u nder the radar screen : the rapid rise of emergent farmers in a frica milu muyanga, t.s. jayne,...
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UNDER THE RADAR SCREEN: THE RAPID RISE OF EMERGENT FARMERS IN AFRICA
Milu Muyanga, T.S. Jayne, Antony Chapoto, Nicholas SitkoAgricultural, Food and Resource Economics Department
Michigan State University, USA
Photo: Christiaensen and Demery (2007)
Presented at the World Bank Annual Conference on Land and Poverty 2014, World Bank, Washington DC, USA, March 26, 2014
1
Introduction• Smallholder farmers constitute the bulk (70%) of agricultural
producers in sub-Saharan Africa
• Majority of them are poor and food insecure
• Agricultural-led growth strategy has been touted as solution for
reductions in poverty and food insecurity in this region
• However, recent turn of events cast doubts about the viability of the
agriculture-led strategy
• Smallholder farming is sliding into landlessness situation as
population density rises
• A substantial fraction of Africa’s rural population lives in high densely
populated areas where land scarcity preclude extensification
• Increased inaccessibility to land and limited off-farm opportunities
2
What does small landholding sizes mean for feasible poverty and food insecurity
reduction in Africa? • Based on the Asia’s Green Revolution experience,
smallholder-led strategy could be an option for Africa
• Asian revolution contributed greatly to increased smallholder
productivity and reduced poverty
• Smallholder agriculture is more equitable development approach
and compensates for urban-biased policies
• Besides equity concerns, efficiency considerations too
exist in support of smallholder agriculture over large farms
• Without agricultural productivity gains, food production will
stagnate or decline as land frontiers close
3
The rapid rise of emergent farmers in Africa [I]
• Shrinking landholding sizes notwithstanding, many African countries have
witnessed an explosion in the number of indigenous medium-scale famers,
also known as “emergent” farmers • Defined as farmers cultivating between 5 to 100 hectares
• Emergent farmers have little in common with large-scale farmers • Farm size, access to finance, input application, farm management practices
• Yet, the processes behind this group’s growth and its productivity compared to smallholder farmers is unclear in many countries • Is this growth driven by farmers who began as smallholders, and now transitioning
to a larger scale status through the capital and assets accumulation?
• Is the growth driven by institutions and policies (deficient policies) that encourage investment in land acquisitions by individuals from non-agricultural employment
4
Smallholder vs medium farm productivity
• Literature exists rooting for smallholder family owned farms
advantages over relatively large farms
• Relationship known as the inverse-productivity hypothesis
• Defining feature of smallholder farms is the reliance on
family labor instead of hired labor
• Argued that reliance on family labor make them more efficient
• However, the debate on whether the emphasis on
smallholder agricultural-led strategy is misplaced is still
lingers
• “… excessive peasant farming romanticism” (Collier, 2008)
5
Study objectives
• Examine the factors driving the growth of this class of farmers
using Kenya as a case study
• What are their characteristics of the medium-scale farmers
• What modes of land acquisition did they embrace to build up their
landholding scale to the current levels?
• Is the growth green or blue?
• Examine the inverse-productivity hypothesis
• Are the smallholder more productive than the medium-scale farms
• Is small still “beautiful”?
6
Data sources
• Household level survey data with 200 medium
scale farmers• Farmers cultivating 5-100 hectares
• Survey year– 2012
• Household level survey data from 296
smallholder farmers • Farmers cultivating less the 5 hectares
• Survey year-- 2010
• 2012 prices deflated using CPI to make them
comparable to 2010 prices
7
Figure 1: Study sites 8
Data analyses• Bivariate descriptive analyses
• Medium scale farmers sample is divided into two
mutually exclusive analytical groups based on the
primary source of capital • Farm-led strategy
• Non—farm led (lateral entry) strategy
• Examine how smallholders and medium scale farmers
compare in terms • Demographics; farming patterns; farm production, assets and
incomes
• Econometric analyses• Pathways into medium scale farming and production
differences • Comparing smallholders and medium scale farmers
• Estimating output supply function
9
Descriptive results [I]10
• Majority (60%)of medium-scale farmers used non-
farm entry strategy
• Majority of them are current/former public sector
employees• Had high education attainment
• Acquired land from savings from non-farm, largely urban jobs
• Only a minority were primarily engaged in agriculture• But had sufficient initial endowment of land
• Owned over two times more land than they were
using for crops:
• High degree of land owned for speculative purposes
• Inability of these farmers to make productive use of their land
Descriptive results [II]
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• Acquired most of their land through purchases
• Owned comparably more fertile land and close to
motorable roads
• Had more land outside the location in which they were
born
• Farmers to initial household heads had relatively large land
endowment
• Farm-led strategy group acquired most of their land before
1990s
• Non-farm led strategy group acquired most of their land in 1990-
2000
Smallholder vs medium scale farms
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Land cultivated (ha)
<2.5 2.5< to 5 5< to 10 10< to 20 20< to 30 30< to 50 50<
N 197 62 72 83 34 23 25
Fertilizer application (kg) per ha cultivated
167.01 288.02 286.00 309.73 268.96 365.28 361.21
Net crop production (million KSh)
0.23 0.90 2.22 4.65 6.46 12.14 49.98
Net crop production per adult available (‘000KSh)
68.37 236.43 505.60 1,165.11 1,850.56 7,357.95 12,025.62
Net crop production per ha cultivated (‘000KSh)
177.92 230.37 315.46 316.97 263.76 308.04 679.34
Net crop production per ha owned (‘000KSh)
97.61 113.08 183.57 199.39 196.72 196.70 392.00
Household asset value (‘million KSh)
0.35 1.25 2.20 3.98 5.40 9.92 11.60
Aggregate income (‘million KSh)
0.23 0.61 1.12 2.46 3.14 4.79 21.50
Non-parametric regressions results (I)0
24
68
'mill
ion K
Sh
25%50% 75% 95%0 10 20 30
land -- cultivated (ha)
Net crop production
40
60
80
100
120
'00
0K
Sh
/ha
ow
ned
25%50% 75% 95%0 15 30 45
land -- cultivated (ha)
Net crop production per hectare owned
150
200
250
300
350
'00
0K
Sh
/ha
cu
ltiva
ted
25%50% 75% 95%0 15 30 45
land -- cultivated (ha)
Net crop production per hectare cultivated
05
00
100
01
50
02
00
02
50
0
'00
0K
Sh
/un
it o
f la
bo
r
25%50% 75% 95%0 15 30 45
land -- cultivated (ha)
Net crop production per unit of labor
13
Non-parametric regressions results (II)0
24
68
10
'mill
ion K
Sh
25% 50% 75% 95%0 15 30 45 60
land -- owned (ha)
Net crop production
50
55
60
65
70
'00
0K
Sh
/ha
ow
ned
25% 50% 75% 95%0 15 30 45
land -- owned (ha)
Net crop production per hectare owned
15
02
00
25
03
00
'00
0K
Sh
/ha c
ulti
vate
d
25% 50% 75% 95%0 15 30 45
land -- owned (ha)
Net crop production per hectare cultivated
05
00
100
01
50
0
'00
0K
Sh
/un
it o
f la
bo
r
25% 50% 75% 95%0 15 30 45
land -- owned (ha)
Net crop production per unit of labor
14
Econometric regression results (I) Log of net value of production (KSh) Coef. P>t Area under crop ('ha) 0.219 0.00 Area under crop—square -0.002 0.00 Level of education of head (0=no education)
_secondary 1.666 0.03 _post-secondary 1.278 0.12
Household size -0.147 0.06 Length of Growing Period (LGP) 0.064 0.00 Slope 0.006 0.04 Distance to nearest motorable road (Km) -0.453 0.02 Rainfall '00mm 0.025 0.01 Observations 496 R squared 0.64 Turning point (hectares) 64.31 Average partial effects 0.20 Partial Effects at 25% percentile 0.21 Partial Effects at 50% percentile 0.20 Partial Effects at 75% percentile 0.13 Partial Effects at 99% percentile -0.03
15
Area cultivated
25th= 0.94ha
50th= 1.93ha
75th= 6.07ha
95th= 27.11ha
99th=72.84ha
Econometric regression results (II) Log of net value of production per unit of labor Coef. P>t Area under crop ('ha) 0.191 0.00 Area under crop-- square -0.001 0.00 Level of education of head (0=no education) _secondary 1.049 0.02 _post-secondary 0.984 0.05 Household size -0.188 0.00 Length of Growing Period (LGP) 0.048 0.00 Slope 0.004 0.03 Distance to nearest motorable road (Km) 0.087 0.05 Distance to nearest electricity (Km) -0.287 0.00 Rainfall '00mm 0.019 0.00 Observations 496 R squared 0.68 Turning point (hectares) 65.89 Average partial effects 0.17 Partial Effects at 25% percentile 0.19 Partial Effects at 50% percentile 0.18 Partial Effects at 75% percentile 0.17 Partial Effects at 95% percentile 0.11 Partial Effects at 99% percentile -0.02
16
Econometric regression results (III) Log of net value of production per ha cultivated Coef. P>t Area under crop ('ha) 0.543 0.00 Area under crop-- square -0.004 0.01 Level of education of head (0=no education)
_primary 0.225 0.63 _secondary 0.907 0.07 _post-secondary 0.788 0.13
Household size -0.088 0.07 Length of Growing Period (LGP) 0.045 0.00 Distance to nearest motorable road (Km) 0.088 0.06 Distance to nearest electricity (Km) -0.291 0.01 Rainfall '00mm 0.018 0.00 Observations 496 R squared 0.61 Turning point (hectares) 61.68 Average partial effects 0.05 Partial Effects at 25% percentile 0.05 Partial Effects at 50% percentile 0.05 Partial Effects at 75% percentile 0.05 Partial Effects at 95% percentile 0.03 Partial Effects at 99% percentile -0.01
17
Econometric regression results (IV) Log of net value of production per ha owned Coef. P>t Area under crop ('ha) 0.086 0.00 Area under crop-- square -0.001 0.00 Length of Growing Period (LGP) 0.036 0.00 Distance to nearest motorable road (Km) 0.088 0.06 Distance to nearest electricity (Km) -0.291 0.01 Rainfall '00mm 0.014 0.01 Observations 496 R squared 0.59 Turning point (hectares) 58.54 Average partial effects 0.08 Partial Effects at 25% percentile 0.08 Partial Effects at 50% percentile 0.08 Partial Effects at 75% percentile 0.08 Partial Effects at 95% percentile 0.05 Partial Effects at 99% percentile -0.02
18
Conclusions• Current land policies undermine the long-term potential of smallholder
agriculture as a pro-poor growth engine
• Land policies and markets are not working for the smallholders
• Medium scale farmer growth is the outcome of political and economic
processes related to land administration
• These preliminary results indicate that the relationship between farm
sizes and productivity is not necessary inverse
• Productivity increases with farm sizes up to a certain threshold, and
thereafter falls
• Small may not be beautiful after all
• Rural poverty and food insecurity is likely to persist unless government
institutes pro-smallholders’ land access and enhanced agricultural
productivity policies
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