Cereal Markets in Ethiopia: Policies and

Performances

Prepared for the EDRI-IFPRI seminarAddis Ababa, April 15, 2009

Shahidur Rashid &

Asfaw Negassa

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

Conceptual framework

Page 3

Public Policies

Indirectly

Affecting

Markets:

For example,

investments in

infrastructure

Policies Directly

Affecting

Markets:

For example,

elimination of

movement

restrictions

Market

Analysis

Structure

Conduct

Performance

Competitive Price

Policy reviews

Policy Regime Major Policy

Objective(s)

Key Observations

Imperial

Regime

Support and promote the

interests of few landlords

and urban consumers

Limited interventions and were not

effective

Socialist

Regime

Complete socialization of

production and marketing

Heavy government intervention

which depressed the development

of private grain trade

The Current

Regime

Price stabilization,

promote private sector

grain trade

Progresses have been made.

However, good intentions are

frustrated with ad hock nature of

policy interventions

Review of Grain Marketing Policy Changes in Ethiopia:

Objectives and key Observations

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

Infrastructural developments

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

200001

95

1

19

63

19

69

19

71

19

73

19

75

19

77

19

79

19

81

19

83

19

85

19

87

19

89

19

91

19

93

19

95

19

97

19

99

20

01

20

03

Asphalt Gravel Rural

Le

ng

th o

f ro

ad

s (

Km

)Trends in road lengths for different classes of roads, 1951

to 2003

Warehouse_NazerethInfrastructural developments (cont.)

Indicator 1997 2002 2005 Absolute change

from 1997 to 2005

Proportion of paved roads in good

condition

17% 35% 54% 37(+)

Proportion of unpaved roads in good

condition

25% 30% 40% 15(+)

Proportion of regional roads in good

condition

21% 28% 33.6% 12.6(+)

Road density: length/1000 sq. km. 24.1km 30.3km 33.6km 9.5(+)

Road density: Length/1000

inhabitants

0.46km 0.49km 0.51km 0.13(+)

Proportion of area more than 5 km

from all-weather road

79% 75% 73% 6.0(-)

Average distance to the road network 21.4km 17.0km 16km 5.4(-)

Improvements in Ethiopian road infrastructure and

accessibility, 1997 to 2005

Infrastructural developments (cont.)

0

50

100

150

200

250

300

350

400

450

500

Lines Apparatuses

Nu

mb

er

('1

00

0')

Trends in number of fixed telephone lines and apparatuses,

1988 to 2003

Infrastructural developments (cont.)

Trends in number of trucks of different

sizes, 1993 to 2004

.00

10000.00

20000.00

30000.00

40000.00

50000.00

Big Small all trucks

Nu

mb

er

of

tru

ck

s

Trends in number of trucks of

different sizes, 1993 to 2004

Warehouse_NazerethInfrastructural developments: key observations

Significant improvements in

marketing infrastructure

How these changes are affecting

grain market performances?

Review of organization and structure of markets

Organization of Cereal Markets

Traditional and Emerging Cereal

Marketing Channels

Broad Changes in Cereal Market

Structure

Cereal value chain map involving traditional market channels

Smallholders

Export

State farms

Wholesalers (deficit)

Processors

Consumers

Food aid agencies/WFP

Assemblers

Wholesalers (surplus)

Brokers

Coops

EGTE

Commercial farms

Retailers/ Ration Shop

Smallholders State farms

Commercial farms

Assemblers

Wholesalers (surplus)

Commodity exchange with brokers

Wholesalers (deficit)

Retailers

Coops EGTE

Processors

Consumers

Exporters Food aid agencies

Cereal value chain map involving commodity exchange

Structure (cont.)

Market level

Key actors Key functions Recent changes

Production Smallholders, commercial farms, and state farms

Production of cereals Re-emergence of private commercial farms

Assembly Petty-traders, farmer traders, cooperatives

Collection and bulking of cereals

Emerging cooperative marketing

Wholesale Large traders, Ethiopian grain trade enterprise, Cooperatives

Temporal and spatial arbitrage services

•Emerging cooperative marketing •Emergence of ECX•Emergence of Commodity Warehouse System

Processing Small-scale, medium-scale, and large-scale flour mills

Custom milling /commercial flour mills, & manufacturing

New large-scale private entrants as opposed to state-dominated processing sector under socialist regime

Retail Small traders, small-scale flour mills, wholesale traders

Sell cereals and flour mills to consumers in small quantities

Emergence of supermarkets carrying locally processed flour mills (mainly wheat) and imported cereal products

Performance

Price analyses (historical data)

Market integration

Seasonality

Price variability

Survey data analyses

Transactions costs

Trade margins

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

Performance: market integration review

Author (s) Commodities Geographic coverage & time

periods

Method of analysis Findings

Dadi, L., A. Negassa, and S.

Franzel. 1992.

Maize and Teff Bako area of Western Shoa and

Eastern Wollega

(1985 -1989)

Price correlation analysis Results indicate that private sector marketing of maize and teff is

characterized by high risk and variable gross margins. Interspatial arbitrage

is serious flawed, correlations in prices range from weak to strong

Dercon, S. 1995. Teff Ethiopia

(1987 – 1993)

Modified Ravallion’s method Liberalization had important effects on the long-run and short-run

integration of markets: most teff markets were c- integrated with Addis

Ababa market

Negassa, A. 1996. Maize, teff,

Noug and

Sorghum

Bako area of Western Shoa and

Eastern Wollega

(1986 – 1993)

Price correlations, Granger’s

and Johansen’s co integration

methods

Deregulation has resulted in an increase in real prices accompanied by an

increase in price variability. Price correlation and Granger methods show

improvement in market integration while Johansen method shows no

significant changes.

Negassa, A. and T. Jayne. 1997. Maize, teff, and

wheat

Ethiopia

(1985 – 1996)

Variance and price correlation

analyses

Cereal price spreads have generally declined since reform. While prices in

surplus producing areas have risen by 12 – 48 percent; prices in deficit

regions declined by 6 -36 percent.

Getnet, K. Verbeke w. and J.

Viaene. 2005.

Teff Ethiopia

(1996 – 2005)

Autoregressive distributed lag

model

Found long-run and short-run relationship between producer prices and the

wholesale price in major terminal market (Addis Ababa)

Getnet, K., E. Gabre-Madhin, S.

Rashid., and S. Tamiru. 2006.

Wheat Ethiopia

(1996 – 2006)

Granger cointegration and

error-correction and Johansen

cointegration methods

Some markets share a common factor but the price dynamics in the entire

market considered are not as such influenced by single common factor.

The implication is that different markets need different policy instruments

to address the price stabilization issues

Negassa, A. and R. Myers. 2007. Maize and

wheat

Ethiopia

(1996 – 2002)

Extended parity bounds model Grain market reform have improved spatial market efficiency in a few

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,

and teff

Ethiopia

(1996 – 2006)

Common trend and

Multivariate co-integration

analyses

Most market locations, except one in the north and another in the eastern

part of the country, are integrated. Analyses of common trends indicate that

shocks to teff markets have little effects and shocks to maize markets have

more persistent effects on the other commodities.

Performance: Seasonality and variability

Basics concepts of seasonality & variability

analyses

Any time series variable can be represented as

follows:

Where T = Trend component; C= Cyclical component

S = Seasonal component; and I = Irregular component

Decomposing these components is essential in

seasonality and variability analyses!!

ISCTt

X

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.

Performance: seasonality

0.80

0.85

0.90

0.95

1.00

1.05

1.10

1.15

Teff_2000s Teff_1980s Teff_1990s

Change of seasonality for teff wholesale

price over time

0.80

0.85

0.90

0.95

1.00

1.05

1.10

1.15

1.20

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Maize_2000s Maize_1980s

Maize_1990s

Change of seasonality for maize

wholesale price over time

0.80

0.85

0.90

0.95

1.00

1.05

1.10

1.15

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Wheat_1980s Wheat_1990s Wheat_2000s

Change of seasonality for Wheat wholesale price over time

Performance: seasonality

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 ____!!!

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!!

Performance: seasonality

0

0.2

0.4

0.6

0.8

1

1.2

1.4

Teff Wheat Maize Sorghum Barley

2000s 1990s 1980s

Seasonality and storage

Performance: variability

Three measures of variability

Time Periods Measures of

Variability aCereals

Maize Wheat Sorghu

m

Barley Teff

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

(based on MA series)

50.17 40.96 43.68 46.59 37.45

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

(based on MA series)

17.07 13.79 14.23 15.18 13.29

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

(based on MA series)

34.72 24.54 26.66 21.14 18.92

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

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 ______!!

What do estimates of costs and margins mean?

Let’s do some math!!

THANK YOU!!!