Algebraic inequalities by Vasile Cirtoaje

By Vasile Cirtoaje

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183–207) allows each individual’s DEA efficiency score to be decomposed into two components: one attributable to the university at which the student studied and the other attributable to the individual student. From the former component, a measure of each institution’s teaching efficiency is derived and compared to the university effects from various multilevel models. The comparisons are made within four broad subjects: pure science, applied science, social science and arts. , having excluded the efforts of the individuals) are not strongly correlated with the university rankings derived from the university effects of the multilevel models.

2 represent the process of estimation of OUTTE using group frontiers, Meta frontier and technology closeness ratio respectively. 2 represents the methodology for finding out the determinants of technical efficiency score for each group GCS, SCS&UT. 3 describes data sources. The empirical findings are presented in Sect. 3. 1 presents estimated results on OUTTE at primary level of education both for GCS, SCS&UT; Sects. 2 represent the estimated results on OUTTE for GCS, SCS&UT respectively. 2 presents estimated results on OUTTE at upper primary level of education both for GCS, SCS&UT; Sects.

Teachers’ salary is found to have positive effect on technical efficiency while the proportion of Kuwaiti teaching staff has a negative impact. All-girls schools are found to have higher efficiency than all-boys schools. Cherchye et al. (2010) presented a nonparametric approach for efficiency and equity evaluation in education using a nonparametric DEA. The model accounts for the fact that typically minimal prior structure is available for the behavior (objectives and feasibility set) under evaluation.

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