benjamin davis, alberto zezza and stefania di giuseppe annual bank conference on africa paris, june...

Benjamin Davis, Alberto Zezza and Stefania di Giuseppe

Annual Bank Conference on AfricaParis, June 23, 2014

A G R I C U L T U R E

I N A F R I C AT E L L I N G F A C T SF R O M M Y T H S

Income diversification patterns in rural Sub-Saharan Africa:Reassessing the evidence

“East Asian countries grew rapidly by replicating, in a much shorter time frame, what today’s advanced countries did following the Industrial Revolution. They turned their farmers into manufacturing workers, diversified their economies, and exported a range of increasingly sophisticated goods. Little of this process is taking place in Africa. … Optimists say that the good news about African structural transformation has not yet shown up in macroeconomic data.” (Rodrik, 2013)

Is Africa different when it comes to rural income diversification?

Revisit the facts: Are rural households in Africa diversifying less out of agriculture than elsewhere?Spatial aspects of income diversification in Africa

Agricultural potentialDistance from urban centersSmall vs large cities

Implications: Structural changeWelfareApproach to rural development

Diversification and RNF literature:Not so many myths after all

Large rural non-farm (or off-farm) sector (though estimates vary)Positively related to household income and GDPRole of assets (edu, land, infrastructure)Barriers to entry, dualism (high/low skills/returns)Likely good for poverty reduction; mixed evidence on inequalityBut despite efforts:

Data issues remain (comparability, measurement issues)Is there an African specificity?Not much on spatial analysis

Countries included in the study

Ethiopia (2011)Ghana (1992, 1998 and 2005)Kenya (2005)Madagascar (1993)Malawi (2004 and 2011)Niger (2010-11)Nigeria (2004 and 2011)Tanzania (2009)Uganda (2005-06 and 2009-10)

• Nepal (1996 and 2003)• Bangladesh (2000 and 2005)• Tajikistan (2003 and 2007)• Pakistan (1991 and 2001)• Nicaragua (1998, 2001 and 2005)• Indonesia (1993 and 2000)• Bolivia (2005)• Guatemala (2000 and 2006)• Albania (2002 and 2005)• Ecuador (1995 and 1998)• Bulgaria (1995 and 2001)• Panama (1997 and 2003)• Vietnam (1992, 1998 and 2002)

We use the following income categories

7 income categories:

1. Crop production2. Livestock production3. Agricultural wage

employment4. Non-agricultural wage

employment5. Non-agricultural self-

employment6. Transfer7. Other

• Agricultural income– crop + livestock + agricultural wage

• Non agricultural income– non-agricultural wage + non-

agricultural self + transfer + other• On farm

– crop + livestock• Non farm

– non-agricultural wage + non-agricultural self

• Off farm– agricultural wage + non-

agricultural wage + non-agricultural self + transfers + other

Rural households in most countries have an on farm activity

Log of 2005 PC GDP

50

60

70

80

90

100

(%)

6 7 8 9GDP (log)

Participation Africa Participation Non-AfricaOverall Trend African trend Africa without NGA

Participation in on farm activities

And a large share a non farm activity (non agricultural wage and self emp)

20

40

60

80

100

(%)

6 7 8 9GDP (log)

Participation Africa Participation Non-AfricaOverall Trend African trend Africa without NGA

Participation in non farm activities

Increasing share of non agricultural income with GDP: Is Africa different?

Or just still at lower levels of GDP?0

20

40

60

80

(%)

6 7 8 9GDP (log)

Africa Non-AfricaOverall Trend African trend Africa without NGA

Share of non agricultural income

Similar story for non agricultural wage income—increasing with GDP

01

02

03

04

0(%

)

6 7 8 9GDP (log)


Share of non agricultural wage income

Do rural households in African have a tendency towards more on farm specialization?...

Household defined as specialized if receives more than 75 percent of income from single source and diversified if no single source is greater than 75 percent

… Possibly! Decreasing, but still high, specialization in on farm activities in Africa

02

04

06

08

0(%

)

6 7 8 9GDP (log)


Share specializing on farm

Increasing specialization in non agricultural wage income with GDP

05

10

15

20

25

(%)

6 7 8 9GDP (log)


Share specializing non agricultural wage

Most African countries specialize in on farm activities, while most non African are diversified

Implications for welfare: Stochastic dominance analysis

Tanzania

Malawi

The role of geography: Theory and literature

Von Thünen (1842)New economic geography: Institutions vs geography (Mostly macro, x-country)Agglomeration, dispersion forcesMicro studies: Fafchamps et al. (Nepal); Foster and Rosenzweig (India); Diechmann et al (Bangladesh); Yamano and Kijima (Uganda) Interaction of location, ag potential, mediated by infrastructure, tradability, wages, etc.

Basic hypotheses on diversification and location (theory and literature)

Specialization outside of farming

Nonlinearities, interactions complicate the picture

Distance to cities

Agricultural

potential

Low High

Low ++ (?)

High +(?) -

The role of geography: Our estimates

Multinomial logit of specialization categoriesOn-farm specialization the baseQuadratic terms for distance, ag. potentialInteraction term b/wen distance and ag potentialNon-linearities not included unless jointly significantSeparately for different city sizes (20K to 1 mln.)

The role of geography: Results

“It depends…”: Non-linearities matter, the role of distance changes with potential and city sizeRole of distance more muted where ag potential is highSmaller towns linked to diversification; larger towns to non-ag

Malawi: Non ag wage specialization, ag potential, and distance from cities

-5

-4.5

-4

-3.5

-3

-2.5

-2

-1.5

-1

-0.5

0Low Distance High Distance

Dep

end

ent

vari

able

Low Potential

High Potential

-4.5

-4

-3.5

-3

-2.5

-2

-1.5

-1

-0.5


Dep

end

ent

vari

able

Low Potential

High Potential

Small town

Large city

High potential flatter: Ag driving

Low potential, small towns: Non-ag higher with distance

Low potential, large cities: Non-ag higher declines with distance

Tanzania: Non ag wage specialization, ag potential, and distance from cities

Mid-size town

Large city

-6

-5

-4

-3

-2

-1


Dep

end

ent

vari

able

Low Potential

High Potential

-5

-4.5

-4

-3.5

-3

-2.5

-2

-1.5

-1

-0.5


Dep

end

ent

vari

able

Low Potential

High Potential

Low potential, mid-size towns: Non-ag lower with distance

High potential flatter: Ag driving (with nuances)

Low potential, large cities: Non-ag higher declines with distance

Conclusions

Diversification patterns in Africa do not seem to differ markedly, for given GDP pcNon-farm and household welfareWe know about barriers to entry: Role of educationNeed to consider spatially explicit policies:

Ag potentialCity sizeLand abundance

Data now allow for more in-depth, spatially explicit analysesNeed (and opportunity) for revitalizing ‘rural development’ discourse in Africa?

Benjamin Davis, Alberto Zezza and Stefania di Giuseppe

Annual Bank Conference on AfricaParis, June 23, 2014

A G R I C U L T U R E

I N A F R I C AT E L L I N G F A C T SF R O M M Y T H S

Income diversification patterns in rural Sub-Saharan Africa:Reassessing the evidence

benjamin davis, alberto zezza and stefania di giuseppe annual bank conference on africa paris, june...

Documents