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Journal of Financial Services Research

Erschienen in:

01.12.2009

Bank Mergers and the Dynamics of Deposit Interest Rates

verfasst von: Ben R. Craig, Valeriya Dinger

Erschienen in: Journal of Financial Services Research | Ausgabe 2-3/2009

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Abstract

Despite extensive research interest in the last decade, the banking literature has not reached a consensus on the impact of bank mergers on deposit rates. In particular, results on the dynamics of deposit rates surrounding bank mergers vary substantially across studies. In this paper, we aim for a comprehensive empirical analysis of a bank merger’s impact on deposit rate dynamics. We base the analysis on a unique dataset comprising deposit rates of 624 US banks with a monthly frequency for the time period 1997–2006. These data are matched with individual bank and local market characteristics and the complete list of bank mergers in the US. The data allow us to track the dynamics of bank mergers while controlling for the rigidity of the deposit rates and for a range of merger, bank, and local market features. An innovation of our work is the introduction of an econometric approach for estimating the change of the deposit rates given their rigidity.

Vorheriger Artikel Mergers and Acquisitions of Financial Institutions: A Review of the Post-2000 Literature

Nächster Artikel Discussion of “Bank Mergers and the Dynamics of Deposit Rates”

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See Sheshinski and Weiss (1977), Caplin and Spulber (1987), Cabalero and Engels (2007).

In a study that inspired the early research on the effect of mergers, Kim and Singal (1993) find that airline mergers have resulted in higher airfares. However, Connor et al. (1997) find that hospital mergers have resulted in lower consumer prices.

Corvoisier and Gropp (2002) replicate Berger and Hannan’s (1989) analysis on a sample of EU banks.

Kahn et al. (2005) study the dynamics of loan rates in a similar framework.

Sapienza (2002) studies loan rate dynamics in a similar framework.

Berger et al. (1998), and Calomiris and Karceski (2000) argue that the gestation period needed to restructure a merged bank is three years.

The structure of bank liabilities has been the subject also of a growing literature on market discipline. It has argued that banks may not refinance in the wholesale market because wholesale exposures are not insured and create incentives for the lenders to monitor. Therefore, banks which are perceived as riskier may prefer to refinance mostly with insured retail deposits (Billett et al. 1998).

Park and Pennacchi use bank size as a proxy for geographical scope.

Our merger data start roughly 10 years before the start of our deposit rate dataset. This is motivated by the fact that we need data about past mergers in order to examine both the short-term and the long-term effects of bank mergers on deposit rates.

Hannan and Prager (1998) find no significant impact of bank mergers on certificate of deposit rates.

As in Hannan and Prager (1998), we concentrate on substantial in-market mergers defined as mergers which led to a rise in the local market’s HHI of at least 100 basis points.

As argued by Hannan and Prager (1998), because the dependent variable is first differenced, fixed effects are not needed in the estimation.

Our approach is slightly different from Hannan and Prager’s here. They adopt a dummy variable for each of the −12/+12 months around the merger.

In these regression specifications we follow Hannan and Prager (1998) and do not control for any features of the bank or the local market.

Note that by using the relative rate as a dependent variable, a coefficient of −1 on the reference rate, which corresponds to a perfect adjustment of deposit rates to reference rates, is assumed. This is a strong assumption given the rigidity of deposit rates.

Our set of control variables slightly differs from Focarelli and Panetta’s in that we include the squared bank size term (significant in all regression specifications) in addition to bank size to control for nonlinearity in the size’s impact on deposit rates. The Herfindahl index (HHI) is included as a market structure proxy instead of the concentration ratio used by Focarelli and Panetta (2003).

http://www.iiw.uni-bonn.de/dinger/

Although less obvious, the censoring problem is also present in Focarelli and Pannetta’s (2003) framework, where the difference between the deposit and the interbank rates is used as a dependent variable. Again, since deposit rates change very infrequently, the changes of the dependent variable are driven only by changes in the interbank rate.

The derivation of the spline values will be discussed in detail in the next section.

Our dependent variable data are monthly, whereas some of the bank and local market-level controls are quarterly or annual. To deal with this issue we estimate the model using clustered standard errors.

(S,s) models were first introduced to model retail inventories, where inventory levels had to fall below a threshold value, “s”, before the firm would order new production. In the last two decades they have been extensively used to model lumpy price adjustments (Sheshinski and Weiss 1977; Cabalero and Engels 2007).

Neumark and Sharpe (1992) and Berger and Hannan (1991) show that deposit rates are especially inflexible when the pressure is to adjust upward.

The merger date is the date on which the target bank loses its charter.

See Craig and Santos 1997.

http://www.iiw.uni-bonn.de/dinger/

Summary of Deposits publishes market shares as of June 30; therefore, we define the year in this case as the period July 1 to June 30.

The Supervisory Master File of Bank Mergers and Acquisitions provides data for the target banks’ ID. Given these, we match the acquiring banks’ data with the target banks’ data from the Call Report.

The results of the first-stage of the estimation (the probit regressions on positive or negative deposit rate changes) are available from the authors upon request and on the authors’ website (http://www.iiw.uni-bonn.de/dinger/).

The marginal effects are estimated by computing the exponential of the estimated coefficient of the spline knot. In other words, the marginal change at the knot is equal to exp(β) – 1, where β is the estimated knot coefficient.

We derive the cumulative effects by integrating the marginal effects estimated from the spline knots. Because this also integrates the estimation error, we believe that the confidence intervals for these estimates are very large, and thus emphasize that the large magnitude of the cumulative effects should be treated with caution.

Gropp et al. (2007) find evidence on incomplete and delayed adjustment of deposit rates offered by European banks.

Again, we conjecture that the confidence interval for the cumulative effect to be large.

This result is consistent with the results of Park and Pennacchi’s (2008) study.

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Titel: Bank Mergers and the Dynamics of Deposit Interest Rates
verfasst von: Ben R. Craig
Valeriya Dinger
Publikationsdatum: 01.12.2009
Verlag: Springer US
Erschienen in: Journal of Financial Services Research / Ausgabe 2-3/2009
Print ISSN: 0920-8550
Elektronische ISSN: 1573-0735
DOI: https://doi.org/10.1007/s10693-008-0042-7

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