Introduction
Conceptually, there are two general methodologies to measure frontier efficiency; the parametric approach using econometric techniques, and the non-parametric approach utilising the linear programming method. Both approaches differ mainly in how they handle the random error and the assumptions made on the shape of the efficient frontier. However, each of the techniques has its own strengths and weaknesses. The most widely employed parametric methods are stochastic frontier approach (SFA), thick frontier approach (TFA) and distribution-free approach (DFA). On the other hand, the commonly used non-parametric techniques are free disposal hull analysis (FDH) and Data Envelopment Analysis (DEA).
This paper follows the DEA nonparametric approach. In this regard, Farrell (1957) originally developed this non-parametric efficiency approach. The DEA is non-parametric in the sense that it simply …show more content…
The CRS assumption is only justifiable when all DMUs are operating at an optimal scale. However, firms or DMUs in practice might face either economies or diseconomies of scale. Thus, if one makes the CRS assumption when not all DMUs are operating at the optimal scale, the computed measures of technical efficiency will be contaminated with scale efficiencies.
Banker et al. (1984) extended the CCR model by relaxing the CRS assumption. The resulting ‗‗BCC‘‘ model was used to assess the efficiency of DMUs characterised by variable returns to scale (VRS). The VRS assumption provides the measurement of pure technical efficiency (PTE), which is the measurement of technical efficiency devoid of the scale efficiency effects. If there appears to be a difference between the TE and PTE scores of a particular DMU, then it indicates the existence of scale
Conceptually, there are two general methodologies to measure frontier efficiency; the parametric approach using econometric techniques, and the non-parametric approach utilising the linear programming method. Both approaches differ mainly in how they handle the random error and the assumptions made on the shape of the efficient frontier. However, each of the techniques has its own strengths and weaknesses. The most widely employed parametric methods are stochastic frontier approach (SFA), thick frontier approach (TFA) and distribution-free approach (DFA). On the other hand, the commonly used non-parametric techniques are free disposal hull analysis (FDH) and Data Envelopment Analysis (DEA).
This paper follows the DEA nonparametric approach. In this regard, Farrell (1957) originally developed this non-parametric efficiency approach. The DEA is non-parametric in the sense that it simply …show more content…
The CRS assumption is only justifiable when all DMUs are operating at an optimal scale. However, firms or DMUs in practice might face either economies or diseconomies of scale. Thus, if one makes the CRS assumption when not all DMUs are operating at the optimal scale, the computed measures of technical efficiency will be contaminated with scale efficiencies.
Banker et al. (1984) extended the CCR model by relaxing the CRS assumption. The resulting ‗‗BCC‘‘ model was used to assess the efficiency of DMUs characterised by variable returns to scale (VRS). The VRS assumption provides the measurement of pure technical efficiency (PTE), which is the measurement of technical efficiency devoid of the scale efficiency effects. If there appears to be a difference between the TE and PTE scores of a particular DMU, then it indicates the existence of scale