Determinants of rural households’ livelihood diversification strategies: In the case of north Wollo zone, Amhara National Regional State, Ethiopia

Figures & data

Figure 1. Conceptual Framework: Determinants of rural livelihood diversifications.

Sources: Adapted from Ellis (1998), DFID (Department for International Development; 1999), and Barrett et al. (2001).

Figure 2. Map of Study Area.

Source: Made by the author (2020)

Table 1. Sample size distribution for each sample districts

Name of districts	Number of rural household	Number of sample household
Wadila	12,776	100
Raya kobo	20,017	156
Meket	16,509	128
Total	49,302	384

Source: Own computation based on districts administration data, 2020

Table 2. Definition, measurement, and hypothesis of variables used in the MVP Model

	Variable	Type and definitions	Measurements	Expected effect/ Hypothesis
Dependent Variables	Livelihood diversification strategies choice	Polychromous, livelihood diversification strategies	k = 1, Agriculture k = 2, Non-farm income k = 3, Off-farm income	Agriculture	Non-farm income	Off-farm income
Independent Variables	Sex of the household head	Dummy, sex of a household head	1 = Male, 0 = Female	+	-	-/+
	Age of head of the household	Continuous, age of household head	years completed	-	-	-
	Family size	Continuous, numbers of family size of the head	Number	+	+	+
	Dependency ratio	Continuous, family members < 15 > 64 old age	in adult equivalent	+	+	+
	Level of education	Continuous, education completed by household head	Years of schooling	+	+	-
	Size of land	Total farm land cultivated owned by household head	Hectare	+	-	-
	Livestock	Continuous, number of livestock owned by the household head	In TLU	+	-	+
	Distance to market	Continuous, distance from nearest market	kilometers	+	+	+
	Extension contact	Continuous, frequency of the household head from agricultural extension office	Frequency	+	-	-
	Total income	Continuous, the total income of a household head	ETB	+	+	+
	Membership in Cooperatives	Dummy, membership in cooperatives	1 = Yes, 0 = Otherwise	+	+	-
	Credit Access	Dummy, credit use by the household head	1 if HHS used credit, 0 = Otherwise	+	+	-
	Access to Irrigation	Dummy, access to irrigation	1 = Yes, 0 = Otherwise	+	-	-
	Receiving remittance	Dummy, access to economic support	1 = Yes, 0 = Otherwise	+	+	-
	R-Productive Safety Net Project	Dummy, participating in the project	1 if a household head is participating in Rural-Productive Safety Net Project and 0, otherwise.	+	+	+

Table 3. Sex of sample household head (categorical variables)

Variables	Categories	Summary statistics of total sample households
		Frequency	Percentage
Sex of Household Head	Female	77	20.05
	Male	307	79.95
Cooperative Membership	Non-member	115	29.95
	Member	269	70.05
Credit Use	Non-users	51	13.28
	Users	333	86.72
Irrigation Use	Non-users	147	38.28
	Users	237	61.72
Remittance	Non-receivers	173	45.05
	Receivers	211	54.95
Participation in productive safety net	Non-participants	79	20.57
	Participants	305	79.43

Source: Own survey results, 2020

Table 4. Demographic, socio-economic, and institutional characteristics of household heads (continuous variables)

Variables	Variable Names	Mean	Std. Dev
AGEHH	Age of household head	47.98	11.39
FMZ	Family size	1.97	1.43
DEPR	Dependent ratios	0.79	0.58
EDUHH	Formal education level of household head	2.66	2.08
LAND	Land holding	0.79	0.37
LVSTKTLU	Total livestock unit	2.57	1.87
TOTINC	Total income of household head	42,386.38	17,151.5
DISTMK	Distance to the nearest market	1.61	0.73
EXTCONT	Extension contact frequency	4.79	2.44

Source: Own survey results, 2020

Table 5. Summary of the livelihood strategies adopted by rural household

Variables	Observation	Mean	Std. Dev.
Agriculture	384	0.7161458	0.4514551
Non-farm	384	0.640625	0.4804433
Off-farm	384	0.5911458	0.4922636

Source: Own survey results, 2020

Table 6. Multivariate probit estimation results for determinants livelihood diversification strategies choice

Variables	Agriculture		Non-farm		Off-farm
	Coef.	Std. Err.	Coef.	Std. Err.	Coef.	Std. Err.
Age of household head	0.0098	0.0068	−0.004	0.006	−0.001	0.006
Sex of household head	0.317*	0.185	−0.294*	0.177	0.407**	0.183
Family Size	0.042	0.056	0.058	0.051	0.005	0.054
Dependency ratio	0.142	0.139	0.259**	0.123	−0.093	0.129
Formal Education level	0.026	0.036	0.056*	0.033	−0.057	0.037
Land holding	0.463*	0.238	0.043	0.214	−0.894***	0.242
Livestock (TLU)	0.049	0.049	0.050	0.042	−0.127***	0.042
Distance to market	−0.323***	0.113	−0.146	0.104	−0.178	0.114
Extension contact frequency	0.016	0.034	−0.042	0.030	−0.021	0.032
Total income	3.26e-06	4.96e-06	0.000012***	4.57e-06	−1.78e-06	4.80e-06
Cooperative membership	0.717***	0.177	−0.013	0.171	−0.854***	0.191
Credit use	0.338	0.213	0.126	0.198	−0.375*	0.227
Irrigation use	0.185	0.158	0.150	0.144	0.016	0.159
Remittance	0.087	0.154	0.394***	0.142	−0.187	0.152
RPSFTNTP	0.359***	0.183	−0.349**	0.176	−0.449**	0.194
Constant	−1.686***	0.576	−0.037	0.508	3.100***	0.581
Predicted probability	0.723		0.642		0.589
Joint probability (success)		0.234
Joint probability (failure)		0.000
Number of draws (#) = 15		Number of obs. = 384		Log likelihood = −590.90
Wald chi2(45) = 245.19 ***		Prob > chi2 = 0.0000
(-) rho21***, and (+) rho32**
Likelihood ratio test of rho21 = rho31 = rho32 = 0 chi2(3) = 37.81***

Dependent variable is livelihood diversification strategies choice where Y1 = Agriculture, Y2 = Non-farm, and Y3 = Off-farm.

Note: ***, ** and *are statistically significant at 1%, 5% and 10% significance levels respectively.

Source: Own computation from survey result, 2020

Ellis, F. (1998). Household strategies and rural livelihood diversification. Journal of Development Studies, 35(1), 1–38. https://doi.org/10.1080/00220389808422553

 Web of Science ®Google Scholar

DFID (Department for International Development). (1999). Sustainable Livelihoods Guidance Sheets (Sections 1 & 2). (Accessed November 24, 2016). http://www.eldis.org/go/topics/dossiers/livelihoods

 Google Scholar

Barrett, C. B., Reardon, T., & Webb, P. (2001). Nonfarm income diversification and household livelihood strategies in rural Africa: Concepts, dynamics, and policy implications. Food Policy, 26(4), 315–331. https://doi.org/10.1016/S0306-9192(01

 Web of Science ®Google Scholar