TESTING THE IMPACT OF INPUT AND OUTPUT SUBSTITUTABILITY IN NONPARAMETRIC PRODUCTION ANALYSIS: EVIDENCE FROM LIFE INSURANCE INDUSTRY IN INDIA

抄録

In this paper, two different variants (constrained and unconstrained) of a data envelopment analysis (DEA) model are used to compare inferences about production correspondence of the life insurance industry in India. While the unconstrained model implicitly assumes input substitutions and output transformations without their empirical verification, the constrained model explicitly incorporates weight restrictions on those inputs and outputs that are not substitutable and transformable, respectively. Our key findings are as follows. First, although the constrained model seems closely related to the notion of industry (structural) efficiency model, this link remains unexplored: we suggest a link between both models. Second, though the constrained model generates efficiency scores that are no more than those of its unconstrained counterpart, both models are in broad agreement in revealing that the life insurance industry experiences a sustained surge in its efficiency due to competition arising from insurance reforms adopted by the government over years, thus supporting the competition and X-efficiency hypothesis. Third, when the economic requirement of input substitutions is absent, both the models are found to give statistically significant results on efficiency ratings, returns to scale possibilities, and total factor productivity growth. In such a case, the unconstrained model generates benchmarking results based on an incorrect production frontier, which are potentially misleading and can hardly be used in managerial contexts. This finding, therefore, cautions the researchers not to blindly use any unconstrained model to evaluate the efficiency, productivity growth and returns to scale characterizations of firms without empirically verifying the presence/absence of input substitutions and output transformations.