1. Does inclusion of large farms reverse the farm-size productivity relationship? Evidence from Ethiopia
Sinafikeh Gemessa, Daniel A. Ali, Klaus Deininger
Annual World Bank Conference on Land and Poverty
20 March 2017

2. Motivation – what does existing empirical evidence tell us?
Agricultural production is characterized by constant returns to scale, and
A recurring evidence in the literature of agricultural production has been the existence of an inverse farm-size productivity relationship. The potential explanations include:
application of more than the optimum amounts of inputs due to imperfections in labor, land and insurance markets (e.g., Sen 1972, Feder 1985; Barrett 1996; Ali et al. 2014);
a failure to properly measure land size and unobserved soil quality (e.g., Lamb 2003)
But, almost all the empirical applications use data from smallholder agriculture

3. Empirical literature focuses on smallholder agriculture
Average and standard deviation of land size for some studies that look at inverse land size & yield r/ship
Study
Country
Mean
S.D
Ali and Deininger (2014)
Rwanda
0.46
Chen et al. (2010)
China
0.66
0.59
Barrett et al. (2010)
Madagascar
6.64
7.70
Lamb (2003)
India
0.88
Heltberg (1998)
Pakistan
3.00
Barrett (1996)
13.40
Benjamin (1995)
Indonesia
0.76
0.01

4. This paper…. Aims at contributing to the debate by:
Including commercial farms in the analysis;
Looking at not only physical yield or value output but also some measure of “profit” (but heavily depends on availability of input prices, e.g., for family labor)

5. Data
Two rounds of smallholder panel household survey (<10h); 2014, 2016
Two rounds of panel large and medium commercial farm survey (10 ha and above); 2014, 2015
The data allow us to address measurement error related issues:
Farm area is measured using handheld gps – ‘better than farmer estimation’
Panel nature of the data helps to control for unobserved household level heterogeneity (to some extent parcel characteristics)

6. Distribution of farm size
Median size in ha
Smallholders = 0.3
Commercial Farms = 93
The last centile
Smallholders = 4.4
Commercial Farms = 2385

7. Descriptive: Farm size and crop choice (2014)
Small (< 10 ha)
Medium ( ha)
Large (>50ha)
No of operational farms (sample)
1194
404
530
Total area per farm (ha)
1.4
29.1
329.0
… % for maize
15.9
10.1
12.5
… % for sorghum
21.6
41.8
18.5
… % for wheat
9.6
1.9
14.3
… % for sesame
4.4
35.6
46.1
… % for other grains
48.5
10.6
8.7
Grain area per farm (ha)
1.3
28.6
322.5
52%
89%
91%

8. Input use: any difference across farm types?
Small (< 10 ha)
Medium ( ha)
Large (>50ha)
% using fertilizer
60.2
100.0
99.7
if yes, quantity (KG/ha)
88.5
208.8
243.5
% using improved seed
21.3
11.4
23.0
% using other chemicals
31.4
55.7
74.5
% using hired labor
26.6
% owning tractor
0.0
66.2
Number of tractors owned
0.5
1.4
Area per tractor (ha/one tractor)
23.6
331.9
Has machine pulled plow/harrower
26.1
47.3
Has combine harvestor
4.9
Has thresher
5.3
13.4
Has water pump
23.3
29.0
Small (< 10 ha)
Medium ( ha)
Large (>50ha)
% using fertilizer
60.2
100.0
99.7
if yes, quantity (KG/ha)
88.5
208.8
243.5
% using improved seed
21.3
11.4
23.0
% using other chemicals
31.4
55.7
74.5
% using hired labor
26.6
Small (< 10 ha)
Medium ( ha)
Large (>50ha)
% owning tractor
0.0
31.4
66.2
Number of tractors owned
0.5
1.4
Area per tractor (ha/one tractor)
23.6
331.9
Has machine pulled plow/harrower
26.1
47.3
Has combine harvestor
4.9
Has thresher
5.3
13.4
Has water pump
23.3
29.0

9. Yield (Quintals/ha): commercial farms produce more than double
Small (< 10 ha)
Medium ( ha)
Large (>50ha)
Maize
12.0
31.4
34.2
Sorghum
10.6
21.9
21.6
Wheat
10.2
17.0
20.7
Sesame
4.5
8.5
8.2

10. Farm size yield relationship: non-parametric regression
Maize
Sorghum

11. Farm size yield relationship (cont.)
Wheat
Sesame

12. Farm size and value of grain output (Q/ha)

13. Estimation strategy: Farm fixed effects, controlling for survey year
Physical yield of selected crops
Value of grain output
Profit (accounting for value of purchased inputs only)

14. Maize - log(yiled) Smallholders Commercial farms Pooled (1) (2) (3)
(1)
(2)
(3)
(4)
(5)
(6)
log (area in ha)
-0.41***
-0.44***
-0.27***
-0.34***
-0.39***
-0.33***
(0.032)
(0.033)
(0.079)
(0.122)
(0.035)
(0.040)
log (area in ha) squared
-0.00
0.00
(0.006)
Input use (fertilizer, chemicals, improved seed) NO
YES
Observations
2,267
334
272
2,613
2,551
R-squared
0.130
0.177
0.069
0.230
0.118
0.188

15. Sorghum - log(yiled) Smallholders Commercial farms Pooled (1) (2) (3)
(1)
(2)
(3)
(4)
(5)
(6)
log (area in ha)
-0.39***
-0.31***
-0.29***
-0.36***
-0.32***
(0.044)
(0.035)
(0.085)
(0.030)
(0.042)
log (area in ha) squared
0.01*
0.01
(0.005)
(0.008)
Input use (fertilizer, chemicals, improved seed) NO
YES
Observations
1,315
981
600
2,303
1,923
R-squared
0.120
0.152
0.144
0.233
0.180

16. Wheat - log(yiled) Smallholders Commercial farms Pooled (1) (2) (3)
(1)
(2)
(3)
(4)
(5)
(6)
log (area in ha)
-0.34***
-0.35***
-0.43**
0.17
-0.28***
(0.046)
(0.047)
(0.211)
(0.946)
(0.065)
(0.075)
log (area in ha) squared
-0.02
-0.01
(0.014)
(0.016)
Input use (fertilizer, chemicals, improved seed) NO
YES
Observations
1,125
120 65
1,249
1,194
R-squared
0.097
0.151
0.071
0.342
0.138
0.159

17. Sesame - log(yiled) Smallholders Commercial farms Pooled (1) (2) (3)
(1)
(2)
(3)
(4)
(5)
(6)
log (area in ha)
-0.36***
-0.32***
-0.72***
-1.06***
0.06
-0.23**
(0.126)
(0.116)
(0.045)
(0.081)
(0.083)
(0.099)
log (area in ha) squared
-0.02**
0.01
(0.010)
(0.012)
Input use (fertilizer, chemicals, improved seed) NO
YES
Observations
195
1,497
1,021
1,692
1,215
R-squared
0.097
0.324
0.260
0.599
0.527
0.686

18. Value of grain output in Birr- log(value per ha)
Smallholders
Commercial farms
Pooled
(1)
(2)
(3)
(4)
(5)
(6)
log (area in ha)
-0.12***
-0.22***
-0.82***
-0.74***
-0.17***
(0.017)
(0.021)
(0.044)
(0.053)
(0.020)
(0.025)
log (area in ha) squared
0.01*
0.00
(0.003)
Input use (fertilizer, chemicals, improved seed) NO
YES
Observations
2,596
2,216
2,115
6,081
5,980
R-squared
0.042
0.113
0.242
0.345
0.371
0.387

19. Profit in Birr - log(profit per ha)
Smallholders
Commercial farms
(1)
(2)
(3)
(4)
log (area in ha)
-0.16***
-0.22***
-0.84***
-0.82***
(0.021)
(0.026)
(0.046)
(0.052)
Input use (fertilizer, chemicals, improved seed) NO
YES
Observations
2,168
2,072
2,216
2,115
R-squared
0.238
0.361
0.242
0.345

20. Implications for future research
Results show that inclusion of commercial farms (at least in the Ethiopian context) does not reverse the inverse farm size productivity relationship
There is a need to investigate for potential causes:
Re-visit market imperfections (labor, land and insurance markets) if they also affect the performance of commercial farms
Assess the effect of farm heterogeneity – e.g., does level of mechanization play a role?
Re-visit measurement error related issues – e.g., does large commercial farms tend to underreport for fear of taxation?
if not time varying, it will be controlled for by the FE strategy
use of remote sensing data might help for future data collection