Journal of Agricultural Economics, Extension and Rural Development

ISSN 2360-798X

Economic Analysis of Land Tenure Systems on Arable Crops Production in Ekiti State, Nigeria.


Accepted 9th June, 2017.


The study examined economic effect of land tenure systems on arable crop production in Ekiti State, Nigeria. Attempts were made to examine the type of land ownership rights problems of land acquisition, the pattern of land use and the resource use efficiency of land as a factor of production in arable crop production in the study area. Data were collected from 120 arable farmers randomly selected for interview with the aid of questionnaire were used to analyze. The study revealed that the arable farmers were fairly educated with about 41.7% having secondary education and 16.7% having primary education. The sampled farmers were small holders with 80.8% having less than 4ha of land, this agreed with the fact that most of the arable crop producers were producing for family consumption with the 76.7% of the farmers operated on subsistence basis. It was also indicated that the prevailing tenure type was inheritance ownership right with 60% of the respondents acquiring their land through inheritance. It was also discovered that the prevailing traditional tenure (inheritance, communal) systems has resulted to farmland fragmentation which would not encourage mechanization and commercial agriculture. According to the study, the prevailing land use patterns were the arable cultivation followed by permanent crop cultivation. The production function analysis showed that all the variables were productively used for having positive estimate except fertilizer and agrochemicals that had negative estimate elasticity. Therefore, government must seriously address the issue of land acquisition so that prospective farmers have free access to arable land empowered them to solely make their own production decision (in accordance with the principle of land use) without the dictatorship of the landlords.


Keyword: Land Tenure, Arable crops, Multiple Regression Analysis