The Impact of Cooperative Membership on Fish Farm Households’ Income: The Case of Ghana

Abstract

The emergence of agricultural cooperatives is extensively viewed as a necessary institutional arrangement that can help farmers in developing countries overcome the constraints that impede them from improving sustainable agricultural production and acquiring new marketing opportunities. Therefore, this study examines the determinants of cooperative membership and its impact on fish farm household income, using data collected from two regions in Ghana. An endogenous switching regression (ESR) model is utilized to address the potential sample selection bias issue. The results show that household heads’ decisions to join cooperatives are affected by their access to credit, off-farm work, education level, and peer influence. Cooperative membership can increase both household and farm income by 28.54% and 34.75%, respectively. Moreover, we show that different groups of households’ cooperative impacts on farm and household income are heterogeneous. Our findings highlight the importance of cooperative patronization and provide implications that can improve households’ welfare.

Empirical impact of financial service access on farmers income in Ghana

“…Wages/salaries, rent, remittances, pensions, and dividends are all examples of off-farm income. After following other literature (e.g., ANKRAH TWUMASI et al, 2021;MA et al, 2018; and our available data, some other variables (e.g., age, gender, education, farming experience, distance from farmers' resident to the nearest financial institution, financial literacy and household size) were added as control variables to establish consistency in our estimation (The definitions of the other control variables may be found in Table 1). STATA 15 was used to edit and code the data to guarantee accuracy, validity, uniformity, consistency, and completeness.…”

“…Furthermore, because few financial institutions provide such services in rural areas, smallholders have limited access to institutional savings facilities. This analysis is based on insufficient empirical information on whether access to financial services can affect farmers' income (SIAW et al, 2017;TWUMASI et al, 2020TWUMASI et al, , 2021.…”

Research on influences of education and financial literacy on commercial insurance purchase in China

“…The literature indicated that education attainment and financial literacy were positively correlated (Murphy, 2013; Arrondel, 2018; Nanziri and Leibbrandt, 2018). Education was also identified as an important demographic characteristic that significantly affected financial literacy (Ankrah Twumasi et al , 2021). Financial illiteracy was particularly prevalent among those with low educational attainment, such as those who have not pursued postsecondary education (Hilgert et al , 2003; Lusardi and Mitchell, 2007; Lusardi and Mitchell, 2008).…”

“…Third, although the mediating effect of financial literacy between financial education and financial behavior has been occasionally studied (Son and Park, 2019; Carpena and Zia, 2020; Fan and Zhang, 2021), the mediating effect of financial literacy between education and financial behavior has been occasionally studied (Son and Park, 2019; Carpena and Zia, 2020; Fan and Zhang, 2021), yet the mediating effect of financial literacy between education and financial behavior including commercial insurance purchase is rare. Literature shows that formal education affects financial literacy and commercial insurance purchase (Ankrah Twumasi et al , 2021; Li et al , 2021), and financial literacy impacts commercial insurance purchase (Liu et al , 2023; Duan et al , 2022). Therefore, the mediating effect of financial literacy between education and purchase of commercial insurance might exist, the detection of which will provide a causal mechanism of education on financial insurance purchase, which will enhance the contribution of education in promoting commercial insurance purchase.…”

Factors Hindering Agricultural Cooperative Societies in Contributing Adequately to Poverty and Hunger Eradication among the Rural Community Dwellers in Ido-Osi Local Government Area in Ekiti State

“…Data from two regions of Ghana allowed Ankrah, Jiang, Addai, Ding, Chandio, Fosu, Asante, Siaw, Danquah, Korankye, Ntim-Amo, Ansah, and Agbenyo (2021) to analyse the connection between cooperative membership and family income from fish farming. An endogenous switching regression (ESR) model is used to control for selection bias in the sample population.…”