*Iheke, O. R. and **Ukonna, N. F.
*Department of Agricultural Economics, Michael Okpara University of Agriculture, Umudike, Nigeria
**Department of Agribusiness and Management, Michael Okpara University of Agriculture, Umudike, Nigeria
DOI: https://doi.org/10.5281/zenodo.14628131
ABSTRACT
This study analyzed the determinants of investment among catfish entrepreneurs in Abia State, Nigeria. Specifically, the study described the socio-economic and demographic characteristics of the catfish entrepreneurs, ascertained the pattern and the determinants of investment in catfish enterprises in the study area. Data were collected from 112 respondents through structured questionnaire which were analyzed using both descriptive and inferential statistical tools. The result showed that that majority of the respondents (64.29%) were male and the mean age of the entrepreneurs was 36 years. About 51.79% of the respondents were married while 48.21% were
single. The mean farming experience was approximately 5 years and majority (51.79 %) having secondary form of education. The mean household size of farmers was 6 persons per household. The location of the business is mostly in the rural area. Result revealed that the catfish entrepreneurs invested majorly on land (N 592,946.40k), this was followed by borehole (N249,830.40k), pond expansion (N242,714.30k), generator (N161,785.70k) and pumping machine (N64,160.71k). The significant determinants of investment on catfish enterprises were age (p<0.01), sex (p<0.01), education (p<0.01), experience (p<0.01), cooperative (p<0.01), extension visit (p<0.05) and income (p<0.01). It could be concluded that the major operating cost is the cost of feed and the major investments by catfish entrepreneurs were on land, borehole, pond expansion, generator and pumping machine. It was recommended that since feed cost constitute a major operating cost in production, there is the need to formulate feed locally in order to reduce costs associated with the business as this would enhance commercial catfish production in the study area and Nigeria in
general. Variables such as age, sex, education, experience, cooperative, extension visit and income should also be taken into consideration in policy formulation.