ERRATUM The Efficiency of Traditional and Hybrid Maize Production in Eastern Ethiopia

27 Pages·2006·0.16 MB·English

doi:10.1093/jae/ejl020
ERRATUM
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JOURNALOFAFRICAN ECONOMIES, ad
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The Efficiency of Traditional and Hybrid Maize Production s
in Eastern Ethiopia: An Extended Efficiency Decomposition ://ac
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Approach e
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Arega D. Alene and Rashid M. Hassan .ou
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The Publisher wishes to apologise to the authors of this paper, due rtic
to a typesetting error it was published with formatting problems le
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9
The Efficiency of Traditional and Hybrid Maize Production
in Eastern Ethiopia: An Extended Efficiency Decomposition
Approach
Arega D. Alenea and Rashid M. Hassanb
D
aInternational Institute of Tropical Agriculture, Ibadan, ow
n
Nigeria and lo
a
bUniversity of Pretoria, South Africa de
d
fro
m
h
ttp
The productive efficiencies of traditional and hybrid maize producers in s://a
eastern Ethiopia are derived using an efficiency decomposition technique c
a
d
that we extend to account for scale effects. The paper illustrates the e
m
sensitivity of the conventional approach to scale effects. The results ic
.o
revealed high inefficiency among both traditional and hybrid maize u
p
producers. High inefficiency among hybrid maize producers is consistent .co
m
withtheargumentthatfoodproductiongainsfromimprovedagricultural /ja
e
technologies have not been realised in poor countries like Ethiopia due /a
mainlytopoorsupportservices,includingextension,education,creditand rtic
le
input supply. -a
b
s
tra
c
t/1
5
/2
1. Introduction /i/7
8
8
8
A lot of empirical work on technical efficiency of farmers in the 5
4
developing world has been carried out following Schultz’s (1964) b
y
‘poor but efficient’ hypothesis. The hypothesis greatly influenced gu
e
development thinking at the time by showing that there were st o
actually few or no possibilities for increasing agricultural pro- n
1
duction with available resources other than expanding the 2 A
pScrhoduultczt’isownoproks,smibailnityyefmropnitrieicrasltshtruoduigehshnaevwetaescshenssoelodgtyh.eFtoelclohwniicnagl pril 20
1
efficiency of smallholder farmers and refuted the efficiency 9
hypothesis. However, Schultz’s (1964) work and the latter studies
carried out to validate the efficiency hypothesis have neither dealt
with the same aspect of efficiency nor provided a complete
representationofproductionefficiencyimpliedbyeconomictheory.
qq TThhee aauutthhoorr 22000055.. PPuubblliisshheedd bbyy OOxxffoorrdd UUnniivveerrssiittyy PPrreessss oonn bbeehhaallff ooff
the Centre for the Study of African Economies. All rights reserved.
For permissions, please email: [email protected]
Maize Production in Eastern Ethiopiaiii
A proper analysis of economic efficiency of farmers requires the
estimation of both technical and allocative efficiencies.
The modelling and estimation of both technical and allocative
efficiencyof agriculturalproductionis oftenmotivatedbytheneed
for a more complete representation of economic efficiency of
farmers implied by the economic theory of production. However,
D
while a considerable number of studies have dealt with technical o
w
efficiencyoffarmersindevelopingcountries,veryfewstudieshave n
lo
analysedbothtechnicalandallocativeefficiencies(e.g.,Bravo-Ureta ad
e
andRieger,1991;Bravo-UretaandEvenson,1994;Tayloretal.,1986; d
Sharma et al., 1999). The few studies that have analysed both from
technical and allocative efficiency of farmers employed the h
ttp
stochastic efficiency decomposition technique of Bravo-Ureta and s
Rieger (1991), which was an extension of the model introduced by ://ac
a
Kopp and Diewert (1982). Singh et al. (2000) noted, however, that de
m
due to scale biases arising from imposing an input-oriented ic
framework on the output-oriented stochastic production frontier .ou
p
results, the efficiency estimates derived from the conventional .c
o
m
efficiency decomposition technique either overestimate or under- /ja
estimate the true measures and are thus inconsistent. e
/a
Theobjectiveofthispaperwastoextendthetraditionalefficiency rtic
decompositiontechniquetoaccountfortheeffectsofreturnstoscale le-a
b
on farm-specific efficiency estimates. The proposed method is s
illustrated with applications to traditional and hybrid maize trac
production in eastern Ethiopia, a topic of greater significance t/15
/2
undertheunfolding newtechnologicaland economicenvironment /i/7
in Ethiopia. The rest of the paper is organised as follows. The next 8
8
8
section motivates the study on maize production efficiency. The 5
4
third section presents the conventional efficiency decomposition b
y
approach, the nature of the scale biases associated with the gu
e
conventional approach and the proposed approach to accounting st o
for scale effects. The fourth section presents the data and empirical n 1
methodology, while the fifth section presents and discusses the 2 A
p
results. The last section draws conclusions and implications. ril 2
0
1
9
2. Motivation for Efficiency Analysis of Maize Production in
Ethiopia
Many developing countries, including Ethiopia, have made
substantial investments in agricultural research and extension to
iv AregaD.Aleneand RashidM. Hassan
increaseagriculturalproductionthroughnewtechnologies.Despite
considerable technological change since the Green Revolution,
however, agricultural production in developing countries encoun-
ters substantial inefficiencies due to farmers’ high degree of
unfamiliarity with new technology, poor extension and education
services, and poor infrastructure, among others (Ali and Byerlee,
D
1991).Further,thereislimitedabilityand/orwillingnesstoachieve o
w
fulladjustmentofinputlevelsonthepartofproducersduetotheir n
lo
longadaptabilitytotraditionalpractices(i.e.,Schultz’s(1964)‘poor ad
e
but efficient’ hypothesis) and institutional and cultural constraints d
(Ghatak and Ingersent, 1984; Xu and Jeffrey, 1998). Since the from
introduction of new technologies requires intensive management h
ttp
andinformation, farmersin developingcountrieswithlowliteracy s
rates, poor extension services and inadequate physical infrastruc- ://ac
a
tureshavegreatdifficultyinadaptingtonewtechnologies,letalone de
m
exploitingtheirfullpotentials.Ifintroductionofnewtechnologiesis ic
aonce-and-for-allphenomenon,farmerscanadjustovertimetothis .ou
p
change. However, new technologies are being generated and .c
o
m
diffused continuously, and farmers therefore always have to cope /ja
with the disequilibrium created by the continuous changes in the e
/a
technological and economic conditions. rtic
The development strategy of the Ethiopian government focuses le-a
b
primarily on agricultural development and food security. The s
present agricultural development strategy evolved from the trac
economic reforms of the structural adjustment programmes, t/15
/2
which included removal of taxation on agriculture, market liberal- /i/7
isationanddevaluation(Mulat,1999).Thepresentstrategyrevolves 8
8
8
around productivity improvement of smallholder agriculture and 5
4
industrialisation based on utilisation of domestic raw materials b
y
with labour-intensive technology. The strategy also aims at gu
e
achieving food self-sufficiency through increased agricultural st o
productivity with improved technologies and liberalisation of the n 1
input and product markets to allow private sector participation, 2 A
p
deregulation of prices, and expansion of extension services (Mulat, ril 2
1999). Within the framework of the agricultural development-led 0
1
industrialisationpolicyoftheEthiopiangovernment,anewsystem 9
ofagriculturalextensionknownasparticipatorydemonstrationand
training extension system was launched in 1994–5 to demonstrate
tofarmersthebenefitsofapackageofinputs,notablybalancedand
higher rates of fertiliser, improved seeds, pesticides and better
Maize Production in Eastern Ethiopiav
cultural practices. More widespread adoption of high-yielding
varieties of major cereal crops, of which maize is the principal
component, by the majority of resource poor farmers has been
considered as a key strategy by the government.
Maize is the most important cereal grain in Ethiopia in terms of
production, area coverage, availability and utilisation of new
D
production technologies (Central Statistical Authority, 1997; o
w
Mulat, 1999). The maize sector has benefited from relatively n
lo
better technological change in terms of high-yielding varieties of ad
e
seeds, fertiliser, chemicals and post-harvest techniques. The first d
maize hybrid in the Ethiopian breeding programme was BH-140, from
which was released in 1988 from the Bako Research Center h
ttp
(Kebede, 1993). With subsequent efforts, BH-660 was also released s
in 1994 by the Bako Research Center and became one of the most ://ac
a
successful hybrid varieties. It has a wider adaptability, growing at de
m
altitudes ranging from 1650 to 2200m, with annual precipitation ic
of 1000–1500mm. It needs up to 170 days to mature and .ou
p
performs better under high rainfall, good soil conditions and .c
o
m
a high dose of fertiliser. Maize research has yet to develop /ja
high-yielding and drought-tolerant varieties for the drought- e
/a
prone farming zones. The yield potential of BH 660 is well over rtic
10 metric tons/ha. The recommended packages for hybrid maize le-a
b
technology are 100kg/ha DAP, 100kg/ha UREA and 25kg/ha s
seed, following appropriate cultural practices such as row trac
planting (Kebede, 1993). However, weak capacity in producing t/15
/2
and distributing the hybrid seeds and the high risk associated /i/7
with weather problems have been the major constraints to wider 8
8
8
adoption of BH 660. 5
4
New maize technologies require a new set of skills and b
y
g
knowledge, farmers’ integration into the input and product u
e
markets, and access to credit and extension services to fully st o
exploit their productivity-enhancing potentials. Mulat (1999) n 1
2
argued, for instance, that the potential to increase yield through A
p
improved management practices is not given due attention in ril 2
Ethiopia. The effort directed towards enhancing the technical 0
1
skill and management capacity of the farmers leaves much to be 9
desired. The research system has yet to develop location-specific
optimal fertiliser rates and management practices. The extension
system operates based on recommendations that show little
variation across different environments. Therefore, inefficiencies
vi AregaD.Aleneand RashidM. Hassan
and hence ‘forgone’ agricultural output under modern tech-
nology are hypothesised to be high in Ethiopia.
3. Analytical Framework
The production technology of a firm is represented by a stochastic
D
production frontier as follows (Aigner et al., 1977): o
w
n
Yi ¼ fðXi;bÞþvi2ui ð1Þ load
e
d
whereYimeasuresthequantityofoutputoftheithfirm,Xiisavector fro
oftheinputquantities,bisavectorofparameters,f(X;b)isasuitable m
i h
production function, vis are assumed to be independently and ttp
identicallydistributedNð0;s2vÞrandomerrors,independentofthe s://a
us, and the us are non-negative random variables, associated with c
i i a
d
technical inefficiency in production, and are assumed to be e
m
independently and identically distributed as half- ic
normal, u , jNð0;s2uÞj. The maximum likelihood estimation of .ou
p
equation (1) yields estimators for b and l where l¼su: .co
s m
v
The assumptions made on the statistical distributions of v and u, /ja
vmia2keuii.tTpecohsnsiibclaeletofficcaielncucyla(tTeEt)hoefcaonnindditiivoindaulamlfieramn iosfdueifignievdenasetih¼e e/article
rYaift,iobootfhthineoorbisgeinrvaeldunoiutstp,auntdYictaontbheegciovrernesapsondingfrontieroutput -abstra
c
Y fðx;bÞexpðv 2uÞ t/1
TEi ¼ Yfii ¼ fiðxi;bÞexpiðviÞ i ¼ expð2uiÞ: ð2Þ 5/2/i/7
8
8
The measurement offirm-specific technical efficiency thus requires 85
4
the estimation of the non-negative error u and the random normal b
i y
errortermv. g
i u
e
s
t o
n
3.1. The Conventional Efficiency Decomposition Methodology 1
2
A
p
Technical Efficiency ril 2
0
1
Thelevelofoutputofeachfirmadjustedforstatisticalnoiseandthe 9
observed input ratios are simultaneously solved to derive the
technicallyefficientinputquantities(Bravo-UretaandRieger,1991).
Firm-specific technical efficiencies are then derived as ratios
of weighted sums of technically efficient input quantities to
Maize Productionin Eastern Ethiopia vii
the weighted sums of observed (or actual) input quantities, the
weights being the respective input prices.
Actual output is first adjusted for statistical noise by subtracting
v from both sides of equation (1) as
i
p
Y ¼ Y 2v ¼ fðX;bÞ2u ð3Þ
i i i i i
D
p o
whereY istheithfirm’sobservedoutputadjustedforthestatistical w
i n
noise captured by v, which represents the random component of lo
overall deviations friom the frontier. Adjusted output Yp is used to ade
i d
derive the technically efficient input vector, Xt. fro
The technically efficient input vector Xt is derived by simul- m
i h
taneously solving equation (3) and the observed input ratios given ttp
s
as ://a
c
a
x d
x1i ¼ kiði . 1Þ ð4Þ emic.o
u
where k is equal to the observed ratio of the two inputs in the p
productiion of Yp. The technically efficient input vectors form the .com
i
basisforderivingthetechnical efficiency measuresbytakingratios /ja
e
of the vector norms of the efficient (W 0Xt) and observed (W 0X) /a
input quantities as i i i i rticle
-a
b
TEi ¼ WWii00XXtii ð5Þ stract/15
/2
where Wi represents the vector of input prices facing the ith firm. /i/7
8
For a fully technically efficient firm, technically efficient input 8
8
5
vectors and actual input vectors are equal and hence 4
b
y
W 0Xt ¼ W 0X gu
i i i i e
s
implying that it will have a technical efficiency of one. t on
1
2
A
p
Economic and Allocative Efficiencies ril 2
0
1
Firm-specific economic efficiencies are computed from a dual cost 9
functionthatisalgebraicallyderivedfromtheestimatedparameters
of the self-dual stochastic frontier production function (SFPF).
Specifically,economicallyefficient inputvectors arefirst derivedas
the partial derivatives of the dual frontier cost function (Kopp
viii Arega D.Alene and Rashid M. Hassan
and Diewert, 1982), and firm-specific economic efficiencies are
computed as ratios of the weighted sums of economically efficient
inputquantitiestotheweightedsumsofobservedinputquantities,
the weights again being the respective input prices.
Assumingthattheproductionfunctioninequation(1)isself-dual
(e.g.,Cobb–Douglas),thedualcostfrontierisderivedalgebraically
D
and written in a general form as o
w
n
C ¼ CðW ;Yp;aÞ ð6Þ loa
i i i d
e
d
whereCiistheminimumcostoftheithfirmassociatedwithoutput fro
Y andaisavectorofparameterstobeestimated.Theeconomically m
i h
efficient input vector for the ith firm, Xei, is derived by applying ttps
Shephard’s lemma and substituting the firm’s input prices and ://a
adjusted output level into the resulting system of input demand ca
d
equations em
ic
›Ci ¼ XeðW ;Yp;aÞ ð7Þ .oup
›Wn i i i .com
where n ¼ 1;2; …;N are inputs. The observed and economically /jae
0 /a
eWffi0cXiee,ntrecsopstesctoivfeplyro.dTuhcetisoencoofstthme ietahsufirrems aarreeeuqsueadl totoWcioXmipauntde rticle
i i -a
economic efficiency (EE) indices for the ith firm as b
s
tra
EE ¼ Wi0Xei : ð8Þ ct/15
i W0X /2
i i /i/7
8
8
Following Farrell (1957), the allocative efficiency (AE) index can 8
5
be derived from equations (7) and (8) as 4 b
y
g
W 0Xe ue
AEi ¼ Wi0Xit: ð9Þ st on
i i 1
2
A
p
ril 2
0
3.2. Limitations of the Conventional Approach 19
Biased Technical Efficiencies
Asnotedabove,technicalefficiencyintheconventionalapproachis
derivedbyfirstobtainingtechnicallyefficientinputquantitiesfrom
Maize Production in Eastern Ethiopiaix
a simultaneous solution of adjusted outputs (equation 3) and the
observed input ratios (equation 4). However, adjusted output is
obtained from an output orientation, whereas input ratios have an
inputorientation.Thisimpliesthattheapproachimposesaninput-
based framework on the output-based production function par-
ameters.Becauseoftheinfluenceofscale,thiswillbeproblematicif
D
theproductiontechnologydoesnotexhibitconstantreturnstoscale o
w
(CRTS). In the case of output-oriented approaches, the fact that the n
lo
same scale effect is embedded both in the observed and frontier ad
e
outputs (equation 2) means that scale effects will not influence the d
resulting efficiency measure. In the case of input-oriented from
approaches, the scale effect remains unaccounted for, as the output h
ttp
containing the scale information is not employed in the derivation s
of technical efficiency. Adopting an input orientation for efficiency ://ac
a
decomposition when original specifications have an output de
m
orientation thus requires that observed output be adjusted for ic
scale effects, in addition to the conventional adjustment for .ou
p
statistical noise. .c
o
m
To illustrate the nature of the technical efficiency bias under /ja
increasing returns to scale (IRTS) and decreasing returns to scale e
(DRTS),letuidenotethescaleeffectandYpip denoteobservedoutput /artic
adjusted for both statistical noise vi and scale effects ui. Further, let le-a
Xts and TEs denote, respectively, the scale-adjusted technically bs
efificient inpui t vectors and the corresponding technical efficiencies trac
ðmoXfotijtnYhopieÞto.inthiðcXfitisrjpmYrpi.opÞdU.uIntcdftoieolrlnoIwRsTteStch,hauntio.lo0gya,ndYpiY.pi .YpipYpip.imApslsiuems intghaat t/15/2/i/7888
5
W 0(cid:1)XtjYp(cid:2) W 0(cid:1)XtsjYpp(cid:2) 4 b
TE ¼ i i i . TEs ¼ i i i : ð10Þ y g
i W 0X i W 0X ue
i i i i st o
n
Equation (10) shows that conventional technical efficiencies over- 1
2
estimate the true technical efficiencies under IRTS. Under DRTS, A
p pp p
uYip,,0YappnidmYpili,esYthi a.tA(cid:1)sXsutjmYpi(cid:2)ng,a(cid:1)mXtosjnYoppt(cid:2)o.nIitcfporlolodwuscttihoanttechnology, ril 20
i i i i i i 1
9
W 0(cid:1)XtjYp(cid:2) W 0(cid:1)XtsjYpp(cid:2)
TE ¼ i i i , TEs ¼ i i i : ð11Þ
i 0 i 0
W X W X
i i i i
xAregaD. Alene andRashid M.Hassan
Equation (11) shows that conventional technical efficiencies under-
estimate the true technical efficiencies under DRTS.
Biased Economic Efficiencies
A scale bias is associated with output, and because economically
D
efficient input vectors are a function of output adjusted only for o
p w
statisticalnoise,Y ,economicefficiencyestimateswillalsobebiased n
i lo
unless the production technology exhibits CRTS. To illustrate the ad
e
natureoftheeconomicefficiencybiasunderIRTSandDRTS,letXes d
and EEsi denote, respectively, the scale-adjusted economicalliy from
efficient input vectors and the corresponding economic efficiencies h
p pp ttp
of the ith firm. Under IRTS, u . 0 and Y . Y . Assuming a s
ðmXoeijnYopitÞo.niðcXeispjYrpiopÞd.uItctfioollnowstetchhantiology, Ypi .i Ypip i implies that ://academ
W 0(cid:1)XejYp(cid:2) W 0(cid:1)XesjYpp(cid:2) ic.o
EEi ¼ iW 0Xi i . EEsi ¼ i W 0iX i : ð12Þ up.co
i i i i m
/ja
Equation (12) shows that conventional economic efficiencies over- e/a
estimate the true economic efficiencies under IRTS. Under DRTS, rtic
uYip,,0YappnidmYppili,esYthpipa.tA(cid:1)sXsuejmYpi(cid:2)ng,a(cid:1)mXeosjnYoptpo(cid:2).nIitcfporlolodwuscttihonattechnology, le-abs
i i i i i i tra
W 0(cid:1)XejYp(cid:2) W 0(cid:1)XesjYpp(cid:2) ct/1
EE ¼ i i i , EEs ¼ i i i : ð13Þ 5/2
i W 0X i W 0X /i/7
i i i i 8
8
8
Equation(13)showsthatconventionaleconomicefficienciesunder- 5
4
estimate the true economic efficiencies under DRTS. by
g
u
e
s
3.3. Accounting for Scale Effects t on
1
2
Accounting for scale effects is analogous to the traditional A
p
adjustment of observed output for statistical noise where vi is ril 2
subtracted from both sides of the frontier function 0
1
9
Y ¼ fðX;bÞþv 2u
i i i i
to yield