INTERNATIONAL JOURNAL OF SOCIAL SCIENCES AND MANAGEMENT RESEARCH (IJSSMR )

E-ISSN 2545-5303
P-ISSN 2695-2203
VOL. 9 NO. 9 2023
DOI: https://doi.org/10.56201/ijssmr.v9.no9.2023.pg118.144


Causes of Poverty among Genders in Micro and Small Scale Enterprises in Jalingo, Nigeria

Magaji Ibrahim Yakubu , Mamman Andekujwo Baajon and Zechariah Wanujeh


Abstract


Ending poverty is a key issue of discussion in the world and the first goal of the seventeen sustainable development goals. Nigeria is richly endowed with natural resources, yet her people are severely improvised, trapped in vicious cycle of poverty. High levels of poverty among genders have been found to be detrimental to people’s well-being and economic growth. Previous studies on microcredit were mostly in relation to economic growth with little attention on poverty and genders. This study fills this gap by investigating the relationship between micro-credit and Poverty among genders of micro and small-scale entrepreneurs. The simple unifying neoclassical scarcity-driven poverty theoretical framework and cross-sectional survey research design were adopted. Data analysis was based on the questionnaires retrieved from 186 and 726 small and micro entrepreneurs, a total of 912 obtained from the 229 and 794 samples determined by the Cochran’s simple random sampling formula. The Probit and regression models were estimated using the Maximum Likelihood and Ordinary Least Square techniques respectively. Descriptive analysis was conducted to examine the demographic features of the respondents. The heteroskedasticity robust standard analysis was done and statistical significance at p? 0.05. The mean age of the respondents was 40 years and 63% were with formal education. The FGT poverty rate, depth and severity are 61.95%, 24.67% and 12.92% respectively, while the SST poverty rate is 32.68% and the Gini coefficient is 35.63%, indicating high poverty level of Poverty among the entrepreneurs. Probit results show that respondents who obtain micro-credit from deposit money banks (DMBs), microfinance banks, and relatives are less likely to be poor, with 16.9%, 11.8%, and 6.8% probabilities respectively. Also, respondents with monthly (43.88%), quarterly (48.56%), and yearly (37.08%) access to microcredi


keywords:

Poverty, Probit Model, Gini Coefficient, Microcredit, Jalingo and OLS


References:


Abur, C.C., &Torruam, J.T. (2012). Micro-credit as a strategy of poverty reduction in Makurdi
local government area of Benue State Nigeria. International Journal of Humanities and Social
Science, 2(12), 179-186.

Afe-Babalola, A. (2020). Nigeria’s poverty capital status: Solution (2). Retrieved from
http//www.vanguardngr.com/2020
Agbaeze, E.K., &Onwuka, I.O. (2014). Impact of microcredit on poverty alleviation in Nigeria:
The case of Enugu East local council. International Journal of Business and Management
Review, 2(1), 27-51.

Aisha, I., Waqar, A., Hafiz, Z.M., & Muhammed, I. (2014). Impact of microfinance on poverty
reduction: A case study of district Faisalabad. Journal of Economics and Sustainable
Development, 5(9), 60-65.


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