim<strong>in</strong>ates <strong>storage</strong> loss, the bias factor is 6% for a second period dem<strong>and</strong> elasticity <strong>of</strong><br />
–0.8. If the consumption share <strong>of</strong> the second period is <strong>in</strong>creased to 30% without chang<strong>in</strong>g<br />
other parameters, the bias factor is 14% at the second period dem<strong>and</strong> elasticity <strong>of</strong><br />
–0.8. Table 1 values <strong>in</strong>dicate that the bias factor can be important for some plausible<br />
parameter values.<br />
Table 1. Values <strong>of</strong> the bias factor (–∆/EE’) for some representative values <strong>of</strong> other<br />
parameters.<br />
Storage loss reduction factor α<br />
3.0 0.50 0.70 1.00<br />
Basel<strong>in</strong>e<br />
η 2<br />
–0.4 0.01 0.02 0.02 0.03<br />
–0.8 0.02 0.03 0.04 0.06<br />
–1.2 0.03 0.05 0.06 0.08<br />
–1.6 0.04 0.06 0.08 0.10<br />
Higher consumption share <strong>in</strong> second period 30%<br />
η 2<br />
–0.4 0.03 0.05 0.06 0.08<br />
–0.8 0.06 0.09 0.12 0.14<br />
–1.2 0.09 0.13 0.16 0.19<br />
–1.6 0.12 0.17 0.20 0.24<br />
Elastic first period dem<strong>and</strong> η 1<br />
= –10<br />
η 2<br />
–0.4 0.01 0.02 0.02 0.03<br />
–0.8 0.02 0.03 0.05 0.06<br />
–1.2 0.03 0.04 0.07 0.09<br />
–1.6 0.04 0.07 0.09 0.12<br />
*Given the basel<strong>in</strong>e <strong>storage</strong> loss factor, φ = 2, α = 1 <strong>in</strong>dicates zero <strong>storage</strong> loss.<br />
**Basel<strong>in</strong>e parameter values are: first period dem<strong>and</strong> elasticity, η 1<br />
= –0.4; consumption share<br />
period one, q 1<br />
= 0.60; <strong>storage</strong> share = 0.40; consumption share period two, q 2<br />
= 0.20; price period<br />
1, P 1<br />
= 1; price period 2, P 2<br />
= 4.8; discount rate r = 0.2; <strong>storage</strong> loss, δ = 0.5; discount factor, ρ = 1.2;<br />
<strong>storage</strong> loss factor, φ = 2.<br />
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<strong>Impact</strong> <strong>of</strong> <strong>cowpea</strong> <strong>breed<strong>in</strong>g</strong> <strong>and</strong> <strong>storage</strong> <strong>research</strong> <strong>in</strong> <strong>Cameroon</strong><br />
The theoretical model developed by Diaz-Hermelo <strong>and</strong> Lowenberg-DeBoer (1999)<br />
shows that when production <strong>and</strong> <strong>storage</strong> <strong>in</strong>novation occur together <strong>and</strong> impact assessment<br />
is done separately, the results tend to overestimate impact if the <strong>storage</strong> <strong>in</strong>novation<br />
reduces <strong>storage</strong> losses. Numerical examples <strong>in</strong>dicate that the bias <strong>in</strong> impact assessment<br />
results can reach 20% for some plausible parameter values.<br />
<strong>Cameroon</strong> example<br />
From the beg<strong>in</strong>n<strong>in</strong>g <strong>of</strong> the Purdue/IRAD effort, <strong>storage</strong> <strong>research</strong> has <strong>in</strong>cluded both <strong>breed<strong>in</strong>g</strong><br />
for resistance to <strong>storage</strong> pests <strong>and</strong> postharvest <strong>storage</strong> technology (Purdue/IRA 1987).<br />
The concept was that postharvest technologies would be developed <strong>and</strong> extended rapidly<br />
as an <strong>in</strong>termediate term response, while longer-term genetic resistance to <strong>storage</strong> pests<br />
would be added to the portfolio <strong>of</strong> strategies.<br />
The Bean–Cowpea CRSP has been collaborat<strong>in</strong>g with IRAD s<strong>in</strong>ce 1982. Before 1998<br />
IRAD was known as the Institute for Agricultural Research (IRA). Initially, the CRSP<br />
focused on field pest management <strong>and</strong> agronomy, under the leadership (on the US side)<br />
<strong>of</strong> the University <strong>of</strong> Georgia (UGA). On the <strong>Cameroon</strong> side, leadership is <strong>in</strong> the h<strong>and</strong>s <strong>of</strong><br />
the IRA Cowpea Section at the experiment station at Maroua <strong>in</strong> the Far North Prov<strong>in</strong>ce.<br />
The UGA/IRA collaboration was part <strong>of</strong> the effort that led to the release <strong>of</strong> the varieties<br />
Vya <strong>in</strong> 1986, <strong>and</strong> BR1 <strong>and</strong> BR2 <strong>in</strong> 1987. Vya is a selection from a traditional variety from<br />
the Kaélé area <strong>of</strong> the Far North Prov<strong>in</strong>ce. BR1 <strong>and</strong> BR2 are closely related varieties with<br />
genetics from the International Institute <strong>of</strong> Tropical Agriculture (<strong>IITA</strong>). BR1 <strong>and</strong> BR2<br />
show some bruchid resistance.<br />
<strong>Impact</strong> assessment showed that <strong>cowpea</strong> <strong>research</strong> at IRAD from 1979 to 1987, <strong>in</strong>clud<strong>in</strong>g<br />
the CRSP effort, had IRR under basel<strong>in</strong>e assumptions <strong>of</strong> 15% annually (Sterns <strong>and</strong><br />
Bernste<strong>in</strong> 1993). The <strong>research</strong> benefits were largely l<strong>in</strong>ked to the widespread plant<strong>in</strong>g <strong>of</strong><br />
BR1 <strong>and</strong> BR2 <strong>in</strong> monocrop by farmers look<strong>in</strong>g for a cash crop as an alternative to cotton.<br />
Based on <strong>in</strong>terviews with key <strong>in</strong>formants <strong>in</strong> the region, Sterns <strong>and</strong> Bernste<strong>in</strong> (1993)<br />
estimated adoption <strong>of</strong> improved varieties to be 25% <strong>of</strong> <strong>cowpea</strong> area <strong>in</strong> 1990. Adoption <strong>of</strong><br />
these varieties was facilitated by SODECOTON, the <strong>Cameroon</strong> cotton parastatal, which<br />
sold seed <strong>and</strong> <strong>cowpea</strong> pesticides.<br />
In 1987, the focus shifted to <strong>cowpea</strong> <strong>storage</strong> under the leadership <strong>of</strong> Purdue University.<br />
Storage <strong>research</strong> started with a study <strong>of</strong> <strong>in</strong>digenous <strong>cowpea</strong> <strong>storage</strong> methods (Wolfson<br />
1990). Five general techniques were identified, which were pursued <strong>in</strong> on-station <strong>and</strong><br />
on-farm <strong>research</strong>: ash <strong>storage</strong>, solar heat<strong>in</strong>g, hermetic <strong>storage</strong>, oils, <strong>and</strong> botanicals. In<br />
1988 <strong>and</strong> 1989, <strong>cowpea</strong> l<strong>in</strong>es from <strong>Cameroon</strong> <strong>and</strong> <strong>IITA</strong> were screened for resistance to<br />
<strong>storage</strong> <strong>in</strong>sects, a solar heater for dis<strong>in</strong>fect<strong>in</strong>g <strong>cowpea</strong> was tested at the experiment station<br />
<strong>in</strong> Maroua, <strong>and</strong> improved methods were developed for ash <strong>storage</strong> (Murdock <strong>and</strong> Shade<br />
1988; Murdock et al. 1989). Resistance screen<strong>in</strong>g <strong>in</strong>cluded the search for nondehiscent<br />
pods that formed a barrier to <strong>in</strong>sects, as well as for harder seed coats that were more difficult<br />
for bruchids to penetrate. Pod resistance is potentially important <strong>in</strong> <strong>Cameroon</strong>, because<br />
Wolfson’s <strong>research</strong> showed that farmers <strong>of</strong>ten store <strong>cowpea</strong> <strong>in</strong> pod form for several months<br />
before thresh<strong>in</strong>g. A form <strong>of</strong> hermetic <strong>storage</strong> was added to the technology portfolio <strong>in</strong><br />
1990 <strong>in</strong> the form <strong>of</strong> triple bagg<strong>in</strong>g (Purdue/IRA <strong>and</strong> TLU/NCRE 1990).<br />
In 1990 <strong>and</strong> 1991, on-farm test<strong>in</strong>g <strong>of</strong> promis<strong>in</strong>g postharvest <strong>storage</strong> technologies was<br />
begun <strong>in</strong> four villages <strong>in</strong> the Maroua area (Purdue/IRA <strong>and</strong> TLU/NCRE 1990). Those<br />
technologies were:<br />
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Cowpea postharvest <strong>and</strong> socioeconomic studies<br />
• solar heater dis<strong>in</strong>festations<br />
• triple plastic bags<br />
• ash <strong>storage</strong><br />
It should be noted that neither solar dis<strong>in</strong>festation nor hermetic <strong>storage</strong> <strong>of</strong> gra<strong>in</strong>s are<br />
novel ideas. The contribution <strong>of</strong> the Purdue/IRA team was to adapt these ideas to the materials<br />
<strong>and</strong> constra<strong>in</strong>ts <strong>of</strong> <strong>Cameroon</strong>ian farmers. Extension materials were developed for each<br />
technology (Kitch <strong>and</strong> Ntoukam 1991 a, b; Ntoukam <strong>and</strong> Kitch, undated) <strong>and</strong> translated<br />
<strong>in</strong>to French <strong>and</strong> Fulfuldé. In 1992–1993, the <strong>storage</strong> technologies were demonstrated<br />
<strong>in</strong> 100 villages by agents <strong>of</strong> SODECOTON <strong>and</strong> MINAGRI, the <strong>Cameroon</strong>ian national<br />
agricultural extension agency (Purdue/IRA 1992; Purdue/IRA 1993). The <strong>storage</strong> technologies<br />
became a st<strong>and</strong>ard part <strong>of</strong> the farmer tra<strong>in</strong><strong>in</strong>g <strong>of</strong>fered by private <strong>and</strong> government<br />
extension organizations <strong>in</strong> northern <strong>Cameroon</strong> (Lowenberg-DeBoer, 1995, 1996, 1997).<br />
The techniques were featured <strong>in</strong> a radio program on <strong>cowpea</strong> <strong>storage</strong> <strong>in</strong> French, Fulfuldé,<br />
<strong>and</strong> other local languages. The program was produced by SODECOTON <strong>in</strong> 1995.<br />
Economic studies <strong>in</strong>dicated that the IRA/CRSP <strong>storage</strong> technologies were potentially<br />
pr<strong>of</strong>itable for some producers (Schultz 1993; Kamuanga <strong>and</strong> Kitch 1994; Lowenberg-<br />
DeBoer 1994). Use <strong>of</strong> the ash technique was limited primarily by the quantity <strong>of</strong> ash<br />
required. Access to materials for the solar heater <strong>and</strong> triple bagg<strong>in</strong>g was identified as<br />
another constra<strong>in</strong>t. Both plastic sheets <strong>and</strong> bags are readily available <strong>in</strong> the market <strong>in</strong><br />
Maroua, but not necessarily available <strong>in</strong> rural areas. SODECOTON facilitated access to<br />
solar heaters by sell<strong>in</strong>g pre-cut solar heater kits through their village agents <strong>in</strong> 1995.<br />
Lowenberg-DeBoer (1994) concluded that the triple bagg<strong>in</strong>g <strong>and</strong> solar heater technologies<br />
were competitive with those <strong>of</strong> <strong>storage</strong> <strong>in</strong>secticides, especially for <strong>storage</strong> periods<br />
longer than three months. He also noted that given the high opportunity cost <strong>of</strong> capital<br />
<strong>in</strong> northern <strong>Cameroon</strong> <strong>and</strong> throughout rural West Africa, many farmers would cont<strong>in</strong>ue<br />
to sell at harvest. They have urgent need for cash for family <strong>and</strong> bus<strong>in</strong>ess purposes, <strong>and</strong><br />
cannot afford to store, regardless <strong>of</strong> the technology.<br />
Merchants are very active <strong>in</strong> <strong>cowpea</strong> <strong>storage</strong>, but most <strong>of</strong> the extension effort on <strong>cowpea</strong><br />
<strong>storage</strong> has focused on farmer <strong>storage</strong>. Oumarou (1999) found that merchants <strong>in</strong> Maroua<br />
have <strong>storage</strong> for 25 000 to 30 000 t <strong>of</strong> <strong>cowpea</strong>. In most cases, this <strong>cowpea</strong> is stored us<strong>in</strong>g<br />
<strong>in</strong>secticides. Most <strong>of</strong> this <strong>cowpea</strong> is shipped out <strong>of</strong> the region, to the cities <strong>of</strong> southern<br />
<strong>Cameroon</strong>, to Nigeria, <strong>and</strong> <strong>in</strong>creas<strong>in</strong>gly to Gabon <strong>and</strong> Congo.<br />
Plant <strong>breed<strong>in</strong>g</strong> <strong>research</strong> focused on the development <strong>of</strong> <strong>storage</strong> pest resistance cont<strong>in</strong>ued<br />
through the early 1990s. In 1994, 1995, <strong>and</strong> 1996, varieties were evaluated on-station<br />
dur<strong>in</strong>g the grow<strong>in</strong>g season by farmers known <strong>in</strong> their communities as master <strong>cowpea</strong><br />
growers (Kitch et al. 1998). Two varieties were identified; they have the breed codes <strong>of</strong><br />
24–130 <strong>and</strong> 2–38 <strong>and</strong> have been given the names Lori Niébé <strong>and</strong> CRSP Niébé, respectively<br />
(IRAD 1999). In the 1997 <strong>and</strong> 1998 seasons they were tested <strong>in</strong> on-farm trials. In 1999,<br />
multiplication for seed dissem<strong>in</strong>ation started.<br />
Cowpea area <strong>and</strong> production<br />
There are two primary sources <strong>of</strong> statistics on <strong>cowpea</strong> area <strong>and</strong> production: the Prov<strong>in</strong>cial<br />
Agroeconomic Survey <strong>and</strong> Agricultural Plann<strong>in</strong>g Service (SPEAPA) <strong>and</strong> the National<br />
Directorate <strong>of</strong> the Agricultural Census (DEAPA). SPEAPA statistics are based on extension<br />
agents’ reports. DEAPA data were drawn from a r<strong>and</strong>om sample <strong>of</strong> farm households.<br />
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<strong>Impact</strong> <strong>of</strong> <strong>cowpea</strong> <strong>breed<strong>in</strong>g</strong> <strong>and</strong> <strong>storage</strong> <strong>research</strong> <strong>in</strong> <strong>Cameroon</strong><br />
The DEAPA effort was funded by a USAID project that ended <strong>in</strong> the early 1990s. The<br />
shortcom<strong>in</strong>gs <strong>of</strong> each data source are discussed by Lowenberg-DeBoer (1994, 1995).<br />
Both DEAPA <strong>and</strong> SPEAPA data show substantial year-to-year variation <strong>in</strong> area <strong>and</strong><br />
production. There is some <strong>in</strong>dication <strong>of</strong> an upward trend <strong>in</strong> yields <strong>in</strong> both the DEAPA<br />
<strong>and</strong> SPEAPA data, which confirm anecdotal reports, but when regressed on a l<strong>in</strong>ear trend<br />
l<strong>in</strong>e the estimates are not statistically significant. The best fitt<strong>in</strong>g regression model is a<br />
quadratic trend (R 2 = 65%), but that results <strong>in</strong> unrealistically high <strong>cowpea</strong> area by the<br />
end <strong>of</strong> the study period (more than 1 million ha). In an alternative regression, changes <strong>in</strong><br />
<strong>cowpea</strong> area are not well expla<strong>in</strong>ed by prices from the previous year. As a compromise,<br />
the basel<strong>in</strong>e analysis uses the last DEAPA observation (1992) as the area <strong>and</strong> yield estimate<br />
for the period 1993–2015. This <strong>in</strong>corporates the <strong>in</strong>crease <strong>in</strong> area <strong>and</strong> yield that had<br />
occurred up to that time, but does not <strong>in</strong>clude later <strong>in</strong>creases. The 1991 gap was filled with<br />
the mean for the data period. Sensitivity tests will be done us<strong>in</strong>g DEAPA <strong>and</strong> SPEAPA<br />
average area <strong>and</strong> yield.<br />
Adoption<br />
Adoption <strong>of</strong> <strong>storage</strong> technologies can be estimated us<strong>in</strong>g data from a survey <strong>in</strong> 1994<br />
(Lowenberg-DeBoer 1994) <strong>and</strong> <strong>in</strong>terviews with key <strong>in</strong>formants <strong>in</strong> the region after that<br />
time (Lowenberg-DeBoer 1995, 1996). The new varieties Lori Niébé (24-130) <strong>and</strong> CRSP<br />
Niébé (2-38) are at the beg<strong>in</strong>n<strong>in</strong>g <strong>of</strong> the seed dissem<strong>in</strong>ation process, so there are no adoption<br />
data. Their adoption potential will be estimated based on previous experience with<br />
Vya, BR1, <strong>and</strong> BR2.<br />
The 1994 data collection used a modified rapid rural appraisal design. Six villages<br />
were chosen r<strong>and</strong>omly from a list <strong>of</strong> all villages <strong>in</strong> the Départements <strong>of</strong> Diamaré, Mayo<br />
Danay, Mayo Kani, Mayo Sava, <strong>and</strong> Mayo Tsanaga <strong>in</strong> the Far North Prov<strong>in</strong>ce <strong>and</strong> the<br />
Département <strong>of</strong> Mayo Louti <strong>in</strong> the North Prov<strong>in</strong>ce. This covers the pr<strong>in</strong>cipal <strong>cowpea</strong><br />
grow<strong>in</strong>g areas <strong>of</strong> North <strong>Cameroon</strong>.<br />
One village per département was chosen r<strong>and</strong>omly from a list <strong>of</strong> all villages. None <strong>of</strong><br />
the villages chosen had been exposed to <strong>cowpea</strong> <strong>storage</strong> demonstrations. Discussions were<br />
held <strong>in</strong> a village meet<strong>in</strong>g context, thus the unit <strong>of</strong> observation is the village. In addition,<br />
case studies were done on two villages with long-term <strong>cowpea</strong> extension efforts, to ga<strong>in</strong><br />
a perspective on adoption when <strong>in</strong>formation on the techniques was available. Details <strong>of</strong><br />
the data collection methods <strong>and</strong> results are given by Lowenberg-DeBoer (1994).<br />
In the r<strong>and</strong>omly selected villages, about 23% <strong>of</strong> <strong>cowpea</strong> area was planted with the<br />
improved varieties Vya, BR1, <strong>and</strong> BR2. About 13% <strong>of</strong> 1991 <strong>cowpea</strong> area was planted<br />
to BR1 <strong>and</strong> BR2. About 10% was planted to Vya. BR1 <strong>and</strong> BR2 are grown ma<strong>in</strong>ly as<br />
monocrops. Vya is grown primarily <strong>in</strong>tercropped with sorghum. The 23% estimate is<br />
very close to the 25% improved variety area estimated earlier by Sterns <strong>and</strong> Bernste<strong>in</strong><br />
(1993) by <strong>in</strong>formal <strong>in</strong>terviews. This suggests that the use <strong>of</strong> these improved varieties has<br />
reached a plateau.<br />
Farmers <strong>in</strong> the case study villages were well <strong>in</strong>formed about CRSP <strong>storage</strong> techniques.<br />
In Douroum, Mayo Tsanaga, about 20% <strong>of</strong> the harvest was stored with the improved ash<br />
method, 7–10% <strong>of</strong> farmers used triple bagg<strong>in</strong>g, <strong>and</strong> 5% the solar heater. In Gatouguel,<br />
Mayo Louti, farmers had used the eight solar heaters supplied by IRA until they were <strong>in</strong><br />
tatters. They said that about 50% <strong>of</strong> <strong>cowpea</strong>s produced <strong>in</strong> the village had been treated when<br />
the solar heaters were available. At the time <strong>of</strong> the study they were eager to buy plastic to<br />
replace the orig<strong>in</strong>al heaters, but this was not available <strong>in</strong> the village.<br />
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Cowpea postharvest <strong>and</strong> socioeconomic studies<br />
The fall <strong>of</strong> 1994 <strong>and</strong> 1995 was a period <strong>of</strong> major extension activity <strong>in</strong> <strong>cowpea</strong> <strong>storage</strong>.<br />
SODECOTON sold about 300 heaters <strong>in</strong> the first few months <strong>of</strong> 1995. The National<br />
Agricultural Extension <strong>and</strong> Tra<strong>in</strong><strong>in</strong>g Project (PNVFA) dissem<strong>in</strong>ated the technology to<br />
approximately 1500 villages <strong>in</strong> the Far North Prov<strong>in</strong>ce where it has a regular presence.<br />
Programs <strong>in</strong> French <strong>and</strong> local languages were aired on local radio.<br />
Interviews with key <strong>in</strong>formants <strong>in</strong> the fall <strong>of</strong> 1995 <strong>in</strong>dicated that about 5% <strong>of</strong> farmers<br />
were us<strong>in</strong>g CRSP technologies, ma<strong>in</strong>ly the solar heater (Lowenberg-DeBoer 1995). Triple<br />
bagg<strong>in</strong>g is not widely used <strong>in</strong> rural areas because <strong>of</strong> the lack <strong>of</strong> bags. The solar heater<br />
was used on about 90% <strong>of</strong> the farms’ <strong>cowpea</strong> production. Interviews <strong>in</strong> 1996 <strong>and</strong> 1997<br />
<strong>in</strong>dicated that the use <strong>of</strong> the solar heater cont<strong>in</strong>ued to rise, but that <strong>storage</strong> <strong>in</strong>secticide use<br />
was grow<strong>in</strong>g rapidly (Lowenberg-DeBoer 1996, 1997). These <strong>in</strong>secticides are readily<br />
available at low cost from SODECOTON or from Nigeria border markets. By 1977 it<br />
was estimated that 70% <strong>of</strong> <strong>cowpea</strong>s stored was treated with <strong>in</strong>secticides <strong>and</strong> the use <strong>of</strong><br />
the CRSP technologies, primarily the solar heater, appeared to have reached a plateau <strong>of</strong><br />
about 10% <strong>of</strong> <strong>cowpea</strong> production.<br />
For the impact analysis a logistic function was used to estimate adoption for both the<br />
postharvest technologies <strong>and</strong> varieties. The basel<strong>in</strong>e scenario used a plateau <strong>of</strong> 10% for<br />
postharvest technologies <strong>and</strong> 13% for varieties. A sensitivity test will be done on a plateau<br />
<strong>of</strong> 25% for both <strong>in</strong>novations.<br />
Prices<br />
There is no regular system for report<strong>in</strong>g <strong>cowpea</strong> price data <strong>in</strong> northern <strong>Cameroon</strong>. Sterns<br />
<strong>and</strong> Bernste<strong>in</strong> (1993) documented monthly prices for the period 1985–1990. Lowenberg-<br />
DeBoer (1995, 1996) obta<strong>in</strong>ed some monthly price data for the period 1992–1995. S<strong>in</strong>ce<br />
September 1997, the Purdue/IRAD project has collected <strong>cowpea</strong> price <strong>and</strong> quality data<br />
monthly, start<strong>in</strong>g with two markets <strong>in</strong> the Maroua area <strong>and</strong> later extend<strong>in</strong>g the collection<br />
to two additional markets (Langy<strong>in</strong>tuo <strong>and</strong> Lowenberg-DeBoer 1999).<br />
For the model outl<strong>in</strong>ed by Diaz-Hermelo <strong>and</strong> Lowenberg-DeBoer (1999), prices are<br />
needed for two periods, harvesttime <strong>and</strong> after <strong>storage</strong>. Cowpea harvest typically starts <strong>in</strong><br />
October. Cowpeas are all h<strong>and</strong>-harvested by pick<strong>in</strong>g pods <strong>in</strong> the field. Harvest<strong>in</strong>g cont<strong>in</strong>ues<br />
through early December. Many producers store <strong>cowpea</strong> <strong>in</strong> pods on a raised <strong>storage</strong><br />
platform called a danki (Wolfson 1990). Danki <strong>storage</strong> may last for two to three months.<br />
Thresh<strong>in</strong>g may occur any time between the beg<strong>in</strong>n<strong>in</strong>g <strong>of</strong> harvest <strong>and</strong> the follow<strong>in</strong>g March.<br />
For the model it was assumed that newly threshed <strong>cowpea</strong> might be marketed any time<br />
from October to March <strong>and</strong> the price (P1) was the simple average price from the data for<br />
those months. Stored gra<strong>in</strong> was assumed to be stored for six months <strong>and</strong> sold at the simple<br />
average price for the period April to September (P2).<br />
Period one <strong>and</strong> two prices were estimated as the simple average for the periods October<br />
to March, <strong>and</strong> April to September <strong>in</strong> the available data. Gaps were filled with the average<br />
price for the data period, 193 real 1998 FCFA for P1 <strong>and</strong> 236 real 1998 FCFA for P2.<br />
Elasticities<br />
For the purpose <strong>of</strong> the analysis, <strong>cowpea</strong> supply is the <strong>cowpea</strong> gra<strong>in</strong> produced <strong>in</strong> the<br />
three northern prov<strong>in</strong>ces <strong>of</strong> <strong>Cameroon</strong>—Far North, North, <strong>and</strong> Adamoua. The dem<strong>and</strong><br />
is the sum <strong>of</strong> local dem<strong>and</strong> for consumption <strong>and</strong> dem<strong>and</strong> for export outside the northern<br />
<strong>Cameroon</strong> region. For the analysis, <strong>cowpea</strong> purchased for export <strong>in</strong> period 1 is treated as<br />
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<strong>Impact</strong> <strong>of</strong> <strong>cowpea</strong> <strong>breed<strong>in</strong>g</strong> <strong>and</strong> <strong>storage</strong> <strong>research</strong> <strong>in</strong> <strong>Cameroon</strong><br />
consumed; only <strong>cowpea</strong> stored for local consumption is considered by the <strong>storage</strong> model.<br />
Thus <strong>storage</strong> by merchants <strong>in</strong> Maroua await<strong>in</strong>g export is treated <strong>in</strong> this analysis as part<br />
<strong>of</strong> the first period dem<strong>and</strong>.<br />
There are no statistics on the proportion <strong>of</strong> <strong>cowpea</strong> reta<strong>in</strong>ed for local consumption<br />
<strong>in</strong> the <strong>storage</strong> period. Cowpea market studies <strong>in</strong>dicate that a large portion <strong>of</strong> <strong>cowpea</strong><br />
production <strong>in</strong> northern <strong>Cameroon</strong> is exported <strong>and</strong> most <strong>of</strong> the <strong>cowpea</strong> for export is purchased<br />
around harvesttime. The basel<strong>in</strong>e scenario will assume that 80% <strong>of</strong> <strong>cowpea</strong> gra<strong>in</strong><br />
is either consumed locally or purchased for export <strong>in</strong> the first period. That leaves 20% <strong>of</strong><br />
the <strong>cowpea</strong> stored, <strong>and</strong> given estimates (described below) <strong>of</strong> 52% <strong>storage</strong> losses prior to<br />
the <strong>in</strong>troduction <strong>of</strong> CRSP technologies, about 10% <strong>of</strong> the total production is available for<br />
local consumption <strong>in</strong> the second period. A sensitivity test will be done assum<strong>in</strong>g 40% <strong>of</strong><br />
<strong>cowpea</strong> is stored.<br />
Empirical estimates <strong>of</strong> the supply <strong>and</strong> dem<strong>and</strong> for <strong>cowpea</strong> <strong>in</strong> northern <strong>Cameroon</strong> are<br />
yet to be made. This analysis used the logic outl<strong>in</strong>ed by Masters et al. (1996) to determ<strong>in</strong>e<br />
elasticity parameters. He states that the typical supply elasticity is <strong>in</strong> the range <strong>of</strong> 0.2 to<br />
1.2, <strong>and</strong> dem<strong>and</strong> <strong>in</strong> the range <strong>of</strong> –0.4 to –10. The dem<strong>and</strong> elasticity <strong>of</strong> –10 would occur<br />
when the product is traded <strong>in</strong> a larger <strong>in</strong>ternational market. The lower end <strong>of</strong> the range<br />
would be for food crops with only local markets.<br />
The <strong>cowpea</strong> market <strong>in</strong> northern <strong>Cameroon</strong> is open to <strong>in</strong>ternational trade, but Lowenberg-<br />
DeBoer (1994) observed that this trade occurred ma<strong>in</strong>ly around harvesttime. Later <strong>in</strong> the<br />
year, markets <strong>in</strong> northern <strong>Cameroon</strong> were dom<strong>in</strong>ated by local dem<strong>and</strong>. This observation<br />
expla<strong>in</strong>s the high <strong>and</strong> volatile prices <strong>in</strong> the April to September period. The basel<strong>in</strong>e scenario<br />
<strong>in</strong> this analysis assumes that the first period has a very elastic dem<strong>and</strong> (–1.0) because <strong>of</strong><br />
<strong>in</strong>ternational trade <strong>and</strong> low elasticity <strong>in</strong> the second period (–0.40) when local dem<strong>and</strong><br />
dom<strong>in</strong>ates. For the supply side, a midrange estimate <strong>of</strong> 0.7 will be used. Sensitivity tests<br />
will be done on both dem<strong>and</strong> <strong>and</strong> supply elasticities.<br />
Storage losses<br />
For the basel<strong>in</strong>e model it was assumed that one hole per gra<strong>in</strong> was sufficient to cause a<br />
merchant to sort out that gra<strong>in</strong>. While that damaged gra<strong>in</strong> may still have value as livestock<br />
feed, this value is much less than that for human consumption. No salvage value for damaged<br />
gra<strong>in</strong> was <strong>in</strong>cluded <strong>in</strong> the model.<br />
The number <strong>of</strong> holes per gra<strong>in</strong> after a given <strong>storage</strong> period was estimated us<strong>in</strong>g data from<br />
on-farm tests <strong>of</strong> CRSP <strong>storage</strong> technologies <strong>in</strong> 1990–92 (Purdue/IRA 1990; Purdue/IRA<br />
1992 supplemental). The on-farm <strong>storage</strong> tests all ran for about three months. A logistic<br />
function <strong>of</strong> time similar to that used by Schultz was employed (Schultz 1993) to obta<strong>in</strong><br />
estimates <strong>of</strong> losses after six months <strong>of</strong> <strong>storage</strong>. Unfortunately, no <strong>in</strong>secticide treatments<br />
were used <strong>in</strong> the on-farm trials; it was assumed that damage levels with <strong>in</strong>secticide treatment<br />
would be similar to that <strong>of</strong> the solar dis<strong>in</strong>festations.<br />
The <strong>in</strong>itial loss parameter (δ) was estimated as the weighted average loss given the<br />
distribution <strong>of</strong> <strong>storage</strong> techniques estimated by Wolfson (1990) at the time when the<br />
project started. This required lump<strong>in</strong>g techniques <strong>in</strong>to categories for which loss estimates<br />
were available. The percentage <strong>in</strong> each category was ash, 24%; <strong>in</strong>secticide, 23%; herbs or<br />
“noth<strong>in</strong>g”, 48%; hermetic <strong>storage</strong>, 2%; heat<strong>in</strong>g, 2%. Ash loss was estimated by data on<br />
the CRSP ash technique (11% after six months), even though the <strong>in</strong>digenous technique is<br />
<strong>of</strong>ten less reliable because a lower proportion <strong>of</strong> ash is used. Because the CRSP trials did<br />
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Cowpea postharvest <strong>and</strong> socioeconomic studies<br />
not <strong>in</strong>clude <strong>in</strong>secticide or heat<strong>in</strong>g treatments, <strong>in</strong>secticide loss <strong>and</strong> heat<strong>in</strong>g are measured by<br />
data on the solar dis<strong>in</strong>festations (4% after six months). Hermetic <strong>storage</strong> loss is estimated<br />
with data from the triple bagg<strong>in</strong>g treatment (4% after six months).<br />
Each <strong>of</strong> these loss estimates assumes that <strong>cowpea</strong> put <strong>in</strong>to <strong>storage</strong> has an <strong>in</strong>itial damage<br />
level like that <strong>of</strong> Vya after three months on a danki <strong>in</strong> pod form (4.3%). Vya is typical <strong>of</strong><br />
many local <strong>cowpea</strong> varieties that are not particularly resistant to bruchids <strong>in</strong> pod form.<br />
While it is clear that the actual <strong>storage</strong> situation is much more complicated than this<br />
set <strong>of</strong> simple categories <strong>and</strong> loss rates, it is argued that the weighted average loss (52%)<br />
is a reasonable estimate. Insecticides <strong>and</strong> ash are not always used correctly <strong>and</strong> higher<br />
losses may result. In particular, a lower proportion <strong>of</strong> ash may be used (<strong>of</strong>ten because<br />
<strong>of</strong> a lack <strong>of</strong> an adequate quantity <strong>of</strong> ash) or the second <strong>in</strong>secticide treatment after three<br />
months may be omitted. Some <strong>Cameroon</strong>ian botanicals may reduce <strong>storage</strong> losses, even<br />
though that has not yet been proven <strong>in</strong> the laboratory. Thus, ash <strong>and</strong> <strong>in</strong>secticide losses may<br />
be somewhat higher than estimated <strong>and</strong> the herbs <strong>and</strong> “noth<strong>in</strong>g” category losses may be<br />
lower, but these <strong>of</strong>fset each other.<br />
If the basel<strong>in</strong>e loss parameter (δ) is 52%, the model loss parameter (φ) is 2.09. The loss<br />
reduction for solar heat<strong>in</strong>g (α) is 1.04 (φ) –1/(1–0.043)).<br />
Pod resistance is a characteristic <strong>of</strong> the newly developed varieties Lori Niébé <strong>and</strong> CRSP<br />
Niébé. This would affect the damage that occurs before the <strong>cowpea</strong>s are threshed. For the<br />
model, on-farm trial data with BR1 <strong>and</strong> BR2 were used. After three months on a danki<br />
these varieties showed only 0.8% damage, compared to the 4.3% with Vya. The 0.8%<br />
was then used as the start<strong>in</strong>g damage <strong>in</strong> the six-month <strong>storage</strong> estimates. This is done by<br />
recalibrat<strong>in</strong>g the logistic function used to estimate losses to pass through an <strong>in</strong>itial level<br />
<strong>of</strong> 0.8%, <strong>in</strong>stead <strong>of</strong> 4.3%. With the 0.8% <strong>in</strong>itial damage, the weighted average loss (δ) is<br />
50% <strong>and</strong> an alpha parameter (α = 0.10) is 10%.<br />
Storage costs<br />
Storage costs were estimated based on data provided by Lowenberg-DeBoer (1994). All<br />
technologies except ash <strong>and</strong> triple bagg<strong>in</strong>g were assumed to store gra<strong>in</strong> <strong>in</strong> woven sacks,<br />
valued at 250 FCFA for those that can hold 80 kg. Ash is stored <strong>in</strong> large clay pots called<br />
cannari commonly used to hold water <strong>in</strong> northern <strong>Cameroon</strong>. New pots are valued at<br />
1500 FCFA <strong>and</strong> can hold about 50 kg <strong>of</strong> <strong>cowpea</strong> when mixed 50/50 with ash. They are<br />
assumed to last for five years. Plastic bags are valued at 150 FCFA/bag <strong>and</strong> are assumed<br />
to be used for one season because <strong>of</strong> the risk that reused bags may have small holes.<br />
Insecticide is valued at 175 FCFA/packet with one packet treat<strong>in</strong>g 80 kg seed every three<br />
months. The solar heater is composed <strong>of</strong> two sheets <strong>of</strong> plastic, one clear the other black,<br />
valued at 3500 FCFA <strong>and</strong> given a useful life <strong>of</strong> two years. The estimate used the high<br />
volume estimate outl<strong>in</strong>ed by Lowenberg-DeBoer <strong>in</strong> which 4000 kg seed are treated per<br />
year per solar heater. For lack <strong>of</strong> data, labor is assumed to be the same for all technologies<br />
at 100 FCFA/hour.<br />
The <strong>in</strong>terest cost on the durable <strong>in</strong>vestment is annual, while the <strong>in</strong>terest on variable<br />
cost <strong>in</strong> the model (r) is semiannual.<br />
Us<strong>in</strong>g the estimates, the <strong>in</strong>itial nom<strong>in</strong>al cost <strong>of</strong> <strong>storage</strong> is 6049 FCFA/t or 7117 <strong>in</strong> 1998<br />
FCFA. The nom<strong>in</strong>al cost for the solar heater is 4166 FCFA/t or 4902 <strong>in</strong> 1998 FCFA. Thus<br />
the <strong>storage</strong> cost reduction is estimated at 2215 FCFA <strong>in</strong> 1998 FCFA.<br />
416
<strong>Impact</strong> <strong>of</strong> <strong>cowpea</strong> <strong>breed<strong>in</strong>g</strong> <strong>and</strong> <strong>storage</strong> <strong>research</strong> <strong>in</strong> <strong>Cameroon</strong><br />
Yield <strong>of</strong> improved varieties<br />
Yields <strong>of</strong> improved varieties Lori Niébé <strong>and</strong> CRSP Niébé <strong>in</strong> station trials are documented<br />
by Kitch et al. (1998) <strong>and</strong> Purdue/IRAD (1997). In these on-station trials, Lori Niébé <strong>and</strong><br />
CRSP Niébé were statistically significantly different from a commonly used variety at<br />
the 5% level. In general, improved varieties yield less <strong>in</strong> farmers’ fields than under the<br />
almost ideal conditions <strong>of</strong> the <strong>research</strong> station. The on-farm yield was estimated at 80%<br />
<strong>of</strong> the station yield. This results <strong>in</strong> a simple average yield improvement <strong>of</strong> 0.02 t/ha or<br />
about 2%. These data suggest that the ma<strong>in</strong> benefit <strong>of</strong> the new varieties is the <strong>storage</strong> pest<br />
resistance, not <strong>in</strong>creased yield.<br />
Improved yield always comes at some cost, even if that cost is difficult to calculate.<br />
Increase <strong>in</strong> seed cost due to the <strong>in</strong>troduction <strong>of</strong> these varieties will probably be negligible.<br />
These are varieties <strong>and</strong> once farmers have the variety, they can easily save their<br />
own seed or get from friends <strong>and</strong> relatives. Increased yields remove more nutrients from<br />
the soil, but <strong>in</strong> northern <strong>Cameroon</strong>, farmers rarely plant <strong>cowpea</strong> with fertilizer. In the<br />
long run, a greater need for fertilizer should be expected from <strong>in</strong>creased yield, but <strong>in</strong> the<br />
variety extension period <strong>of</strong> 2000–2015 it is unlikely that there will be a major move <strong>in</strong><br />
that direction. Increased yield requires more labor <strong>and</strong> even if that is family labor it has<br />
an opportunity cost. Abdoulaye (1995) estimates that the harvest rate is about 28 kg/day<br />
<strong>in</strong> Niger. With an eight-hour day <strong>and</strong> a cost <strong>of</strong> 100 FCFA/hour, this is an added cost <strong>of</strong><br />
about 29 FCFA/kg.<br />
Opportunity cost <strong>of</strong> capital<br />
Opportunity cost <strong>of</strong> capital <strong>in</strong> West Africa can be very high compared to levels <strong>in</strong> <strong>in</strong>dustrialized<br />
countries, <strong>of</strong>ten ris<strong>in</strong>g to over 100% annually for small-scale <strong>in</strong>formal sector<br />
enterprises (Vijverberg 1991; Lowenberg-DeBoer et al. 1994). Lowenberg-DeBoer (1994)<br />
presents case study evidence that female <strong>cowpea</strong> street food vendors earn these high returns<br />
on their very limited capital.<br />
One hypothesis is that opportunity costs <strong>of</strong> capital are highest for low resource people<br />
with very little capital <strong>and</strong> drop as capital levels <strong>in</strong>crease. The economic logic suggests that<br />
very poor people will seek out the higher return activities for their very limited capital. As<br />
they acquire more money, they exhaust those high return activities <strong>and</strong> <strong>in</strong>vest <strong>in</strong> somewhat<br />
lower return larger scale enterprises. As capital levels become large, the opportunity cost<br />
approaches the level <strong>in</strong> the formal sector.<br />
Calculations suggest that returns to <strong>cowpea</strong> <strong>storage</strong> vary substantially from year to<br />
year, but s<strong>in</strong>ce 1985 they have averaged from 15 to 25% annually depend<strong>in</strong>g on exactly<br />
how the calculation is done. This suggests that <strong>cowpea</strong> <strong>storage</strong> is an activity undertaken<br />
by those with relatively large amounts <strong>of</strong> capital, not the poor, <strong>and</strong> may expla<strong>in</strong> why a<br />
large part <strong>of</strong> <strong>cowpea</strong> <strong>storage</strong> is h<strong>and</strong>led by merchants <strong>in</strong> Maroua.<br />
As a conservative estimate <strong>of</strong> the opportunity cost <strong>of</strong> capital, the average real cost<br />
<strong>of</strong> formal sector capital <strong>in</strong> <strong>Cameroon</strong> (15% annually) was used for the parameter “r” <strong>in</strong><br />
equation 1. A sensitivity test was done with the 50% annual cost <strong>of</strong> capital suggested by<br />
Lowenberg-DeBoer et al. (1994). It should be noted that the opportunity cost <strong>of</strong> capital <strong>in</strong><br />
the model is def<strong>in</strong>ed on a six-month basis, so <strong>in</strong> the basel<strong>in</strong>e analysis r = 0.15/2 = 0.075.<br />
For the NPV calculation, the real cost <strong>of</strong> long-term capital to the pr<strong>in</strong>cipal donor, the US<br />
government, was used. It was estimated as the real <strong>in</strong>terest rate <strong>of</strong> 4.22% on long-term<br />
US government bonds from 1985 to 1998.<br />
417
Cowpea postharvest <strong>and</strong> socioeconomic studies<br />
Research <strong>and</strong> extension costs<br />
Allocation <strong>of</strong> <strong>research</strong> <strong>and</strong> extension costs is one <strong>of</strong> the most difficult parts <strong>of</strong> economic<br />
impact assessment. The allocation <strong>of</strong> such resources is seldom as clear as the theory suggests.<br />
A key problem is the cumulative nature <strong>of</strong> science. Scientific discoveries today<br />
are built on the <strong>research</strong> <strong>of</strong> the past <strong>and</strong> are the foundation <strong>of</strong> future work. An additional<br />
problem is the broad responsibility <strong>of</strong> most public sector agricultural <strong>research</strong> organizations.<br />
A team, such as the Purdue/IRAD group, is seldom able to focus exclusively on a<br />
narrow set <strong>of</strong> problems, but must respond to producer <strong>and</strong> consumer concerns on a wide<br />
range <strong>of</strong> issues.<br />
In allocat<strong>in</strong>g costs, the cumulative nature <strong>of</strong> science is dealt with follow<strong>in</strong>g the logic<br />
suggested by Masters et al. (1996). All costs related to decisions that were already made<br />
when the CRSP <strong>and</strong> IRA decided to <strong>in</strong>itiate <strong>cowpea</strong> <strong>storage</strong> <strong>research</strong> are considered sunk<br />
costs <strong>and</strong> not charged to the project. Thus, costs <strong>in</strong>curred by <strong>IITA</strong> <strong>in</strong> develop<strong>in</strong>g the genetic<br />
materials that became part <strong>of</strong> the parentage <strong>of</strong> the new CRSP varieties are not charged<br />
to the Purdue/IRAD project. Similarly, costs <strong>in</strong>curred by CRSP <strong>and</strong> other organizations<br />
<strong>in</strong> develop<strong>in</strong>g <strong>and</strong> extend<strong>in</strong>g BR1 <strong>and</strong> BR2 are not charged to the <strong>storage</strong> project even if<br />
BR1 <strong>and</strong> BR2 were among the parents <strong>of</strong> the new varieties, <strong>and</strong> even if the extension <strong>of</strong><br />
BR1 <strong>and</strong> BR2 created a precedent that other new varieties can follow.<br />
The pr<strong>in</strong>cipal use <strong>in</strong> allocation <strong>of</strong> costs is that the <strong>in</strong>tellectual debt to previous <strong>research</strong>ers<br />
is acknowledged, but the cost <strong>of</strong> previous <strong>research</strong> is not added <strong>in</strong>. Similarly, benefits<br />
<strong>of</strong> the project for future <strong>research</strong> are discussed, but not deducted from the <strong>research</strong> <strong>and</strong><br />
extension costs. The benefits <strong>of</strong> the “sweet <strong>cowpea</strong>” variety that was discovered dur<strong>in</strong>g<br />
the development <strong>of</strong> the new varieties are not <strong>in</strong>cluded <strong>in</strong> this analysis.<br />
The diverse responsibilities <strong>of</strong> many agricultural <strong>research</strong>ers are <strong>of</strong>ten more difficult<br />
to deal with than previous <strong>research</strong> <strong>and</strong> extension. Often there is no good way to allocate<br />
time <strong>and</strong> resources. Field trials may be done at the same site <strong>and</strong> cared for by the same<br />
technicians. A computer <strong>and</strong> s<strong>of</strong>tware purchased by one organization is also used <strong>in</strong>cidentally<br />
to analyze data from a related effort. For example, after the CRSP collaboration<br />
with IRAD was refocused on <strong>storage</strong>, some effort cont<strong>in</strong>ued on the previous agronomy<br />
<strong>research</strong>, especially <strong>in</strong> the first few years <strong>of</strong> the <strong>storage</strong> effort. For this analysis all costs<br />
<strong>in</strong>curred by CRSP <strong>in</strong> <strong>Cameroon</strong> <strong>and</strong> for <strong>Cameroon</strong>, <strong>and</strong> by IRAD for CRSP collaboration<br />
are treated as be<strong>in</strong>g for development <strong>of</strong> the postharvest technologies <strong>and</strong> the new varieties.<br />
It is acknowledged that this probably overstates the cost <strong>of</strong> <strong>research</strong>, but given the lack <strong>of</strong><br />
<strong>in</strong>formation on <strong>research</strong>er time <strong>and</strong> resource allocation it is the only practical solution.<br />
Bean–Cowpea CRSP expenditures are taken from account<strong>in</strong>g records at Purdue University<br />
<strong>and</strong> at the CRSP Management Office at Michigan State University. The CRSP amounts<br />
represent two categories <strong>of</strong> expenditure: those <strong>in</strong> <strong>Cameroon</strong> by CRSP <strong>and</strong> by IRAD <strong>and</strong><br />
those made <strong>in</strong> the US explicitly for IRAD. A typical example <strong>of</strong> the “for <strong>Cameroon</strong>”<br />
expenditure is the purchase <strong>of</strong> scientific equipment <strong>in</strong> the US for shipment to <strong>Cameroon</strong>.<br />
Expenditure for short-term tra<strong>in</strong><strong>in</strong>g is <strong>in</strong>cluded. Long-term tra<strong>in</strong><strong>in</strong>g typically has objectives<br />
beyond the development <strong>of</strong> specific technology <strong>and</strong> is not <strong>in</strong>cluded <strong>in</strong> <strong>research</strong> costs for<br />
this analysis. The CRSP is a collaboration with benefits expected on both sides. The US<br />
costs are assumed to be paid for by US side benefits. The IRAD costs are those reported<br />
by the Institute to the CRSP as their contribution to the overall <strong>cowpea</strong> effort.<br />
In <strong>Cameroon</strong>, the Purdue/IRAD team worked closely with the National Cereals<br />
Research <strong>and</strong> Extension (NCRE) project. This occurred <strong>in</strong> particular with the on-farm<br />
418
<strong>Impact</strong> <strong>of</strong> <strong>cowpea</strong> <strong>breed<strong>in</strong>g</strong> <strong>and</strong> <strong>storage</strong> <strong>research</strong> <strong>in</strong> <strong>Cameroon</strong><br />
test<strong>in</strong>g <strong>of</strong> the postharvest <strong>storage</strong> technology. The NCRE allocation <strong>of</strong> funds to those<br />
jo<strong>in</strong>t activities was estimated with the help <strong>of</strong> Dr Emanuel Atayi, former NCRE team<br />
leader (Emmanuel Atayi, Personal Communication), <strong>and</strong> with <strong>in</strong>formation from NCRE<br />
plans <strong>of</strong> work for 1988–89, 1991, 1992, 1993, <strong>and</strong> 1994.<br />
Extension <strong>of</strong> the postharvest technologies <strong>and</strong> new varieties was done <strong>in</strong> collaboration<br />
with several private <strong>and</strong> public organizations, especially the National Program for<br />
Agricultural Extension <strong>and</strong> Tra<strong>in</strong><strong>in</strong>g (PNVFA), which is the M<strong>in</strong>istry <strong>of</strong> Agriculture’s<br />
extension project; Support Service for Grassroots Initiatives <strong>in</strong> Development (SAILD),<br />
an NGO with ma<strong>in</strong>ly Austrian support; Africa, Women <strong>and</strong> Development (AFP), an<br />
NGO focus<strong>in</strong>g on women’s issues; <strong>and</strong> SODECOTON, the <strong>Cameroon</strong> cotton parastatal.<br />
For each <strong>of</strong> these extension efforts, cost estimates are based on <strong>in</strong>terviews with<br />
adm<strong>in</strong>istrators <strong>in</strong> the organization.<br />
Economic surplus<br />
The economic surplus calculations follow the method outl<strong>in</strong>ed by Masters et al. (1996),<br />
modified by the need to comb<strong>in</strong>e <strong>storage</strong> <strong>and</strong> yield <strong>in</strong>creas<strong>in</strong>g <strong>in</strong>novations as outl<strong>in</strong>ed<br />
by Diaz-Hermelo <strong>and</strong> Lowenberg-DeBoer (1999).<br />
Table 2 shows IRR <strong>and</strong> NPV results. It <strong>in</strong>dicates that the <strong>in</strong>vestment <strong>in</strong> <strong>research</strong><br />
<strong>and</strong> extension was only slightly above the real cost <strong>of</strong> capital (4.22%) when only the<br />
benefits <strong>in</strong> <strong>Cameroon</strong> are considered. Transfer <strong>of</strong> CRSP <strong>storage</strong> technologies to Ben<strong>in</strong>,<br />
Niger, Nigeria, Senegal, <strong>and</strong> other countries (Lowenberg-DeBoer 1999) is add<strong>in</strong>g<br />
substantial benefits with mostly extension costs. Estimation <strong>of</strong> these spillover benefits<br />
is an important topic, but beyond the scope <strong>of</strong> this analysis.<br />
Separate estimation yields an IRR <strong>and</strong> NPV only slightly higher. This is consistent<br />
with the bias estimates <strong>in</strong> Table 1. The basel<strong>in</strong>e parameters <strong>of</strong> period 2 dem<strong>and</strong><br />
elasticity (η 2<br />
) <strong>and</strong> the reduction <strong>in</strong> <strong>storage</strong> loss (α) are such that the bias <strong>in</strong> separate<br />
estimation is m<strong>in</strong>imized. In addition, the potential for bias only occurs when the new<br />
varieties are <strong>in</strong>troduced after 2000. Thus, the bias occurs ma<strong>in</strong>ly toward the end <strong>of</strong><br />
the analysis period when the NPV effect would be reduced.<br />
Sensitivity test<strong>in</strong>g shows that for most parameter values the conclusions are the<br />
same concern<strong>in</strong>g both the benefits <strong>of</strong> the <strong>cowpea</strong> <strong>research</strong> <strong>and</strong> extension effort, <strong>and</strong><br />
the effects <strong>of</strong> separate estimates. A lower first period dem<strong>and</strong> elasticity (η 1<br />
= –0.4)<br />
or higher opportunity cost <strong>of</strong> capital (r = 0.25) have little impact on the results.<br />
Alternative values <strong>of</strong> the <strong>cowpea</strong> area, supply elasticity, <strong>and</strong> proportion consumed<br />
<strong>in</strong> the second period result <strong>in</strong> higher benefits. If the supply elasticity is near the lower<br />
end <strong>of</strong> the range (ε = 0.2), the gra<strong>in</strong> from <strong>in</strong>creased yields <strong>and</strong> that saved by <strong>storage</strong><br />
loss reduction are more valuable, result<strong>in</strong>g <strong>in</strong> an NPV <strong>of</strong> over US$800 000 <strong>and</strong> an<br />
IRR <strong>of</strong> 7.70. Similarly, if the proportion <strong>of</strong> <strong>cowpea</strong> consumed <strong>in</strong> the second period<br />
is higher (q s<br />
= 0.4), NPV <strong>and</strong> IRR are <strong>in</strong>creased because more gra<strong>in</strong> is stored <strong>and</strong> the<br />
lower costs <strong>and</strong> value <strong>of</strong> reduction <strong>of</strong> <strong>storage</strong> losses are multiplied by a larger quantity.<br />
With <strong>cowpea</strong> area estimated with the quadratic trend that gives the best statistical fit,<br />
IRR rises to 21%.<br />
Higher, long-term adoption plateaus (M = 0.25) <strong>in</strong>crease the economic impact.<br />
If postharvest technologies have a plateau <strong>of</strong> 0.25 <strong>in</strong>stead <strong>of</strong> 10%; the NPV rises to<br />
US$1.4 million <strong>and</strong> IRR to 10%. Rais<strong>in</strong>g the new variety yield plateau to 0.25 has a<br />
smaller effect, because the yield ga<strong>in</strong> is small.<br />
419
420<br />
Table 2. Summary comparison <strong>of</strong> comb<strong>in</strong>ed <strong>and</strong> separate estimation, ex-post <strong>and</strong> sensitivity analysis.<br />
Comb<strong>in</strong>ed Separate Difference<br />
Relative NPV<br />
IRR IRR difference IRR<br />
NPV (%) Annual NPV (%) Annual NPV (%) (%) Annual<br />
Basel<strong>in</strong>e values 100 469 4.74 6072 103 214 4.75 6 238 2745 2.73 0.01 166<br />
Sensitivity analysis<br />
η 1<br />
= –0.4 88 131 4.68 5326 92 525 4.70 5592 4394 4.99 0.02 266<br />
η 2<br />
= –10.00 628 261 0.08 –37 970 –588 763 0.44 –35 582 39 498 6.29 0.36 2387<br />
q s<br />
= 0.4 1 456 093 10.20 88 000 1 461 715 10.22 88 340 5623 0.39 0.01 340<br />
r = 0.25 102 198 4.75 6,176 104 870 4.76 6 338 2672 2.61 0.01 161<br />
Supply elasticity = 0.2 866 055 7.70 52 341 875 404 7.73 52 906 9349 1.08 0.03 565<br />
Adoption plateau = 0.25 349 294 5.83 21 110 358 461 5.87 21 664 9167 2.62 0.04 554<br />
Two holes/gra<strong>in</strong> –626 172 0.32 –37 843 –625 126 0.33 –37 780 1046 0.17 0.01 63<br />
P2 higher 113 552 4.80 6863 115 743 4.82 6995 2191 1.93 0.01 132<br />
SPEAPA avg † –110 673 3.62 -6689 –107 677 3.64 –6508 2996 2.71 0.02 181<br />
DEAPA avg ‡ –656 382 –0.07 –39 669 –654 508 –0.06 –39 556 1874 0.29 0.02 113<br />
Cowpea postharvest <strong>and</strong> socioeconomic studies<br />
†<br />
SPEAPA average yield, which is higher than DEAPA average yield.<br />
‡<br />
with DEAPA average yield.
<strong>Impact</strong> <strong>of</strong> <strong>cowpea</strong> <strong>breed<strong>in</strong>g</strong> <strong>and</strong> <strong>storage</strong> <strong>research</strong> <strong>in</strong> <strong>Cameroon</strong><br />
At some relatively extreme values <strong>of</strong> the parameter ranges the IRR drops below the cost<br />
<strong>of</strong> capital <strong>and</strong> the NPV is negative. If second period dem<strong>and</strong> is very elastic (η 2<br />
= –10) or<br />
if it assumed that two holes constitute a loss, the IRR is less than the opportunity cost <strong>of</strong><br />
capital <strong>and</strong> the NPV is negative. The difference between separate <strong>and</strong> comb<strong>in</strong>ed estimates<br />
is largest when the second period dem<strong>and</strong> elasticity is large (η 2<br />
= –10), but even then it<br />
is still less than a one percentage po<strong>in</strong>t difference <strong>in</strong> the IRR. The NPV is also negative<br />
when either the SPEAPA or DEAPA average area <strong>and</strong> yield are used.<br />
Given the <strong>in</strong>formation on elasticities, partition<strong>in</strong>g <strong>of</strong> the economic surplus <strong>in</strong>to producer<br />
<strong>and</strong> consumer surplus is not particularly reliable, but it can provide some <strong>in</strong>sight<br />
<strong>in</strong>to potential distributional effects. Producer surplus <strong>in</strong> the separate estimate <strong>of</strong> <strong>storage</strong><br />
impacts is negative every year after the postharvest technologies are <strong>in</strong>troduced. In effect,<br />
reduc<strong>in</strong>g <strong>storage</strong> loss substitutes “saved” gra<strong>in</strong> for produced gra<strong>in</strong>. As def<strong>in</strong>ed <strong>in</strong> the model,<br />
producers only ga<strong>in</strong> by produc<strong>in</strong>g <strong>and</strong> hence they lose when less total gra<strong>in</strong> is needed. Of<br />
course <strong>cowpea</strong> producers are also <strong>cowpea</strong> consumers who ga<strong>in</strong> every year. The pr<strong>of</strong>its for<br />
<strong>storage</strong> are built <strong>in</strong>to the <strong>storage</strong> cost calculation. Because <strong>of</strong> the high dem<strong>and</strong> elasticity<br />
<strong>in</strong> the first period, most <strong>of</strong> the impact due to yield ga<strong>in</strong>s from the new varieties goes to<br />
producers. In the comb<strong>in</strong>ed estimation, producer surplus is positive after the new varieties<br />
are <strong>in</strong>troduced because the production benefit from higher yield outweighs the producer<br />
surplus decl<strong>in</strong>es from reduced <strong>storage</strong> loss.<br />
Conclusions<br />
From a methodological perspective we have shown that the <strong>in</strong>teraction <strong>of</strong> production<br />
<strong>and</strong> <strong>storage</strong> technology can have important consequences for impact assessment. Higher<br />
yields <strong>and</strong> reduced <strong>storage</strong> losses are two ways to have more usable product. The sum <strong>of</strong><br />
their separate benefits is <strong>of</strong>ten greater than the comb<strong>in</strong>ed estimate <strong>of</strong> benefits. The bias<br />
<strong>in</strong>troduced by separate estimation is greatest when the dem<strong>and</strong> for the product <strong>in</strong> period<br />
two is elastic <strong>and</strong> when the <strong>storage</strong> loss reduction is large. Comb<strong>in</strong>ed estimation should<br />
be used when the bias is likely to be large, but a simpler separate estimate is still useful<br />
for other situations.<br />
For the <strong>Cameroon</strong> <strong>cowpea</strong> example, separate estimation had little effect on impact<br />
estimates. With conservative estimates <strong>of</strong> <strong>cowpea</strong> area <strong>and</strong> new technology adoption, both<br />
comb<strong>in</strong>ed <strong>and</strong> separate analyses estimate the basel<strong>in</strong>e IRR at about 5% <strong>and</strong> the NPV at<br />
about US$200 000. With a real opportunity cost <strong>of</strong> capital <strong>of</strong> about 4%, the <strong>Cameroon</strong><br />
project is about breakeven from just the adoption <strong>in</strong> <strong>Cameroon</strong> alone. The real net ga<strong>in</strong>s<br />
from the <strong>research</strong> are com<strong>in</strong>g from the extension <strong>of</strong> <strong>cowpea</strong> <strong>storage</strong> technologies <strong>in</strong>to<br />
other areas <strong>of</strong> West Africa.<br />
As with any empirical impact assessment, the <strong>Cameroon</strong> example has numerous limitations.<br />
The <strong>cowpea</strong> area, production, yield, <strong>and</strong> price data provide a general <strong>in</strong>dication<br />
<strong>of</strong> conditions <strong>in</strong> northern <strong>Cameroon</strong>, but they are not perfect. In particular, the data on<br />
trends <strong>in</strong> area <strong>and</strong> production were hard to <strong>in</strong>terpret. The postharvest adoption estimates<br />
were based ma<strong>in</strong>ly on <strong>in</strong>terviews with key <strong>in</strong>formants. The new variety adoption estimates<br />
were made with the assumption that they would follow a path similar to those <strong>of</strong> BR1<br />
<strong>and</strong> BR2. The analysis assumed l<strong>in</strong>ear supply <strong>and</strong> dem<strong>and</strong> throughout. Changes <strong>in</strong> gra<strong>in</strong><br />
quality due to the new varieties are not <strong>in</strong>cluded <strong>in</strong> benefit calculations. The focus was<br />
on economic impact. Environmental <strong>and</strong> human health benefits from the reduction <strong>in</strong> use<br />
<strong>of</strong> <strong>storage</strong> chemicals were not assessed.<br />
421
Cowpea postharvest <strong>and</strong> socioeconomic studies<br />
References<br />
Abdoulaye, T. 1995. <strong>Impact</strong> <strong>of</strong> opportunity cost <strong>of</strong> capital on adoption <strong>of</strong> new technologies <strong>in</strong> the<br />
Birni N’Konni Region <strong>of</strong> Niger. MS thesis, Dept. <strong>of</strong> Agricultural Economics, Purdue University,<br />
West Lafayette, IN, USA.<br />
Ak<strong>in</strong>o, M. <strong>and</strong> Y. Hayami. 1975. Efficiency <strong>and</strong> equity <strong>in</strong> public <strong>research</strong>: rice <strong>breed<strong>in</strong>g</strong> <strong>in</strong> Japan’s<br />
economic development. American Journal <strong>of</strong> Agricultural Economics 57: 1–10.<br />
Alston, J. 1991. Research benefits <strong>in</strong> a multimarket sett<strong>in</strong>g: a review. Review <strong>of</strong> Market<strong>in</strong>g <strong>and</strong><br />
Agricultural Economics 59: 23–52.<br />
Alston, J., G. Norton, <strong>and</strong> P. Pardey. 1995. Science under scarcity: pr<strong>in</strong>ciples <strong>and</strong> practices for<br />
agricultural <strong>research</strong> evaluation <strong>and</strong> priority sett<strong>in</strong>g. Cornell University Press, Ithaca, NY,<br />
USA.<br />
Diaz-Hermelo, F. <strong>and</strong> J. Lowenberg-DeBoer. 1999. Estimat<strong>in</strong>g <strong>research</strong> benefits with both production<br />
<strong>and</strong> postharvest technology: the case <strong>of</strong> <strong>cowpea</strong>s <strong>in</strong> <strong>Cameroon</strong>. West Africa Regional Social<br />
Science Report no. 2. Bean–Cowpea CRSP. East Lans<strong>in</strong>g, MI, USA.<br />
Echeverria, R. 1990. Assess<strong>in</strong>g the impact <strong>of</strong> agricultural <strong>research</strong>. In Methods for diagnos<strong>in</strong>g<br />
<strong>research</strong> system constra<strong>in</strong>ts <strong>and</strong> assess<strong>in</strong>g the impact <strong>of</strong> agricultural <strong>research</strong>, Vol. 2, ISNAR,<br />
The Hague, The Netherl<strong>and</strong>s.<br />
Fuglie, O. 1995. Measur<strong>in</strong>g welfare benefits from improvements <strong>in</strong> <strong>storage</strong> technology with application<br />
to Tunisian potatoes. American Journal <strong>of</strong> Agricultural Economics 77: 162–173.<br />
Institute <strong>of</strong> Agricultural Research for Development (IRAD). 1999. “Procés verbal de la réunion<br />
d’homologation des variétés de niébé” (Vigna unguiculata) 24–130 et 2–38 développées par le<br />
Projet Bean–Cowpea CRSP en collaboration avec IRAD-Maroua, Maroua Regional Agricultural<br />
Research Center, Maroua, <strong>Cameroon</strong>, 23 Sept 1999.<br />
Kamuanga, M. <strong>and</strong> L. Kitch. 1994. On-farm test<strong>in</strong>g <strong>and</strong> extension <strong>of</strong> <strong>cowpea</strong> <strong>storage</strong> technologies<br />
<strong>in</strong> northern <strong>Cameroon</strong>. Unpublished paper, Institute for Agricultural Research (IRA), Maroua,<br />
<strong>Cameroon</strong>.<br />
Kitch, L. <strong>and</strong> G. Ntoukam. 1991a. Air-tight <strong>storage</strong> <strong>of</strong> <strong>cowpea</strong> <strong>in</strong> triple plastic bags. Technical Bullet<strong>in</strong>.<br />
Bean–Cowpea CRSP, East Lans<strong>in</strong>g, MI, USA.<br />
Kitch, L. <strong>and</strong> G. Ntoukam. 1991b. Storage <strong>of</strong> <strong>cowpea</strong> <strong>in</strong> ash. Technical Bullet<strong>in</strong>. Bean–Cowpea<br />
CRSP, East Lans<strong>in</strong>g, MI, USA.<br />
Kitch, L., O. Boukar, C. Endondo, <strong>and</strong> L.L. Murdock. 1998. Farmer acceptability criteria <strong>in</strong> <strong>breed<strong>in</strong>g</strong><br />
<strong>cowpea</strong>. Experimental Agriculture 34: 475–486.<br />
Langy<strong>in</strong>tuo, A. <strong>and</strong> J. Lowenberg-DeBoer. 1999. Hedonic price analysis as a multidiscipl<strong>in</strong>ary<br />
activity: the case <strong>of</strong> <strong>cowpea</strong> <strong>in</strong> <strong>Cameroon</strong>. West Africa Regional Report, no. 3. East Lans<strong>in</strong>g, MI,<br />
USA.<br />
L<strong>in</strong>dner, R.K. <strong>and</strong> F.G. Jarret. 1978. Supply shifts <strong>and</strong> the size <strong>of</strong> <strong>research</strong> benefits. American Journal<br />
<strong>of</strong> Agricultural Economics 60: 48–56.<br />
Lowenberg-DeBoer, J. 1994. Trip report: Ghana, <strong>Cameroon</strong>, <strong>and</strong> Mali, 11–30 October, 5–9 November<br />
1994. Bean–Cowpea CRSP, Purdue/IRA Cowpea Storage Project.<br />
Lowenberg-DeBoer, J., T. Abdoulaye, <strong>and</strong> D. Kaboré. 1994. The opportunity cost <strong>of</strong> capital for<br />
agriculture <strong>in</strong> the Sahel: case study evidence from Niger <strong>and</strong> Burk<strong>in</strong>a Faso. Staff Paper no. 94-2,<br />
Dept. <strong>of</strong> Agricultural Economics, Purdue University, West Lafayette, IN, USA.<br />
Lowenberg-DeBoer, J. 1995. Trip report: <strong>Cameroon</strong>, 10–22 December 1995. Bean–Cowpea CRSP,<br />
Purdue/IRA Cowpea Storage Project.<br />
Lowenberg-DeBoer, J. 1996. Trip report: Ghana, Senegal, <strong>and</strong> <strong>Cameroon</strong>. 7–28 September 1996.<br />
Bean–Cowpea CRSP, Purdue/IRA Cowpea Storage Project.<br />
Lowenberg-DeBoer, J. 1997. Trip report: <strong>Cameroon</strong>, 5–21 May 1997. Bean–Cowpea CRSP, Purdue/<br />
IRA Cowpea Storage Project.<br />
422
<strong>Impact</strong> <strong>of</strong> <strong>cowpea</strong> <strong>breed<strong>in</strong>g</strong> <strong>and</strong> <strong>storage</strong> <strong>research</strong> <strong>in</strong> <strong>Cameroon</strong><br />
Lowenberg-DeBoer, J. 1999. Trip report: Zimbabwe, Mozambique, Ben<strong>in</strong>, 15 February to 10 March<br />
1999. Bean–Cowpea CRSP, East Lans<strong>in</strong>g, MI, USA.<br />
Masters, W., B. Coulibaly, D. Sanogo, M. Sidibe, <strong>and</strong> A. Williams. 1996. The economic impact <strong>of</strong><br />
agricultural <strong>research</strong>: a practical guide. Purdue University, West Lafayette, IN, USA.<br />
Murdock, L. <strong>and</strong> R. Shade. 1988. 1988 Annual Report, Bean–Cowpea CRSP, Purdue University/IRA-<br />
<strong>Cameroon</strong> Project.<br />
Murdock, L., R. Shade, <strong>and</strong> Z. Boli. 1989. 1989 Annual Report, Bean–Cowpea CRSP, Purdue<br />
University/IRA-<strong>Cameroon</strong> Project.<br />
Murdock, L.L., R.E. Shade, L.W. Kitch, G. Ntoukam, J. Lowenberg-DeBoer, J.E. Hues<strong>in</strong>g, W. Moar,<br />
O.L. Chambliss, C. Endondo, <strong>and</strong> J.L. Wolfson. 1997. Postharvest <strong>storage</strong> <strong>of</strong> <strong>cowpea</strong> <strong>in</strong> sub-<br />
Saharan Africa. Pages 302–312 <strong>in</strong> Advances <strong>in</strong> <strong>cowpea</strong> <strong>research</strong>, edited by B.B. S<strong>in</strong>gh, D.R.<br />
Mohan Raj, K.E. Dashiell, <strong>and</strong> L.E.N. Jackai. Copublication <strong>of</strong> International Institute <strong>of</strong><br />
Tropical Agriculture (<strong>IITA</strong>) <strong>and</strong> Japan International Research Center for Agricultural Sciences<br />
(JIRCAS). <strong>IITA</strong>, Ibadan, Nigeria.<br />
Muth, R.F. 1964. The derived dem<strong>and</strong> curve for productive factor <strong>and</strong> the <strong>in</strong>dustry supply curve.<br />
Oxford Economic Papers 16: 221–234.<br />
Ntoukam, G. <strong>and</strong> L. Kitch. Solar heaters for improved <strong>cowpea</strong> <strong>storage</strong>. Technical Bullet<strong>in</strong>. Bean–<br />
Cowpea CRSP, East Lans<strong>in</strong>g, MI, USA.<br />
National Cereals Research <strong>and</strong> Extension (NCRE) Project, Plan <strong>of</strong> Work, Republic <strong>of</strong> <strong>Cameroon</strong>,<br />
M<strong>in</strong>istry <strong>of</strong> Higher Education <strong>and</strong> Scientific Research (MESIRES), Institute <strong>of</strong> Agricultural<br />
Research (IRA), 1988, 1991, 1992, 1993, 1994.<br />
Oumarou, J.-P. 1999. Etude sur le circuit commerçial du niébé dans la Prov<strong>in</strong>ce de l’Extreme Nord<br />
du Cameroun. Undergraduate thesis, University <strong>of</strong> Ngaoundéré, Ngaoundéré, <strong>Cameroon</strong>.<br />
Purdue University/Institut de la Recherche Agronomique (Purdue/IRA). 1987. Detailed Project<br />
Annual Report, Bean–Cowpea CRSP, Purdue University/IRA-<strong>Cameroon</strong> Project.<br />
Purdue University/Institut de la Recherche Agronomique pour le Développement (Purdue/IRA).<br />
1992. Detailed Project Annual Report, Bean–Cowpea CRSP, Purdue University/IRA-<strong>Cameroon</strong><br />
Project.<br />
Purdue University/Institut de la Recherche Agronomique pour le Développement (Purdue/IRA).<br />
1993. 1993 Detailed Project Annual Report, Bean–Cowpea CRSP, Purdue University/IRA-<strong>Cameroon</strong><br />
Project.<br />
Purdue University/Institut de la Recherche Agronomique pour le Développement (Purdue/IRA).<br />
1997. 1996 Detailed Project Annual Report, Bean–Cowpea CRSP, Purdue University/IRAD -<br />
<strong>Cameroon</strong> Project.<br />
Purdue University/Institut de la Recherche Agronomique pour le Développement (Purdue/IRA) <strong>and</strong><br />
the National Cereals Research <strong>and</strong> Extension Project Test<strong>in</strong>g <strong>and</strong> Liason Unit (NCRE/TLU).<br />
1990. On-farm tests <strong>of</strong> <strong>storage</strong> technologies: 1990–1991. In Supplement to the 1990 Detailed<br />
Project Annual Report, Bean–Cowpea CRSP, Purdue/IRA-<strong>Cameroon</strong> Project.<br />
Rose, F. 1980. Supply shifts <strong>and</strong> the size <strong>of</strong> <strong>research</strong> benefits: comment. American Journal <strong>of</strong> Agricultural<br />
Economics 62: 834–837.<br />
Schultz, M.A. 1993. Economic assessment <strong>of</strong> <strong>cowpea</strong> gra<strong>in</strong> <strong>storage</strong> techniques: a case study <strong>of</strong><br />
North <strong>Cameroon</strong>. Unpublished MSc Thesis, Dept. <strong>of</strong> Agricultural Economics, Michigan State<br />
University, East Lans<strong>in</strong>g, MI, USA.<br />
Sterns, J. <strong>and</strong> R. Bernste<strong>in</strong>. 1993. Assess<strong>in</strong>g the impact <strong>of</strong> <strong>cowpea</strong> <strong>and</strong> sorghum <strong>research</strong> <strong>and</strong> extension<br />
<strong>in</strong> northern <strong>Cameroon</strong>. Michigan State University, International Development Work<strong>in</strong>g Paper<br />
No. 43. Michican State University, East Lans<strong>in</strong>g, MI, USA.<br />
Vijverberg, W.P. 1991. Pr<strong>of</strong>its from self-employment: the case <strong>of</strong> Côte d’Ivoire. World Development<br />
19(6): 683–696.<br />
Wolfson, J. 1990. Analysis <strong>of</strong> <strong>cowpea</strong> production <strong>and</strong> <strong>storage</strong> methodologies used by small farmers<br />
<strong>in</strong> northern Cameron. Purdue/IRA Cowpea Storage Project, January 1990.<br />
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