Abstract
AbstractIn this study, we combine the latent class stochastic frontier model with the complex time decay model to form a single-stage approach that accounts for unobserved technological differences to estimate efficiency and the determinants of efficiency. In this way, we contribute to the literature by estimating “pure” efficiency and determinants of productive units based on the class structure. An application of this proposed model is presented using data on the Ghanaian banking system. Our results show that inefficiency effects on the productive unit are specific to the class structure of the productive unit and therefore assuming a common technology for all productive units as is in the popular Battese and Coelli model used extensively in the literature may be misleading. The study therefore provides useful empirical evidence on the importance of accounting for unobserved technological differences across productive units. A policy based on the identified classes of the productive unit enables a more ...
Highlights
Estimating efficiency of productive units and its determinants within the stochastic frontier framework is widespread in the applied economic literature
We combined the latent class stochastic frontier model with Battese and Coelli (1995) complex time decay model to form a single-stage approach that accounts for unobserved technological differences to measure efficiency and more importantly examine the determinants of efficiency based on the class structure of the productive unit
We contribute to the literature by estimating “pure” efficiency and determinants of productive units based on the class structure to promote the formulation of cogent policies for efficient decision-making and management of resources
Summary
We attempt to show that it is important to account for the differences in technology of productive units in order to accurately estimate their efficiency and the determinants of efficiency. We use a latent class stochastic frontier model that account for underlying technology differences to derive efficiency as well as determinants. Applying the model using data on the Ghanaian banking system, our results show that inefficiency effects on the productive unit are specific to the class structure of the productive unit and assuming a common technology for all productive units as is normally done in the literature may be misrepresentative. The study provides useful empirical evidence on the importance of accounting for technological differences across productive units. A policy based on the identified classes of the productive unit enables a more accurate and effectual decision-making
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