Cattle Prices in Ethiopia: Trends, quality premiums, and associates

1. Photo Credit Goes Here
Cattle Prices in Ethiopia: Trends, quality
premiums, and associates
Fantu Bachewe, Derek, Headey, and Bart Minten
Ethiopian Economics Association
15th International Conference on the Ethiopian Economy
20-22 July 2017, Addis Ababa

2. 1. Introduction
• Agriculture important contributor to rapid economic growth in
Ethiopia over last decade
o Livestock contributed little to the growth (crop/livestock=26.4/5.9)
• Considerable livestock, particularly cattle, production potential
Supply side:
• Large stock of cattle as well as other livestock species
• During 2006-2015 on average 80% rural HHs owned at least
one cattle (on average 4.4 heads)
Demand side:
• Beef largest source of animal-based protein & component of
total livestock expenditures (38% in rural & 56% in urban areas)

3. • Real expenditure and share in total food spending of animal
products increased by 4% & 7.4%, resp., during 2005-2011
• Rapid growth in value of live animal and meat export (21.5%)
over 2006-2015
• Proportion of cattle sold grew at 1.6% during period studied
However, the data also show productivity and marketed supply
mostly stagnated
• Meat per cattle stagnated & milk yields declined over 2004-2013
• Proportion of beef, milk, and milk products sold by farmers
declined or stagnated during 2008/09-2015/16 (CSA)
1. Introduction…Contd.

4. Objectives
• Study patterns and trends in real cattle prices over 2006–2015
• Focus on premiums paid for qualitative attributes and
associates of cattle prices,
Methodology
• Descriptive and Hedonic price formation analysis
Data:
1. Ethiopian Livestock Market Information System (ELMIS) data
covering Jan. 2006-Aug. 2015 and 8 regions (39 markets)
• Information on 4 cattle & shoat attributes along prices observed
2. CSA producer price data, and agricultural and manufacturing
output and input use data also used
1. Introduction…Contd.

5. Table 1—Real cattle prices, Jan 2006-Aug. 2015 (Dec. 2011 birr)
Cattle attributes
Age Sex Average
(by G-S)Immature Young Mature Female Male
Grade
Very thin 1,811 2,600 2,836 2,113 3,311 2,700
Thin 2,165 2,973 4,277 2,827 4,036 3,559
Moderate 2,257 3,588 5,851 3,550 5,243 4,587
Fat 2,599 4,639 8,382 4,678 7,799 6,789
Sex
Female 2,045 2,940 3,939 3,406
Male 2,354 4,041 6,860 5,363
Average (by age) 2,257 3,585 5,729 4,613
2. Patterns and trends in cattle prices

6. Quality premiums
• Comparisons should ideally consider all attributes
• Young, mature, & male cattle sold about 60% higher than
immature, young, & females, respectively
• Thin, moderate, & fat sold 32%, 29%, and 48% higher than
very thin, thin, and moderate, respectively.
o Generally, these price patterns held in all breeds.
• Price of Harar breed 37%, 87%, & 107% higher than mixed,
Danakil, & Afar breeds, which are ranked 2nd, 7th, & 8th in prices
• Harar breed has highest price in almost all age, sex, & grades
o Cattle production more commercialized/integrated with market in
Western and Eastern Hararghe
2. Patterns in cattle
prices…Contd.

7. Trends in prices and quality premiums
• Growth in real prices averaged 1.5% per year in overall sample
• Average price growth the highest for fat-immature-male (8.1%),
• Prices of thin-mature-male declined the fastest (-0.8%/year)
• Price gap of mature-female Vs. young-male decreased & that
of young-male Vs. young-female increased considerably (20%)
• Price gap of mature-male Vs. young-male/female declined
slightly & that of mature-male Vs. mature-female a/b the same
• Price growth generally higher for younger, esp. male, cattle
• Change in prices positive in all but 3 grade-age-sex groups
2. Trends in cattle
prices…Contd.

8. Figure 1—Quality premiums across age & sex (2006– 2015)
2. Trends in cattle
prices…Contd.
60 63 66
60
26
29 32
30
134
143 148
132
25 26
22 20
91
98 94
87
50 54 53 48
0
20
40
60
80
100
120
140
160
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Ox Vs cow Bull Vs heifer Ox Vs heifer
Cow Vs bull Ox Vs bull Cow Vs heifer

9. 3. Associates of cattle prices: Econometric model
• Implicit value of cattle attributes estimated using a Hedonic
price formation analysis
• Other factors directly and/or indirectly associated with prices
(through DD & SS) included in analyses
𝑃𝑖𝑗𝑡
𝜆
= 𝛼0 + ℎ=1
13
𝛼ℎ 𝐴𝑡𝑡𝑟ℎ,𝑖𝑗𝑡 + 𝑘=1
11
𝛽 𝑘 𝑋 𝑘𝑖𝑗𝑡
(𝜆)
+ 𝛽12,𝑖𝑗𝑡 𝐿𝑅𝑅𝐷 𝑅𝐹𝑗𝑡 +
𝛾1 𝐿𝐿𝑗 + 𝑗=2
39
𝛾𝑗 𝑧𝑗 + 𝑡=1
6
𝜃𝑡 𝑆𝑒𝑎𝑠𝑜𝑛 𝑡 + 𝑡=7
15
𝜃𝑡 𝑌𝑒𝑎𝑟𝑡 + 𝑒𝑖𝑗𝑡 (1)
where 𝑃𝑖𝑗𝑡
(𝜆)
≡
𝑃𝑖𝑗𝑡
𝜆
−1
𝜆
; 𝑋 𝑘𝑖𝑗𝑡
(𝜆)
≡
𝑋𝑖𝑗𝑘𝑡
𝜆
−1
𝜆
, and 𝑗 ∈ [1, . . . , 39], 𝑡 ∈
[1, . . , 101], & 𝑖 ∈ [1, … , 𝐼] indexes for markets , months, & cattle
• 𝑧𝑗, 𝑆𝑒𝑎𝑠𝑜𝑛 𝑡, & 𝐿𝐿𝑗 stand for zonal, season, & lowland dummies
• 𝑒𝑖𝑗𝑡 is a random error term with 𝑒𝑖𝑗𝑡~𝑁(0, 𝜎2)

10. 3. Associate of cattle prices:
estimation strategy
 Endogeneity
• Null hyp. that shoats’ price can be treated as exogenous rejected
Addressed in 3 ways: IV, NL system, & residual inclusion method
 Sample selection
• Prices known (unknown) for cattle sold (unsold/not in market)
• Decision to sale non-random → sample selection (SS) bias
SS addressed in two ways: 1) using Heckman’s SS model on data
that include cattle with unobserved prices & log-log version of (1)
2) by including in (1) inverse Mill’s ratio from Heckman SS analysis
 Stationarity tests → association can be taken as non-spurious
 Grange causality → relationships between dependent and all
explanatory variables more than just associations, excluding
shoats’ prices & cattle prices in Somalia

11. Price variations across cattle attributes and seasons
• Results consistent with what was expected/descriptive analysis
• Prices increase with body mass & age, and males sold higher
• Danakil & mixed breeds sold higher, Arsi & Boran sold lower,
Afar & Raya Azebo were no different from Zebu, benchmark,
• As expected, estimate of Harar breed dummy was the highest
• Lowland dummy is negative → prices lower in pastoral areas
• Prices higher in meher, during which fewer cattle brought for
sale (lower supply) and farmers’ purchases of cattle increases
(higher demand)
3. Associates of cattle prices: Results

12. Table 2 — Estimates of cattle attributes and season dummies
Variables Coeff. Chi2 Variables Coeff. Chi2
Cattle body mass Festival/season dummies
Thin 0.598*** 19.24 Meher 0.082** 6.081
Moderate 1.369*** 68.53 Ethiopian Christmas 0.130** 6.481
Fat 2.640*** 495.9 Orthodox Christian fasting -0.008*** 24.70
Age Fasika (Easter) 0.014** 6.483
Young 1.513*** 598.2 Eid Alfetir -0.002 0.55
Mature 2.844*** 436.5 Al Arafa -0.015** 6.471
Male 1.222*** 821.2
Breed (Zebu omitted) Lowland -0.507*** 17.90
Afar 0.103 0.783
Arsi -0.507*** 45.96 Lambda 0.170*** 17.86
Boran -0.279*** 15.15 Residuals of shoat price 0.674*** 102.8
Danakil 0.160** 4.806 Inverse Mill's ratio -2.369*** 30.32
Harar 0.600*** 85.18 Constant 4.019
Mixed 0.152*** 9.006 Log likelihood -103,261
Raya Azebo -0.038 0.257 Number of observations 12,077
3. Associates of cattle
prices: Results

13. Supply-side seasonality:
• Two of four short-term rainfall variables significant & positive,
indicating prices decline during periods of relatively low rainfall.
• Estimate of long-term rain shortfall can be taken as evidence of
lasting/negative effects of drought on pasture carrying capacity
Demand-side seasonality:
• Prices are lower during the Orthodox Christian fasting season
• Prices are higher during the one week period of Fasika and
Ethiopian Christmas holidays and, contrary to what we
expected, prices were lower during Al Arafa.
3. Associates of cattle
prices: Results

14. Sources of price change over time
• Prices positively affected by per capita income, w/c grew at 5.8%
o Effects would have been higher if services were included
o Demand for livestock products often increase with income
• Prices positively associated with prices of shoats’ (substitutes)
• Table 3. — Estimates of domestic and international prices
3. Associates of cattle
prices: Results
Variables Coefficient Chi2 Elasticity
Per capita income 0.241*** 73.13 0.227
Regional non-food consumer price index 0.548*** 20.27 0.285
Shoat price 0.062*** 9.992 0.047
Cattle and beef export price 0.210*** 23.27 0.090
Cattle price in Somalia 0.062*** 9.485 0.064
Value of grains/draft cattle 0.051*** 89.59 0.056
Animal transportation fare -0.118*** 24.64 -0.054

15. Cattle prices positively associated with:
• Non-food price index: indicating non-food inflation, w/c grew at
1.2%/month, among important contributors to cattle price increases
• Grains output/draft cattle: implying prices can be higher in
major grain producing areas due to low supply & higher demand
• Beef and live cattle export prices (+ decline in export prices):
imply export prices contributed to slower cattle price growth
• Somalia cattle prices (+ grew at 1.3%/month + associations
stronger at boundary markets): imply prices in two neighboring
countries linked in an important way and further study warranted
• Negative estimate of animal transportation fare implies prices
are relatively lower in remote areas, and decline in TR costs (at
6% per year) contributed for a slower growth in cattle prices
3. Associates of cattle
prices: Results

16. 5. Key findings and implications
• Domestic factors play prominent role than exports/export prices
• Some of the seasonality in cattle markets (e.g. fasting season) appear
unavoidable; however, it appears farmers can take advantage of the
spike in demand that precedes most holidays
• Demand for animal products increase with income → improving
productivity helps generate more income for farmers & stabilize prices
• Results show prices increase with cattle quality. This together with
o Shortage of supply & inferior quality major problems of value chain (Legese
et al., 2008) ↔ only 1% of cattle holdings fattened for sales (10% sold),
 Improving cattle quality an important avenue for increasing livestock
income

17. 5. Key findings and implications…Contd.
• Results show prices are lower in lowland areas, where
o Cattle holdings per household are higher &
o Farmers purchases of cattle are low (20% of total cattle sales)
The latter together with results showing that:
• Prices increase with productivity of cattle in grains production
o Farmers’ purchases higher (70%) in major grain producing regions
Alternative crop production technology that could free even one
of the animals will tremendously boost the number & quality of
cattle produced and marketed

18. Thank you for your comments