Journal of Monetary Economics 20 (1987) 141-153. North-Holland AN ANALYSIS OF FDIC FAILED BANK AUCTIONS* Christopher JAMES University of Oregon, Eugene, OR 97403, USA Peggy WIER University of Rochester, Rochester, NY 14627, USA This paper examines whether the sales mechanism used by the FDIC in failed bank auctions results in wealth transfers from the FDIC to the acquiring banks. We test this hypothesis by examining the returns to winning bidders in FDIC auctions. We find positive abnormal returns to these bidders. More importantly, we find a negative and significant relation between the returns to winning bidders and the number of bidders participating in the auction. This evidence suggests that the FDIC’s auction procedures do generate wealth transfers. 1. Introduction The Federal Deposit Insurance Corporation (FDIC) is both a bank regu- lator and a bank deposit insurer. The FDIC as an insurer is supposed to deal with bank failures in the least costly way that is consistent with its regulatory assignment to preserve the safety and soundness of the banking system. One method of fulfilling the dual role is to arrange a transaction in which a healthy bank purchases some of a failed bank’s assets and assumes its liabilities. Such purchase and assumption transactions (P&A’s) are sealed bid fist price auctions, usually conducted within a few days of the closure of the failed bank. Only banks that possess certain financial characteristics and operate within a specified geographical area around the failed bank are invited to submit bids. No bank may participate in the auction if, in the opinion of the FDIC, its acquisition of the assets would cause a substantial lessening of competition in the failed bank’s output market (12 USC 1823 Section 13). Recent research on auctions suggests that the mechanism used for selling an asset can affect the revenues received by the seller.’ FDIC failed bank auctions < *This research was supported in part by McGraw-Hill Incorporated which provided us access to the Data Resources Incorporated Securities Price File. The authors thank the participants of the finance workshops at the University of Oregon, the University of Michigan and the University of Utah. ‘See, for example, Vickery (1961), Milgrom and Weber (1982), Riley and Samuelson (1981). and Cammack (1985), for analysis leading to this conclusion. 03043932/87/$3.50@1987, Elsevier Science Publishers B.V. (North-Holland)
Transcript
Journal of Monetary Economics 20 (1987) 141-153. North-Holland
AN ANALYSIS OF FDIC FAILED BANK AUCTIONS*
Christopher JAMES University of Oregon, Eugene, OR 97403, USA
Peggy WIER University of Rochester, Rochester, NY 14627, USA
This paper examines whether the sales mechanism used by the FDIC in failed bank auctions results in wealth transfers from the FDIC to the acquiring banks. We test this hypothesis by examining the returns to winning bidders in FDIC auctions. We find positive abnormal returns to these bidders. More importantly, we find a negative and significant relation between the returns to winning bidders and the number of bidders participating in the auction. This evidence suggests that the FDIC’s auction procedures do generate wealth transfers.
1. Introduction
The Federal Deposit Insurance Corporation (FDIC) is both a bank regu- lator and a bank deposit insurer. The FDIC as an insurer is supposed to deal with bank failures in the least costly way that is consistent with its regulatory assignment to preserve the safety and soundness of the banking system. One method of fulfilling the dual role is to arrange a transaction in which a healthy bank purchases some of a failed bank’s assets and assumes its liabilities. Such purchase and assumption transactions (P&A’s) are sealed bid fist price auctions, usually conducted within a few days of the closure of the failed bank. Only banks that possess certain financial characteristics and operate within a specified geographical area around the failed bank are invited to submit bids. No bank may participate in the auction if, in the opinion of the FDIC, its acquisition of the assets would cause a substantial lessening of competition in the failed bank’s output market (12 USC 1823 Section 13).
Recent research on auctions suggests that the mechanism used for selling an asset can affect the revenues received by the seller.’ FDIC failed bank auctions <
*This research was supported in part by McGraw-Hill Incorporated which provided us access to the Data Resources Incorporated Securities Price File. The authors thank the participants of the finance workshops at the University of Oregon, the University of Michigan and the University of Utah.
‘See, for example, Vickery (1961), Milgrom and Weber (1982), Riley and Samuelson (1981). and Cammack (1985), for analysis leading to this conclusion.
142 C. James and P. Wier, FDIC failed bank auctions
provide a unique opportunity to investigate this suggestion empirically. In this paper, we present support for the proposition that the sales mechanism used by the FDIC does matter; specifically that it results in wealth transfers from the insurance fund to the winners of the auctions. Our empirical evidence comes from an examination of the stock returns of wirming bidders. On average we observe positive abnormal returns for winners when auction results are announced. They are significantly larger than abnormal returns for a sample of banks that acquire other banks in transactions unassisted by the FDIC over a two-day announcement period (but not over a five-day period).
Although this result is arguably consistent with the wealth transfer hypothe- sis, it could also arise from differences between the two samples in the nature of the assets sold or in the extent to which the announcements are anticipated. To analyze further whether the FDIC’s auctions result in rents for winning bidders, we examine the relation between changes in the market values of winning bidders and the numbers of bidders participating in the auctions. Auction theory predicts that absent restrictions on bidder participation, there will be a positive relation between a winner’s profits and the number of participating bidders. Restrictions on bidder participation can result in re- duced revenue for the seller, i.e., a wealth transfer to the buyer, as well as an inverse relation between the returns to winning bidders and the number of bidders. The inverse relation evident in our data supports the wealth transfer hypothesis.
A final test of the hypothesis involves examining the relation between the returns to acquirers and the numbers of potential bidders in FDIC and unassisted bank acquisitions. We tind that the presence of other potential buyers of an acquired bank has a significantly smaller effect on the returns to winners of FDIC auctions than on the returns to unassisted acquirers. This result suggests that FDIC procedures reduce competitive pressure on the price of the auctioned banks.’
2. Background on FDIC auctions
The FDIC has two methods to dispose of an insured commercial bank that has been declared insolvent3 In a deposit payoff, the FDIC pays off insured depositors up to the limit of insurance coverage. In a purchase and assumption
‘While FDIC procedures may not maximize revenues from a particular sale, they could offer offsetting benefits. For example, eligibility restrictions could prevent future (costly) bank failures, and the timing could avoid costs to the public of being without bank services for an extended period. We are unable to assess the overall benefits associated with a particular procedure.
‘The authority to close a bank rests with the Comptroller of the Currency in the case of national banks and the state bank supervisors in the case of state chartered institutions. Unless otherwise documented, information about FDIC procedures for handling bank failures is found in FDIC (1984).
C. James and P. Wier, FDIC/ailed bank auctions 143
transaction (P&A) the FDIC auctions a package of the failed banks assets and the obligation to assume the bank’s liabilities. The auctioned package usually contains the banks ‘clean’ assets: premise, cash, securities, performing con- sumer loans and the right to operate the bank. Since a failed bank’s liabilities exceed its assets the FDIC includes in the package to be auctioned enough cash to equate the value of the assets acquired with the value of the liability assumed. The FDIC usually retains the commercial loan portfolio and any non-performing consumer loans. The acquirer is determined by a first price sealed bid auction usually held within forty-eight hours of the closure of the failed bank. Bidders are therefore given only about twenty-four hours to evaluate the specifics of the acquisition and to submit a bid. There are no fees imposed by the FDIC on participants of the auction.
To determine which method to use in liquidating a failed bank the FDIC calculates the cost of a payout, including payments to insured depositors, payout expenses and the estimated shortfall in asset collections. The cost of a payout is used to determine the minimum bid necessary to justify a P&A transaction.
Only banks or bank holding companies that meet certain standards are invited to participate in an auction. They must comply with the FDIC’s capital policy and with state and federal laws governing bank acquisitions, be rated by regulators as low-risk banks, have total assets at least twice the total assets of the failed bank, and operate within the home county of the failed bank and adjoining counties4
While the FDIC will normally award the failed bank to the highest bidder, it is not required to do so. The FDIC Act [12 USA 1823 Section 13 (e)] directs the agency to weigh the benefits to the insurance fund of selecting a particular bidder against any potential anti-competitive effects or adverse effects on the soundness of the banking system. In addition, the Depository Institutions Act of 1982 permits the FDIC to solicit bids from out-of-state commercial banks and other depository institutions in cases involving ‘extraordinary acquisi- tions’. However, when the highest bidder is not an in-state commercial bank the FDIC must permit losers whose bids were within 15 percent of the highest bid to participate in a second round of bidding.’
3. Implications and tests of the wealth transfer hypothesis
There are two possible reasons why the FDIC’s selling procedures may not maximize the revenue it receives from the sale of a failed bank. First, a first
4The last two criteria can be adjusted in appropriate circumstances [FDIC (1982)]. s‘Extraordinary acquisitions’ involve failed banks with total assets of $500 million or more. In
our sample only one auction involved a second I’ound of bidding. The winner in that auction was not the highest bidder.
144 C. James and P. Wier, FDIC failed bank auctions
price sealed bid auction might result in a lower winning bid than could be obtained using a different selling technique, for example an English (i.e., oral ascending bid) auction. Whether the type of auction used affects the selling price depends on the characteristics of the object auctioned, bidders’ informa- tion about the object’s value and the degree of the participants’ risk aversion.6 Second, other features of FDIC auctions, namely the haste with which they are conducted and the restrictions placed on bidder eligibility, could affect the FDIC’s revenues negatively. French and McCormick (1984) and Johnson (1979) show that bidder restrictions have a negative impact on selling price in tist price sealed bid auctions. Their argument implies that if bidder restric- tions and the timing of FDIC auctions exclude some bidders that would otherwise participate, wealth transfers from the FDIC insurance fund to winning bidders can occur. These authors base their conclusions on the assumptions of a common value auction model, in which the value of the auctioned object is the same for all bidders but estimates of the value differ across bidders.7 Under the assumptions of an independent private value auction model (where each bidder knows the value of the object to himself but not to other bidders), restrictions on bidder eligibility may exclude the bidder that values the object most highly. This exclusion would reduce the seller’s revenues but would not necessarily generate profits for the winning bidder. In this case, lack of profits for winners does not necessarily imply that FDIC revenues are maximized.8
In our empirical analysis, we do not attempt to distinguish between these explanations for potential wealth transfers. Rather, we explore whether the sales mechanism used by the FDIC (i.e., the type and timing of the auctions and the rules governing eligibility to bid) cause wealth transfers.
The wealth transfer hypothesis implies that FDIC winners on average pay less for failed bank assets than they are worth. Positive abnormal returns to winners’ shares when auction results are announced (reflecting the difference between price and expected value) are therefore consistent with the hypothesis. Further, if the FDIC’s sales mechanism results in lower prices for failed banks than would obtain were the banks sold without FDIC assistance, we expect that FDIC winners’ abnormal returns will be greater on average than unas- sisted acquirers’ returns. We test these implications by comparing the abnormal
‘The effect of the auction mechanism on the seller’s expected revenue has been extensively analyzed. gee Englebrecht-Wiggan (1980) and Milgrom and Weber (1982) for summaries of this literature.
‘A simple example of a ‘common value’ asset is an envelope containing an unspecified amount oE cash. The cash has the same value to everyone, but estimates of the number of dollars in the envelope differ across bidders.
sHowever, we find positive returns for winning bidders and a negative relation between the winning bidders profits and the number of bidders. These results are consistent with the wealth transfer hypothesis described below.
C. Jomes and P. Wier, FDIC foiled bank auctions 145
stock returns around acquisition announcement dates of FDIC auction winners with abnormal returns of a control portfolio containing banks that acquire other banks without FDIC assistance.
Evidence that abnormal returns for FDIC winners are greater on average than for the control banks is consistent with the wealth transfer hypothesis and with differences between the two sets of acquisitions in the assets sold, the degree of investor anticipation or the costs of bid preparation. Therefore, we construct a second and more powerful test of the wealth transfer hypothesis. It involves examinin g the relation between the return to each winning bidder and the number of bidders participating in the auction. French and McCormick indicate that this relation is positive in first price sealed bid auctions with unrestricted entry and costly bid preparation. The intuition behind this result is as follows: All bidders have an incentive to set their bids below their estimates of the value of the auctioned object conditional on winning. They make these ‘finite bidders’ adjustments’ because the wirming bid must be only slightly above the next highest bid.g As the number of bidders increases, the probability that there will be a bid just below a participant’s value estimate also increases. Thus, the difference between each bidder’s value estimate and the bid that maximiz es the expected gain from bidding narrows as the number of participants rises. The finite bidders’ adjustment is not necessarily a source of rents for winners however. Rather, if participation in the auction is unrestricted, entry will occur to the point where the expected gain to the last bidder - his estimate of the profits he will earn if he wins times the probability of winning - equals his expected bid preparation cost. This unrestricted competitive equilibrium requires that the realized gain for the winner must on average equal the aggregate bid preparation costs of all participants.
If the cost to a bidder of preparing a bid is constant across auctions, unrestricted entry implies that realized gains, reflected by positive abnormal returns, will be greater in auctions with more bidders. This conclusion holds because as the number of bidders rises, the probability of winning the auction declines and the reward to the winner (the realized gain) must increase to offset the reduced chance of winning. But if entry restrictions imposed by the FDIC exclude some bidders that would otherwise participate, the unrestricted equilibrium will not be reached and the positive relation between numbers of bidders and winners’ gains need not hold. A winners’ gain will reflect both the bid preparation cost and a wealth transfer from the seller. We examine the correlation between <bidder numbers and acquirers’ abnormal returns for information about whether entry restrictions are binding.
‘Bidders’ estimates of the value of an auctioned object contain a negative adjustment to avoid the ‘winners’ curse’. Without such an adjustment the bidder making the most optimistic estimate of value will on average win the auction by paying more than the object turns out to be worth. This downward adjustment to the value estimate is separate from the finite bidders’ adjustment to the bid and does not generate expected profits for winning bidders.
146 C. James and P. Wier, FDIC failed bank auctions
Finally, we test the wealth transfer hypothesis by observing how the existence of potential bidders affects the winning bidders’ returns. James and Wier (1987) find that acquirers’ returns are related negatively to the number of potential bidders and positively to the number of alternative targets in acquisitions unassisted by the FDIC. If the set of banks that actually bid for a failed bank encompasses most of the potential competitors for the auctioned assets, then we should observe a similar negative relation between FDIC winners’ returns and numbers of potential bidders. Conversely, if the FDIC’s selling procedures serve to reduce competition for a failed bank, winning bidders? gains should bear little relation to our measure of potential competi- tion in FDIC auctions.
4. Description of the data
The P&A transactions analyzed in this study were obtained from the FDIC’s Annual Reports for the years 1973-1983. Of 138 P&A’s that took place during the period, we found 19 that involved winning bidders with actively traded common stock outstanding for 80 days before to 80 days after the FDIC auction.”
Our event date is the data on which the outcome of the auction appears in The WaN Street Journal. We choose it because the FDIC normally attempts to effect the merger before the business day following the failed bank’s closure, and to publicize the two events simultaneously.” The FDIC does not an- nounce the list of eligible bidders. We found no news of any auctions prior to our event dates.
For each FDIC auction, information on the number of bidders and the dollar amount of each bid submitted was obtained from the FDIC under a Freedom of Information Act (5 USC Section 552) request. Table 1 provides a summary of the number of bidders participating in the auctions and the relation between the highest bid received and other bids submitted. As indicated in panel A, the mean number of bidders is 3 with a range of 1 to 8 bidders. Panels B and C show that on average the second-highest bid sub- mitted is 64 percent of the winning bid, and the lowest bid only 34 percent of the winning bid. These figures suggest quite dramatic differences between winning and losing bids. However, the differences appear less startling in light of the evidence, presented in panel D, that all bids are very small relative to
“Our proxy for trading activity is inclusion in the COMPUSTAT banking and finance file, which contains data on the largest U.S. banks. Price data for firms trading over tie counter were taken from DRI’s Security Price File and for listed firms from the CRSP Daily Returns File.
l1 The normal procedure is for the bank to be declared insolvent on Friday or prior to a holiday. Bids are then solicited and the winner announced on the next business day [FDIC (1984)]. We assume that bidders learn of the auction on the closure date.
Table 1 Characteristics of bids in 19 FDIC failed bank auctions in which the winning bidder was an
actively traded bank; 1973-1983.
Panel A: Numbers oj bidders in auctions and frequency with which given numbers of bidders participated
Number of bidders Number of auctions with participating in auctions specified number of participants
8 1 5 3
4 3 ii 2 2 1 4
Mean number J Total i3 of bids per auctions auction
Panel B: Ratios of lowest to highest bilk and jrequency ojoccurrence
Lowest bid as a Number of auctions with bid proportion of highest bid ratios in specified interval
Panel C: Ratio of second-highest to highest bidr and jrequency of occurrence
Second-highest bid as a Number of auctions with bid proportion of highest bid ratios in specified interval
0.85-0.80 3 0.79-0.70 6
0.69-0.60 0.59-0.50 : 0.49-0.40 1 0.39-0.30 2
less than 0.30 1 Mean 0.64 Total 17 proportion auctions
Panel D: Ratio o/highest bid to deposit size and frequency o/occurrence
Highest bid as a Number of auctions with proportion of auctioned bid/deposit ratios in
bank deposits specified interval
0.14-0.12 0.12-0.10 ii 0.10-0.08 I 4 0.08-0.06 1 0.06-0.04 4 0.04-0.02 5
less than 0.02 3 Mean 0.055 Total 1G proportion auctions
‘Total equals 15 because 4 auctions had only one bidder.
148 C. James and P. Wier. FDIC failed bank auctions
the deposits of the auctioned bank. The largest high-bid-to-deposit ratio is only 13 percent and the mean of these ratios is 5.5 percent.‘*
A control sample, of unassisted bank acquisitions, was constructed as follows: first, we compiled a list of all bank acquisitions involving actively traded bidders during the period 1973-1983 for which an announcement appeared in The Wall Streef Journal. Next, we randomly selected 60 acquisi- tions from the list. Finally, we examined The Wall Street Journal Index to determine whether during a 3-month period prior to the announcement date of the acquisition, an acquiring bank was involved in another acquisition. If so, it was replaced in order to reduce the possibility of including frequent acquirers in the control sample. l3 Information concerning market values and deposits came from the Moody’s Banking and Finance Manual of the year immediately preceding the acquisition.14
Finally, we obtained information on the number of potential bidders and alternative targets from the FDIC’s Bank Operating Statistics. The FDIC divides banks in each state or bank market area into four deposit size classes: under $10 million, $10 to $24.9 million, $25 to $99 miIl.ion, and above $100 million. As in James and Wier (1987) we define potential bidders as banks larger than the acquired bank and geographically eligible to take it over. If the acquired or failed bank belongs to the largest size class, we used Rand McNally’s Banking Directory because it provides information on each bank’s size. As a proxy for alternative targets, we used banks in the same geographic region that belong to the same size class as the acquired or failed bank.
5. Methodology
We used standard event-study methodology to estimate abnormal stock returns [see Brown and Warner (1985) for a description]. We assigned event day 0 to acquisition announcement days. For each firm we estimated market model parameters from days - 80 through - 11 and from days + 11 through + 80. Two sets of parameters were estimated to account for a possible risk
‘*The number of bidders participating in these 19 auctions is similar to the 130 P&A transactions studied by Hirschhorn (1985) over the 1980 through 1984 period. The mean number of bidders in his sample is 2.75 and the mean ratio of premium paid to deposits assumed is 1.2 percent.
I3 We wished to maximize the likelihood of selecting banks for which the acquisition announce- ment represented significant new information that would affect the banks’ share prices. The banks in our control sample were also used in James and Wier (1987).
14The market value of the acquiring bank was calculated using shares outstanding on December 31 of the year preceding the acquisition. Share prices two days prior to announcement of the auction were obtained from The Wall Street Journal. For the acquiring banks, deposit volume and market value information is for the bank holding company when applicable. For the acquired bank in FDIC auctions, deposit data pertain to the bank acquired. For the control group, deposit data pertain to either the bank or bank holding company, whichever was acquired. The average target-to-bidder deposit ratio is 0.13 for the control sample and 0.14 for the FDIC sample.
C. James and P. Wier, FDICyailed bank auctions 149
shift due to an acquisition. Using these estimates we predicted returns for days -10 through +lO and subtracted observed returns from them to generate prediction errors. We summed these over days - 1 and 0 to create each firm’s event period abnormal return. Day -1 is in the event period because an acquisition reported in The Wall Street Journal could have been announced to the public during trading hours the previous day. Averaging abnormal returns across all firms in each sample produced the sample’s mean daily abnormal returns Md for each day d = - 10 through + 10. T-statistics provide tests of the significance of the event period means. They were calculated as follows:
where ME is the sum of M-i and Ma and I& estimates the variance of M,,. f, was measured over days - 10 through + 10, excluding days - 1 and 0.
6. Results
For winners of FDIC auctions the mean abnormal return is 0.66 percent on day - 1 (t = 2.40) and 1.70 percent on day 0 (t = 5.68), yielding a two-day mean abnormal return for the announcement period of 2.36 percent with a t-statistic of 5.57. This result does not appear to be due to large prediction errors for a few firms. Two-thirds of the firms had positive two-day prediction errors. When we exclude the two firms with the largest prediction errors, our two-day portfolio mean abnormal return is 1.5 percent (t = 3.90). No pattern is discernible in the post-announcement abnormal returns (from day +0 day +50).” For acquirers in the control group mean abnormal returns are 0.68 percent for day -1 and 0.39 percent for day 0. The two-day mean of 1.07 percent is statistically different from zero at the 0.01 level (t = 3.09).
The positive abnormal returns to winners of FDIC auctions do not neces- sarily indicate that FDIC auction procedures affect the agency’s revenues. As noted in section 3, they may simply reflect bid preparation costs if entry restrictions are not binding. However, the total dollar gains for bidders appear large relative to these costs. The mean gain for winners in our sample, measured by averaging the products of each &m’s two-day prediction error and the market value of its equity immediately preceding the acquisition, is about $6 million (and the median is about $2 million). If this $6 million is simply an unbiased estimate of the total bid preparation costs in one of our FDIC auctions, then the observation that on average 3 bidders participate in
“Our results differ from those reported by Pettway and Thrifts (1985). They find for 11 FDIC auctions during the 1973 to 1980 period a downward drift in the post announcement average residuals. One reason for the difference in findings may be the difference in sample composition. Another reason may be differences in methodology. Pettway and Thrifts calculate a geometric residual return and base their conclusions on mdvements in cumulative geometric residuals.
150 C. James and P. Wier, FDICfailed bank auctions
Table 2 Coefficients for cross-sectional regressions relating winners’ abnormal returns around FDIC
auction announcements to number of bidders and relative size (r-statistics in parentheses).
‘Dependent variable is winning bidders’ two-day prediction error. bSIZE = ratio of target deposits to winner deposits. ‘N = number of bidders participating in the auction. d ND = 1 for auctions with a losing bid within 20 percent of the winning bid, 0 otherwise.
each auction implies an average cost per bidder of $2 million. Since bid preparation costs are thought to be negligible in FDIC auctions we are not persuaded that the abnormal returns for winners in these auctions can be attributed solely to these costs. l6 On the other hand, unassisted acquirers also earn positive abnormal returns on average around acquisition announcements, and differences between results for these acquirers and FDIC winners are small. The two-day abnormal return for FDIC winners is signikantly greater than for the control sample (the difference is 1.29 percent, with a t-statistic of 3.47), but there is no significant difference between five-day abnormal returns. The longer observation period may be the more appropriate for estimating announcement effects for unassisted acquisitions because of possible pre-pub- lication information leakages. The difference between the five-day abnormal return for the control group and the two-day return for FDIC winners is 0.59 percent. Thus evidence on the wealth transfer hypothesis based on these two samples is ambiguous.
A more powerful test of the hypothesis relates returns for FDIC winners to numbers of bidders participating in the auctions. We estimate several versions of a linear regression model with winners’ prediction errors as the dependent variable. Independent variables include bidder numbers and a size variable, calculated as the ratio of acquired to acquiring banks’ deposits. We include this ratio because other research indicates that for corporate acquisitions in general relative size is positively related to bidder abnormal returns [Asquith (1983)]. The results of our regression analysis are reported in table 2. The coefficients associated with the ‘number of bidders’ variables (N, l/N and ND) are statistically significant and each;indicates a negative relation between
%ee FDIC (1984) for a statement of this opinibn.
C. James and P. Wier, FDIC failed bank auctions 151
number of bidders and value gain. Note that the positive coefficient on l/N is consistent with the others. Its use in eq. (1) produces the best fit of all the specifications, suggesting that the relation between the number of bidders and the value gain is non-linear. This suggestion has intuitive appeal; one expects that a second bidder will have a greater marginal impact on the outcome of an auction than an eighth bidder.17
While the negative relation between bidder returns and the number of bidders participating in the auction is consistent with the wealth transfer hypothesis, we have not demonstrated that the number of actual participants is less than the number of potential participants.‘s To investigate this last issue, we estimated the relation between the number of actual bidders and the number of potential bidders for each auction. If the FDIC eligibility restric- tions are binding the coefficient associated with the number of potential bidders should be significantly different from one. We obtain the following results (f-statistics are in parentheses):
BIDNUM = 2.41 + 0.013 PB, (5.14) (2.85)
R2 = 0.25,
where BIDNUM is the number of banks submitting bids and PB the number of potential bidders. The coefficient on PB is statistically different from 1 at the 0.01 level.lg
A final test of the wealth transfer hypothesis examines the relation between returns to bidders and potential competition on both sides of the market. If FDIC auction procedures actually exclude bidders that otherwise might com- pete to acquire the failed bank, the numbers of these potential bidders should have little or no effect on the returns to the winning bidders. Further, if the assets auctioned by the FDIC are unique in some respect, other banks of similar size are not viable substitutes for the failed bank. In this case the presence of such other banks should be unimportant in explaining returns to winning bidders in FDIC auctions.
We examine the effect of potential competition on bidder returns by estimating the following regression equation: 2o
PEj, = 0~~ + a2SIZEj + a3PBj + a4ATj + tzj,
“We also calculated weighted least squares estimates of the coefficient described in table 2. Weights are reciprocals of standard errors of prediction errors. Results are similar to those reported in table 2.
‘sRestrictions in the general market for bank acquisitions may account for the observed negative relation between bidder returns and the number of bidders.
“The mean and median numbers of potential bidders are 57 and 33, while the mean and median numbers of actual bidders are 3 and 3.
“Tire model is identical to the one we used in James and Wier (1987) and the control group results shown here are the same as those in table 2 of that paper.
152 C. James and P. Wier, FDIC failed bank auchms
Table 3 Coefficients for cross-sectional regressions relating acquirers’ abnormal returns to numbers of potential bidders and alternative targets for FDIC acquisitions and unassisted bank acquisitions
‘SIZE = ratio of target deposits to bidder deposits. bPB = log of the number of potential bidders. ‘AT= log of the number of alternative targets. dDPB = dummy X PB (dummy = 1 if acquisition is in control sample, 0 otherwise). ‘DA T= dummy X AT (dummy = 1 if acquisition is in control sample, 0 otherwise).
where PB and AT measure potential bidders and alternative targets. Regres- sion results are presented in table 3.21
The results in table 3 are consistent with the wealth transfer hypothesis. No statistically significant relation is found between acquirers’ returns and the numbers of potential bidders or alternative targets in the FDIC sample. We do find, however, a negative relation between the returns to acquirers and the number of potential bidders in unassisted bank acquisitions. Moreover, in the pooled sample, we find that the number of potential bidders has significantly greater influence on the acquirers’ returns in unassisted acquisitions than in FDIC auctions. We do not find a significant difference in the influence of alternative targets for the two types of acquisitions.
7. Conclusion
When the FDIC decides to dispose of a failed bank’s assets through a purchase and assumption transaction, it invites a limited number of banks to participate in a sealed bid auction held within days of the declaration that the bank is insolvent. Thus sales of failed bank assets differ in several respects from ordinary bank acquisitions. They offer an opportunity to study whether the mechanism used to sell an asset affects its price. In this paper we present
21No significant difference appears between the influence of size on the FDIC and on the control sample results. I
C. James and P. Wier, FDIC failed bank auctions 153
evidence supporting the hypothesis that the FDIC’s procedures result in wealth transfers to winning bidders. First, we find a significant negative relation between gains to winning bidders and numbers of bidders participat- ing in an auction. This result suggests that participation in the auction is subject to binding restrictions that have a negative impact on the FDIC’s revenues. Second, it appears that FDIC procedures limit competition to acquire the failed banks’ assets since the influence of potential bidders on returns to acquirers is much smaller in FDIC auctions than in unassisted acquisitions.
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