Productivity and efficiency at bank holding companies in the U.S.: a time-varying heterogeneity approach
Guohua Feng (),
Bin Peng () and
Xiaohui Zhang
Additional contact information
Xiaohui Zhang: University of Exeter
Journal of Productivity Analysis, 2017, vol. 48, issue 2, No 6, 179-192
Abstract:
Abstract This paper investigates the productivity and efficiency of large bank holding companies (BHCs) in the United States over the period 2004–2013, by estimating a translog stochastic distance frontier (SDF) model with time-varying heterogeneity. The main feature of this model is that a multi-factor structure is used to disentangle time-varying unobserved heterogeneity from inefficiency. Our empirical results strongly suggest that unobserved heterogeneity is not only present in the U.S. banking industry, but also varies over time. Our results from the translog SDF model with time-varying heterogeneity show that the majority of large BHCs in the U.S. exhibit increasing returns to scale, a small percentage exhibit constant returns to scale, and an even smaller percentage exhibit decreasing returns to scale. Our results also show that on average the BHCs have experienced small positive or even negative technical change and productivity growth.
Keywords: Productivity and efficiency; Bank holding companies; Translog stochastic distance frontier model with time-varying heterogeneity; Bayesian estimation (search for similar items in EconPapers)
JEL-codes: C11 D24 G21 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4) Track citations by RSS feed
Downloads: (external link)
http://link.springer.com/10.1007/s11123-017-0515-5 Abstract (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:kap:jproda:v:48:y:2017:i:2:d:10.1007_s11123-017-0515-5
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/11123/PS2
DOI: 10.1007/s11123-017-0515-5
Access Statistics for this article
Journal of Productivity Analysis is currently edited by William Greene, Chris O'Donnell and Victor Podinovski
More articles in Journal of Productivity Analysis from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().