Does entrepreneurship improve the livelihood of young people? Evidence from the NDE program beneficiaries in Kano state, Nigeria

Figures & data

Figure 1. Map of the study Areas.

Table 1. Socioeconomic and Demographic characteristics of the respondents

Variable	Pooled	Entrepreneurs (n = 148)	Non-entrepreneurs (n = 118)	z-value
Age	25.76	26.58	24.74	−2.94***
Gender (Male)	41.35	45.95	35.59	−1.70*
Marital status (Married)	43.61	48.65	37.29	−1.86*
Years of formal education	12.96	12.53	13.51	2.43**
Household size	9.16	8.98	9.38	0.59
Household head (Yes)	31.20	37.84	22.88	−2.62***
Current residence
Rural area	6.35	6.76	5.93	0.28
Metropolitan city	88.92	9.54	87.29
Large city	4.74	2.70	6.78
Migration (Yes)	26.32	22.97	3.51	−1.39
Dependents (Yes)	68.05	68.92	66.95	−0.34
Consistent income (Yes)	53.01	66.89	35.59	−5.08***
Income	19197.93	26159.80	10466.10	−5.21***
Number of Entrepreneurs in Household	2.69	3.06	2.23	−2.67***
Asset index	.33	.40	.24	−6.26***
Contribution to household expenses (yes)	78.11	91.89	6.68	−6.10***
Perception of Entrepreneurship (Profitable)	91.35	93.24	88.98	−1.23

Source: Author’s computation using STATA 14.

*Significant at 10%, ** Significant at 5%, ***Significant at 1%.

Table 2. Institutional characteristics of the respondents

Variable	Pooled	Entrepreneurs (n = 148)	Non-entrepreneurs (n = 118)	z-value
Credit need (Yes)	9.80	93.88	86.41	−2.01**
Credit access (Yes)	4.51	7.43	.85	−2.57***
Training (Yes)	62.03	74.32	46.61	−4.63***
Group membership (Yes)	12.03	15.54	7.63	−1.97**

Source: Author’s computation using STATA 14.

*Significant at 10%, ** Significant at 5%, ***Significant at 1%.

Table 3. Full information maximum likelihood estimates of the EnSTER model for average monthly income

Variables	Model Estimates
	Entrepreneurship	Entrepreneurs	Non-Entrepreneurs
Age	0.054 (0.02)***	0.050(0.02)***	−0.037(0.03)
Gender	0.198(0.19)	0.225(0.17)	0.303(0.25)
log(Years of formal education)	−0.100(0.22)	0.526(0.19)***	0.364(0.33)
Marital status	−0.013(0.21)	−0.455(0.19)**	0.010(0.28)
log(Household size)	−0.285(0.17)*	−0.201(0.15)	0.187(0.22)
Migration status	−0.165(0.21)	−0.506(0.20)***	0.184(0.26)
Number of dependents	−0.168(0.20)	0.093(0.20)	0.163(0.25)
Consistent source of income	0.616(0.19)***	0.002(0.22)	−0.242(0.29)
Asset ownership	−0.438(0.19)**	0.431(0.19)**	0.567(0.26)**
Credit Access	1.182(0.54)**	−0.181(0.35)	0.919(0.94)
Group Membership	0.141(0.27)	−0.009(0.24)	0.923(0.39)**
No of Household Entrepreneurs	0.107(0.03)***
Entrepreneurship Training	0.552(0.19)***
_cons	−0.943(−0.94)	8.017(0.90)***	6.666(1.17)***
ρ1, ρ2		−0.700(0.26)*	0.917(0.05)***
Model Diagnosis
Wald chi2	50.02***
Log-Likelihood	−491.89
LR test of independence	17.93***

Source: Stata output using survey data.

Notes: Standard error in parenthesis.

*Significant at 10%, ** Significant at 5%, ***Significant at 1%.

Table 4. Full information max. likelihood estimates of the EnSTER model for living condition

Variables	Model Estimates
	Entrepreneurship	Entrepreneurs	Non-Entrepreneurs
Age	0.067(0.02)***	−0.003(0.01)	−0.026(0.02)
Gender	0.322(0.19)*	0.084(0.09)	−0.242(0.13)*
log(Years of formal education)	−0.049(0.24)	−0.022(0.09)	0.138(0.20)
Marital status	−0.024(0.22)	0.182(0.10)*	−0.018(0.15)
log(Household size)	−0.199(0.18)	0.187(0.07)***	0.114(0.12)
Migration status	−0.245(0.22)	0.433(0.10)***	0.170(0.13)
Number of dependents	−0.015(0.03)	−0.039(0.01)***	−0.020(0.02)
Consistent source of income	0.786(0.19)***	0.017(0.10)	−0.062(0.16)
Asset ownership	−0.497(0.20)***	0.048(0.10)	0.276(0.14)**
log(Household wealth status)	0.389(0.16)***	0.442(0.08)***	0.312(0.10)***
Household head employment type	−0.025(0.05)	0.039(0.02)*	0.096(0.03)***
No of Household Entrepreneurs	0.089(0.04)**
Entrepreneurship Training	0.648(0.18)***
_cons	−2.083(0.95)**	0.230(0.43)	0.147(0.63)
ρ1, ρ2		−0.818(0.09)***	−0.597(0.23)**
Model Diagnosis
Wald chi2	76.96***
Log-Likelihood	−316.66
LR test of independence	11.88***

Source: Stata output using survey data.

Notes: Standard error in parenthesis *Significant at 10%, ** Significant at 5%, ***Significant at 1%.

Table 5. Treatment effects

Outcomes	Entrepreneurship	Predictions		Treatment Effect
		Entrepreneurs	Non-entrepreneurs
(log)Income	ATT	9.66	7.09	2.57***
	ATU	1.58	8.66	1.92***
(log)Living condition	ATT	1.27	0.53	0.74***
	ATU	1.65	1.05	0.60***

Notes: *** denotes statistical significance at a 1 % level of significance.

Table A1. Description and definition of variables

Variable	Measurement	Expected sign for Livelihood
Dependents
Engagement in Entrepreneurship	Youth engagement in entrepreneurship (Engaged = 1, Otherwise = 0)	+
Living conditions	Satisfaction with living conditions, ranked between 1 and 10 (1 = Not satisfied, 10 =Very satisfied)
Income	Average monthly income of the respondent
Independents
Age	Age of respondent in years	+
Education	Years of formal education	+
Gender	Gender of the respondent (Male = 1, Female = 0)	+/-
Household Size	Number of people in a respondent’s household	+
Dependents	Number of people who depended on respondent	-
Marital Status	Dummy(Married = 1, Otherwise = 0)	+/-
Residence	Categorical (Rural = 1, Metropolitan = 2 Large city = 3)
Migration	A respondent who is a migrant in his/her current residence (Migrated to current residence = 1, Otherwise = 0)	-
Asset	Ownership of asset (Yes = 1, No = 0)	+
Access to Training	Participation in entrepreneurship training (Yes = 1, No = 0)	+
Access to Credit	Access to credit facilities (Yes = 1, No = 0)	+
Perception of Entrepreneurship	Dummy (Profitable = 1, otherwise = 0)	+
No o Household Entrepreneurs	Number of household engaged in entrepreneurship	+
Household head employment type	Type of employment of the head of the household of a respondent (Formal = 1, Informal = 0)	+/-