Efficiency, Technical Change, and Returns to Scale in Large U.S. Banks: Panel Data Evidence from an Output Distance Function Satisfying Theoretical Regularity
Guohua Feng () and
Apostolos Serletis
No 5/09, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics
Abstract:
This paper provides parametric estimates of technical change, efficiency change, economies of scale, and total factor productivity growth for large banks (those with assets in excess of $1 billion) in the United States, over the period from 2000 to 2005. This is done by estimating an output distance function subject to theoretical regularity within a Bayesian framework. We find that failure to incorporate theoretical regularity conditions results in mismeasured shadow revenue and/or cost shares, which in turn leads to perverse conclusions regarding productivity growth. Our results from the regularity-constrained model show that total factor productivity of the large U.S. banks grew at an average rate of 1.98% over the sample period. However, our estimates also show a clear downward trend in the growth rate of total factor productivity and our decomposition of the primal Divisia total factor productivity growth index into its three components - technical change, efficiency change, and economies of scale - indicates that technical change is the driving force behind this decline.
Keywords: Productivity decomposition; Translog output distance function. (search for similar items in EconPapers)
JEL-codes: C11 D24 G21 (search for similar items in EconPapers)
Pages: 48 pages
Date: 2009-06-24
New Economics Papers: this item is included in nep-ban and nep-eff
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Citations: View citations in EconPapers (12)
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Journal Article: Efficiency, technical change, and returns to scale in large US banks: Panel data evidence from an output distance function satisfying theoretical regularity (2010)
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