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Food
crisis in Zimbabwe: 2.2 million at risk. But where do the figures
come from, and what do they mean
Ian Scoones,
Zimbabwe Land
September 16, 2013
View this article
on the Zimbabwe Land website
The newspapers
have been full of commentary on a looming food crisis in Zimbabwe.
This has followed from the World Food Programme’s press
release that 2.2 million people will be in need of food aid
in the coming months. The Commercial Farmers Union has called it
a ‘man-made crisis’, the direct result of the ‘chaotic’
land reform, and a decade of inappropriate policies.
I wanted to
find out a bit more about where the 2.2 million figure came from.
It’s a big number, and would mean a lot of food imports, way
beyond the means of the Finance ministry. After a bit of digging
I eventually found the figure, buried on page 122 of the ZimVac
(Zimbabwe Vulnerability Assessment Committee) livelihood assessment
draft report for 2013.
Each year ZimVac,
a coalition of NGOs, researchers and government agencies, undertake
a major rural livelihood assessment, based on a sample of over 10,000
households across the country. The sample is drawn according to
the latest ZIMSTAT ‘master sampling frame’, and the
resulting data is aimed to be representative of the country as a
whole. It’s an excellent and important initiative, but it
has its deficiencies, as those involved readily admit.
The process
for deciding the headline figure is complex. It involves assessing
for each household all the cereal production, and then adding in
income from employment, remittances, livestock sales, and other
sources of income that could be used to buy food (p. 120). Assumptions
on prices and market availability are used to translate income into
food and in turn energy (p.121). The food security assessment is
based on the household’s potential access to enough food from
all sources, including purchases, to give each member a minimum
of 2100 kilocalories per day in the consumption period 1 April 2013
to 31 March 2014 (p. 119). The total number in food deficit figure
is then calculated as a sum of all of those experiencing any negative
balance in the accounting period.
It’s a
complicated procedure with lots of steps and plenty of assumptions.
What the headline figure doesn’t indicate – although
the report does, and the background documents for the ZimVac surveys
over the years are quite transparent about this – is that
the big number includes many people who may have a projected deficit
for actually a very short period. Indeed, at the time of the survey
in May 2013, over 80% of households surveyed had no hunger problems
with only a very small proportion recording ‘severe hunger’
(p. 115). The report shows that there is a progression of food insecurity,
with a peak of 2.2m people expected in January to March 2014 (p.124).
31% of the total (683,000 people) move into food deficit only in
this crunch period before the next harvest; and some of whom may
in fact be food insecure for only a very few days.
The 2.2 million
figure is of course a good flag-waving number for the WFP to raise
funds, and for the CFU to bash the government for the land reform
(and even President Mugabe is now joining the critique of the ‘new
farmers’), but the actual implications are more complex. Here
are five reasons why we need to be cautious about the figures.
- First, there’s
geography: as the report shows the problems are concentrated in
the dry south of the country which experienced the worst season
in terms of rainfall and its distribution (p.125-6).
- Second, there
is almost certainly (as ever in surveys) an underreporting of
income, and so purchasing power. Since in drought years, market
purchases are essential for food entitlements, this is rather
crucial.
- Third, the
assessment model allows for only limited sales of livestock to
compensate for food deficits (households are assumed to retain
a minimum of 5 goats and 3 cattle). Yet livestock is precisely
the asset in the drier parts of the country that are used in times
of drought to exchange for grain, and distress sales are common,
and important for food security.
- Fourth, remittances
are especially important in drought-prone areas, yet the figures
used in the model for this year are based on recall of last year’s
receipts. Last year was of course a relatively good year for rural
production, and so remittance flows inevitably dropped. But this
year, you can be sure, they will increase in response to the shortfalls.
For perfectly good reasons, the model does not account for this,
but it’s another reason why we can expect things to be not
as bad as predicted.
- Finally,
the assessment does not include early cropping, for example of
green maize which is often important in that crunch period before
the ‘proper’ harvest.
For all these
reasons and more, we should be cautious about the headline statistics,
and understand in more detail what happens to whom and where.
One of the most
striking figures in the report is the prediction that 98% of rural
households nationally will hit a food deficit by next March if only
cereal production and stocks were included (p. 123). Of course this
includes those with no food production to speak of, such as farm
workers and other rurally-based non-farm households. But even discounting
this group, this is striking, and does suggest a problem in agricultural
production, as Charles Taffs of the CFU indicates. However, again
we must be cautious in jumping to conclusions.
One big concern
I have with recent national surveys is that they have been sampling
according to old sample frames set before the land reform. This
was the case for the 2011 PICES (Poverty, Income, Consumption and
Expenditure Survey) study and the 2010-11 Demographic and Health
Survey, both using the 2002 census sample frame. I have been assured
that the ZimVac survey for 2013 used an updated sample, with ‘enumeration
areas’ allocated proportional to population distribution derived
from the 2012 census. If so, this would have included the significant
populations, especially in A1 areas, who are at least according
to our data from Masvingo producing more and doing better than their
counterparts in the communal areas, where most the earlier rural
samples are drawn from. And in our study areas on A1 sites we see
between half and two-thirds of the households producing sufficient
cereals for the year – not just 2%,
Following the
2012 census, ZIMSTAT is revising the national ‘master sample
frame’, and hopefully from now on national surveys will be
statistically more representative. Unfortunately it is still difficult
to stratify the data according to land use types, and so distinguish
between resettlement areas and others, so Taffs and co should probably
hold off on their outright dismissal of land reform on the back
of this data for now. As ever, it’s more complicated than
it first seems.
That said, last
season was unquestionably a worse one than experienced in the last
few years, including in Masvingo. It also hit some higher potential
areas hard, with a very unevenly spread rainfall. Despite improvements
since 2009, input supply was again erratic and untimely last year.
Also, maize area planted was again down, reflecting the shift from
food crops to tobacco in some areas, perhaps especially in those
food producing areas in the higher rainfall zones. This restructuring
of the crop system is directly driven by incentives – tobacco,
supported through contract arrangements, is a much more profitable
crop than maize, especially if marketed through the Grain Marketing
Board. Over the last decade or more we have seen switches to small
grains (although plantings were down this past year according to
ZimVac), but these are still a small percentage of total crop output,
and it remains maize that drives the food economy, although much
of this circulates outside the formal channels, and so is difficult
to capture in national statistics.
So what should
we make of all this? Certainly there is going to be a problem of
food deficits in the coming months. However, problems are going
to be concentrated in a certain time period, and outside a few areas
and for more vulnerable people, it’s not going to be as bad
as the headline figure and the media commentary perhaps suggests.
Imports will certainly be needed, and targeted food aid will be
important, but other coping strategies will also come into play
to offset the worst.
Indeed this
seems to have been the pattern over many years now. There is a ritualised
flurry of activity around this time of year, with the aid agencies
calling for funds to support food aid, and those critical of land
reform saying that this ‘proves’ that Zimbabwe has gone
for food producer to ‘basket case’. Yet by the end of
the season, the expected famine has not occurred and, although hardships
unquestionably are faced, the scale and depth of the problem is
not as expected. This can be explained due to both sampling and
non-sampling errors inherent in the standard surveys; but also significantly
because assessments have not got to grips with the new patterns
of production (particularly in A1 areas) and marketing (mostly informal).
This will require new, and better attuned, data collection techniques.
Unfortunately
too often the emergency, humanitarian aid and disaster relief momentum
overrides discussion of the developmental issues, and the scramble
for food aid (and all the associated politicking) diverts attention
and resources. As I have mentioned in this blog many times before,
rural development challenges are many. They include the need to
invest in irrigation to offset drought vulnerability, the importance
of investment and reforms to ensure timely supply of inputs, a pricing
and market policy to balance incentives between food and cash crops,
a livestock policy that ensures such assets are secure and available
in times of need, and, overall, more concerted support for the resettlement
areas to ensure that they can indeed supply the nation with food.
Next week, I
will continue this theme and look at the data on production and
imports over time in a bit more detail. Since 2000 there is little
doubt Zimbabwe is in a new era, and policy responses have to take
this into account.
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