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The Emerging “Quiet Revolution”
in African Agrifood Systems:
Challenges for Mozambique
David Tschirley, Michael Dolislager, Jason Snyder, Thomas Reardon
Presentation at MSU/IFPRI conference on “Agricultural Public Investments, Policies, and
Markets for Mozambique’s Food Security and Economic Transformation”
Maputo, Mozambique
20 November 2014
Urbanization
& per capita
income growth
Diet & other
transformations
(farm, midstream,
downstream)
Approach
Policy Private
Investment
Public Investment
Rate & nature of
transformations
Rate of
change
Approach
Urbanization
& per capita
income growth
Diet & other
transformations
(farm, midstream,
downstream)
Policy Private
Investment
Public Investment
Rate & nature of
transformations
Rate of
change
Approach
Urbanization
& per capita
income growth
Diet & other
transformations
(farm, midstream,
downstream)
Approach (2)
• Focus primarily on East and Southern Africa
• LSMS data from Ethiopia, Uganda, Tanzania,
Mozambique, Malawi, Zambia
• Mozambique’s characteristics fit very well
into the regional picture
• Possible exceptions / differences
• Pattern of urban population settlement
• Import dependence now and moving forward
Focus
• African urbanization
• Is African income growth being captured by a
small elite?
• Diet change is a major driver of agrifood system
transformation, and it starts very early in the
income distribution
• Important implications for the pace of change over
the next decade
• How can Africa capture booming African demand
for food?
Urbanization
• Africa is urbanizing rapidly
• Occurring more rapidly in smaller cities and
towns than in large cities
• Good for rural-urban linkages
• Mozambique has the most deconcentrated urban
population distribution in SSA
• Major potential advantage
• Urban demand is already > 50% of the food
market in ESA
• Food security – including rural – is increasingly
about rural-urban supply chains
Income growth
• Widely known that growth has been much faster
over past 15 years
• Its distribution across HHs in ESA – the equity of
growth in the region - has been:
• Generally unequal, but
• Highly variable, and
• Overall, broad enough to drive rapid transformation
if it continues
If growth continues like this …
2010 2040
Income Class
(per capita PPP income)
Share Share
ESA-wide 100% 100%
Poor ($0-$2) 72.5% 19.3%
Vulnerable middle ($2-$4) 19.9% 28.7%
Lower middle ($4-$10) 6.5% 33.9%
Upper Middle ($10-$20) 0.9% 12.0%
Upper (>$20) 0.2% 6.1%
Populations and shares by income class in East and Southern Africa, 2010 and
2040 assuming continuation of rate and distribution of recent GDP growth
Source: Author calculations from PovcalNet
If growth continues like this …
2010 2040
Income Class
(per capita PPP income)
Share Share
ESA-wide 100% 100%
Poor ($0-$2) 72.5% 19.3%
Vulnerable middle ($2-$4) 19.9% 28.7%
Lower middle ($4-$10) 6.5% 33.9%
Upper Middle ($10-$20) 0.9% 12.0%
Upper (>$20) 0.2% 6.1%
Populations and shares by income class in East and Southern Africa, 2010 and
2040 assuming continuation of rate and distribution of recent GDP growth
Source: Author calculations from PovcalNet
Focus
• African urbanization
• Is African income growth being captured by a small
elite?
• Diet change is a major driver of agrifood system
transformation, and it starts very early in the income
distribution
• Important implications for the pace of change over the
next decade
• How can Africa capture booming African demand for
food?
Focus primarily on East and Southern Africa
The rise of processed foods
Unprocessed
Processed,
Low Value
Added
Processed,
High Value
Added
Non-
perishable
Legumes
Maize grain
others
Maize meal
Milled Rice
Sugar
Others
Veg oils
Breads
Food away from
home
Others
Perishable
Vegetables
Fresh fish
Fruit
Others
Beef
Other meat
(incl. poultry)
Dried/pkgd fish
Others
Food away from
home
Dairy
Others
The rise of processed foods
• Processed foods have penetrated
• Deeply (69% share of all purchased food)
• Broadly
• comparable in rural- and urban areas,
• among poor and upper class
• Dramatic change in consumption patterns below the
international poverty line
Kernel regression results on purchased food budget shares,
additionally weighted by population across 5 countries of ESA
Unprocessed non-perishable Low processed non-perishable
High processed non-perishable Unprocessed perishable
Low processed perishable High processed perishable
Source: Author calculations from LSMS data sets
Kernel regression results on purchased food budget shares,
additionally weighted by population across 5 countries of ESA
Unprocessed non-perishable Low processed non-perishable
High processed non-perishable Unprocessed perishable
Low processed perishable High processed perishable
Source: Author calculations from LSMS data sets
Kernel regression results on purchased food budget shares,
additionally weighted by population across 5 countries of ESA
Unprocessed non-perishable Low processed non-perishable
High processed non-perishable Unprocessed perishable
Low processed perishable High processed perishable
Source: Author calculations from LSMS data sets
Kernel regression results on purchased food budget shares,
additionally weighted by population across 5 countries of ESA
Unprocessed non-perishable Low processed non-perishable
High processed non-perishable Unprocessed perishable
Low processed perishable High processed perishable
Source: Author calculations from LSMS data sets
Most diet change has already
occurred by the time a household
rises up to the international poverty
line
ESA measure of total impact on food system change
by level of income
Source: Author calculations from LSMS data sets
ESA measure of total impact on food system change
by level of income
This group – all below
international poverty line
– is driving food system change
 Major implications for structural
change over coming decade
and beyond
Source: Author calculations from LSMS data sets
Food Category Rural Urban ESA-Wide
Consumed own production 0.95 0.39 0.82
Non-perishable
Unprocessed 0.81 0.55 0.75
Processed Low 0.87 0.70 0.83
Processed High 1.07 1.00 1.05
Perishable
Unprocessed 0.73 0.80 0.75
Processed Low 1.20 1.18 1.19
Processed High 1.36 1.28 1.34
Expenditure elasticities by perishability and processing
classification, income class, and rural/urban (2010)
Source: Author calculations from LSMS data
Food Category Rural Urban ESA-Wide
Consumed own production 0.95 0.39 0.82
Non-perishable
Unprocessed 0.81 0.55 0.75
Processed Low 0.87 0.70 0.83
Processed High 1.07 1.00 1.05
Perishable
Unprocessed 0.73 0.80 0.75
Processed Low 1.20 1.18 1.19
Processed High 1.36 1.28 1.34
Expenditure elasticities by perishability and processing
classification, income class, and rural/urban (2010)
Source: Author calculations from LSMS data
Focus
• African urbanization
• Is African income growth being captured by a small
elite?
• Diet change is a major driver of agrifood system
transformation, and it starts very early in the income
distribution
• Important implications for the pace of change over the
next decade
• How can Africa capture booming African demand for
food?
Focus primarily on East and Southern Africa
Will imports capture the surge in
demand?
• We found in the region that net import shares in
food consumption fall with income in urban
areas
• Why?
• Local cereals  imported cereals, BUT
• Bennett’s Law: Cereals  meat, dairy (also
fresh produce)
• all largely locally produced
• But Mozambique may be very different
NetAgriculturalImportsasShareofAgriculturalProduction,
CountriesofESA,1980-2011
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
Netagriculturalimports/agricultural
production
Angola
Botswana
Burundi
Ethiopia
Kenya
Malawi
Mozambique
Rwanda
Tanzania
Uganda
Zambia
Source: Author calculations from FAOSTAT
NetAgriculturalImportsasShareofAgriculturalProduction,
CountriesofESA,1980-2011
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
Netagriculturalimports/agricultural
production
Angola
Botswana
Burundi
Ethiopia
Kenya
Malawi
Mozambique
Rwanda
Tanzania
Uganda
Zambia
Botswana
Source: Author calculations from FAOSTAT
NetAgriculturalImportsasShareofAgriculturalProduction,
CountriesofESA,1980-2011
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
Netagriculturalimports/agricultural
production
Angola
Botswana
Burundi
Ethiopia
Kenya
Malawi
Mozambique
Rwanda
Tanzania
Uganda
Zambia
Angola
Botswana
Source: Author calculations from FAOSTAT
NetAgriculturalImportsasShareofAgriculturalProduction,
CountriesofESA,1980-2011
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
3.5
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
Netagriculturalimports/agricultural
production
Angola
Botswana
Burundi
Ethiopia
Kenya
Malawi
Mozambique
Rwanda
Tanzania
Uganda
Zambia
Angola
Mozam-
bique
Botswana
Source: Author calculations from FAOSTAT
Implications
• Change is happening very rapidly now
• Driven by rapid diet change among the poor
• Huge opportunities for farmers, traders,
transporters , processors
• How can Mozambique get the whole agrifood
system productivity growth needed to capture
these opportunities?
• Benefit its own farmers and entrepreneurs rather
than those in other countries
Implications (2)
• The emerging Quiet Revolution
• Local micro-small-medium businesses
• Non-western multi-nationals becoming major
players
• OLAM, Export Trading Group, others
• South Africans (Shoprite/Checkers, Tiger Brands,
others)
• Also well known players such as Walmart,
Carrefour, Nestle, Parmalat
Implications (3)
• Can micro, small, and medium local firms
compete?
• What packages of assistance can be effectively
delivered?
• Can farmers respond?
• Ag investment needs to increase dramatically
and move away from subsidies towards
productivity enhancers
“Take Home”
Mozambique’s spatially dispersed urban settlement
pattern should be a huge help in building rural-urban
supply chains to capture these opportunities
But its low productivity, current high import
dependence, and coming resource boom present
huge challenges for doing so
Public policy (enabling environment) and
productivity enhancing public investment will be
crucial
Questions?

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