Abstract
We introduce a counterfactual analysis of banks mergers, combining the pre-merger equilibrium setting with post-merger environmental characteristics, while accounting for endogenously propagated changes in market structure. Using this procedure we are able to estimate the effects on loan flows and interest rates that would have been observed if the pre-merger equilibrium was not altered. Results are obtained for firms, households, and banks inside and outside the merging circles separately. We find that mergers increased firms’ access to credit, but had an opposite effect on households and led to a widespread decrease in interest rates.
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Notes
The dangers of neglecting this issue in the analysis of different economic periods are extensively discussed in Lerner and Tufano (2011).
Beck et al. (2009) provide evidence regarding the importance of analyzing household and firm loans separately.
There is less work done on the impact of bank mergers on depositors. There is some empirical evidence for Italian firms which suggests that bank mergers may have positive consequences for depositors in the long-run, even though there may be some negative effects in the short run (Focarelli and Panetta 2003). However, Craig and Dinger (2009), using US data, obtain a different result, given that they do not observe any positive long-term effect of mergers on deposit interest rates. Their results are consistent with previous work done by Prager and Hannan (1998).
Even though Portugal joined the euro area at its inception in 1st January 1999, the effects of the convergence process in credit markets were felt mainly during the 1990s. As discussed in Antão et al. (2009), interest rates decreased gradually during the 1990s due to this convergence process and, simultaneously, credit accelerated during this period. Hence, the effects of joining the euro area were gradual and not concentrated specifically around 1999.
For a discussion on efficiency gains arising from bank mergers, see Sapienza (2002).
See Kim and Vale (2001) for further details.
There are 18 districts in Portugal.
A similar index can be found in Barros (1999).
For a similar approach, see Barros (1999).
We have tried different strategic effects and the results do not change significantly. For instance, we have considered (i) defining the main rival as the bank that has granted more credit during the quarter \((X{\text{ max}}_{it} ),\) (ii) the bank with the closest loan flow in each quarter, (iii) the interaction of the five main rivals, (iv) the average of the interaction of the five main rivals \(X{\text{ max}}_{it} =1/5\sum _{j=1,...,5} {X{\text{ max}}_{jt} } \) or (v) the interactions given by: \(X{\text{ max}}_{it} =\left( {\frac{1}{n_t }} \right)\sum _{_{i=1,...,5} } {\frac{L{\text{ max}}_i }{L_{it} }} (r{\text{ max}}_i -c_{jt} ).\)
For further details on the Monetary and Financial Statistics, please see http://www.bportugal.pt/en-US/Estatisticas/Dominios%20Estatisticos/Pages/EstatisticasMonetariaseFinanceiras.aspx or http://www.ecb.int/ecb/legal/1005/1021/html/index.en.html.
For instance, Berger et al. (1998) consider that the dynamic effects of bank mergers should be analyzed in the three years following the merger.
We consider that both the acquiring and the acquired banking groups are involved in the merger.
As shown by Park and Pennacchi (2009), bank mergers affect differently large and small banks, hence justifying analyzing them separately.
Most of the banks in the sample operate in both the household and the corporate credit markets, even though some small banks display null credit flows in one of these segments in some quarters. All banks considered grant credit to households and only two small banks never grant credit to firms during the entire sample period.
Berg and Kim (1998) empirically document such separability in the Norwegian market and present a discussion on cross-market interactions when banks produce multiple outputs.
For robustness purposes, banking group fixed effects were also included in the regressions, to take into account possible similarities or synergies between financial institutions integrated in the same banking group. The results are broadly consistent and are available upon request. Nevertheless, the value added by these additional fixed effects is marginal and implies an important loss of the degrees of freedom used in the estimations.
In a recent paper, Corvoisier and Gropp (2009) argue that the widespread use of web-based banking platforms should have decreased sunk costs and increased contestability in retail banking, as establishing branches became less important. Nevertheless, the authors find that even though this hypothesis may be true for time and saving deposits, it does not hold for small business loans, where establishing a branching network with local connections is still important.
In the table, we omit the \(t\) stats for this coefficient in columns (1), (3), and (5), as this coefficient is determined by the constraint in system (3).
The lower number of observations in the regressions for households and firms is due to the fact that some small banks show null credit flows in one of these market segments in some quarters, as discussed in Sect. 3.2. Moreover, two small banks never grant credit to firms during the entire sample period.
Controlling for GDP should capture the most relevant time fixed effects. To mitigate concerns about potential cointegration issues, we also considered the GDP growth rate, having obtained broadly similar results.
The estimated coefficient \(\varphi _{42}\) is 5.36 for households (with a \(t\) statistic of 1.94) and 20.13 for firms (with a \(t\) statistic of 6.23).
The choice of the year 2000 is motivated by the large number of mergers observed, some of which involving some of the largest banks. As illustrated in Sect. 3.1, these mergers had a substantial impact on market structure.
To explore in more detail the timing of these effects, we estimated another modified version of our empirical model where instead of \(\alpha _{01} AFTER\) and \(\beta _{01} AFTER\) we consider \(\alpha _{01} AFTERD2000+ \alpha _{02} AFTER D2001+ \alpha _03 AFTERD2002\) and \(\beta _{01} AFTERD2000+ \beta _{02} AFTERD2001+ \beta _{03} AFTERD2002.\) This analysis shows that the negative effect on credit granted to households was gradual, but became slightly larger over time. In turn, the positive effect on loans to firms was concentrated in the immediate post-merger period. For interest rates, the decrease attributable to mergers was gradually felt over time, both for households and for the corporate sector.
Given the recursive nature of the model, the estimated interest rates are used to estimate credit flows in the counterfactual.
As previously documented, out of the seven major financial groups, four were directly involved in the merger wave.
These efficiency gains are expected to be larger when there is a significant market overlap between merging banks. Indeed, this is the case in our sample, where merging banks are large universal banks operating throughout the whole country in most retail segments. It is thus reasonable to argue that the restructuring of overlapping branch networks and business segments may have contributed to efficiency gains.
These differences may have important economic implications, as shown by Beck et al. (2009).
In these columns, the interest rates, loan flows and the strategic interaction variable were computed using the values predicted by the model, instead of using directly the values observed. The results are consistent under both hypotheses.
For robustness purposes, we conducted several sensitivity tests on the definition of the post-merger period (as done for the analysis of the differential impact of the merger wave). More specifically, we consider the possibility that the effect of bank mergers takes some time to be reflected in credit flows and interest rates. Moreover, it is also possible that immediately before the merger there were some strategic effects. To take all this into account, we exclude the last two quarters of 1999 and the year 2000 from our estimations. The results are qualitatively robust. The effect of bank mergers on total credit flows is slightly less significant for the banks directly involved in mergers, but more significant for the whole sample.
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Acknowledgments
We would like to thank the Editor Heather Anderson, two anonymous referees, Daniel Ackerberg, António Antunes, Vittoria Cerasi, Filipa Lima, David Martinez Miera, Hugo Reis, Nuno Ribeiro, Mark Roberts, João Santos, Giancarlo Spagnolo, Jonathan Williams and participants in the CEPR European Summer Symposium in Financial Markets 2011, 2nd Emerging Scholars in Banking and Finance Conference, ZEW Conference on the Quantitative Analysis in Competition Assessments and 2010 Portuguese Finance Network Conference for insightful comments and suggestions. The analysis, opinions and findings of this paper represent the views of the authors, they are not necessarily those of the Banco de Portugal or the Eurosystem.
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This study was initiated when Nuno was working at the Banco de Portugal and Universidade Nova de Lisboa.
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Barros, P.P., Bonfim, D., Kim, M. et al. Counterfactual analysis of bank mergers. Empir Econ 46, 361–391 (2014). https://doi.org/10.1007/s00181-012-0666-1
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DOI: https://doi.org/10.1007/s00181-012-0666-1