The empirical literature has obtained mixed results regarding the probability for more efficient banks to be bidders in merger and acquisitions (M&A) operations. From an econometric point of view, this might be attributed to an inaccurate control of unobserved bank heterogeneity that can bias parameter estimation severely. In this paper, we adequately control for unobserved heterogeneity through a finite mixture, random parameters logistic model, and we estimate the probability for a bank to be a bidder in an M&A depending on its ex-ante efficiency, therefore avoiding any parametric assumption on the distribution of the random effect. This leads to a likelihood function defined as the integral of the kernel density with respect to the mixing density, which has no analytical solution. For this reason, we approximate the integral with a finite sum of kernel densities, each one characterized by a different set of model parameters. We then obtain a set of non-overlapping clusters with matching values of ex-ante efficiency, and assign each bank to a cluster based on the estimated posterior probability of it being in that cluster. Moreover, in our analysis we use two different sets of measures of bank efficiency, obtained using parametric as well as semi-parametric techniques. Our results are based on a sample of 612 banks, from 34 countries, between 1991 and 2006. They show that, considering unobserved heterogeneity, cost efficiency has a major impact on the probability for a bank to bid in a cross-border M&A, but no effect in the case of domestic M&A.

Caiazza, S., Pozzolo, A., Trovato, G. (2016). Bank efficiency measures, M&A decision and heterogeneity. JOURNAL OF PRODUCTIVITY ANALYSIS, 46(1), 25-41 [10.1007/s11123-016-0470-6].

Bank efficiency measures, M&A decision and heterogeneity

CAIAZZA, STEFANO;TROVATO, GIOVANNI
2016-01-01

Abstract

The empirical literature has obtained mixed results regarding the probability for more efficient banks to be bidders in merger and acquisitions (M&A) operations. From an econometric point of view, this might be attributed to an inaccurate control of unobserved bank heterogeneity that can bias parameter estimation severely. In this paper, we adequately control for unobserved heterogeneity through a finite mixture, random parameters logistic model, and we estimate the probability for a bank to be a bidder in an M&A depending on its ex-ante efficiency, therefore avoiding any parametric assumption on the distribution of the random effect. This leads to a likelihood function defined as the integral of the kernel density with respect to the mixing density, which has no analytical solution. For this reason, we approximate the integral with a finite sum of kernel densities, each one characterized by a different set of model parameters. We then obtain a set of non-overlapping clusters with matching values of ex-ante efficiency, and assign each bank to a cluster based on the estimated posterior probability of it being in that cluster. Moreover, in our analysis we use two different sets of measures of bank efficiency, obtained using parametric as well as semi-parametric techniques. Our results are based on a sample of 612 banks, from 34 countries, between 1991 and 2006. They show that, considering unobserved heterogeneity, cost efficiency has a major impact on the probability for a bank to bid in a cross-border M&A, but no effect in the case of domestic M&A.
2016
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore SECS-P/01 - ECONOMIA POLITICA
Settore SECS-P/02 - POLITICA ECONOMICA
Settore SECS-P/11 - ECONOMIA DEGLI INTERMEDIARI FINANZIARI
English
Bank mergers and acquisitions; Efficiency; Finite mixture models; Latent stochastic frontier; Multinomial logit models;
Bank mergers and acquisitions; Latent stochastic frontier; Efficiency; Finite mixture models; Multinomial logit models
Caiazza, S., Pozzolo, A., Trovato, G. (2016). Bank efficiency measures, M&A decision and heterogeneity. JOURNAL OF PRODUCTIVITY ANALYSIS, 46(1), 25-41 [10.1007/s11123-016-0470-6].
Caiazza, S; Pozzolo, A; Trovato, G
Articolo su rivista
File in questo prodotto:
File Dimensione Formato  
caiazza_pozzolo_trovato_23_07_13.pdf

solo utenti autorizzati

Licenza: Copyright dell'editore
Dimensione 394.5 kB
Formato Adobe PDF
394.5 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/171492
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 7
  • ???jsp.display-item.citation.isi??? 4
social impact