This study employs a bivariate smoothing bootstrap technique to obtain a statistical inference for Technical Efficiency and Malmquist Indices and their components of Polytechnics in Ghana over the period 2009-2014. The main contribution of this paper is to provide an Efficiency Analysis using a non-parametric approach with a robust estimator. This methodology is empirically being applied in the analysis of Polytechnic Education in Ghana because it affords us the opportunity to compute the statistical significance of changes in Polytechnics’ Technical Efficiency and Productivity Indices and their respective components. Results showed that averagely, Technical Efficiency fluctuated over the period; however, Polytechnic Education experienced a significant technological regress, with few Polytechnics achieving increases in productivity led by improvements in efficiency. Policy implications are derived.
Road traffic carnages are global concerns and seemingly on the rise in Ghana. Several risk factors have been studied as associated with road traffic fatalities. However, inadequate road traffic fatality (RTF) data and inconsistent probability outcomes for RTF remain major challenges. The objective of this study is to illustrate and estimate probability models that can predict road traffic fatalities. We relied on 66,159 recorded casualties who were involved in road traffic accidents in Ghana from 2015 to 2019. Three generalized linear models, namely logistic regression, probit regression and linear probability model were used for the analysis. We found that gender and age groups have significant effects in predicting the probability of road traffic fatality for all three models. Through a likelihood ratio test, however, it was determined that the logit regression model produced consistent probabilities of traffic fatalities which are very close to the actual probability values across the age groups and gender, compared to the other two models. Thus, we recommend intensified campaign for the use of seat belts in vehicles, targeted at the aged and male users of road transport to reduce the possibility of death in any RTA.
Road traffic carnages are global concerns and seemingly on the rise in Ghana. Several risk factors have been studied as associated with road traffic fatalities. However, inadequate road traffic fatality (RTF) data and inconsistent probability outcomes for RTF remain major challenges. The objective of this study was to illustrate and estimate probability models that can predict road traffic fatalities. We relied on 66,159 recorded casualties who were involved in road traffic accidents (RTAs) in Ghana from 2015 to 2019. Three generalized linear models, namely, logistic regression, probit regression, and linear probability model, were used for the analysis. We found that gender and age groups have significant effects in predicting the probability of road traffic fatality for all three models. Through a likelihood ratio test, however, it was determined that the logit regression model produced consistent probabilities of traffic fatalities which are very close to the actual probability values across the age groups and gender, compared to the other two models. Thus, we recommend intensified campaign for the use of seat belts in vehicles, targeted at the aged and male users of road transport, to reduce the possibility of death in any RTA.
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