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M&A operations and performance in banking. Elena Beccalli (London School of Economics and Università di Macerata) Pascal Frantz (London School of Economics). Conference on “ Mergers and Acquisitions of Financial Institutions” Washington, 30th November 2007. Aims.

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M&A operations and performance in banking

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M a operations and performance in banking l.jpg

M&A operations and performance in banking

Elena Beccalli

(London School of Economics and Università di Macerata)

Pascal Frantz

(London School of Economics)

Conference on “Mergers and Acquisitions of Financial Institutions”

Washington, 30th November 2007


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Aims

  • Do M&A operations cause changes in the performance of banks?

  • What are the sources of such changes, if any?

  • Contributions to the literature:

    • Enlarge the geographical coverage → 714 deals with EU acquirers and worldwide targets over 1991-2005

    • Test of a wide set of performance measures → Accounting ratios (ROE and CFR), cost X-efficiency and profit X-efficiency

    • Disentangle the total change in performance into the part due to the M&A operation itself and the part that would have occurred anyway


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Background

  • Relevance of M&As in the banking industry:

    • US: An intensive M&A process transformed the banking industry over the last decades (DeLong and DeYoung, 2007)

    • EU: A further integration trough cross-border M&As in retail banking is one of the main objectives pursued by the ECB (Trichet, 2007)

  • Nevertheless the evidence on the impact of M&As on performance is inconclusive


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Existing empirical evidence

Surprisingly: mixed evidence, unclear impact of M&A on bank performance


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Existing empirical evidence

  • Nevertheless all the above studies just refer to the overall change in performance by comparing in a dynamic analysis the post-M&A with the pre-M&A performance

  • But some of the change could be due to a continuation of firm-specific performance before the merger or to economy-wide and industry factors → persistency (Healy et al., 1992)

  • Healy et al. (1992) however do not investigate the banking industry (i.e. impact on CFR of the 50 largest US mergers over the period 1979 and 1984)


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Methodology

1. ANOVA test - comparison of:

  • Performance values for banks involved in M&A operations and banks not involved in any M&A operations → Industry-adjusted performance

  • Performance values for target and acquirer in the pre-M&A period

  • Performance for the combined bank resulting after the M&A deal and weighted average of the performance of the target and acquirer prior to the M&A deal → Change in industry-adjusted performance


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Methodology

2.To split the overall change in performance into the change specifically due to the M&A and the change due to economy-wide factors, industry-factors, continuation of bank-specific performance (Healy et al. 1992):

  •  = Impact of the M&A operation on performance

  • β = Change in performance independent from the M&A (persistence in performance)

  • AdjPer = Average annual industry-adjusted performance for each M&A (accounting values and X-efficiency estimation)

    3. To control for the determinants of the change in performance:

  • CV (control variables): deal-specific, bank-specific and regulatory and institutional variables


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Accounting-based measures of performance


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Operating efficiency as performance measure

  • X-efficiency: measure of managerial best practice

  • Methodological choices for the estimation:

    • Parametric approach: SFA

    • Cost efficiency and profit efficiency:

      • Cost efficiency: how close a bank is to the cost sustained by the best practice bank to produce a given mix of outputs

      • Alternative profit efficiency: how close a bank is to the realisation of the maximum level of profit given its mix of outputs → Ability to apply a price premium

    • Functional form: Fourier flexible

    • Definition of input and outputs: intermediation approach

    • Cross-country panel


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Data set and sample

  • Dataset:

    • Data on the M&A deal: Thomson One Banker

    • Prices of listed banks, benchmark and economic indexes: Datastream

    • Bank financial statements: Bankscope

  • M&A sample: M&A deals announced between 1/1/1991 and 31/12/2005 with a EU acquirer and a target located anywhere in the world:

    • 714 deals (394 domestic and 320 cross-border transactions) → Unique sample

  • Control sample: all banks that have not engaged in any M&A:

    • Matching on the basis of: nationalities of acquirers and targets, year and type of activity

    • 7963 observations over 1991-2005


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Adjusted efficiency of acquirers and targets (pre-deal)

% of positive cases under the Wilcoxon test.

°°°, °°, °

Z-test respectively statistically significant at 1%, 5% and 10%.


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Adjusted ROE (BY) of acquirers and targets (pre deal)


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Comparison of adjusted efficiency of acquirers and targets (pre-deal)


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Comparison of adjusted ROE and CFR of acquirers and targets (pre-deal)


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Change in efficiency (pre- vs. post- deal)

Base year are weighted averages of the performance measure in the years prior to the M&A of the target and acquiring banks.


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Change in ROE and CFR (pre- vs. post- deal)


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Change in efficiency pre vs. post (domestic deals)


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Change in efficiency pre vs. post (cross-border deals)


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Change in ROE(BY) pre vs. post(domestic vs. cross-border deals)


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Cost efficiency: M&A vs. persistency (post- vs. pre- deal average)


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Profit efficiency: M&A vs. persistency (post- vs. pre- deal average)


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ROE and CFR: M&A vs. persistency (post- vs. pre- deal average)


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Cost efficiency: M&A vs. persistency (post- vs. pre- deal average) Domestic vs. cross-border deals


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Profit efficiency: M&A vs. persistency (post- vs. pre- deal average) Domestic vs. cross-border deals


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Determinants of changes in efficiency pre- vs. post- deal

Freedom from government (http://www.heritage.org/research/features/index/) = Government expenditures and state-owned enterprises. Regulatory quality (www.worldbank.org) = Ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. Traditional banking = Loans/Total assets; Riskiness = Stand. Dev ROE; Big, Medium, Small = 33°, 66°, 99° percentile (ln (Total assets)).


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Conclusions

  • Slight decrease in ROE, CFR and profit efficiency after the M&A, but pronounced improvement in cost efficiency → Cost efficiency benefits transferred to clients rather than to shareholders

  • Changes in performance are directly determined by the M&A and would have not otherwise occurred

  • Changes in performance exhibit a particularly negative trend for cross-border deals → Importance of geographical relatedness

  • Before the M&A operation, banks involved in M&A operations (both acquirers and targets) are more efficient and profitable than their peers not involved in M&A operations


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Conclusions

  • Before the M&A operation, target banks exhibit weaker performance than acquirers in terms of profit efficiency, CFR, ROE, personnel expenses and operating costs

  • Acquirers should tend to direct investments to those countries with a better regulatory quality and a higher freedom from government

  • To achieve positive changes in efficiency in the medium-term, transactions should be domestic, paid in equity (not in cash), and result in a combined bank with a higher focus on traditional banking activities


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Support slides


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Unadjusted performance of acquirer and target banks (pre-deal)

Return on Equity (ROE) = Net income / Total Equity (end of the year); Non Traditional Banking (NTB) = OBS/Total assets; Net margin (NM) = Net income /Revenues (= Interest income+ Commission income + Trading income); Total Operating Expense Ratio (TOER) = Total non-interest operating expense /Total assets; Personnel expense ratio (PER) = Personnel costs / Total assets. ***, **, * T-test respectively statistically significant at 1%, 5% and 10%.


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Unadjusted performance Comparison of acquirers and targets (pre-deal)

Return on Equity (ROE) = Net income/Total Equity (end of the year); Non Traditional Banking (NTB) = OBS/Total assets; Net margin (NM) = Net income/Revenues (= Interest income+ Commission income + Trading income); Total Operating Expense Ratio (TOER) = Total non-interest operating expense/Total assets; Personnel expense ratio (PER) = Personnel costs/Total assets.

***, **, * T-test respectively statistically significant at 1%, 5% and 10%.


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Adjusted efficiency M&A banks vs. non-M&A banks (by year)


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Adjusted efficiency: M&A banks vs. non-M&A banks (by country)


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Change in ROE (AVG)(pre- vs. post- deal)


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Change in CFR (premia adjusted)(pre- vs. post- deal)


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Descriptive statistics of determinants

Freedom from government: http://www.heritage.org/research/features/index/; Regulatory quality: www.worldbank.org


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