Intensity of income diversification among small-holder farmers in Asayita Woreda, Afar Region, Ethiopia

Figures & data

Figure 1. Map of the study area

Table 1. Definition and units of measurement for explanatory variables used in fractional response model

Variables	Definition	Measurement	Expected sign
MALEHEAD	Sex of household	Male/female 1 if male, 0 Otherwise	+
AGE	Age of household	Years	+
EDUSTAT	Educational status	1 literate,0 otherwise	+
HHSIZ	Household size	Number	+
DEPR	Dependency ratio	Ratio	-
SKILL	Special skill	Yes/no 1 if yes, 0 otherwise	+
INCOME	Annual income of household	Birr	+
ACCEP	Electric power access	Yes/no 1 if yes, 0 otherwise	+
DAM	Distance from market	Hour	-
REMITA	Remittance	Yes/no 1 if yes, 0 otherwise	+
ATTRA	Access to training	Yes/no 1 if yes, 0 otherwise	+
CREDITU	Credit utilization	Yes/no 1 if yes, 0 otherwise	+
LIVEST	Tropical livestock unit	TLU	+
FARMSIZ	Farm size	Hectare	-

Table 2. Descriptive statistics of categorical variables with income diversification

Variables	Variable descriptions	Diversification index (SID)
		Freq	%	Mean	St. Dev.	T value
MALEHEAD	Male-headed households	118	77.1	0.24	0.26	− 0.09
EDUSTAT	Literate households head	62	40.52	0.38	0.26	5.9***
CREDITU	Credit utilize	62	40.52	0.22	0.26	0.76
ACCEP	Household access to electric power	77	50.33	0.3	0.27	3.5***
SKILL	Household who have skill	55	35.95	0.51	0.14	2.7**
ATTRA	Household who got training	73	47.71	0.18	0.28	2.6**

Note: *** and * Significant at p < 0.01 and p < 0.1 respectively. Source: Survey result, 2017

Table 3. Descriptive statistics of continuous variables with income diversification

Variables	Variable descriptions	Diversification index (SID)
		Mean	St. Dev.	Min.	Max.	Correlation coefficient
AGE	Age of the head	53.64	13.08	26	80	−0.11
HHSIZ	Household size (number)	5.57	2.69	2	15	0.19**
DEPR	Dependency ratio	1.13	0.87	0	3	−0.17**
FARMSIZ	Farm size (ha)	2.81	2.03	0.5	5	−0.28***
LIVESTOK	Livestock herd size	19.39	19.7	0	67	−0.15*
DAM	Walking distance to local market	1.53	0.95	0.2	4	−0.79***
INCOME	Annual income of the household (ETB)	74,339.6	36,664.12	12,000	276,300	0.37***

Note: ***^, ** and * Significant at p < 0.01, p < 0.05 and p < 0.1 respectively. Source: Survey result, 2017

Table 4. Fractional response probit model results on income diversification

Predictor variables	dy/dx	Coefficient	Robust std. Err	Z value	p>|z|
MALEHEAD	0.0428	0.129**	0.057	2.25	0.024
AGE	0.0001	0.000	0.002	0.15	0.877
HHSIZ	0.0091	0.027*	0.015	1.83	0.068
EDU	0.0875	0.265***	0.075	3.5	0.000
DEPR	− 0.0071	−0.021	0.033	−0.64	0.523
REMITA	0.0325	0.098	0.066	1.48	0.139
SKILL	0.0441	0.132*	0.073	1.8	0.072
FARMSIZ	− 0.0091	−0.004	0.015	−0.32	0.747
CREDITU	0.0903	0.274***	0.086	3.16	0.002
LIVESTOCK	−0.0011	−0.003	0.002	−1.51	0.132
DAM	−0.1177	−0.357***	0.046	−7.73	0.000
ACCEP	0.0659	0.199***	0.064	3.09	0.002
Log INCOME	0.0231	0.085*	0.046	1.85	0.065
ATTRA	0.0092	0.028	0.079	0.36	0.722
CONSTANT	-	−1.444	0.515	−2.8	0.005

Number of obs = 153, Wald chi² (14) = 365.35, Prob > chi² = 0.0000, Pseudo R² = 0.1388, Log pseudo likelihood = −89.097634. ***, ** and * indicates statically significant at 1, 5 and 10% respectively

Figure 2. Distribution of the farmers by their intensity of income diversification

Source: Survey result, 2017