This paper contributes to the bank efficiency literature through an application of recently developed random parameters models for stochastic frontier analysis. We estimate standard fixed and random effects models, and alternative specifications of random parameters models that accommodate cross-sectional parameter heterogeneity. A Monte Carlo simulations exercise is used to investigate the implications for the accuracy of the estimated inefficiency scores of estimation using either an under-parameterized, over-parameterized or correctly specified cost function. On average, the estimated mean efficiencies obtained from random parameters models tend to be higher than those obtained using fixed or random effects, because random parameters models do not confound parameter heterogeneity with inefficiency. Using a random parameters model, we analyse the evolution of the average rank cost efficiency for Latin American banks between 1985 and 2010. Cost efficiency deteriorated during the 1990s, particularly for state-owned banks, before improving during the 2000s but prior to the sub-prime crisis. The effects of the latter varied between countries and bank ownership types.
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