Analysis of factors affecting technical efficiency of A1 smallholder maize farmers under command agriculture scheme in Zimbabwe: The case of Chegutu and Zvimba Districts

Figures & data

Figure 1. Location of study areas in Mashonaland West Province, Source: (Google maps).

Figure 2. Conceptual framework, source: Modified from (Kassa, 2017).

Table 1. Description of the variables in the model

Variable	Variable name	Type of variable	Description of variable
Yi	Output	Continuous	Total yield/ hectare of maize harvested cultivated under command agriculture scheme (2018/2019 season) expressed in kilogram
X1	Basal fertiliser	Continuous	Total quantity of basal fertiliser per hectare applied to maize expressed in kilograms
X2	Top dressing	Continuous	Total quantity of top dressing applied in kilograms
X3	Labour	Continuous	Total labour utilised in maize production expressed in man-day equivalents (expressed in adult equivalent days per ha, as the sum of family labour and hired labour)
X4	Area	Continuous	Land area allocated to maize under Command Agriculture Scheme in the 2018/2019 season expressed in hectares
	Socio-economic factors
Z1	Age	Continuous	Age of famer in number of years
Z2	Maize farming experience	Continuous	Experience of the farmer in number of years
Z3	Education level	Dummy variable	Educational level of farmer, a dummy variable which takes the value of (1 = tertiary and secondary education, and 0 = otherwise)
Z4	Source of income	Dummy variable	Source of income, dummy variable (1 = Salary and wages, 0 = otherwise)
Z5	Marital status	Dummy variable	Marital status, dummy variable (1 = married, 0 = otherwise)
Z6	Household size	Continuous	Number of family members in the household
Z7	Gender	Dummy variable	Gender of household head (1 = female, 0 = male)
Z 8	Occupation	Dummy variable	Employment of the household head (1 = formal employment, 0 = otherwise)

Table 2. Summary of descriptive statistics

Sampled households				Chegutu district		Zvimba district		Total
Variable	Class			Number of respondents		Number of responde		Variable
				Frequency	Percentage			Frequency
Gender	Male			67	55.83	66	55	133
	Female			53	44.17	54	45	107
Total				120	100	120	100	240
Marital status	Married			57	47.50	58	48.33	115
	Widowed			14	11.67	23	19.17	37
	Divorced			8	6.67	7	5.83	15
	Single			41	34.17	32	26.67	73
Total				120	100	120	100	240
Education status	Pre-school			3	2.5	1	0.83	4
	Primary education (grade1-7)			23	19.17	29	24.17	52
	Secondary education (Form1-6)			55	45.83	60	50	115
	Tertiary education			39	32.50	30	25	69
Total				120	100	120	100	240
Occupation status	Full-time farmer			45	37.50	43	35.83	88
	Part-time farmer			37	30.83	42	35	72
	Pensioner			10	8.33	8	6.67	18
	Formally employed			28	23.33	27	22.5	55
Total				120	100	120	100	240
Other source of Income	Salaries Wages		and	28	23.33	26	21.67	54
	Retirement pension			11	9.17	13	10.83	24
	Remittances			43	35.83	40	33.33	83
	None			38	31.67	41	34.17	79
Total				120	100	120	100	240
Age	20-30			14	11.67	8	6.7	22
	31-40			31	25.83	40	33.3	71
	41-50			36	30	41	34.2	75
	51-60			33	27.5	25	20.83	58
	61-70			6	5	5	4.2	11
	71-80					1	0.83	1
Total				120	100	120	100	240
Maize producing experience	1-5			9	7.5	20	16.67	29
	6-10			35	29.17	40	33.33	75
	11-15			67	55.83	49	40.83	116
	16-20			8	6.67	11	9.17	19
	21-25			1	0.83			1
Total				120	100	120	100	240
Household size	1-5			71	59.17	67	55.83	138
	6-10			44	36.67	53	44.17	97
	11-15			5	4.17			5
Total				120	100	120	100	240
	Chegutu district					Zvimba district
	Min		Max		Ave	Min	Max		Ave
Age		23	69		44.42	24	73		46.48
Household size		1	13		5.36	2	10		4.96

Maize 2 2 1 1 1 2 19 9.49 producing experience

Table 3. Frequency table for technical efficiency

Technical efficiency (%)	Chegutu district		Zvimba district
	Frequency	Percentage	Frequency	Percentage
30<	1	0.8%	1	0.8%
31–50	3	2.5%	9	7.5%
51–60	2	1.6%	5	4.2%
61–70	3	2.5%	5	4.2%
71–80	18	15%	7	5.8%
81–90	35	29%	30	25%
91–100	58	48%	63	52.5%
Total	120	100%	120	100%
Mean TE	85%		94%
Minimum TE	27%		29%
Maximum TE	97%		99%

Table 4. Results for stochastic frontier normal /truncated-normal model

Variables	Chegutu District		Zvimba District
	Log likelihood = 29.7771 Number of observations = 120 Wald Chi^2(4) = 166.77 Prob > Chi^2 = 0.0000		Log likelihood = 51.0131 Number of observations = 120 Wald Chi^2(4) = 146.77 Prob > Chi^2 = 0.0000
	Coefficient P > I z I		Coefficient P > I z I
Efficiency
ln Basal Fertilizer	.5050014	0.012**	.1601673	0.002***
ln Topdressing (Nitrogen) fertilizer	.0078996	0.958	.1015932	0.021**
ln Labour	.433437	0.000***	.0018922	0.945
ln Area	.4862647	0.000***	.2732007	0.000***
Constant	−3.166892	0.000	−.2027457	0.297
Inefficiency
Age	.0160226	0.073*	−.0056353	0.543
Maize farming experience	−.0636937	0.024**	−.0651351	0.003***
Education	−.4618088	0.100	−.7382213	0.008***
Other source of Income	.1257705	0.148	.2850171	0.021**
Marital status	−.2394319	0.229	−.3986791	0.040**
Household size	−.0568161	0.260	.0394243	0.384
Gender	−.6177181	0.173	.3998544	0.004***
Occupation	−.0880149	0.777	.3865227	0.030**
Cons	.5893647	0.100	.2587617	0.224
Diagnostics
Sigma_u	.2935304	0.001	.0487456	0.000
Sigma_v	.1451364	0.000	.1565852	0.000
lambda	2.022445	0.000	.3113042	0.000
Mean technical efficiency = 84%			Mean technical efficiency = 94%

*, ** and *** means significance at 10%, 5% and 1%, respectively

Table 5. Elasticity of production and returns to scale (RTS)

Variable	Chegutu district	Zvimba district
	Elasticity	Elasticity
In Basal Fertiliser	.5050014	.1601673
In Topdressing (Nitrogen) fertiliser	.0078996	.1015932
In Labour	.433437	.0018922
In Area	.4862647	.2732007
RTS	1.4326027	0.5368534

Kassa, Y. (2017). Determinants of technical efficiency in maize production of smallholder farmers; The Case of Fogera District, South Gondar Zone, Ethiopia. University of Gondar. https://core.ac.uk/download/pdf/199937443.pdf

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