spatial analysis of cereal market prices: effects of remoteness on market price
DESCRIPTION
The 4th ESRI-Eastearn Africa Conference, Addis Ababa, 25 September, 2009TRANSCRIPT
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Spatial Analysis of Cereal Market Prices: Effects of Remoteness on Market Price
Emily Schmidt and Hailu ShiferawThe 4th ESRI-EA Conference 24 -25 September 2009Addis Ababa, Ethiopia
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Overview
• Introduction
• Methodology
• Results
• Policy options
• Conclusions
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An important determinant of household food security
is the market price of key cereal grains.
• Given Ethiopia’s unique biophysical landscape, and spatial placement
of key infrastructures, cereal prices vary across geographic areas.
• We analyze price variations over space for four major cereals
• Taking into account:
• Geographic location of 120 cereal markets
• Travel time from cereal markets to large cities
• Whether a market center is in a region that is classified as surplus
or deficit
• Teff
• Wheat
• Maize
• Sorghum
Introduction
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Effects of location on grain prices
We test the hypothesis:
• Highest prices of cereal grains are in the rural-remote,
deficit producing areas
• High transportation costs to remote areas, with local deficit
production accounts for higher prices in these areas in order to
account for transaction costs
• Lowest prices are in the rural-remote, surplus grain
producing areas
• Rural, remote areas which are growing a surplus amount of
grain, but do not have access to larger markets (or cities)
forced to sell excess supply at low prices
Introduction
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Each market is categorized by:
• Net Cereal Supply:• Surplus: Net production is greater than 10% reported consumption
• Autarky (Balanced): Net production is between 10% above and below reported consumption
• Deficit: Net production is below 10% of consumption
• Travel Time:• Remote (greater than 5 hours travel time from a major city)
• Non remote (less than 5 hours travel time from a major city)
• Rural/Urban: • Rural towns (markets within a town less than 20,000 people)
• Small towns (markets within a town with at least 20,000 people)
• Large city (Addis Ababa and Dire Dawa)
Methodology
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Cereal markets and net supply
for all grains
Methodology
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Net Wheat Supply
Net Teff Supply
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Market Access and Remoteness
• Euclidean distance does not take into account biophysical features such as mountains and rivers, nor does it assess road quality and travel speed
• The shortest route in kilometers may not always be the fastest route
• By calculating a travel time from each market, to an urban hub (city of 50,000 people), we are able to classify our study markets into:
• Remote: more than 5 hours travel time to a city
• Non – remote: less than 5 hours travel time to a city
Methodology
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Travel Time calculation incorporates:• Road types and classes:
• Paved, all weather / dry weather
• Gravel, all weather / dry weather
• Earth
• Landcover – walking speed
• Rivers
• Waterbodies
• Slope (calculated using DEM)
• These layers are then reclassified and combined into a friction layer that reflects the time in minutes to cross a single 1km. cell (pixel).
• This friction layer is then used as input data to calculate a cost distance (travel time) to a given target
Methodology
Travel time to cities of at least 50,000 people
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Market centers and travel time
to a city of at least 50,000 people
Results
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• Several markets in
Benishangul – Gumuz have
surplus grain production,
but remain further than 5
hours travel time to a large
city
• Areas in SNNP region
show deficit production
levels and are not
connected to a major road
network nor are they within
5 hours of a city
•Afar region also has
population in deficit, distant
areas
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Markets disaggregated by production, remoteness,
and urban / rural classifications
Results
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• A majority of sorghum
production is found in the
Northwest of Ethiopia, Surplus
– distant markets are found in
Benishangul – Gumuz
• Maize, wheat and teff are
grown primarily in the
highlands of Oromia and
Amhara regions
• Some surplus area maize is
grown in Afar region, as well
as selected regions in
Benishangul - Gumuz and
west Oromia
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Location Teff Wheat Maize Sorghum
Rural 3.99 2.97 1.53 2.03
Small Town 3.98 3.10 1.62 2.27
Large Cities 4.44 3.41 1.89 3.40
Addis Ababa 4.46 3.42 1.88 3.40
Distant 3.89 3.02 1.35 1.73
Connected 4.01 3.06 1.63 2.28
Surplus 3.81 2.93 1.56 2.04
Autarky 4.06 3.19 1.52 2.26
Deficit 4.13 3.09 1.59 2.19
Average Grain Price by Location and Cereal (birr/kg, 2006/07)
When aggregated by
all grains, our
hypothesis holds true.
Large cities and small
towns (expected to be
deficit producers)
experience higher
grain prices.
Markets in areas with
surplus production
have lower prices than
deficit markets
Results
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Average Teff Price by Location and Variety (birr/kg, 2006/07)
• Compared to rural distant deficit markets, the rural distant surplus markets have
generally lower prices for all teff varietals
• Rural markets that are distant and have deficit production have teff values that
cost roughly 50 cents more per quintile, but urban prices remain the highest for
white and black teff
• Rural deficit prices in connected markets are higher by up to 12 percent for white
and mixed teff.
White Teff Black Teff Mixed Teff
Location Distant Connected Distant Connected Distant Connected
Rural Surplus 3.68 4.16 3.25 3.22 3.50 3.82
Rural Autarky 4.52 4.15 4.00 4.00 4.00 4.00
Rural Deficit 4.27 4.68 3.71 3.58 4.00 4.38
Large cities - 4.99 - 4.00 - 4.33
Addis Ababa - 5.01 - 4.00 - 4.36
Results
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Average Wheat Price by Location and Variety (birr/kg, 2006/07)
• Unlike teff, urban prices for white and mixed wheat are not substantially higher
than rural prices
• In distant, deficit areas, white wheat is 15 cents per kilogram higher than in deficit
connected producing areas
• Mixed teff in rural deficit areas is more expensive than in Addis Ababa
• We hypothesize that Ethiopia imports a larger percentage of wheat in comparison
to other grains, and imports of wheat in urban markets may be depressing prices
White Wheat Mixed Wheat
Location Distant Connected Distant Connected
Rural Surplus _ 3.04 _ 2.86
Rural Autarky 3.07 2.95 3.34 _
Rural Deficit 3.22 3.07 3.08 3.02
Large cities 3.22 3.00
Addis Ababa _ 3.23 _ 3.06
Results
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9,202 1,855
21,77233,119
4,278
Deficit Distant
Surplus Distant
Deficit Connected
Surplus Connected
Autarky Connected
Population (thousands) in Surplus or Deficit
Producing Areas and Connected or Distant
Regions
Results
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• More than 33 million people
live in areas that experience
surplus grain production and
are within 5 hours of a city of
50,000 people
• Almost 22 million people
live in deficit producing areas,
but are able to access a large
city within 5 hours travel time
• Over 9 million people live in
distant, deficit producing
areas and half are from
SNNP region (4.6 million)
•Almost 2 million people have
surplus production, but
limited access to a large
market
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High price, Distant Markets outside of the
Productive Safety Net Areas
Woredas that are deficit , remote and experience high market prices
Teff:
• Selamago (SNNP)
• Asayita (Afar)
• Dubti (Afar)
• Moyale (Somali)
Wheat:
• Bambasi (Benshangul-Gumuz)
• Shambo (Oromia)
• Asayita (Afar)
• Dubti (Afar)
• Dahana (Amhara)
Maize:
• Dahana (Amhara)
Sorghum:
• Dubti (Afar)
• Moyale (Somali)
• Dahana (Amhara)
• Basketo (SNNP)
Results
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Possible policy interventions for further exploration
In the short term:
• Currently 7.5 million people receive from PSNP program
• Remote, deficit areas facing high grain prices could benefit from PSNP assistance in-kind
In the long term:
• The Road Sector Development Plan initiated in 1997, built and/or improved roughly 15,000km. of trunk and regional roads.
• A future RSDP could assess road investments in order to increase connectivity along specified transportation networks between deficit producing areas and surplus grain markets.
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Conclusions
• Analyzing grain prices across geographic space in Ethiopia at an
aggregate level illustrates that most markets are well-connected (in terms
of transport networks) and transaction costs (as reflected in the gross
margins) between rural and urban areas are generally reflected in the
higher prices reported in cities.
• When comparing distant, deficit areas with PSNP receiving woredas,
several woredas emerged that may benefit from PSNP assistance in-kind .
• In the long run, further improvements to transportation infrastructure
between deficit and surplus areas would improve access to key goods and
services, as well as decrease transaction costs between markets.
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