Abstract
This paper compares the productivity and efficiency of large banks and community banks in the United States over the period 1997–2006. This comparison is performed by estimating a true random effects stochastic distance frontier model—a model that is capable of disentangling unobserved heterogeneity from inefficiency—within a Bayesian framework. We find that failure to consider unobserved heterogeneity results in a misleading ranking of banks and mismeasured technical efficiency, productivity growth, and returns to scale. Our results show that, compared with community banks, large banks have experienced much higher productivity growth and higher levels of returns to scale. Our estimates of total factor productivity growth show a clear downward trend for both large and community banks, and our decomposition of the output-distance-function-based Divisia productivity index indicates that technical change is the driving force behind this trend.
Published Version
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