Productivity and efficiency heterogeneity among maize smallholder farmers in Ethiopia

Figures & data

Table 1. Sample size per kebele.

Kebeles	Target population (n)	Proportion of sample per kebele	Sample per kebele
Kudmi	4103	n/N = 4103/7235 = 0.57	198*0.57 ≈ 112
Dilbetigel	3132	n/N = 3132/7235 = 0.43	198*0.43 ≈ 86
Total (N)	7235	—	198

Table 2. Definitions and measurements of variables.

Variable	Description	Unit
Yield	Maize output per land cultivated	Kg
Seed	Improved seed	1= if improved maize seed used, 0 = otherwise
DAP	DAP	Kg
UREA	UREA	Kg
Labor	Man labor used to grow Maize^4	Man-Equivalent
Livestock	Total number of livestock owned	TLU
Credit	Access to credit	1 = yes, 0 = otherwise
Gender	Gender of the household head	1 = male,0 = female
Extension	Extension service	1= if farmers had extension advisory services; 0= otherwise;
Irrigation	Irrigation use	1 = yes, 0= no
Pesticide	Pesticide use	1 = yes, 0= no
Age	Age of the household head	Year
Market-dis	Market distance	Kilometer
Fragment	Fragment	Plot
Land_Owned	Land size owned by the household	Hectare
Gender	Gender of the household head	1 = male,0 = female
Hazard	Hazard perception	1 = if the household has been perceived no environmental hazard (like drought, flood, snow…) in the 2018/19 production year, and 0= otherwise.
Input_acc	Input access	1= if farmers access farming inputs at the required time and amount, and 0= otherwise
Cropping	Simultaneous production of other crops with Maize	1 = yes, 0= no
Education	The educational level of the household head	Measured in years of schooling
Farm_struc	Farm structure	1= if farmers cultivate their own land and 0= otherwise
Exp-price	Expected maize price	1= if they perceive an increase in Maize in the next harvest season and 0= otherwise
Plot_dis	Plot distance to the residence of the respondents	Kilometer

Table 3. Socio-demographic characteristics of surveyed households.

Variable	Obs	Mean	Std. Dev	Min	Max
Yield	198	32.37	14.43	2.67	48
Age	198	42.52	17.45	19	88
Gender	198	0.69	0.46	0	1
Market_Dis	198	18.63	8.08	4	35
Fragment	198	3.73	1.57	1	7
Input_acc	198	0.47	0.50	0	1
Cropping	198	0.53	0.50	0	1
Plot distance	198	3.78	1.60	0.5	7
Education	198	1.43	2.24	0	11
Land_owned	198	1.08	0.47	0.25	1.75
Land Cult	198	0.78	0.38	0.25	1.50
Pesticide	198	0.48	0.50	0	1
Seed	198	0.43	0.50	0	1
Irrigation	198	0.70	0.46	0	1
Livestock	198	10.66	7.53	1.07	38.5
Labor	198	9.08	5.51	1	28
Credit	198	0.34	0.47	0	1
UREA/hec	198	180.77	155.16	12.5	1000
Extension	198	0.57	0.50	0	1
DAP/hec	198	220.71	208.74	12.5	1100

Figure 1. Productivity and efficiency heterogeneity by different characteristics of the households.

Table 4. The stochastic frontier half-normal model estimation result.

lnYield	Observed coef	Bootstrap Std. Err	z	P > z	Normal-based [95% Conf	Interval]	Sig
Irrigation	0.156	0.050	3.120	0.002	0.058	0.255	***
Seed	0.168	0.052	3.220	0.001	0.066	0.271	***
Pesticide	−0.025	0.048	−0.530	0.598	−0.118	0.068
lnLivestock	0.108	0.081	1.340	0.181	−0.050	0.267
lnLabor	0.268	0.080	3.350	0.001	0.111	0.425	***
Credit	0.071	0.059	1.210	0.225	−0.044	0.187
lnUREA/hec	−0.079	0.043	−1.850	0.064	−0.163	0.005	*
lnDAP/hec	0.436	0.038	11.330	0.000	0.360	0.511	***
_cons	0.165	0.372	0.440	0.657	−0.564	0.895	***
/lnsig2v	−2.563	0.604	−4.240	0.000	−3.747	−1.379
/lnsig2u	−3.171	3.768	−0.840	0.400	−10.557	4.214
sigma_v	0.278	0.084			0.154		0.502
sigma_u	0.205	0.386			0.005		8.223
sigma2	0.119	0.146			−0.167		0.405
lambda	0.738	0.426			−0.098		1.574

Note: ***p < 0.01, **p < 0.05, *p < 0.1; Number of obs = 198; Bootstrap Replications = 9,994; Wald chi2(11) = 838.18; Log likelihood = −45.000112; Prob > chi² = 0.0000.

Table 5. Summary statistics.

Variable	Obs	Mean	Std. Dev	Min	Max
TE	198	0.856	0.041	0.687	0.931
EE	198	0.861	0.088	0.544	0.975
AE	198	0.738	0.091	0.470	0.883

Table 6. Determinants of efficiency in maize production among sample households.

	(1)	(2)	(3)
Variables	TE model	EE model	AE model
Age	−0.002***	0.001	−0.004*
	(0.004)	(0.010)	(0.002)
Gender	−0.007	−0.031***	−0.032***
	(0.006)	(0.011)	(0.011)
Extension	0.006	0.006	0.009
	(0.005)	(0.011)	(0.011)
Market-dis	−0.002**	0.001	−0.001
	(0.002)	(0.001)	(0.001)
Fragment	−0.007***	−0.004	−0.009**
	(0.002)	(0.004)	(0.004)
Exp-price	0.016***	0.044***	0.052***
	(0.005)	(0.010)	(0.011)
Cropping	0.006	0.016	0.019*
	(0.005)	(0.010)	(0.010)
Education	−0.001	−0.018***	−0.016***
	(0.001)	(0.002)	(0.002)
Farm_struc	−0.003	0.006	0.003
	(0.005)	(0.010)	(0.010)
Hazard	−0.004	−0.002	−0.005
	(0.005)	(0.010)	(0.010)
Plot_dis	−0.012**	0.007**	0.004
	(0.004)	(0.003)	(0.003)
Input_acc	0.038	0.018	0.046
	(0.114)	(0.547)	(0.141)
Gender* Input_acc	−0.075***	−0.049**	−0.082
	(0.030)	(0.014)	(0.114)
Constant	0.921***	0.861***	0.795***
	(0.015)	(0.029)	(0.030)
/sigma	0.035***	0.068***	0.071***
	(0.002)	(0.003)	(0.004)

Note: Standard errors in parentheses ***p < 0.01, **p < 0.05, *p < 0.1.

Figure 2. Graph plot of quantile regression result.

Data availability statement

The data that support the findings of this study are available from the corresponding author, Mengistu Alemu, upon reasonable request.