Impact of country-level corporate governance on entrepreneurial conditions

Figures & data

Figure 1. The relationship between worldwide governance index and global entrepreneurship index.

Table 1. Prior studies on CLCG and entrepreneurship

Panel A. Some previous studies related to CLCG
No.	Studies By	Sample		Methods	Results
		Size	Time limit
1	Avram et al. (2015)	132	2009– 2011	Regression, and PLS	Auditing strength and reporting norms are influenced by CLG.
2	Sayed and Chawla (2017)	9	2008– 2013	Multivariate regression	Analysts ‘ accuracy in Asian countries is influenced by CLCG.
3	Groşanu et al. (2015)	95	2007– 2012	Regression	Entrepreneurship and the ease of doing business are affected by CLG.
4	Hillier et al. (2011)	11	1990– 2003	OLS Regression	R&D to cash flow sensitivity decreased by strong corporate governance.
5	Pindado et al. (2015)	12	1986— 2003	Regression	R&D projects’ market valuation increased by effective corporate governance.
6	Lin et al. (2014)	44	2000– 2009	Regression	Information of semipublic stock rebalancing depends on the strength of quality of governance.
7	Boţa-Avram et al. (2018)	54	2006– 2015	Regression	There is a significant positive one direction relationship of CLCG and economic growth.
8	Agyemang et al. (2015)	39	2009– 2012	OLS Regression	Ethical behavior of firms is influenced positively and significantly by CLCG. (rule of law, control of corruption regulatory quality).
‘9	Rachisan et al. (2017)	132	2007– 2012	OLS Regression	The strength of investor protection is affected by CLCG.
10	Thenmozhi and Narayanan (2016)	111	1999– 2007	Cross- sectional regression	CLCG has no effect on post-acquisition performance where developed market firms acquire emerging market firms.
11	Curti and Mihov (2018)	1270 event s	2002– 2012	Descriptive Regression	CLCG plays a major role in fraud recovery for firms with low quality of risk management.
12	Ernstberger and Grüning (2013)	1044	2007	Descriptive, Regression.	Corporate disclosure is replaced by the legal environment and corporate governance arrangements.
13	Kamarudin et al. (2016)	74 bank s	2007– 2011	Data Envelopment Analysis	Income efficiency of traditional and Islamic banks in the GCC are influenced by and rule of law, Regulatory quality and voice and accountability. While RQ impacts Islamic banks, political stability and control of corruption affect commercial banks.
14	Saona and Martín (2016)	769	1997– 2013	Panel data models	A premium in the company market value is associated with the rule of law.
15	Sarhan et al. (2019)	494	2009– 2014	Descriptive regression	Quality of CLCG has a favorable and significant impact on voluntary compliance and disclosure.
16	Seifert and Gonenc (2018)	2914	2002– 2013	Descriptive, Regression.	The level of CLCG enhances the cash value and the quantity of money holding.
17	Tong et al. (2018)	171	2003– 2012	Panel data models	DOI is positively linked with CLCG; political stability, regulatory quality, rule of law and control of corruption.
Panel B. Some previous studies related to entrepreneurship
1	Amha and Ageba (2006)	974	2003 Survey	Percentages	Major hindrances for MSEs access to markets and finance
2	Ngunjiri (2010)	N.A	2008	Theoretical	Corruption is detrimental where formal institutions are relatively efficient.
3	Avnimelech et al. (2011)	176	2009– 2010	OLS Regression	Entrepreneurship is influenced significantly and negatively by corruption.
4	Jiménez and Alon (2018)	93	2002– 2007	Regression	Firm creation is significantly influenced by high level of corruption
5	Álvarez and Amorós (2014)	49	2001-	Regression	Entrepreneurship is positively influenced by unemployment
6	Álvarez et al.(2014)		2010		Legislation in developed countries but it is negative in other countries.
7	Shagbazian and Aistov (2017)	98 count ry	1999–2016	Regression	Early-stage business survival rate is significantly and positively associated with rule of law and control of corruption but no but no relationship with entrepreneurship.
8	Kim et al. (2015)	16 count ry	2004	Regression	Entrepreneurial action has a positive link with Social protection
9	Haggard and Haggard (2018)	71 count ry	2017	Regression	Legal origin impacts ease of getting credit, number of procedures and length of time needed.
10	Chambers and Munemo (2017)	119	2001– 2012	Regression	Countries with excessive barriers to entry and lack of high- quality governmental institutions have a significant and negative impact on business creation.
11	Dempster and Isaacs (2017)	47	2001– 2011	Panel least squares regressions	Level of entrepreneurial activity is determined by economic freedom (EF). EF moderates the relationship between productive entrepreneurship, human capital and corruption.
12	Estrin et al. (2017)	15	1999– 2005	logistic regressions	Creditors care about different elements of the bankruptcy process than do entrepreneurs.
13	Raza et al. (2019)	51	2001– 2008	logistic regressio	There is a strong association between entrepreneurial readiness and entrepreneurial behaviour.
14	Dheer (2016)	84	2005– 2014	Hierarchical multiple regression	“Individualism positively moderates the effect of political freedom, negatively moderates the effect of corruption, and positively moderates the effect of education, on the rate of entrepreneurial activity across nations”.
15	Shinnar et al. (2012)	3	NA	PLS model	Gender moderates the relationship between barriers and entrepreneurial intentions.
16	Tsai et al. (2016)	2	2010	Logistic regression	An inter-relationship of perceived capability & opportunity and fear of failure which is higher in China than Taiwan.
17	Tabares (2017)	62	2015– 2016	–	International entrepreneurial activity is affected by conditions in public policy regulations in Latin America
18	Ghosh (2016)	79	2001– 2016	Panel regression	“Entrepreneurial intention is reduced by stricter credit market regulation and more stringent labor regulations restricts job availability and thereby encourage more people to take up entrepreneurship as a career choice”.
19	Goltz et al. (2015)	53	2002– 2008	Logistic regression	Rule of law moderates the entry into entrepreneurship
20	Kim et al. (2012)	16	2004	Logistic regression	Social protection leads to skill developments and then encourage individuals to start business.
21	Giotopoulos et al. (2017)	32	2005– 2011	Regression	In adverse economic conditions, business opportunities influence high-quality entrepreneurship. There is gender impact on entrepreneurs’ high-growth intentions and export orientation
22	Peris-Ortiz et al. (2018)	44	2009– 2013	Regression	The association between innovation practices and TEA differs in accordance with the state of development of each economy.
23	Afzal, Mansur et al. (2018)	5	2010– 2016	panel model	Entrepreneurship capability is influenced positively by perceived opportunities and entrepreneurship as a good career choice but it is affected negatively by Fear of failure rate.
24	Schillo et al. (2016)	67	2009– 2012	Multilevel logistic Regression	“Entrepreneurial readiness has significant explanatory power with regard to individuals’ entrepreneurial intention”.
25	Darnihamed ani et al., (2018)	53	2004– 2011	Regression	Innovative entrepreneurship is negatively influenced by corporate taxes but it is positively associated with high start-up costs.
26	Aidis et al. (2012)	47	1998– 2005	Regression	There is an inverse relationship between the size of the government and entrepreneurship entry.
27	Urbano and Aparicio (2016)	43	2002– 2012	Regression	Entrepreneurship capital types have a positive effect on economic growth
28	Afzal, Siddiqui et al. (2018)	5	2010– 2016	panel Model	“Entrepreneurship as a good career choice and perceived opportunities have played a significantly positive role on the EC environment of ASEAN 05”.
29	Hung et al. (2020)	1 country	2006–2017	3-stage regression model	“The results show that higher government quality will boost economic growth and reduce inequality among provinces. On the other hand, economic growth can improve government quality but increase income inequality among provinces”.
30	Khan et al. (2019)	954	NA	PLS-SEM	Findings reveal that board size (BSZ) and board diversity (BDV) have a positive influence on organizational performance.
31	Son et al. (2020)	120	2004–2017	3SLS regressions	The results showed that the relationship between corruption and the ratio of nonperforming loans was positive, thus deteriorating the soundness of the banking system
32	Kyazze et al. (2017)	293	NA	The CFA and SEM	Cooperative governance was a good predictor of social performance.
33	Iwamoto & Suzuki (2019)	219	NA	SEM and Bayesian SEM	The analysis results clarify that CSR activities directly impacts corporate financial performance and mediates the impact of human capital on corporate financial performance.

Figure 2. Research framework.

Table 2. Selected countries in the sample

No.	Country	No.	Country	No.	Country	No.	Country	No.	Country
1	Canada	12	United Kingdom	23	Ecuador	34	Iran	44	Egypt
2	Malaysia	13	Chile	24	Germany	35	Italy	45	Estonia
3	Slovenia	14	Croatia	25	Indonesia	36	Latvia	46	France
4	United States	15	India	26	Mexico	37	Luxembourg	47	Argentina
5	Brazil	16	Kazakhstan	27	Portugal	38	Netherlands	48	Australia
6	Burkina Faso	17	Peru	28	Switzerland	39	Panama	49	Bulgaria
7	South Africa	18	Puerto Rico	29	Taiwan	40	Slovakia	50	Guatemala
8	Colombia	19	Qatar	30	Finland	41	Sweden	51	Morocco
9	Ireland	20	South Korea	31	Greece	42	Uruguay	52	Poland
10	Thailand	21	Spain	32	Hungary	43	Vietnam
11	Cameroon	22	China	33	Lebanon	44

Table 3. Variables’ definitions

Variable			Acronym	Measure	Data source
Dependent variables Entrepreneurial Framework Conditions (EFCs)		Entrepreneurial Finance	EF	“The availability of financial resources—equity and debt—for small and medium enterprises (SMEs) (including grants and subsidies)”.	GEM Database
		Government Policy	GP	“The extent to which public policies support entrepreneurship. This EFC has two components: a) Entrepreneurship as a relevant economic issue and b) Taxes or regulations are either size-neutral or encourage new and SMEs”.
		Government Entrepreneurship Programs	GEP	“The presence and quality of programs directly assisting SMEs at all levels of government (national, regional, municipal)”.
		Basic School Entrepreneurship Education and Training	BSEE	“The extent to which training in creating or managing SMEs is incorporated within the education and training system at all levels. This EFC has two components: a) Entrepreneurship Education at basic school (primary and secondary) and b) Entrepreneurship Education at post-secondary levels (higher education such as vocational, college, business schools, etc.)”.
		Post School Entrepreneurship Education and training	PSEE
		R&D Transfer	R&DT	“The extent to which national research and development will lead to new commercial opportunities and is available to SMEs”.
		Commercial and Legal Infrastructure	CLI	“The presence of property rights, commercial, accounting and other legal and assessment services and institutions that support or promote SMEs”.
		Internal Market Openness	IMO	“This EFC contains two components: a) Market Dynamics: the level of change in markets from year to year, and b) Market Openness: the extent to which new firms are free to enter existing markets”.
		Physical Infrastructure	PI	“Ease of access to physical resources—communication, utilities, transportation, land or space—at a price that does not discriminate against SMEs”.
		Cultural and Social Norms	CSN	“The extent to which social and cultural norms encourage or allow actions leading to new business methods or activities that can potentially increase personal wealth and income”.
		Taxes and Bureaucracy	TB	“The extent to which public polices support entrepreneurship taxes or regulations are either size/neutral or encourage new and SMEs”
Independent Variables	Worldwide Governance Indicators (WGIs)	Voice and Accountability	VA	“Reflects perceptions of the extent to which a country’s citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media.”	The World Bank
		Political Stability No Violence	PSV	“Political Stability and Absence of Violence/Terrorism measures perceptions of the likelihood of political instability and/or politically- motivated violence, including terrorism.”
		Government Effectiveness	GE	“Reflects perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies.”
		Regulatory Quality	RQ	“Reflects perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development.”
		Rule of Law	RL	“Reflects perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence.”
		Control of Corruption	CC	“It reflects perceptions of the extent to which public power is exercised for personal benefit, including small and large types of corruption, as well as elite and private interest “capture” of the state.”
		Directors’ Liability	DL	Director liability index measures a plaintiff’s ability to hold directors of firms liable for damages to the company, that is, measures the strength of minority shareholder protections against directors’ misuse of corporate assets for personal gain.

Table 4. Descriptive statistics

Variable	Obs	Mean	Std. Dev.	Min	Max
Dependent Variables
EF	208	2.56	0.43	1.62	3.71
GP	208	2.59	0.50	1.56	3.75
TB	208	2.42	0.56	1.28	3.77
GEP	208	2.64	0.50	1.34	3.63
BSEE	208	1.97	0.45	1.16	3.43
PSEE	208	2.82	0.40	1.82	3.86
R&DT	208	2.37	0.40	1.57	3.73
CLI	208	2.96	0.37	1.26	3.79
IMO	208	2.55	0.37	1.29	3.73
PI	208	3.80	0.47	2.1	4.82
CSN	208	2.84	0.50	1.62	4.07
Independent Variables
VA	208	62.64	27.87	5	100
PS	208	54.17	25.53	7	98
GE	208	68.62	21.13	20	100
RQ	208	67.84	24.23	5	99
CC	208	62.01	25.54	11	100
RL	208	64.42	25.58	12	100
DL	208	46.89	21.92	10	90

Note: “PO = Perceived Opportunities, PC = Perceived Capabilities, FOF = Fear of Failure, EI = Entrepreneurial Intentions, TEA = Total Early-Stage Entrepreneurial Activity, EBO = Established Business Ownership, HJCE = High Job Creation Expectation, INN = Innovation, VA = Voice and Accountability, PS = Political

Table 5. Correlation analysis

	EF	GP	TB	GEP	BSEE	PSEE	R&DT	CLI	IMO	PI	CSN	VA	PS	GE	RQ	CC	RL	DL
EF	1
GP	0.46*	1
TB	0.44*	0.55*	1
GEP	0.46*	0.69*	0.68*	1
BSEE	0.61*	0.42*	0.45*	0.44*	1
PSEE	0.28*	0.37*	0.37*	0.50*	0.58*	1
R&DT	0.61*	0.53*	0.57*	0.73*	0.64*	0.57*	1
CLI	0.55*	0.29*	0.48*	0.57*	0.51*	0.45*	0.59*	1
IMO	0.62*	0.37*	0.59*	0.62*	0.62*	0.42*	0.71*	0.68*	1
PI	0.29*	0.21*	0.41*	0.33*	0.15	0.11	0.35*	0.33*	0.40*	1
CSN	0.40*	0.42*	0.51*	0.41*	0.62*	0.53*	0.42*	0.31*	0.5 0*	0.14	1
VA	0.29*	0.07	0.21*	0.45*	0.21*	0.11	0.48*	046*	0.48*	0.27*	−0.04	1
PS	0.29*	0.15	0.29*	0.45*	0.25*	0.08	0.48*	0.48*	0.44*	0.43*	−0.06	0.73*	1
GE	0.51*	0.31*	0.40*	0.55*	0.36*	0.09	0.61	0.50*	0.49*	0.49*	0.09	0.77*	0.79*	1
RQ	0.46*	0.20*	0.42*	0.52*	0.31	0.12	0.49	0.52*	0.50*	0.37*	0.1	0.78*	0.75	0.79*	1
CC	0.09	0.12	−0.01	0.04	0.12	0.13	0.7	0.07	0.09	−0.11	0.04	0.06	−0.09	−0.06	0.08*	1
RL	−0.19	0.15	−0.02	−0.01	−0.01	0.01	0.01	−0.11	−0.05	0.07	0.11	−0.18	−0.04	−0.08	−0.26	0.11	1
DL	0.22*	0.14	−0.07	0.13	0.13	0.01	0.12	0.05	0.03	0.02	0.09	0.23*	0.22*	0.35*	0.33	−0.12	−0.16	1

Note: “PO = Perceived Opportunities, PC = Perceived Capabilities, FOF = Fear of Failure, EI = Entrepreneurial Intentions, TEA = Total Early-Stage Entrepreneurial Activity, EBO = Established Business Ownership, HJCE = High Job Creation Expectation, INN = Innovation, VA = Voice and Accountability, PS = Political Stability absence of Violence, GE = Government Effectiveness, RQ = Regulatory Quality, RL = Rule of Law, CC = Control of Corruption, DL = Directors’ Liability”

*Indicates 1% sig.

Table 6. Regression results estimation

	EF	GP	TB	GEP	BSEE	PSEE	R&DT	CLI	IMO	PI	CSN
CON	1.77*** (0.05) [32.66[	2.05*** (0.09) [22.95]	1.86*** (0.06) [32.18]	1.71*** (0.07) [24.34]	1.28*** (0.07) [17.82]	2.53*** (0.10) [25.29]	1.54*** (0.05) [29.07]	2.46*** (0.03) [75.95]	2.01*** (0.07) [29.25]	3.14*** (0.05) [57.67]	2.46*** (0.06) [42.18]
VA	−.00*** (0.00) [−3.91[	−.01*** (0.00) [−4.37]	−.01*** (0.00) [−14.08]	−.00 (0.00) [−1.15]	−.00 (0.00) [−1.48]	.00 (0.00) [1.08]	.00*** (0.00) [3.47]	.00 (0.00) [1.48]	.00** (0.00) [2.04]	−.01*** (0.01) [−9.03]	−.00*** (0.00) [−4.42]
PS	−.01*** (0.00) [−6.86]	−.01*** (0.00) [−5.40]	−.00*** (0.00) [−3.19]	−.00*** (0.00) [−3.67]	−.00 (0.00) [−0.37]	.00** (0.00) [2.01]	−.00 (0.00) [−1.58]	.00*** (0.00) [3.15]	.00 (0.00) [0.36]	.00*** (0.00) [3.30]	−.01*** (0.00) [−7.69]
GE	.02*** (0.00) [6.18]	.02*** (0.00) [3.87]	.00 (0.00) [1.61]	.01*** (0.00) [2.89]	.02*** (0.00) [8.77]	.01*** (0.00) [2.85]	.02*** (0.00) [11.47]	.00 (0.00) [0.89]	.01** (0.00) [2.47]	.02*** (0.00) [7.36]	.01*** (0.00) [6.25]
RQ	.00 (0.00) [1.33]	−.00*** (0.00) [−3.71]	.01*** (0.00) [8.23]	.00*** (0.00) [2.71]	.00 (0.00) [1.51]	.01*** (0.00) [6.53]	−.00*** (0.00) [−3.37]	.01*** (0.00) [3.56]	.00** (0.00) [2.22]	−.00* (0.00) [−1.70]	.01*** (0.00) [5.61]
CC	−.00 (0.00) [−0.27]	.01** (0.00) [2.34]	.01*** (0.00) [7.31]	.01*** (0.00) [6.81]	−.00 (0.00) [−1.26]	.00*** (0.00) [4.37]	.00 (0.00) [0.30]	−.00 (0.00) [−0.40]	.00 (0.00) [0.55]	.01** (0.00) [2.23]	.00 (0.00) [1.43]
RL	.00 (0.01) [0.77]	.00 (0.00) [0.94]	−.01* (0.00) [−1.82]	−.01** (0.00) [−2.07]	−.01*** (0.00) [−5.08]	−.02*** (0.00) [−6.02]	−.01** (0.00) [−1.97]	.00 (0.00) [0.21]	−.00 (0.00) [−1.30]	−.00 (0.00) [−1.07]	−.01*** (0.00) [−2.66]
DL	−.00 (0.00) [−0.22]	.00 (.00) [0.40]	−.01*** (0.00) [−7.32]	−.00* (0.00) [−1.90]	−.00 (0.00) [−0.31]	.00 (0.00) [0.38]	−.00*** (0.00) [−5.15]	−.00*** (0.00) [−7.74]	−.00*** (0.00) [−5.45]	−.00*** (0.00) [−5.06]	.00 (0.00) [1.35]
R-squared	0.34	0.21	0.33	0.33	0.18	0.13	0.41	0.31	0.21	0.32	0.11
Wald chi2(7)	4257.16	757.05	82,758.27	19,518.86	1264.26	323.57	19,136.67	13,580.57	9344.35	395.70	1467.98
Prob.	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000

Notes: Note: “PO = Perceived Opportunities, PC = Perceived Capabilities, FOF = Fear of Failure, EI = Entrepreneurial Intentions, TEA = Total Early-Stage Entrepreneurial Activity, EBO = Established Business Ownership, HJCE = High Job Creation Expectation, INN = Innovation, VA = Voice and Accountability, PS = Political Stability absence of Violence, GE = Government Effectiveness, RQ = Regulatory Quality, RL = Rule of Law, CC = Control of Corruption, DL = Directors’ Liability”

Figures in [] indicating standard error & figures in () indicating t value.

***, ** and * indicate at 1%, 5% and 10% level of significance respectively.

Table 7. Regression results estimation

	EF	GP	TB	GEP	BSEE	PSEE	R&DT	CLI	IMO	PI	CSN
CON	1.77*** (0.06) [32.00]	2.05*** (0.09) [22.90]	1.78*** (0.04) [40.59]	1.78*** (0.07) [24.33]	1.28*** (0.07) [19.23]	2.55*** (0.09) [29.39]	1.53*** (0.05) [30.20]	2.43*** (0.03) [93.48]	1.98*** (0.07) [29.61]	3.11 (0.05) [67.40]	2.47*** (0.05) [52.23]
VA	−.00*** (0.01) [−4.52[	−.01*** (0.00) [−4.39]	−.011*** (0.00) [−14.86]	−.00 (0.00) [−1.37]	−.00* (0.00) [−1.75]	.00 (0.00) [0.77]	.00** (0.00) [2.12]	.00 (0.00) [0.17]	.00 (0.00) [1.10]	−.00*** (0.01) [−12.01]	−.00*** (0.00) [−4.11]
PS	−.01*** (0.00) [−7.22]	−.01*** (0.00) [−5.15]	−.00*** (0.00) [−3.75]	−.00*** (0.00) [−3.81]	−.00 (0.00) [−0.80]	.00 (0.00) [1.52]	−.00** (0.00) [−2.40]	.00*** (0.00) [2.88]	−.00 (0.00) [−0.32]	.00 (0.00) [1.00]	−.01*** (0.00) [−7.12]
GE	.02*** (0.00) [6.31]	.02*** (0.00) [4.03]	.00 (0.00) [0.26]	.01*** (0.00) [2.78]	.02*** (0.00) [8.28]	.01*** (0.00) [2.81]	.02*** (0.00) [12.21]	.00 (0.00) [0.11]	.00* (0.00) [1.90]	.01*** (0.00) [6.80]	.01*** (0.00) [6.00]
RQ	.00 (0.00) [1.62]	−.00*** (0.00) [−4.31]	.01*** (0.00) [8.45]	.00*** (0.00) [2.77]	.00* (0.00) [1.69]	.01*** (0.00) [8.95]	−.00** (0.00) [−2.22]	.01*** (0.00) [3.99]	.01*** (0.00) [2.74]	−.00 (0.00) [−0.45]	.01*** (0.00) [5.19]
CC	−.00 (0.00) [−0.39]	.01** (0.00) [2.42]	.02*** (0.00) [7.37]	.01*** (0.00) [7.42]	−.00 (0.00) [−1.49]	.01*** (0.00) [4.57]	.00 (0.00) [0.27]	−.00 (0.00) [−0.18]	.00 (0.00) [0.75]	.01** (0.00) [2.29]	.00 (0.00) [1.31]
RL	.00 (0.01) [0.96]	.00 (0.00) [0.80]	−.01* (0.00) [−1.67]	−.01** (0.00) [−2.17]	−.01*** (0.00) [−4.42]	−.02*** (0.00) [−6.29]	−.00 (0.00) [−1.61]	.00 (0.00) [0.35]	−.00 (0.00) [−0.80]	−.00 (0.00) [−0.64]	−.01*** (0.00) [−2.65]
DL	−.08*** (0.03) [−3.03]	.06** (0.03) [2.04]	−.21*** (0.02) [−12.37]	−.03* (0.02) [−1.65]	−.08** (0.03) [−2.27]	−.06 (0.05) [−1.41]	−.17*** (0.02) [−12.15]	−.14*** (0.02) [−7.84]	−.19*** (0.03) [−6.40]	−.26*** (0.04) [−6.80]	.01 (0.03) [0.27]
R- squa red	0.35	0.21	0.34	0.33	0.18	0.14	0.44	0.32	0.33	0.36	0.11
Wald chi2( 7)	2047.15	753.33	15429.60	21419.7 8	2323.62	877.75	8294.96	4424.14	10576.2 1	496.03	1147.02
Prob.	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000

Note: “PO = Perceived Opportunities, PC = Perceived Capabilities, FOF = Fear of Failure, EI = Entrepreneurial Intentions, TEA = Total Early- Stage Entrepreneurial Activity, EBO = Established Business Ownership, HJCE = High Job Creation Expectation, INN = Innovation, VA = Voice and Accountability, PS = Political Stability absence of Violence, GE = Government Effectiveness, RQ = Regulatory Quality, RL = Rule of Law, CC = Control of Corruption, DL = Directors’ Liability”

Figures in [] indicating standard error & figures in () indicating t value.

***, ** and * indicate at 1%, 5% and 10% level of significance respectively.

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