Post-harvest losses in Ethiopia: measures and associates

1. ETHIOPIAN DEVELOPMENT
RESEARCH INSTITUTE
Post-harvest losses in Ethiopia:
measures and associates
Fantu Bachewe, Bart Minten, Karl Pauw, and Alemayehu S. Taffesse
FAO-MAFAP and IFPRI-ESSP
International Livestock Research Institute
May 17, 2017
Addis Ababa, Ethiopia
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2. Presentation outline
The presentation has the following sections
• Context of study
• Data and methods
• Storage and associates of storage decisions
• Losses and associates of losses during storage
• Conclusions
• Note: All results presented herein are very preliminary.

3. 3
1. Context of study
• This study is a collaboration between UN-FAO and IFPRI-ESSP
• FAO is providing ongoing technical support to MoANR to develop a
post-harvest management strategy for grains
• Process includes:
• Drafting of strategy document (2016)
• Baseline analysis by Jimma University (2016)
• Develop results framework, investment plan, and M&E framework
(ongoing)
• FAO’s MAFAP program supports the process through
• Review of documents, and analyses & participation in validation events;
• Identified need for further evidence on extent of post-harvest losses
• IFPRI-ESSP (in collaboration & with financial support from FAO-
MAFAP) undertaking a household level assessment of post-harvest
losses (PHL) in grain crops

4. 4
1. Context of study…Contd.
• Jimma University adopted a case study approach to assess
quantitative and qualitative losses; also identified “critical loss
points” along supply chains
• Systematic and detailed but costly data collection of data,
• Sample includes only surplus producers (in 14 woredas of 4 regions),
• Results not nationally representative.
• Current study:
• Aimed at complementing/contributing to existing knowledge and
• Better inform the debate on PHL & related policy or investment responses

5. 5
2. Data and methods
Methods
• Descriptive analyses are used to study
• Proportion of households (HHs) that store grain crops and that
suffered losses during storage
• Quantity/periods of crops stored
• Estimate losses during storage
• Regional differences in storage and losses during storage
• We employ:
• Probit analysis to indicate associates of crop storing decisions
• Tobit analyses to study crop losses during storage

6. 6
2. Data and methods
Data
• Presentation includes results obtained from Feed the Future (FtF)
midline survey data
• Study will include AGP midline survey (8000 HHs, 2012/13 meher)
• The FtF midline survey
• Was conducted in May 2015 (pertains to 2014/15 meher season)
• Includes 8/4, 22/7, 29/13, & 20/13 woreds/zones in Tigray, Amhara,
Oromiya, & SNNP
• 6,691 HHs surveyed; analyses include 5,766 with relevant data (10%,
28.3%, 34.7%, & 27% of HHs in respective regions)
• Caveats of FtF midline survey data
• Data available only on crop losses during storage (PHL broader)
• Households’ own estimate of losses used, which may be biased;
• As a result, estimates on PHL need to be carefully interpreted

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2. Data and methods…Contd.
• Household total crop area averaged about 1.2 ha
• Area without 2, 2, and 1 zones in Tigray, Amhara & Oromiya about 1 ha
• 19.7% of total sample area covered with teff, maize 15.7%, wheat,
pulses, sorghum, and oilseeds for 12%, 11%, 9.3%, & 7.6%.
• Crop area around 0.4 ha in most crops except sorghum (0.65) and
teff (0.57) while oilseeds (0.9) area is high
• Oilseeds area dominated by Western Tigray, North Gondar, Horo Gudru W.
• Without these zones average oilseeds area 0.36 ha
• HHs cultivate 4 crops and this is similar across regions
• 3.7 in Oromiya, 3.8 in Tigray, and 4.2 in Amhara & SNNP
• 65%-75% of output consumed (slightly higher in sorghum & maize);
• Most oilseeds is sold (70%) & teff is the most commercialized cereal

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2. Data and methods…Contd.
Table 1. Summary of crop area, output, and crop utilization
Crop
HHs
cultivating
crop (%)
Crop
area (ha)
Yields
(Q/ha)
Percent of crop output utilized for
Consu
mption Sales Seed
Other
uses
Teff 40.1 0.57 7.3 65.6 25.1 7.3 2.0
Barely 23.0 0.40 12.9 75.0 10.7 12.6 1.7
Wheat 29.0 0.47 13.8 66.4 18.5 13.4 1.7
Maize 49.8 0.36 17.7 81.6 13.0 3.1 2.2
Sorghum 16.6 0.65 10.3 84.4 8.0 5.8 1.8
Pulses 34.5 0.37 9.5 66.5 22.4 9.6 1.5
Oil-seeds 9.7 0.90 4.7 22.9 69.7 6.3 1.1
All crops - 0.40 23.8 69.8 22.3 6.1 1.8

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3.1 Crop storage
Households storing crops
• 40%-50% of cereal growing HHs store crops and proportions are
lower in pulses (36.5%) and oilseeds (23%)
• Have higher average output in all crops relative to non-storing HHs
Figure 1. Households storing crops (%) and quantity stored (kgs)
0
10
20
30
40
50
60
0
200
400
600
800
Teff Barely Wheat Maize Sorghum Pulses Oil-seeds
HHsstoringcrop(%)
Quantity(kgs)
output (non-storing, kgs) Output average (kgs)
Output (storing, kgs) HHs that stored crop (%)

10. 3.1 Crop storage…Contd.
• HHs store almost all (>97%) of the harvest
• HHs store most crops for 3-6 months (44%) and 6-9 months (32%)
• Less than 10% store crops longer than 9 months (except in sorghum)
Table 2. Quantity (kgs) and number of months crops were stored
Crop
Stored
quantity
(kgs)
Percent of HHs stored crops for … months
0 to 3 >3 to 6 >6 to 9 >9 to 12
Teff 364 16.1 46.8 27.6 9.5
Barely 489 14.4 40.5 37.5 7.5
Wheat 800 15.8 44.4 31.4 8.4
Maize 799 18.4 53.3 22.6 5.7
Sorghum 554 7.4 34.6 47.7 10.3
Pulses 307 20.6 47.3 25.8 6.3
Oil-seeds 249 22.3 37.7 30.8 9.2

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3.1 Crop storage…Contd.
• Depending on food culture & agroecology, regions vary in proportion
of HHs growing crops and HH average output levels,
• Patterns in crop storage unique across regions
• Proportion of HHs storing all crops except oilseeds & maize higher in
Tigray, followed by Amhara & Oromiya
Figure 2. Percent of households storing crops
0
10
20
30
40
50
60
70
Teff Barely Wheat Maize Sorghum Pulses Oil-seeds
Tigray Amhara Oromiya SNNP

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3.2 Associates of crop storage
• We use a probit model to estimate a crop storage decision equation
• Works on PHL often state structural equations that associate crop
storage decision & losses during storage with variables representing
• Output levels and degree of commercialization in crop production
• Availability of improved storage technologies and crop protection
• Weather/climate in locality, esp. humidity and temperature
• e.g. Kaminski & Christiaensen (2014), Stathers et al. (2013), & Park (2006)
• However, except weather variables, proximate determinants often
correlated with unobserved HH factors that also affect storage & PHL
• Moreover, most variables used in literature unavailable in our data
• Thus, we follow literature in estimating reduced form equations that
also enable a more causal interpretation of results

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3.2 Associates of crop storage…Contd.
• The decision to store crops positively associated with:
• HH size (higher consumption needs, availability of labor);
• Storage likely in HHs with female, younger, and more educated heads
• Seasonal price gap (opportunity cost of not storing higher) and
• Number of months between harvest & beginning of next season (non-
linear)
• Crop storage negatively associated with
• HH wealth (can afford purchasing food latter/less subsistence),
• Proximity to urban centers (more integrated with market/access to
food market), and
• Long-run average annual humidity in area (higher humidity may lead to
crop rotting and pest infestation).

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3.2 Associates of crop storage…Contd.
Table 3. Average marginal effects of decision to store equation (probit)
Variables Aver. Marg. Eff. SE
HH head female (=1 if yes) 0.082*** 0.015
Age of HH head -0.001** 0.000
Education (literate, primary incomplete) 0.021* 0.012
Education (literate, primary complete) 0.048*** 0.015
HH size 0.011*** 0.002
HH wealth index -0.042*** 0.008
Seasonal producer price gap 0.025*** 0.005
Distance of town near village 0.003*** 0.001
Distance of market near village -0.0003 0.001
Average annual temperature -0.003 0.003
Average annual relative humidity -0.021*** 0.004
Months between harvest and next season 0.189*** 0.038
Months b/n harvest and next season squared -0.008*** 0.002
Zonal and crop dummies Yes
Chi2 1,884
Probability of Chi2 0.00
Number of observations 13,289

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4.1 Crop losses during storage
• A large proportion (60%-84%) of HHs that stored grain cops did not
suffer losses
• Among HHs that actually suffered losses during storage
• Highest proportion reported losses of only 1-10% of quantity stored
• Next higher proportion reported highest losses (90%-100%) in most crops
Table 4. Proportion of households that reported crop damages
Crop No damage 1%-10% 11%-20% 21%-90% 91%-100%
Teff 77.1 17.4 1.0 0.9 3.5
Barely 76.7 14.3 1.9 1.7 5.4
Wheat 71.8 18.7 1.7 2.9 5.0
Maize 62.5 23.4 6.7 5.6 1.8
Sorghum 64.8 22.9 5.8 5.2 1.4
Pulses 69.2 19.9 3.2 3.6 4.1
Oil-seeds 83.8 9.2 0.8 1.5 4.6

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4.1 Crop losses…Contd.
• Losses during storage averaged: 5% in teff, sorghum, & oilseeds; 6%
in barley & maize; and 7% in wheat & pulses
Figure 3. Crop losses during storage
0
10
20
30
40
50
0
2
4
6
8
10
Teff Barely Wheat Maize Sorghum Pulses Oil-seeds
Lossesduringstorage(kgs)
Lossesduringstorage(%)
kgs Percent

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4.1 Crop losses…Contd.
• Proportions similar to other SSA countries (Tanzania and Uganda) and
slightly higher than Malawi (Kaminski & Christiaensen, 2014)
• Lower than FAO (2011) on-farm handling and storage PHL estimate (8%)
• Averaged across all HHs (including non-storing) losses are at least half
the proportion when only storing HHs are considered
Figure 4. Crop losses during storage, all households
0
10
20
30
0
2
4
6
Teff Barely Wheat Maize Sorghum Pulses Oil-seeds
Lossesduringstorage(kgs)
Lossesduringstorage(%)
kgs Percent

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4.1 Crop losses…Contd.
• Losses mostly increase across months crops were stored
• HHs enquired to assign grades for intensity of damages sustained
• Grades assigned appear consistent with percent of crop lost during storage
Table 5. Storage losses by months stored & intensity of damage
Crop
Losses by number of months stored (%) Losses by intensity of damage (%)
0 to 3 >3 to 6 >6 to 9 >9 to 12 Minor Medium Major
Teff 4.9 2.4 5.3 15.8 8.0 25.0 90.5
Barely 7.2 8.5 5.1 7.1 10.2 23.6 85.6
Wheat 10.9 6.9 5.3 7.8 8.5 35.0 88.0
Maize 6.5 6.2 5.9 6.5 9.1 25.5 75.0
Sorghum 5.5 6.0 3.9 5.9 8.2 21.2 74.0
Pulses 7.7 7.6 3.7 10.8 9.3 26.4 86.3
Oil-seeds 7.1 0.5 4.3 24.6 5.0 21.7 95.0

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4.2 Associates of losses during storage
• Given argument made earlier reduced form PHL equation estimated
• Percent of crop lost during storage negatively associated with:
• HH size (higher labor availability/a food need) but education has a wrong sign
• Seasonal price gap (opportunity cost of losses higher)
• Length of period between harvest and beginning of next season
• Temperature during post-harvest season, which reduces moisture in crops
• Percent of crop lost during storage positively associated with:
• Wealth (lower care) and with proximity to urban centers (less subsistence);
• Humidity during post-harvest period
• Most results consistent with what was expected
• Storage and crop loss equations estimated simultaneously using
Heckman’s sample selection method (given losses are unobservable
for those that did not store)
• Results similar (and qualitatively same) to those discussed so far.

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4.2 Associates of losses…Contd.
Table 6. Tobit model estimates of crop damage equation
Variables (Dep. Var.: percent of crop damaged) Coeff. SE
HH head female (=1 if yes) -2.379 1.957
Age of HH head -0.041 0.060
Education (literate, primary incomplete) 5.833*** 2.174
Education (literate, primary complete) -2.532 2.668
HH size -1.523*** 0.440
HH wealth index 5.230** 2.043
Seasonal producer price gap -3.390** 1.627
Distance of town near village -0.202** 0.081
Distance of market near village -0.054 0.118
Average annual temperature during storage season -1.108** 0.563
Average relative humidity during storage season 1.344*** 0.398
Months between harvest and next season -26.30*** 6.744
Months b/n harvest and next season squared 1.293*** 0.327
Constant -175.7*** 42.05
Zonal and crop dummies Yes
Chi2 1,884
Number of observations 5,629

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5. Summary
• Less than half HHs that grow grains store crops
• Storing less frequent in more commercialized oilseeds
• Most (76%) HHs store crop for 3 to 6 months
• Storing more frequent in Tigray followed by Amhara
• A large proportion of HHs (over 60%) did not suffer storage losses
• Out of that suffered losses higher proportion reported lower losses
• Losses during storage estimated between 5% & 7% of stored output
• Factors associated positively with storing grain (HH size, seasonal
price gap, and number of months b/n harvest and next season) are
negatively (consistently) associated with losses during storage and
the reverse is true for HH wealth and proximity to urban centers,
• Caveat: Further investigation/purposefully collected data needed to
understand divergence between the proportion of HHs that
consume a large proportion of the output but state not storing crop:
• Out of those that consumed 100%/>=75% only 31%/40% stored crops

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Comments welcome
Thank you