Andere Kunden interessierten sich auch für
![The problem of access of enterprises to bank credit]( "The problem of access of enterprises to bank credit")
The problem of access of enterprises to bank credit27,99 €![Determinants of SME access to bank credit in Goma city]( "Determinants of SME access to bank credit in Goma city")
Determinants of SME access to bank credit in Goma city39,99 €![Credit Risk Management and Financial Performance of Commercial Banks]( "Credit Risk Management and Financial Performance of Commercial Banks")
Credit Risk Management and Financial Performance of Commercial Banks39,99 €![Increasing access to qualified midwives in remote-rural areas]( "Increasing access to qualified midwives in remote-rural areas")
Increasing access to qualified midwives in remote-rural areas16,99 €![HIERARCHICAL ACCESS CONTROL]( "HIERARCHICAL ACCESS CONTROL")
HIERARCHICAL ACCESS CONTROL50,99 €![Leadership Styles and Employee Performance in State Owned Enterprises]( "Leadership Styles and Employee Performance in State Owned Enterprises")
Leadership Styles and Employee Performance in State Owned Enterprises51,99 €![How Loyalty Effect Consumer Credit Risk?]( "How Loyalty Effect Consumer Credit Risk?")
How Loyalty Effect Consumer Credit Risk?38,99 €
Nigeria Small Scale Enterprise(SSE) sector is largely underdeveloped due to financial constraints. Therefore, this study (i) examined the socio-economic characteristics of small scale entrepreneurs (ii) evaluated factors influencing their access to use of credit from formal and informal credit institution (iii) investigated the characteristics of their demand for credit and (iv) analyzed their credit constraints. Stratified sampling technique was employed to select 350 respondents in the study area as the small-scale enterprises were scattered all over the study area in form of one man businesses, family businesses and cooperative societies. The objectives were addressed using (i) descriptive statistics (ii) multinomial logit regression (iii) probit and tobit models. The results showed that demand for credit is strongly influenced by gender, age, education, location, value of assets owned and other dwelling characteristics at 1%, 5% and 10% level of significant. Moreso, the availability of different sources of credit has impact on demand for credit.