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• Comparing ols and rank-based estimation techniques for production analysis: An application to Ghanaian maize farms.

  125-130

  Henry De-Graft Acquah

  Views:

  338

  This paper introduces the rank-based estimation method to modelling the Cobb-Douglas production function as an alternative to the least squares approach. The intent is to demonstrate how a nonparametric regression based on a rank-based estimator can be used to estimate a Cobb-Douglas production function using data on maize production from Ghana. The nonparametric results are compared to common parametric specification using the ordinary least squares regression. Results of the study indicate that the estimated coefficients of the CobbDouglas Model using the Least squares method and the rank-based regression analysis are similar. Findings indicated that in both estimation techniques, land and Equipment had a significant and positive influence on output whilst agrochemicals had a significantly negative effect on output. Additionally, seeds which also had a negative influence on output was found to be significant in the robust rank-based estimation, but insignificant in the ordinary least square estimation. Both the least squares and rank-based regression suggest that the farmers were operating at an increasing returns to scale. In effect this paper demonstrate the usefulness of the rank-based estimation in production analysis.

  JEL CODE: Q18, D24, Q12, C1 and C67

• Measuring technical, economic and allocative efficiency of maize production in subsistence farming: evidence from the central rift valley of Ethiopia

  63-73

  H. Ahmed Musa

  Z. Lemma

  G. Endrias

  Views:

  754

  This study measured the technical, allocative and economic efficiencies of maize production in the central rift valley of Ethiopia using cross sectional data collected from randomly selected 138 sample households. The estimated result showed that the mean technical, allocative and economic efficiencies were 84.87%, 37.47% and 31.62% respectively. Among factors hypothesized to determine the level of efficiency scores, education was found to determine allocative and economic efficiencies of farmers positively while the frequency of extension contact had a positive relationship with technical efficiency and it was negatively related to both allocative and economic efficiencies. Credit was also found to influence technical and economic efficiencies positively and distance to market affected technical efficiency negatively. The model output also indicated that soil fertility was among significant variables in determining technical efficiency in the study area. The result indicated that there is a room to increase the efficiency of maize producers in the study area.

  JEL Classifications: C67, D24, D61, L23, Q12, Q18