Does informality help entrepreneurs achieve firm growth? evidence from a post-conflict economy

Figures & data

Table 1. Reasons for not registering company (in percentage), 2017.

Reasons for not registering	N	Percentage
Don’t know how (or where) to do so	8	4.47
Have not had the time	17	9.50
Don’t see benefit in doing so	97	54.19
Cannot afford to do so	40	22.35
Other	17	9.50
Totals	179	100.00

Source: Millennium Challenge Corporation 2017. Authors’ own calculations.

Note: This table includes only respondents that ticked one reason to have clear cut responses on reasons for not registering company.

Table 2. Treatment effects model: Impact of starting up unregistered and operating informally in desired firm growth.

VARIABLES	(1) Second stage equation	(2) First stage equation
Entrepreneur level explanatory variables
Entrepreneur’s age	−0.00220	0.0159**
	(0.00248)	(0.00784)
Gender (1 = male)	−0.0507	0.213
	(0.0584)	(0.192)
Marital status (1 = married)	0.0126	−0.440*
	(0.0840)	(0.237)
Education (1 = tertiary education)	−0.00922	−0.201
	(0.0689)	(0.199)
Firm level explanatory variables
Firm size (No of employees)	−0.00620	0.0311
	(0.0125)	(0.0368)
Necessity-driven entrepreneur	−0.287***	0.227
	(0.0753)	(0.206)
Urban location	0.125**	−0.283*
	(0.0518)	(0.170)
Manufacturing	−0.0711	0.255
	(0.0860)	(0.238)
Services	0.0944*	−0.418**
	(0.0573)	(0.168)
Treatment effect variable
1.Informality (1 = started unregistered and operating unregistered)	0.788***
	(0.132)
Instrumental variable
Perception of entrepreneurship environment		0.437**
		(0.209)
Constant	0.509***	−1.874***
	(0.118)	(0.400)
Diagnostics
/athrho	−1.435*** (0 .165)
/lnsigma	−0.623*** (0.022)
Wald test of indep. eqns. (rho = 0): chi2(1) = 75.87 Prob > chi2 = 0.0000
Log pseudo likelihood = −436.40864
N	487	487

Robust standard errors in parentheses.

*** p < 0.01,

** p < 0.05,

* p < 0.1.

Table 3. The cases.

	Formal				Informal
Entrepreneur	A1	B1	C1	D1	A2	B2	C2	D2
Gender	M	M	M	F	M	M		F
Age (years)	26	42	32	12	30	38	38	41
Firm
Age (years in operations)	7	20	6	34	5	15	5	5
Sector	Online shopping and delivery	Construction	Services (design and web services)	Food processing	Online shopping and delivery	Construction	Services (design and web services	Food processing
Number of employees	11	8	5	22	7	5	3	5

Source: Authors’ qualitative interviews.