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Usein Imo State, Nigeria Nigerian Agricultural Policy Research Journal. Volume 1, Issue 1, 2016. http://aprnetworkng.org Usein Imo State, Nigeria A. O. Ejiogu and E.C. Onyenoneke Department of Agricultural Economics, Imo State University, Owerri Corresponding author email: [email protected] Abstract child labour use in Imo State of Nigeria. Specifically, the study determined the effect of the socioeconomic factors that -stage random sampling was employed in choosing the respondents for this study. One local government area (LGA) in each of the three agricultural zones was purposively selected for the study based on suitability for rice production. Communities which are known for rice production were purposively selected from the selected LGAs. The list of rice farmers in each chosen community was obtained from Imo ADP. The list formed the sampling frame from which the respondent rice farmers were selected using random sampling procedure. Thirty rice farmers were selected from each community, making a sample size of 90.Data was analyzed with binary logistic regression technique. The variables namely gender, marital ge and educational attainment were significant at 1% level. Furthermore, gender, marital status, family size, farm size, educational attainment and rice farm experience were statistically significant variables with negatively effect on the use of child labour. Age though statistically significant, had positive effect on the use of child labour. Efforts aimed at curbing the adverse effects of child labour should to all intents and purposes be fundamentally targeted at the predisposing socioeconomic factors. Key Words: Rice farmers, labour use, socioeconomic, Imo State 1. Introduction Rice is a staple food for many people in Imo rice production in Nigeria has been identified to State, Nigeria. It is the most rapidly growing consist of lack of competiveness resulting from food source in the state and is of significant low and uneconomic productivity, poor access importance to food security for a large number to expensive inputs (especially fertilizer and of low- income food deficit countries including credit), low capacity to meet quality standard. It Nigeria (FAO, 2004). Rice-based production should be added that labour is one of the system and the associated post-harvest inputs on which lots of money is expended. operations employ many hands in rural areas Labour is an important factor of production. It of West Africa including Imo State. According means the physical and mental effort provided to Imo ADP (2009), the key problems facing by an individual worker towards production. Nigerian Agricultural Policy Research Journal. Volume 1, Issue 1, 2016. http://aprnetworkng.org In most cultures children help their immediate rice seedling, weeding, providing fire wood for families through work in manner that is neither parboiling before milling, applying fertilizer and hazardous nor exploitative. However, child pesticides. Togunde and Carter (2008) stated labour effectively deprives children of their that children engage in work in order to humanity, their childhood, their self-worth, their contribute financially to the sustenance of their potential and their general well being. Child families, and to acquire training needed in labour can equally interfere with the education future occupations. of the child. This comes about when children According to Ezedinma (2005), there is are forced to combine their education with scarcity of labourers in the rural areas; hence hazardously long and tedious work. It may also child labour becomes the alternative. Dillon find expression in children leaving school (2009) noted that illiteracy of the parents leads earlier than is expected; in extreme forms child to child labour. Basu and Van (1998) stated labour entails children not attending school that child labour is as a result of poverty and and are left to cater for themselves (UNDP, occurs when family or the household income is 2015). Child labour is an economic activity below subsistence level. There is still gap in performed by a person under the age of 18 understanding the effect of socioeconomic (Tiaji et. al., 2005). Whether these activities characteristics of rice farmers on the use of are paid or unpaid, they constitute child labour child labour in rice production. This study is an to the extent that they prevent the child within attempt to fill that gap in knowledge by this age limit from attending to school investigating the sign and size of the effect of activities. socioeconomic characteristics of the farmers According to Sartyarthi (2015) children are on the use of child labour in their farm preferred by way of child labour because they operations. The overall objective of the study is are the cheapest or even free, if bonded- to highlight the sign and size of the effect of labour. Sartyarthi (2015) further stated that the socioeconomic characteristics of the rice children are physically and mentally docile; do farmers on the use of child labour in their farm not form unions; do not go to court and so operations. Specifically, the objective is to pose no challenge to the employer. The determine the effect of the socioeconomic highest prevalence of child labour is in Sub- Saharan Africa, at one child in five (ILO, 2013). child labour. The hypothesis of the study is Nigeria is one of the countries that make up Sub-Saharan Africa. Imo ADP (2009) noted characteristics do not significantly affect the that children are involved in labour use in rice use of child labour in rice production. The production in Imo State and that the findings of the study will bring to light the contributions of children in rice production in the area include scaring birds, transplanting Nigerian Agricultural Policy Research Journal. Volume 1, Issue 1, 2016. http://aprnetworkng.org socioeconomic characteristics on child labour variable can be examined with that of the use in rice production. independent variables. Such models cannot be estimated by either multiple regression or the Conceptual Framework Ordinary Least Square (OLS) techniques According to Imo ADP (2009), in Imo State, which may result in invalid parameter children are employed to scare birds from the estimates and wrong magnitude of the effects rice farm mostly with their catapults at the early of the independent variables on the dependent morning and evening hours. Togunde and variable, the OLS assumptions that the Carter (2008), noted that globalization of the variance of the error terms are constant and economy has led to the desire for cheap labour not correlated with the level of independent and profit maximization. However, one major variables are violated. backlash of the global development and Nonetheless, four commonly used approaches spread of industries has been the exploitation to estimate such models include: the linear of children in terms of low wages and their probability Model (LPM), logit model, probit deplorable working conditions. model and the tobit model (Gujarati, 2000). According to Ezedinma (2005), there is The LPM is not generally recommended scarcity of labourers in the rural areas; hence, because it provides predicted values that may the child labour becomes the alternative. In fall outside the 0-1 interval, thus violating the Nigeria, child labour is often taken as a means assumptions of the probability. Logit, probit of teaching the children survival skills and as a and tobit models give maximum likelihood means of social integration. This is clear when estimates and overcome most of the short the farmers go to the farm with their children, comings of LPM by providing consistent and showing them one skill or the other. efficient estimates. The logit model framework In analyzing the effect of socio-economic is however preferred among the other three characteristics of the respondents in the model framework because it has been found to involvement of children in rice production, this be efficient in explaining such dichotomous study employs a model that deals with child decision variables (Gujarati, 2000). labour use or not as the dichotomous dependent variable. That is the theoretical Binary Logistic Regression basis for the choice of Logit model for the Binary logistic regression is a form of regression which is used when the dependent from which the technique derives name is the variable is dichotomous and independent variables are of any type. They are used to The odds indicate the relative probability of predict a dependent variable on the basis of interest (Allan, 1986; Eboh, 2009). The independent variables, to determine the relationship of this behavioural dependent percentage of variance in the dependent Nigerian Agricultural Policy Research Journal. Volume 1, Issue 1, 2016. http://aprnetworkng.org variable explained by the independent Li = logistic model, Ln = log, Pi = probability of variables, to assess interaction effects and the event occurring, Bo = constant or intercept, understanding the impact of the covariate B1X1 = coefficient of the independent variable. variables. It applies maximum likelihood estimation after 2. Research Methods transforming the dependent into logit variable Study Area:The study was carried out in Imo (the natural log of odds of the dependent State, Nigeria. The major economic activity of occurring or not). Logistic regression estimates the people of Imo State is farming. Among the the probability of a certain events, that is, major crops grown in the area are cassava, change in the log of odds of the dependent maize, yam, tree crops, vegetables and rice. and not changes in the dependent variable The crops are typically grown on small holder itself as the OLS regression does. plots. Imo State has suitable ecologies for The Probability of the event occurring is given production of different varieties of rice (Imo by the relationship ADP, 2009). This consists of temporary Pi = 1/1+e-z-------------------- (equation 1.1) flooded area and river banks. The shallow Where Pi = the probability of the event swamps have areas such as Imo River Basin occurring which ranges between 0-1 at Ihitte Uboma, Nzerem, Umuna (all in Z = Bo + B1x1 (which ranges - Okigwe agricultural zone); Urashi River basin e = the base of the natural logarithm (approx.
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