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

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

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

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)

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)

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

Descriptive: Farm size and crop choice (2014) Small (< 10 ha) Medium (10 - 50ha) 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%

Input use: any difference across farm types? Small (< 10 ha) Medium (10 - 50ha) 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 (10 - 50ha) 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 (10 - 50ha) 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

Yield (Quintals/ha): commercial farms produce more than double Small (< 10 ha) Medium (10 - 50ha) 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

Farm size yield relationship: non-parametric regression Maize Sorghum

Farm size yield relationship (cont.) Wheat Sesame

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

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)

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

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

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

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

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

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

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