This study was conducted to analyze the effects of policy on the development of Agro-based micro-enterprises in the informal sector of Bayelsa State of Nigeria. Structured questionnaires were used to collect data from 150 micro-enterprises that were randomly selected. Descriptive statistics, multiple regression, Access model and the t- statistics were employed for data analysis. Among the major findings were that the agricultural micro-enterprises span the entire agricultural sector of crop production, animal, fisheries, processing and trading. The age range of the entrepreneurs were between 31-65 years (85.4%), with women dominating the sector (58.0%). The level of education was appreciable with 44.0% having more than primary education, the enterprises were relatively new with experience range of 1-10years and 80.7% employed between 1 and 10 persons. The average income was N100,000 per annum and an asset holding of N100,000 to N150,000. Econometric estimation showed that experience, size, income level, value of asset-holdings and credit history affected the amount of micro-credit obtained significantly. Also, age, gender of entrepreneur and level of education did not affect the amount of credit obtained significantly. Further findings showed that only 23.3% had access to training and only 9.3% have benefited in government market facilities. The access index of micro-credit was 0.26 representing 26.0% in the entire state. The survey also showed that tax policy also significantly affected the development of urban and rural micro-enterprises. Also poor transportation, poor road network, poor electricity supply, inadequate market infrastructure, inadequate subsidies and micro-credit were the identified constraints to micro-enterprises development. It is therefore recommended that the government, NGOs multinationals should re-address the infrastructural policies, micro-credit policies, tax, training programmes and if possible partner with private companies for a total over-haul of the sector.

1.1      Background Information

Micro-enterprises are generally small–to–medium scale economic units, organizations, ventures or enterprises which activities are systematic and purposeful, with many usually distinctively specialized in scope, but effectively isolated in technological span and capacity (Osuala, 2004).

The Federal Government small-scale Business Development Programme (SBDP) also defines micro-enterprise as “any manufacturing, processing, trading and service industry with a capital investment not exceeding one hundred and fifty thousand naira (N150,000) in machinery, stores and other equipment and employing not more than fifty (50) workers.” The United States Agency for International Development (USAID, 2003) also defines a micro-enterprise as one that comprises 10 or fewer employees, including unpaid family workers, in which the owner or operator is considered poor.
Micro-enterprises in Nigeria fall into four classes within which there are more than 35 identifiable categories or typologies (Olomola, 1991). They include the production, manufacturing, trading and service providing micro-enterprises. In Bayelsa state, all these categories of micro-enterprises are found in the rural, peri-urban and urban centres. Production micro-enterprises (especially in the farming and fishing categories) are common in rural areas but are not exclusive to them. Micro-enterprises involved in activities like furniture-making are typically more in urban, while those in firewood, tooth pick production, garri processing and oil-milling are more common in rural areas. Also the non-agriculture-based and trading micro-enterprises are about equally distributed between the three locations but with a higher volume concentrated in the Peri-urban and urban centres. However, this study was focused on agro-based micro enterprises.

Micro-enterprises in the informal sector of Bayelsa State Span the entire agricultural production (ie processing, distribution, marketing and consumption) spectrum. Most of these micro-enterprises are proprietorships with a single owner-operator. In more than 90 percent of the cases, they are usually not.....

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