Ethiopian Development Research Institute(EDRI) and IFPRI Ethiopia Strategy Support Program 2 (IFPRI-ESSP2) Seminar Series April 15, 2009

1. Cereal Markets in Ethiopia: Policies and
Performances
Shahidur Rashid &
Asfaw Negassa
Prepared for the EDRI-IFPRI seminar
Addis Ababa, April 15, 2009

2. Outline
 Motivation
 Cereal sub-sector is dominant within agriculture
 Largest contributor to GDP
 Largest employer
 Heavy emphasis in the GoE’s growth strategies
 Conceptual framework
 Study findings
 Policies and infrastructural development
 Changes in structure
 Changes in performance
 Tentative conclusions

3. Conceptual framework
Market
Analysis
Public Policies Policies Directly
Indirectly Affecting
Affecting Structure Markets:
Markets:
For example,
For example, elimination of
investments in Conduct movement
infrastructure restrictions
Performance
Competitive Price
Page 3

4. Policy reviews
Review of Grain Marketing Policy Changes in Ethiopia:
Objectives and key Observations
Policy Regime Major Policy Key Observations
Objective(s)
Imperial Support and promote the Limited interventions and were not
Regime interests of few landlords effective
and urban consumers
Socialist Complete socialization of Heavy government intervention
Regime production and marketing which depressed the development
of private grain trade
The Current Price stabilization, Progresses have been made.
Regime promote private sector However, good intentions are
grain trade frustrated with ad hock nature of
policy interventions

5. Policy reviews: key lessons
 Ad hock nature of policy interventions
 No sufficient details in the design and implementations
 No sufficient resources assigned to implement the planned
policy interventions
 Policy not implemented or not effective
 Created uncertainty in the market which affects private sectors
optimal operational and investment decisions
 Eroded public confidence in governments’ intervention measures
 Grain marketing policies have been designed with
too many objectives, which are often conflicting
 For example, the EGTE has been expected to be commercially
profitable while at the same time to meet social objectives of price
stabilization under tight financial support from the government
 Price stabilization requires sufficient working capital and stocks –
adequate budgeting of policy interventions

6. Infrastructural developments
Trends in road lengths for different classes of roads, 1951
to 2003
20000
18000
16000
14000
Length of roads (Km)
12000
10000
8000
6000
4000
2000
0
1951
1963
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
Asphalt Gravel Rural

7. Infrastructural developments (cont.)
Warehouse_Nazereth
Improvements in Ethiopian road infrastructure and
accessibility, 1997 to 2005
Indicator 1997 2002 2005 Absolute change
from 1997 to 2005
Proportion of paved roads in good 17% 35% 54% 37(+)
condition
Proportion of unpaved roads in good 25% 30% 40% 15(+)
condition
Proportion of regional roads in good 21% 28% 33.6% 12.6(+)
condition
Road density: length/1000 sq. km. 24.1km 30.3km 33.6km 9.5(+)
Road density: Length/1000 0.46km 0.49km 0.51km 0.13(+)
inhabitants
Proportion of area more than 5 km 79% 75% 73% 6.0(-)
from all-weather road
Average distance to the road network 21.4km 17.0km 16km 5.4(-)

8. Infrastructural developments (cont.)
Trends in number of fixed telephone lines and apparatuses,
1988 to 2003
500
450
400
350
Number ('1000')
300
250
200
150
100
50
0
Lines Apparatuses

9. Infrastructural developments (cont.)
Trends in number of trucks of different
sizes, 1993 to 2004
50000.00
40000.00
Trends in number of trucks of
Number of trucks
30000.00 different sizes, 1993 to 2004
20000.00
10000.00
.00
Big Small all trucks

10. Infrastructural developments: key observations
Warehouse_Nazereth
 Significant improvements in
marketing infrastructure
 How these changes are affecting
grain market performances?

11. Review of organization and structure of markets
 Organization of Cereal Markets
 Traditional and Emerging Cereal
Marketing Channels
 Broad Changes in Cereal Market
Structure

12. Cereal value chain map involving traditional market channels
Smallholders State farms Commercial
farms
Assemblers
Wholesalers
(surplus) Coops
Brokers EGTE
Wholesalers Export
(deficit)
Food aid agencies/WFP
Processors
Retailers/ Ration Shop
Consumers

13. Cereal value chain map involving commodity exchange
Smallholders State Commercial
farms farms
Assemblers Coops EGTE
Wholesalers
(surplus)
Commodity exchange with brokers
Wholesalers
Exporters (deficit) Processors Food aid agencies
Retailers
Consumers

14. Structure (cont.)
Market Key actors Key functions Recent changes
level
Production Smallholders, Production of cereals Re-emergence of private
commercial farms, commercial farms
and state farms
Assembly Petty-traders, farmer Collection and Emerging cooperative marketing
traders, cooperatives bulking of cereals
Wholesale Large traders, Temporal and spatial •Emerging cooperative marketing
Ethiopian grain trade arbitrage services •Emergence of ECX
enterprise, •Emergence of Commodity
Cooperatives Warehouse System
Processing Small-scale, medium- Custom milling / New large-scale private entrants as
scale, and large-scale commercial flour opposed to state-dominated
flour mills mills, & processing sector under socialist
manufacturing regime
Retail Small traders, small- Sell cereals and flour Emergence of supermarkets
scale flour mills, mills to consumers in carrying locally processed flour
wholesale traders small quantities mills (mainly wheat) and imported
cereal products

15. Performance
 Price analyses (historical data)
 Market integration
 Seasonality
 Price variability
 Survey data analyses
 Transactions costs
 Trade margins

16. Performance: market integration concept
 Consider the following facts:
 In 1985, price of kg of teff was 7.7 Birr in Gojjam BUT 15.7
Birr in Wello
 In 1974, price of rice in the district of Rangpur in
Bangladesh (a deficit area) was almost three times the
prices in surplus and well developed districts
 What is common in these two cases?
 Both countries had famines: Ethiopia in 1984/5 and
Bangladesh in 1974.
 Hard hit famine areas lacked integration with the surplus
and well developed regions.
 In both countries there were restrictions on grain
movements

17. Performance: market integration review
Author (s) Commodities Geographic coverage & time Method of analysis Findings
periods
Dadi, L., A. Negassa, and S. Maize and Teff Bako area of Western Shoa and Price correlation analysis Results indicate that private sector marketing of maize and teff is
Franzel. 1992. Eastern Wollega characterized by high risk and variable gross margins. Interspatial arbitrage
(1985 -1989) is serious flawed, correlations in prices range from weak to strong
Dercon, S. 1995. Teff Ethiopia Modified Ravallion’s method Liberalization had important effects on the long-run and short-run
(1987 – 1993) integration of markets: most teff markets were c- integrated with Addis
Ababa market
Negassa, A. 1996. Maize, teff, Bako area of Western Shoa and Price correlations, Granger’s Deregulation has resulted in an increase in real prices accompanied by an
Noug and Eastern Wollega and Johansen’s co integration increase in price variability. Price correlation and Granger methods show
Sorghum (1986 – 1993) methods improvement in market integration while Johansen method shows no
significant changes.
Negassa, A. and T. Jayne. 1997. Maize, teff, and Ethiopia Variance and price correlation Cereal price spreads have generally declined since reform. While prices in
wheat (1985 – 1996) analyses surplus producing areas have risen by 12 – 48 percent; prices in deficit
regions declined by 6 -36 percent.
Getnet, K. Verbeke w. and J. Teff Ethiopia Autoregressive distributed lag Found long-run and short-run relationship between producer prices and the
Viaene. 2005. (1996 – 2005) model wholesale price in major terminal market (Addis Ababa)
Getnet, K., E. Gabre-Madhin, S. Wheat Ethiopia Granger cointegration and Some markets share a common factor but the price dynamics in the entire
Rashid., and S. Tamiru. 2006. (1996 – 2006) error-correction and Johansen market considered are not as such influenced by single common factor.
cointegration methods The implication is that different markets need different policy instruments
to address the price stabilization issues
Negassa, A. and R. Myers. 2007. Maize and Ethiopia Extended parity bounds model Grain market reform have improved spatial market efficiency in a few
wheat (1996 – 2002) markets, worsened it in a few others, but generally to have had little effect
on the spatial efficiency of Ethiopian grain market
Rashid and Gabre-Madhin, 2007. Maize, wheat, Ethiopia Common trend and Most market locations, except one in the north and another in the eastern
and teff (1996 – 2006) Multivariate co-integration part of the country, are integrated. Analyses of common trends indicate that
analyses shocks to teff markets have little effects and shocks to maize markets have
more persistent effects on the other commodities.

18. Performance: Seasonality and variability
 Basics concepts of seasonality & variability
analyses
 Any time series variable can be represented as
follows:
X T C S I
t
 Where T = Trend component; C= Cyclical component
 S = Seasonal component; and I = Irregular component
 Decomposing these components is essential in
seasonality and variability analyses!!

19. Performance: seasonality analyses
 Centered moving averages eliminates
Seasonal and Irregular components from the
time series.
 That is, CMX = T x C.
 Dividing Xt by CMX leaves seasonal and irregular
components.
 By doing one more adjustment, the irregular
component can be eliminated; and we are left with
seasonal index.

20. Performance: seasonality
Change of seasonality for teff wholesale Change of seasonality for maize
price over time wholesale price over time
1.15 1.20
1.10 1.15
1.10
1.05
1.05
1.00
1.00
0.95
0.95
0.90 0.90
0.85 0.85
0.80
0.80
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Maize_2000s Maize_1980s
Teff_2000s Teff_1980s Teff_1990s Maize_1990s

21. Performance: seasonality
Change of seasonality for Wheat wholesale price over time
1.15
1.10
1.05
1.00
0.95
0.90
0.85
0.80
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Wheat_1980s Wheat_1990s Wheat_2000s

22. Performance: seasonality
 Three things we can do with the estimated
seasonality indices
 Future price projection
 Competitiveness in storage behaviors
 Tests for the change in seasonality patterns
 Future price projection
 Suppose we want to project August price of teff in
January based on the following info:
 price of teff in January is 350 Birr /quintal
 Seasonal indices for January & August are 0.95 & 1.1,
respectively.
 August price will roughly be ____!!!

23. Performance: seasonality
 Competitiveness in storage
 Suppose someone wants to make profits by buying
maize when prices are low and selling when prices
are high
 Also suppose
 The minimum and maximum seasonality indices are 0.93 and
1.1, respectively.
 The trader need to store at least for six months to make profits
 Maize loses 5 percent weight in six months
 Trader borrowed money from bank at an interest rate of 12%.
Is this trader’s storage competitive or is he making
excess profit!!

24. Performance: seasonality
Seasonality and storage
1.4
1.2
1
0.8
0.6
0.4
0.2
0
Teff Wheat Maize Sorghum Barley
2000s 1990s 1980s

25. Performance: variability
 Three measures of variability
Time Periods Measures of Cereals
Variability a
Maize Wheat Sorghu Barley Teff
m
2000s Coefficient of Variation 71.33 53.45 59.82 60.95 51.27
Cuddy Le Valle Index 36.37 24.40 29.35 23.05 28.48
Coefficient of Variation 50.17 40.96 43.68 46.59 37.45
(based on MA series)
1990s Coefficient of Variation 23.01 16.81 20.05 17.75 16.00
Cuddy Le Valle Index 22.59 11.45 18.67 15.06 9.49
Coefficient of Variation 17.07 13.79 14.23 15.18 13.29
(based on MA series)
1980s Coefficient of Variation 41.91 31.95 31.54 28.45 24.67
Cuddy La Valle Index 41.79 31.18 30.07 28.37 24.39
Coefficient of Variation 34.72 24.54 26.66 21.14 18.92
(based on MA series)

26. Performance: costs and margins
Costs and Margins 1996 2002 2008 Absolute change since
1996 2002
A. Transaction costs
Total transaction costs (Birr/
ton) 323.57 123.14 54.58 -269.00 -68.57
Cost of handling 58.24 38.17 14.74 -43.51 -23.44
Cost of sacking 25.89 39.41 17.47 -8.42 -21.94
Cost of transport 100.31 25.86 8.19 -92.12 -17.67
Cost of storage 0.00 0.62 0.55 0.55 -0.07
Cost of road stops 16.18 0.49 0.00 -16.18 -0.49
Cost of brokers 25.89 11.08 -- -- --
Cost of travel 3.24 1.11 0.55 -2.69 -0.56
Cost of others 93.84 6.40 12.01 -81.83 5.60
B. Trade Margins
Price difference (Birr/ton) 338.98 203.78 84.90 -254.08 -118.88
Gross margin rate (%)b -- 7 4 -- -3
Net margin (Birr/ton)c 77.04 58.22 30.32 -46.72 -27.90

27. What do estimates of costs and margins mean?
Let’s do some math!!
 What would have been the maize price in 2008 if
there had been no change in transaction costs?
 Total transaction costs in1996 was 28 percent of
wholesale price
 Price of maize in 1996 was 750 Birr per ton
 In 2008, price of maize was 4170 Birr per ton; and
transaction costs was less than 3 percent of the
wholesale prices.
 If transaction costs had remained the same,
prices in 2008 would have been ______!!

28. THANK YOU!!!