The study examined the economies of scale and technical efficiency of small-scale farmers in Edo State, Nigeria. The data used in the study were mainly from primary sources. The data were collected from 200 rice farmers selected using multistage sampling technique and analyzed using descriptive statistics, and stochastic frontier model. Production functions among hybrid rice and inbred (local) rice producers were estimated independently using the Battese and Coelli (1995) model to specify a stochastic frontier Cobb-Doglas production function with behaviour inefficiency component to estimate all parameters together and the level of significance in one-step maximum likelihood estimation. The returns-to-scale (RTS) for the production function showed that the farmers operated in the irrational zone (stage I) of the production surface having RTS of 0.676 and 1.299 for inbred and hybrid species respectively. The mean technical efficiency of 0.317 and 0.925 for inbred and hybrid varieties respectively were obtained from the data analysis, indicating that the hybrid sample farmers were relatively more efficient technically than the inbred rice farmers. The mean technical efficiency of the farms was estimated as 1.263. This means that average rice farm in the sample area has production that are about 26% above the minimum defined by the frontier. However, the result of the analysis indicated that presence of technical inefficiency had effects in the food crop production as depicted by the significant estimated gamma coefficient of each model, the generalized likelihood ratio test and the predicted technical efficiencies within the farmers. Improved variety of rice as well as the technology improves the efficiency of the farmers.

The study examined a time-series analysis of Nigeria rice supply and demand with a view to determining any long-run equilibrium between them using the Error Correction Model approach (ECM). The data used for the study represents the annual series of 1960-2007 (47 years) for rice supply and demand in Nigeria, derived from the World Rice Statistics compiled by the International Rice Research Institute (IRRI, 2009). The order of integration and the level of co-integration were determined using the Augmented Dickey Fuller (ADF), Johansen co-integration and Granger causality test. The result of the descriptive statistics showed that rice supply and demand had means of 1.8 and 1.6 million metric tonnes respectively with a demand-supply lag of 0.18 million metric tons. The Trace test indicated one co-integrating equation at the 0.05 level of significance while the Granger causality ran one-way from supply to demand. The result of the ECM shows that the coefficient of the short-run and long-run relationships between rice demand and supply were 1.102963 and-0.043497 respectively. There is disequilibrium between Nigeria rice supply and demand in the short-run but re-equilibrates at 0.043. Thus, the more the demand for rice, the higher the production is expected in order to avoid any shortage, in the short-run, which though will always even out in the long-run. Nigeria rice supply-demand exhibit disequilibrium in the short-run but has a long-run equilibrium.

Abstract-The study examined the economics of snail production in Edo state of Nigeria. The socio-economic characteristics of the respondents cost and returns and factors affecting revenue generation in snail production were the specific areas of focus of the study. Snow balling sampling technique was adopted to identify a total of 95 snail farmers in the study area and this formed the sample size for the study. Data analysis was done using descriptive statistics, budgetary and regression analyses. The results indicated that the respondents had average stock size of 630 snails. The business of snail production required low capital investment and was highly profitable with gross margin and net profit per snail of N68.45 and N63.44 respectively. The results further showed that stock size, labor cost and educational level were the significant factors influencing revenue from snail production. They all correlated positively with the revenue and explained about 79% of the variation in the revenue (R 2 = 0.785). It was concluded that since snail production required low capital investment, low income earners could comfortably embark on it; and in view of the high profit level of the business, it could be a veritable enterprise for uplifting the living standard of its producers and advance the economy of the nation.

The dispersion in price of rice across different markets in exclusive location, and the astronomic annual increase of 30% in the past 7-8 years in Edo state cannot be attributed mainly to transport costs. Consequently, the study examined spatial price variation of rice vis-à-vis beans, garri, and palm oil as typically consumed substitutes/complements food commodities from a segment of 286 food commodity marketers in Ovia North-East Local Government Area (LGA) of Edo state, Nigeria using the spatial lag model of price-cost of transport data set. The outcomes of the descriptive data showed that the price of 1Kg rice under random test became N1576.82. The consequences of Moran's I (3.652) and Lagrange multiplier exams (10.753) for spatial lag, and Moran's I (0.175) and Geary's c check (0.460) for spatial autocorrelation suggest evidence of clustering in the spatial price of rice at the nearby markets and spatial price of rice between markets than might be under a random experiment. However, the results confirmed no spatial structure, no spatial dependence in the error term, nor spatial dependence within the costs of garri, beans and palm oil. The effects of the spatial lag model showed a mean price of 1kg of rice as N1597.77 with an average total effect of 0.406 comprising 0.274 direct effect and 0.132 indirect effects. Hence, the own-market price of rice in the study area is affected by the across-market price in the nearby markets, in addition to the cost of transportation from market of purchase.

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