focus of this paper is the reliability, or rather the lack of it, of
agricultural statistics in emerging markets. This subject is particularly
important given the importance of the agricultural sector in GDP in many of
these countries. The agricultural sector’s significance as a provider of income
and employment in both monitored and informal economies is also reflected in
the attention paid to it in the policies of national governments and the
concerns of multinational bodies like the World Bank. Much of the interest is
concerned with the need to raise levels of agricultural productivity, but in
order to monitor the success of policies aimed at this objective it is
necessary to be able to measure agricultural outputs and inputs as accurately
as possible. Unfortunately, the political economy of the process of the
creation and dissemination of agricultural datasets often results in published
data reflecting more the exigencies of national governments than underlying
problems can be illustrated by the recent experience of the use of fertilizer
subsidies in Malawi. The results from the most recent agricultural census,
published in 2010, indicate that the maize crop output for 2006/2007 was 2.1
million metric tonnes. This compares with the previously reported 3.4 million
metric tonnes, thus implying that the total output of the main food crop in
Malawi was only 60 percent of what was previously thought. This is a striking
discrepancy, but it begs the question of why were previous estimates of maize
output so high? Was it simply due to incompetence or lack of resources in the
relevant statistical agencies responsible for data collection or was it
something more insidious? The answer perhaps lies in the political use made by
statistics by governments to demonstrate the success of controversial policies
aimed at raising output and labour productivity in the agricultural sector such
as subsidising inputs.
paper dissects the recent Malawian experience on fertilizer subsidies, but it
is noted that measuring the success of agricultural policies becomes almost
impossible when there are political and economic incentives to distort reported
aggregate agricultural data. The unreliability of the data in many emerging
markets casts doubt on the reliability of premature assessments on the cost
effectiveness of interventionist policies.
agricultural inputs such as fertilizer, seeds or fuel are often justified
either as corrections of a ‘market failure’ or as a means of breaking out of
the ‘vicious circle of underdevelopment’ (Nurkse: 1953). The
argument is that there is a potential high return on investment in fertilizer,
but this potential is not met because of capital shortage. Low initial capital
thus results in underinvestment in agriculture. In turn, this may provide justification
for government intervention and/or official development assistance. Indeed, fertilizer
subsidies were an integral part of the state-led development push in the 1960s
and 1970s, but were then scaled down as part of a larger trend of cuts in state
spending during the structural adjustment programmes of the 1980s and 1990s.
Malawian government decided to break with the anti-subsidy consensus that had
emerged at the IMF and the World Bank by re-introducing fertilizer subsidies.
This move reignited the debate on the efficacy of such interventionist policies
in which there are two sides in the controversy. The two main protagonists
representing these sides are Jeffrey Sachs and those who support his ‘big push
approach’ and William Easterly and his supporters who are sceptical of
top–down, aid-financed development schemes. Sachs strongly supported the
Malawian government’s reintroduction of subsidies. Writing in the New York
Times, he applauded the country’s President Bingu wa Mutharika who “broke
old donor-led shibboleths by establishing new government programs to get
fertilizer and high-yield seeds to impoverished peasant farmers who could not
afford these inputs. Farm yields soared once nitrogen got back into the
depleted soils” (Sachs, 2010).
broader importance of the Malawian experiment and Mutharika’s policies in terms
of the debate on input subsidies is that they have seemingly succeeded in
changing the World Bank’s stance on the issue.
1997 World Bank Country Report for Malawi targeted the removal of input
subsidies. By contrast, in 2011 the Bank states on its website that it
“strongly supports Malawi’s efforts to improve smallholder production. The
national input subsidy has made an important contribution to this objective” (World
Bank web post). Easterly explains the change proposing
that the development debates on subsidies are re-occurring in a pendulum-like
fashion (Easterly 2009). However, such debates are not driven purely by policy
agendas and fashions; empirics and evidence are also important.
is widely acknowledged that the change from recurring famines to more recent
relative affluence is due to an increase in land yields which has been helped
by the increased use of subsidized agricultural inputs (Lea and Hanmer, 2009:
8). While the lack
of reliable evidence to monitor the optimal use of subsidies is a problem, for some
governments, the paucity of data provides an opportunity to ensure that the
evidence that does exist supports their policies! Statisticians are vulnerable
to this pressure because the data basis itself is weak and any data series
covering developing countries rests on questionable assumptions, especially
those regarding food production.
suggested solution to this problem has been the use of randomized trials, thus
countering what Banerjee calls “the resistance to knowledge” (2007: 16). The
issue of fertilizer subsidies has been subject to such randomized trials by
Duflo et al. (2008). Set in Kenya, the study conducted some
demonstration experiments in which treatment and control plots were randomly
selected. Unsurprisingly, it was found that “fertilizer, when used in
appropriate quantities, is highly profitable” (Duflo et al., 2008: 487).
However, well promoted, randomized laboratory-like studies reveal little
understanding of how the political dimensions of provision affect agricultural
production in the aggregate or how the returns to fertilizer are distributed.
aggregate output data provided by national statistics offices are constructions
that are subject to political influence. In this case in order to answer the
question: what do we know about the effects of state intervention in providing
agricultural inputs a central issue is how the political system will respond to
and manage a fertilizer subsidy programme. Studying these issues in
laboratory-like experiments ignores the political dimension. In Malawi President
Mutharika’s political success has been intimately linked to the perceived results
of his agricultural policies. The fertilizer subsidy programme was proposed as
part of his larger Malawi Economic Growth Strategy during the election campaign
in 2004 and it is thought that this contributed significantly to his electoral
victory. The agricultural focus of the implemented development agenda targeted
smallholders generating broad support among the electorate (Cherwa et al.,
2006). Mutharika was subsequently re-elected to the Presidency in 2009,
obtaining 66 percent of the popular vote.
voting figures show the psephological evidence demonstrating the
political importance of the government’s agricultural policies, but the
available evidence on the economic impact of the subsidies is conflicting. Dorward
and Chirwa (2011: 237) explain the scale of the
involved in 2008/9 the selection from over 2.5 million farm households of more
than 1.5 million fertiliser coupon beneficiaries, the printing and distribution
of 5.9 million coupons, and purchase and distribution of over 3.4 million bags
of fertiliser. All of this was done to tight deadlines, to widely dispersed
farmers across the country (some in poorly accessible areas), with fraud and
theft a major temptation and threat (the value of all subsidised commodities
was approximately US$220 million, and of each fertiliser coupon was greater
than 10% of annual household income for more than 40% of the population).
authors estimate that the programme accounted for about 6, 8, 9 and 16 percent
of the national budget in 2005/6, 2006/7, 2007/8, 2008/9 respectively. In turn,
direct donor support for the programme was 9, 7 and 38 US$ million, which
accounted for 9, 10 and 14 percent of the total financing for the programme.
The allocation of national resources to the fertilizer subsidy programme were
significant, therefore, and totalled 4.6 percent of GDP in 2008/2009, or
approximately one-third of the aid inflows (Lea and Hanmer, 2009).
impressive growth data reported from Malawi, and re-reported in the New York
Times, following the re-introduction of the fertilizer subsidies was based
on crop data collected by the Ministry of Agriculture published in the Malawi
Annual Economic Report. These reported crop data were
based on the last census, in 1992/1993, and the annual projections of
agricultural production were built up by using yield and acreage observations
from agricultural extension officers (Malawi, 2009).
a National Census of Agriculture and Livestock funded by the Norwegian Agency
for Development Cooperation (NORAD) conducted by the National Statistical
Office (NSO) was undertaken in 2006/2007, but not released until 2010. The reporting
delay was an issue of concern (Malawi, 2009), but when it was finally
published, the results were not accepted by the Ministry of Agriculture.
The problem was that the census showed remarkably lower figures for the total
output of all crops (see Table), including the prestigious maize crop. Notably,
the maize figures reported are much closer to national food needs, while the
official figures in 2006/2007 would imply that either huge stockpiles of maize were
accumulating or that the average Malawian was consuming something in excess of
4,000 calories a day, compared to the commonly assumed figure of around 1,500
to 2,000 (personal communication IMF, 2010).
Census data and Ministry of Agriculture data compared,
2006/2007 crop estimates
(1) Figure cited in NACAL p xii; note that tables 3.8 and 3.9 show identical
figures for sweet potato and groundnuts, so there is an error somewhere.
(2) Figure cited in NACAL pg. xii for beans,
pulses, and groundnuts.
(3) Figure in MEPD report for pulses alone.
difference between the two reports stems not from average yield figures, but
from how the data are aggregated. The issue of disagreement is the number of
agricultural households, where the Ministry of Agriculture used a figure nearly
1 million higher than that used by the census. Statistical officers
diplomatically stated that this may have been due to the different definitions
of the household being employed (NSO, personal communication, 2010). Less
diplomatically, there were hints that some farmers might have been invented in
some cases in order to qualify for subsidies (NORAD, IMF personal
communication, 2010). There was an economic incentive for both farmers and
agricultural extension officers to ‘increase’ the numbers of households since
the vouchers themselves have a market value. There is some evidence and growing
concern that the vouchers are not reaching the right recipients, and that
officials and local authorities are able to profit from them (Africa Research
Institute, 2007; International Food Policy Research Institute, 2009).
is no direct evidence of tampering with the data, but the indications that it
happened are strong, as were the incentives to do so. Domestically, the
President and the Ministry desired good, consistent performance in order to
keep the electorate convinced of the continued success of the agricultural
development strategy. Externally, the government needed to be able to convince
donors that the fertilizer and seed programmes were working, to ensure that
political and financial support would be forthcoming. However, donors
have grown increasingly weary of the Mutharika government in recent years, and
following political suppression of political protest during the summer 2011,
donors, and central among them, the UK Department for International Development
(DfID) have suspended aid to Malawi (for a discussion of the events see Wroe
2012, 135). This may in turn mean less funding for a fertilizer programme,
which has undoubtedly been important for farmers’ livelihoods in Malawi, but
which aggregate success has been overstated because of its political importance.
situation of agricultural data in Malawi fits into an established pattern of
strong executive pressure on statistical authorities to get the particular data
that the leadership needs, where the motivation is not to monitor the economy,
but to affirm success (personal communication, Malawi Reserve Bank, NSO).
case of Malawi illustrates a general point that the state provision of
subsidies and inputs is embedded in political economies marked by weak evidence
across locations with varying political priorities. This provides ample room
for a negotiation of the agricultural data used in monitoring the success of
programmes. Pressures from above to ‘cheat’ are strong if politicians need to
justify their policies. However, the causation does not only run from top to
bottom. The very existence of subsidies, particularly in the form of per capita
vouchers, does provide an incentive for the agricultural sector to expand
spontaneously. It is in the interest of peasants and agricultural extension
officers to ‘increase’ the numbers of farming households, not only to please
superiors, but also because the vouchers themselves have a market value. The
example from Malawi discussed above shows how the re-introduction of
agricultural subsidies from 2005 onwards created a perpetual political demand
for high growth rates, which was spontaneously met by peasants who
oversubscribed to fertilizer vouchers.
The research for this paper has been funded
by the Social Sciences and Humanities Research Council of Canada (3-year
Standard Grant). The author would like to thank those who were willing to share
their information during the field research conducted in Malawi in 2010. While
writing the paper I got useful advice from Colin Poulton, Ronald J. Herring,
Andrew Dorward and Brian Cooksey. An earlier draft of this paper was presented
at the African Economic History Workshop held at the Graduate Institute in
Geneva, May 2011, and at the African Studies Association Meetings in Washington
DC, November 2010. The author would like to thank participants in these events
for helpful comments. The author is also thankful to John Harriss who read an
earlier version of this manuscript and provided very useful comments. The usual
Morton Jerven has recently published a book Poor Numbers:
how we are misled by African development statistics and
what to do about published by Cornell University Press.
The book is in the Cornell catalogue
and from Amazon
A podcast where he discusses his work on economic
statistics is also available
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