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On identifying risk-adjusted efficiency gains or losses ofprospective mergers and acquisitions

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On identifying risk-adjusted efficiency gains or losses ofprospective mergers and acquisitions. / Tsionas, Mike G; Baltas, Konstantinos N.
In: Annals of Operations Research, Vol. 318, No. 1, 30.11.2022, p. 619-683.

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Tsionas MG, Baltas KN. On identifying risk-adjusted efficiency gains or losses ofprospective mergers and acquisitions. Annals of Operations Research. 2022 Nov 30;318(1):619-683. Epub 2022 Jul 15. doi: 10.1007/s10479-022-04826-w

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Tsionas, Mike G ; Baltas, Konstantinos N. / On identifying risk-adjusted efficiency gains or losses ofprospective mergers and acquisitions. In: Annals of Operations Research. 2022 ; Vol. 318, No. 1. pp. 619-683.

Bibtex

@article{dd44bb6b1da64d45af6831896fd6265a,
title = "On identifying risk-adjusted efficiency gains or losses ofprospective mergers and acquisitions",
abstract = "We propose a new approach to evaluate and compare ex-ante the risk-adjusted efficiency gains or losses of potential mergers and acquisitions (M &A). We test our methodology in the banking sector by estimating a latent class stochastic frontier model to account for the unobserved heterogeneity. We show that post-prospective M &A financial institutions can be better equipped to withstand potential adverse economic conditions. We highlight that similarities in strategic characteristics are vital in the creation of post-consolidation cost efficiency surplus. Our results are consistent after various robustness tests. Our findings have important policy implications in light of the challenges the traditional banking business model faces in the current digitalisation era. ",
keywords = "M A, Efficiency, Stochastic frontier, Latent class",
author = "Tsionas, {Mike G} and Baltas, {Konstantinos N}",
year = "2022",
month = nov,
day = "30",
doi = "10.1007/s10479-022-04826-w",
language = "English",
volume = "318",
pages = "619--683",
journal = "Annals of Operations Research",
issn = "0254-5330",
publisher = "Springer",
number = "1",

}

RIS

TY - JOUR

T1 - On identifying risk-adjusted efficiency gains or losses ofprospective mergers and acquisitions

AU - Tsionas, Mike G

AU - Baltas, Konstantinos N

PY - 2022/11/30

Y1 - 2022/11/30

N2 - We propose a new approach to evaluate and compare ex-ante the risk-adjusted efficiency gains or losses of potential mergers and acquisitions (M &A). We test our methodology in the banking sector by estimating a latent class stochastic frontier model to account for the unobserved heterogeneity. We show that post-prospective M &A financial institutions can be better equipped to withstand potential adverse economic conditions. We highlight that similarities in strategic characteristics are vital in the creation of post-consolidation cost efficiency surplus. Our results are consistent after various robustness tests. Our findings have important policy implications in light of the challenges the traditional banking business model faces in the current digitalisation era. 

AB - We propose a new approach to evaluate and compare ex-ante the risk-adjusted efficiency gains or losses of potential mergers and acquisitions (M &A). We test our methodology in the banking sector by estimating a latent class stochastic frontier model to account for the unobserved heterogeneity. We show that post-prospective M &A financial institutions can be better equipped to withstand potential adverse economic conditions. We highlight that similarities in strategic characteristics are vital in the creation of post-consolidation cost efficiency surplus. Our results are consistent after various robustness tests. Our findings have important policy implications in light of the challenges the traditional banking business model faces in the current digitalisation era. 

KW - M A

KW - Efficiency

KW - Stochastic frontier

KW - Latent class

U2 - 10.1007/s10479-022-04826-w

DO - 10.1007/s10479-022-04826-w

M3 - Journal article

C2 - 35855448

VL - 318

SP - 619

EP - 683

JO - Annals of Operations Research

JF - Annals of Operations Research

SN - 0254-5330

IS - 1

ER -