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VOUCHERS VERSUS GRANTS
OF INPUTS: EVIDENCE FROM MALAWI'S STARTER PACK PROGRAM
Amy E. Gough, Christina H. Gladwin, and Peter E. Hildebrand
ABSTRACT: The majority
of Malawi’s smallholders use low purchased-input technologies
and as a result, produce low yields; 40 to 60 percent of rural
households face chronic food insecurity for two to five months
every year. These households are therefore in need of a program
to increase their productivity and improve their food security.
Such a program, entitled the “starter pack program,”
was initiated in 1998/99 by Malawi’s Ministry of Agriculture
in collaboration with donor agencies. The program aimed
to distribute “starter packs” to all farming households,
containing small packs of hybrid maize seed, fertilizer, and
either groundnuts or soybeans. The 1999 starter pack distribution
also included a pilot voucher project that distributed two different
types of vouchers, in a test to see whether the vouchers received
by some of the farmers were more effective than the packs received
by other farmers. The purpose of this paper is to evaluate that
test. We examine the differences between the three distribution
systems of the starter pack, starter pack voucher, and flexi
voucher, in order to determine which is the more effective tool
for improving food security among Malawian smallholder farmers.
We also determine if the impacts depend on particular household
characteristics, including gender and marital status of the
household head.
Editor's
Note
INTRODUCTION
Within the small African country of Malawi, agriculture
provides employment for nearly 90% of all households, accounts
for 40% of the GDP, and generates 77% of the revenue from
Malawi's exports.
[1]
The Ministry of Agriculture estimates that 2,786,576 households
are farming families.
[2]
The majority use low purchased-input technologies and as a
result, produce low yields and experience food insecurity
chronically, i.e., before the April harvest every year.
In southern Malawi, 40 to 60 percent of rural households face
chronic food insecurity for two to five months every year. [3] These households are therefore
in need of a program with the potential to increase their
productivity and improve their food security.
In both the 1998/1999 and 1999/2000 planting
seasons, such a program -- entitled the “starter pack
program” -- was initiated by the Ministry of Agriculture
in collaboration with numerous international donor agencies.
The program aimed to distribute “starter packs”
to all farming households, containing small packs of hybrid
maize seed, fertilizer, and either groundnuts or soybeans.
The packs were intended to allow smallholders to plant 0.1
hectare of land with modern yield-increasing inputs including
fertilizer. Additionally, the 1999 starter pack distribution
included a pilot voucher project that distributed two different
types of vouchers in a test to see whether a voucher distribution
system was more effective than distribution of a bulky package
of free inputs, and if so, which kind of voucher was more
effective.
This paper aims to evaluate this test, and examine
the differences between the three distribution systems of
the starter pack, starter pack voucher, and flexi voucher,
in order to determine which is the more effective tool for
improving food security among Malawian smallholder farmers.
We also analyze how the three alternative grant distribution
systems impact rural households, and see if the impacts depend
on particular household characteristics, including gender
and marital status of the household head. A priori,
we expect grants of starter packs to benefit female headed
households (FHH) more than male headed households (MHH), because
proportionately more FHHs are found in the poorest 40 percent
of Malawi’s population and are therefore more likely
to be chronically food insecure. [4]
THE CURRENT PROBLEM OF FOOD INSECURITY IN MALAWI
Malawi is chronically food insecure, according to
criteria adopted by the Food and Agricultural Organization
of the United Nations (FAO). [5] They
consider a country or region is food secure if “all
human beings at all times have physical and economic access
to the basic foods they need.”
[6]
Clearly, Malawi does not meet these criteria. [7]
The problem of chronic food insecurity in Malawi is
a result of numerous recent shocks and stresses to the livelihood
systems of Malawi’s rural smallholders. Shocks
include severe droughts in 1991 and 1993 followed by the collapse
of the credit system in 1994 and several debilitating devaluations
of the Malawi Kwacha (MK). [8] Compounding these shocks
are more routine but persistent stressors, which include annual
population growth rates of 2.5 to 3 percent, increasing fertilizer
prices, and as a result, depleted soils and low yields per
hectare. These factors, along with social considerations
such as the high incidence of HIV/AIDS, changing patterns
in labor migration, and adaptations to the newly established
market structure, have pushed farmers away from the sole activity
of farming and towards secondary or tertiary nonfarm activities
to improve food security.
Devaluations of Local Currency
During the 1999/2000 starter pack and voucher distribution, the Malawi
Kwacha ranged from 38-48 per US $1.00. Agricultural
input prices increased so much that a ten-kilogram bag of
commonly planted Panner maize seed cost MK 595, a fifty-kilogram
bag of urea fertilizer cost MK 825, and a fifty-kilogram bag
of 23:21:0 +4s fertilizer cost MK 780. These increased
prices forced smallholders to either abandon fertilizer purchases
or drastically reduce them.
Increasing Population Density
Population pressures have reduced the amount of land
available to smallholders. With many households in the
southern region farming only 0.3 hectares or less, Malawi’s
most densely populated region has no land in natural fallow
systems, as does its neighbor, eastern Zambia. Maize
continuously cultivated on depleted soils with little to no
soil amendments are the norm. [9] As Uttaro also shows here, smallholder
farmers in areas close to urban centers such as Blantyre (in
southern region), Lilongwe (in central region), and Mzuzu
(in northern region) also face the problem of limited land
availability due to high population densities.
Collapse of the Credit System
During the 1980s Malawi was a model for providing
access to credit at low interest rates for African smallholders. [10]
In 1994, however, with the transition in leadership from the
near dictatorship of Dr. Kamuzu Banda to the multiparty system
of Dr. Bakili Muluzi, economic changes resulted in rising
default rates on credit repayments. During this time,
interest rates that were subsidized at ten percent became
unsubsidized at thirty to fifty percent. [11]
Fertilizer subsidies were additionally phased out
during the 1980s and early 1990s as part of structural adjustment
reforms. The removal of these subsidies, coupled with
rising world fertilizer prices, decreased the profitability
of fertilizing food crops. [12]
Fertilizer use has therefore dropped significantly since 1994. [13]
Decreasing Yields
Compounding these factors is the problem of consistently
decreasing yields of food and cash crops in the smallholder
sector, caused by diminishing soil fertility. Farmers
attribute the fall in the productivity of their land to the
increased cost of inorganic fertilizers. [14]
Coupled with their lack of access to credit for fertilizer,
smallholders have minimal opportunities to increase their
yields and intensify their agricultural production, contrary
to Smale’s optimistic claims that Malawi during the
1990s was on the verge of experiencing a “delayed Green
Revolution.” [15]
Faced with a crisis of chronic food insecurity, unheard
of during the Banda years, Malawian smallholders in the early
1990s sought governmental assistance through food for work
programs, welfare programs, and free input programs.
Food security analysts repeatedly called for “safety
net” programs. [16] Safety net programs function
under the assumption that sustainability of a livelihood system
depends upon increasing the resilience of the most marginal
and poorest quintile(s) of the population. Interestingly,
however, Malawi’s starter pack program, first implemented
in the 1998/1999 season and repeated in 1999/2000, was targeted
at all subsistence farmers and not only the most marginal.
Why?
THE STARTER PACK: A TOOL FOR HOUSEHOLD FOOD
SECURITY
The suggestion for the starter pack program was presented
in 1998 by Charles Mann, of Harvard Institute for International
Development (HIID), who stated that national food security
could be best achieved by distributing hybrid seed and fertilizer
to all Malawian farmers. [17] The
objectives of the starter pack distribution in 1999/2000 were:
“a) to assist in filling the food gap; b) to promote
crop diversification; and c) to promote the concept of soil
fertility improvement”. [18] With the intention of jump-starting
yields, the program distributed five kilograms of urea fertilizer,
ten kilograms of 23:21:0+4s fertilizer, two kilograms of groundnuts
or soybeans, and two kilograms of hybrid maize seed to smallholders.
In addition, the 1999/2000 starter pack program included a pilot project
designed to distribute up to 50,000 starter packs or other
household items utilizing existing private-sector retail outlets.
Selected households did not directly receive starter pack
input packages, rather vouchers redeemable at local retailers.
Forty-nine thousand of these vouchers were redeemable only
for starter packs. The remaining 1,000 “flexi
vouchers” could be redeemed for either a starter pack or goods valuing up to MK 450.00. [19]
Subject to availability, flexi vouchers could be redeemed
for soap, salt, oil, fertilizer (often limited in availability),
hybrid maize seed, agricultural tools, pots and pans, blankets,
lamps, or similar household items. Participating retail
outlets varied between the southern, central, and northern
regions. The purpose of the voucher pilot project was
to “test the capability of the national retail chains
to transport, store and distribute packs to recipients, and
to examine the various modalities of distribution”. [20]
At three selected test sites, the pilot project tested the
number of distributing outlets, timing of voucher distribution,
and transportation of starter packs to retail outlets.
The purpose of the flexi voucher was to test a third distribution
method, in this case utilizing previously available goods
instead of specially packaged and distributed starter packs.
RESEARCH METHODS AND OBJECTIVES
The primary purpose of this paper is to evaluate the differences in effectiveness
of the starter pack, starter pack voucher, and flexi voucher
as tools for improving food security among Malawian smallholder
farmers. We assess whether the vouchers received by
some of the farmers were more effective than the packs received
by other farmers; and if so, which kind of voucher was more
effective, starter pack voucher or flexi voucher.
If a particular type of starter pack input distribution method succeeds
in enhancing food security within particular households during
the years of distribution, it may hold potential as a safety
net program. Further, if households demonstrate increases
in productivity and/or discretionary cash in years following
actual distribution of starter pack inputs, that input
distribution method may also be a productivity-enhancing safety
net or “PES-net.” [21]
DATA COLLECTION
Detailed household information was collected from forty-seven households
nationwide, who were chosen based on three criteria of geographic
location, status as a recipient of starter pack inputs, and
gender and marital status of the head of household.
For example, 15 households were selected from the southern
region, 17 from the central region, and 15 from the northern
region. Households were also classified according to
the type of inputs received through distribution of the 1999/2000
starter pack. Households interviewed consisted of 14
households receiving inputs in the form of an assembled starter
pack; 9 households receiving a starter pack voucher; 12 households
receiving a flexi-voucher; and 12 households who, although
eligible, were unintentionally omitted from one of the above
programs. [22]
Households were also disaggregated by the gender of head of
household, to understand the relationship between gender and
marital status of the household head and the impact of the
starter pack program. Fifteen female-headed households
(FHHs), 20 men in male- headed households (MHHs), and 12 married
women in male-headed households (MFs) were therefore interviewed.
DATA ANALYSIS: ETHNOGRAPHIC LINEAR PROGRAMMING
To determine the potential of the starter pack, households
were simulated utilizing ethnographic linear programming. [23]
Linear programs are designed to reflect the reality of the
livelihood systems of each particular household, and can model
considerable individual variation in resource availability
and use. [24] The linear programming model,
constructed in Microsoft EXCEL, includes assumptions about
the labor, cash, and consumption requirements of the livelihood
system, as well as the cash and labor constraints of commonly
produced crops, and additional components of the livelihood
system such as off-farm employment and receipt of remittances.
The model evaluates options available to the individual household
and predicts the land, labor, and activity allocation most
optimal to maximize household discretionary cash income.
Households here are modeled for a time period of seven years,
first without any starter pack inputs and then after receiving
inputs through each of the three distribution methods.
Once the model accurately simulates the reality of
the household livelihood system, it is assumed that the model
can also make accurate predictions of activity distribution
upon introducing the starter pack or voucher inputs into the
system. Analysis of predictions can effectively function
as a tool to understand the potential benefit of vouchers
versus grants of starter packs, through observation of differences
in discretionary year-end cash and a household’s ability
to meet consumption requirements with the differential introduction
of vouchers versus starter packs into the system.
The models can also be used to categorize different kinds
of households into “recommendation domains” according
to shared characteristics. Particular household types,
such as female-headed households, may benefit differently
from male-headed households with a greater amount of land
or more access to credit, fertilizer, or off-farm employment.
ASSUMPTIONS UTILIZED IN THE LINEAR PROGRAM
The primary activity presented to households modeled in the linear program
was agricultural production. Predominant crops of local
maize, hybrid maize, groundnuts, beans, and tobacco were included
in the linear program. Households reporting access to
a small garden plot of land (dimba) were modeled with the
opportunity to plant a combination of vegetables and maize
there.
Famine Early Warning System (FEWS) data provided baseline yield figures.
FEWS nationwide yield figures for the 1999/2000 season were
organized by Extension Planning Area (EPA), the same category
used for distribution of starter pack and flexi vouchers.
Average yield data for EPAs containing interviewed households
were combined to create regional averages. With the
use of Benson’s data from the nationwide Fertilizer
Verification Trials of 1995/96, these averaged yield figures
were converted to reflect yields with varied amounts of fertilizer. [25]
The linear program model also included data on consumption needs of each
household. Food and Agriculture Organization (FAO) consumption
requirements for an adequate nutritional diet were utilized
and cross-referenced with maize consumption data as reported
by households during interviews. Suggested and reported
maize requirements were found to be similar, indicating the
validity of utilizing the FAO suggested requirements.
In making this comparison, a program entitled Furnishing Essential
Diets (FED) was utilized. [26] Each household members’
age, sex, and physical activity level was used in collaboration
with country specific averages for individual body weights
to calculate energy requirements in kilocalories. Data
collected during interviews were compared with the FED suggested
consumption requirements. The two sources were found
to be consistent with a correlation coefficient of 0.6540
and the use of FED was continued.
Using 1.0 to represent the total household kilocalorie requirements
suggested by FED, we assumed that 0.7 of caloric intake was
obtained from maize, 0.055 from beans, 0.02 from groundnuts,
0.034 from vegetables, and 0.191 from purchased items such
as oil. We assumed that maize consumption was obtained
through the locally prepared “nsima”, calculated
to contain 3168 kcals/kilogram (kg) or 12% less than the total
kilocalorie content found in one kg of maize, in order to
account for the portion lost during processing. [27] In addition, beans were assumed
to contain 3320 kcals/kg, groundnuts 5536 kcals/kg (unshelled),
and vegetables 350 kcals/kgs. Consumption requirements
were adjusted as household members aged over the seven-year
period.
The linear program provides predictions of the optimal scenarios for
each of the 47 households with the ultimate objective of maximizing
household discretionary cash income at the end of the year.
The program calculates the cost and income of available activities
and makes predictions of labor allocation, cropland distribution,
and involvement in off-farm income generating activities,
predicting that households will engage in those activities
generating the greatest discretionary cash income.
While simulating households through the linear program, the primary objective
remains maximizing household discretionary cash while meeting
consumption requirements during the seven-year time period
modeled. The linear program simulates maintainable household
activities, and does not provide opportunity for activities
such as thieving or decreased consumption. If these
activities are necessary in order to meet cash or consumption
requirements, as they commonly are for Malawian smallholders,
households are considered food insecure. Because of
this, many households in the linear program are unable to
meet the designated cash and consumption requirements.
LINEAR PROGRAM SCENARIOS
All forty-seven households are simulated according to seven different
linear program scenarios, each for a period of seven years.
First, households are modeled while receiving no starter pack
inputs. Next, households are modeled while receiving
a starter pack for only the first two of the seven years (scenario
2), then with a starter pack voucher for only the first two
of the seven years (scenario 3), and then with a flexi voucher
for only the first two of the seven years (scenario 4).
Finally, households are modeled while receiving a starter
pack for the first five of the seven years (scenario 5), a
starter pack voucher for the first five of the seven years
(scenario 6), and then a flexi voucher for the first five
of the seven years (scenario 7).
LINEAR
PROGRAM RESULTS: PREDICTIONS WITHOUT STARTER PACK INPUTS
Household simulations with the first linear program scenario are evaluated
here, and reveal the inability of most households to meet
cash and consumption requirements for the seven year time
period without any starter pack inputs. Results show
only 14 of the 47 modeled households are able to meet cash
and consumption requirements for the whole time period, implying
they are the only households with “sustainable livelihood
systems” over the seven-year time period. It is
assumed here that households have “sustainable livelihood
systems” as described in the sustainable livelihoods
(SL) literature if they can satisfy cash and consumption requirements
over the seven-year time period modeled. If not, if
the model has an infeasible solution for at least one of the
seven years modeled, this means the household cannot satisfy
both cash and consumption requirements with the livelihood
activities currently in the model. In this case, the
livelihood system of the household is considered “unsustainable.”
Linear programming models are thus used here to quantify the
ideas presented qualitatively in the sustainable livelihoods
(SL) literature. [28]
The remaining 33 households (70%) are unable to meet full cash and consumption
requirements. They are of particular interest as they
represent severely food insecure households and examples of
“unsustainable” livelihood systems. To determine
the severity of the cash or food deficit of the remaining
households, the stated cash and consumption requirements are
reduced incrementally. By doing this, four groups of
households are created:
Group One: Households
able to meet full consumption and cash requirements,
Group Two: Households
able to meet full consumption requirements and 50% of the
cash requirements,
Group Three: Households
able to meet 75% consumption requirements and 50% of the cash
requirements,
Group Four: Households
able to meet 66% consumption requirements and 50% of the cash
requirements, while exhibiting negative year-end cash values,
implying they are in debt. Allowing group-four households
to dip into negative numbers reveals the extent of their inability
to meet cash and consumption requirements and the size of
their debt.
Although there may be some data inaccuracies, the need to reduce cash
and consumption reflects the reality that many Malawian households
do not now meet their consumption requirements through “accepted”
livelihood activities, particularly in the pre-harvest season.
Realities for chronically food insecure households would expectedly
include begging, borrowing, or stealing.
DIFFERENCES BETWEEN THE FOUR GROUPS
Of the 47 modeled households, 17 (36%) are in group-four, representing
the most impoverished households. To characterize households
in group-four, this research looks for shared household characteristics
by considering three possible criteria; gender of the head
of household, geographic location, and available land.
A comparison of the gender characteristics in figure
1 shows that six of the 15 (40%) female-headed households
interviewed are in group-four, versus 11 of the 32 (34%) male-headed
households. Notably, of the total 15 female-headed households,
only two (13%) are in group-one, whereas 21 male-headed households
(38%) are in this group (figure 1). Results from scenario
1 thus show that more MHHs are in the richer group-one, while
more FHHs are in the poorer groups, unable to provide their
households with sustainable livelihoods without the starter
pack.

Results of evaluating geographic location in scenario 1 show that half
of those in the poorest group-four come from the region of
the greatest population density in Malawi, the southern region
(figure 4). In contrast, the greatest proportion (41.18%)
of households able to meet full requirements (group-one) live
in the central region where Malawi’s predominant cash
crop of tobacco is produced. Households in the southern
region are relatively worse off than northern households and
in turn central households. In terms of available land,
households in group-four have considerably less land than
those in groups one through three. Only three of the
18 households in group-four have more than two acres
of available land.
Potential
of the Starter Pack for Household Food Security
Next, households are modeled while receiving a starter
pack for only the first two of the seven years (scenario 2),
then with a starter pack voucher for only the first two of
the seven years (scenario 3), and then with a flexi voucher
for only the first two of the seven years (scenario 4).
Finally, households are modeled while receiving a starter
pack for the first five of the seven years (scenario 5), a
starter pack voucher for the first five of the seven years
(scenario 6), and then a flexi voucher for the first five
of the seven years (scenario 7). To analyze the impact
of the starter pack inputs on household food security, two
aspects are examined: changes in year-end discretionary
cash income earned by the household with the inputs or vouchers,
and changes in maize produced by the household.
Changes in Year-End Cash Income with the
Starter Pack
Overall results of introducing the starter pack via
the various distribution methods (starter pack, starter pack
voucher, and flexi voucher) are disappointing: a run of each
model in scenarios 2-7 shows that predicted increases in a
household’s discretionary cash income are less than
seven percent and thus not substantial (figure 2).
Whether or not the household receives the input grants for
two years or five years, out of a total seven years, makes
little difference to these results: there is practically no
increase in discretionary cash income over the control of
“no starter pack.” As shown by the flat
graphs in figure 2, household average annual cash of sample
households in Malawi’s central region does not increase
with starter pack inputs or vouchers.

However, the linear program predicts the greatest
discretionary cash increase when households receive flexi
vouchers (scenarios 4,7). Yet these results are also
not encouraging for the starter pack. In all cases,
the linear program predicts households redeem flexi vouchers
for goods (soap, salt, etc.) rather than get a starter pack
with the flexi voucher. Because the linear program considers
the retail outlet value of the flexi voucher as a direct cash
contribution to the household, redemption of flexi vouchers
for goods provides an immediate cash value of MK 900 and MK
2250 when receiving flexi vouchers for two and five-years,
respectively.
In scenarios 3 and 6, when households are provided
with a starter pack voucher, the linear program applies these
inputs directly to the household resource pool if it predicts
the household redeems the voucher for inputs. Households
can use or sell all or some of the inputs; e.g., they can
keep the hybrid maize seed, use the fertilizer, and sell the
legume seed. If households do not redeem the voucher,
it can be sold informally for a value reportedly less than
the value of selling the starter pack. The linear program
therefore assumes transaction costs when acquiring a starter
pack after receipt of a voucher.
Results show that households receiving starter pack
vouchers earn an average annual cash income slightly less
than those households receiving flexi vouchers and slightly
greater than those households receiving starter packs.
In scenario 6 with households receiving starter pack vouchers
for five years, the linear program in most cases predicts
households sell vouchers during the first two years and redeem
vouchers for starter packs during the remaining three years.
Reportedly, sales of vouchers provide the household with an
immediate cash value between MK100 and MK300. In these
cases, the cash benefit to households occurs primarily during
the first two years when vouchers are sold. In other
cases, particularly in the northern region, the model predicts
households redeem vouchers for starter packs in all years,
resulting in annual discretionary cash averages similar to
those exhibited with starter pack distribution in scenarios
2 and 5. [29]
Results show that distribution of assembled starter
packs (scenarios 2, 5) demonstrates the smallest comparative
increase in total year-end cash income with the grants program.
Similar to scenarios 3 and 6 with receipt of a starter pack
voucher, receipt of a starter pack in scenarios 2 and 5 does
not consistently add cash income to the household. In
some cases, the increase in household discretionary cash after
receiving five years of an assembled starter pack is less
than the cash increase after receiving only two years of flexi
vouchers. With the two-year value of flexi vouchers
equivalent to MK 900, the five-year starter pack value is
then less than MK 900, or MK180 annually. Some households
sell part of the pack, use only the fertilizer, and save the
rest. The increase in household cash income is thus quite
variable, depending on how the household utilizes the inputs
and whether or not it sells, plants, trades, or saves them.

These results do not paint a rosy picture of the benefits of the starter
pack program, at least in the way it was universally distributed
to all smallholder farms in Malawi in 1998 and1999.
Does the picture improve somewhat if we look only at the benefits
accruing to the poorest group-four, the group that Gladwin’s
introduction to these papers claim should have been the only
group targeted with a safety net program? Figures 3
and 4 show the results disaggregated by the household grouping
described above, where group-one is the richest group with
sustainable livelihood systems and group-four is the poorest
group with unsustainable livelihood systems. The disaggregated
results in figure 3 show households in group-four increase
their cash incomes by less than MK 1000 with receipt of the
starter pack, versus MK 2143 with the flexi voucher.
Of all the groups, group-four achieves the largest percentage
increase in household cash income after five years of starter
pack inputs, but this is a paultry 3.47% (figure 4).
This minimal increase is doubled to 6.5% with the flexi voucher.
Both increases in cash income, however, are small and do not
provide much support for the starter pack program in its present
form.

Change in Total Maize Production After Input Distribution
The potential of the starter pack program as an effective
formal safety net, however, may not be reflected in its ability
to increase household disposable cash income, but rather in
its ability to improve household food production, both during
the time period of free inputs and in subsequent years.
To determine this potential, we examine the increases in household
maize production over the seven-year time period, and then
aggregate household maize production over the 47 households
to get an estimate of aggregate maize production (for these
47 households). To compare pre- and post- starter pack
maize production, a six-year analysis is compiled from a combination
of scenarios 5-7 described above. The first year represents
results from the linear program model without starter pack
inputs, while years two through six represent results when
starter pack inputs are included as activities of the linear
program.
Graphs of aggregate maize production of the forty-seven
households in figures 5-7 indicate that the greatest total
maize production occurs when households receive starter pack
inputs (figure 5), and the smallest total maize production
occurs when households receive flexi vouchers (figure 7).
This increase in maize production reflects increases in hybrid,
not local, maize production.

With households receiving starter pack vouchers (figure 6), maize production
does not increase in the first two years due to the predictions
that households sell the vouchers for immediate cash.
In later years, where predictions indicate that voucher recipients
redeem vouchers for starter packs, an increase in maize production
is evident. The increase, however, is less than that
achieved when households receive an assembled starter pack
for the five-year period (figure 5).

With households receiving flexi vouchers (figure 7),
the model predicts many households redeem the voucher for
household goods available at retail outlets. Because
the model predicts these goods are comprised of non-agricultural
inputs, maize production increases minimally in this case.

DRAWING
CONCLUSIONS OF THE STARTER PACK: DEFINING APPROPRIATE
INPUTS
The purpose of this paper was to evaluate a test conducted by the government
of Malawi in 1999/00 to distribute free inputs to smallholder
farmers. With a sub-sample of selected farmers, government
tested the efficacy of distributing vouchers versus assembled
starter packs, to see whether the vouchers received by some
of the farmers were more effective than the assembled packs
received by other farmers. Using ethnographic linear
programming models simulating the livelihood systems of 47
Malawi households, we examined the differential impact of
the three distribution systems -- the starter pack, starter
pack voucher, and flexi voucher, in order to determine which
was the more effective tool for improving food security among
Malawian smallholder farmers.
Results showed the most economically enhancing tool
for smallholders, especially the poorest in group-four, were
flexi vouchers. The benefit of distributing flexi vouchers
was manifested through increased household cash income (averaging
MK 2143 in group-four) and not maize production. We
concluded this MK 2143 would purchase 450 kg of maize over
the five-year period, enough to feed a chronically food-insecure
family (with food requirements of 700 kg of maize per year)
for 7.7 months spread over the five-year time period, or 1.54
months per year. [30]
Unfortunately, this additional maize is probably not enough
to make a chronically food-insecure household in Malawi food-secure.
It is just too little in the Malawi situation where food-insecure
households now face hunger seasons of five to six months.
This discretionary cash increase is less than the
value of the vouchers, MK 2250, because of the labor or cash
necessary to redeem the voucher. Further, it is unlikely
that households would use all the additional cash for purchasing
maize for consumption. Because of the strong desire
among smallholders to produce their own maize, many households
would invest in agricultural inputs and some would purchase
household items. If this were the case, many households
might not reach the highest potential increase in discretionary
cash income.
We also tried to determine if the impacts depended on particular household
characteristics, including gender and marital status of the
household head. We concluded that because the majority
of sample female-headed households were in the poorest group-four
(figure 1), they would benefit relatively more than male-headed
households from receipt of starter packs or flexi vouchers.
In scenario 5 with five years of starter packs, the average discretionary
cash increase for group-four was only MK 868. Again,
if the increased discretionary cash income were used solely
for purchasing maize for consumption, a household would be
able to purchase three and a half bags of maize. This
175-kilogram increase, however, represents only thirty-eight
percent of the potential increase (450-kilograms) from flexi
vouchers. Yet households increased maize production
more after receiving starter packs and not flexi vouchers.
Adding the 200 kilogram increase in maize production exhibited
by these households, the potential maize increase of households
after starter pack inputs becomes roughly 375 kilograms –
still less than that occurring with flexi vouchers.
RECOMMENDATIONS
The actual cash or maize production increase that households experienced
after receiving five-years of starter pack or vouchers was
less than 8% in all cases. Yet even a minimal increase
could constitute a significant degree of improved food security
for the poorest households. The starter pack program,
however, may not be the most effective mechanism of providing
smallholders with a safety net. If a variation of the
starter pack program is to be continued as a mechanism for
improving food security for the poorest of the poor in Malawi,
suggestions for defining appropriate inputs include:
a) Distribution of flexi vouchers or a similar tool allowing
for household selection of goods;
b) Enhanced cooperation from retail outlets in order
to increase smallholders’ access to inorganic fertilizer;
c)
Utilization of local retail outlet goods for distribution
instead of distribution of prepackaged inputs in order to
increase availability of desired goods (e.g., fertilizer)
at retail outlets.
In conclusion, the starter pack distribution increased household discretionary
cash and maize production minimally. Most households
exhibited minimal increases in discretionary cash or total
maize production after receiving inputs for even a five-year
duration. Considering the massive cost of the program
and the extensive amounts of planning, labor, and cooperation
required, we recommend reducing the target population to group-four
(and group-three if funds are available) and distributing
inputs in a manner similar to that of flexi vouchers.
Providing the option to obtain either agricultural inputs
or goods with immediate cash value allows for the greatest
potential increase in household cash income. Assigning
inputs appropriate to the needs of the targeted households
can potentially reduce misuse of inputs (i.e. selling or trading)
and simplify the input distribution. While these changes
might result in minimal improvements in food security, they
do represent the comparatively greatest increase available
from starter pack inputs included in the 1999/2000 distribution.
Utilization of flexi vouchers holds potential benefit as a
productivity-enhancing tool if redemption procedures allow
smallholders – culturally, economically, and in a timely
manner – access to those resources deemed beneficial
to improving food security.
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NOTES
[1]
Sahn & Arulpragasam, 1991; Gladwin et al. 2001;
Uttaro in this special edition.
[2]
Malawi’s Ministry of Agriculture and Irrigation
(MoAI), July 2000.
[3]
Lele 1999; Gladwin et al., 2001.
[4]
Lele 1999; Gladwin et al. 1997; Gladwin et al. 2001.
[5]
Food and Agricultural Organization (FAO).
[6]
Thomson and Metz, 1997.
[7]
Kumwenda et al. 1996.
[9]
Kumwenda et al. 1996.
[12] Sahn & Arulpragasam, 1991.
[16] Mann, 1998; Devereux 1999; Gladwin et al. 1999.
[18] Clark, 2000. page ii.
[19] Longley et al. 1999. During the time of voucher redemption,
MK 450.00 was equivalent to approximately US $ 9.00.
[20] Killick, 2000. page 1-2.
[21] Devereux, 1999; Gladwin et al. 1999; Gladwin et al.
2001.
[22] Either because the smallholder population in Malawi
is perhaps greater than 2.86 million, or because some households
received more than one input package, a number of households
received no starter pack inputs although they were eligible
for input receipt.
[23] Hildebrand et al. 2002.
[24] Hildebrand & Poey 1985.
[27] Ranhotra, 1985; from Penderson, 1989.
[28] Conway and Chambers 1992; Scoones 1998.
[29] Minimal differences between starter pack and starter
pack voucher annual discretionary cash averages were due specifically
to differences in labor requirements for traveling to redeem
vouchers. In many cases, vouchers required more time
due to the need to both obtain the voucher and travel to the
retail outlet to redeem the voucher. However, the organization
of local distributors and transport equipment created much
variation in the amount of time required to obtain goods through
any method of distribution.
[30] Gladwin et al. 2001: Table 1, p. 182.
Reference Style: The following is the suggested format for referencing this article:
Gough, Amy E. , Christina H. Gladwin, and Peter E. Hildebrand.
"Vouchers Versus Grants of Inputs: Evidence From Malawi's
Starter Pack Program." African Studies Quarterly 6,
no.1: [online] URL: http://web.africa.ufl.edu/asq/v6/v6i1a8.htm
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