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Review of Quantitative Finance and Accounting

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05.05.2021 | Original Research

The effect of TARP on lending: Evidence from the lead bank’s share in syndicated loans

verfasst von: Bolortuya Enkhtaivan, Wenling Lu

Erschienen in: Review of Quantitative Finance and Accounting | Ausgabe 4/2021

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Abstract

We investigate the effect of the Troubled Asset Relief Program (TARP) on the shares of lead banks in syndicated loans by using quarterly data for the period from 2008 to 2011. We find that TARP capital injections to lead banks have a significantly positive effect on their shares of syndicated loans. Specifically, we estimate that the effect of TARP on the lending of lead banks increases their shares by 6.1% that is equivalent to an additional $50.37 million for an average syndicated loan of $840 million. The significantly positive effect is stronger for a lead bank that is larger, has a greater appetite for risk, and is not under supervisory stress. Overall, our results show that TARP was an effective mechanism for promoting the lending of lead banks. The larger fractional share of lead banks in syndicated loan packages signals both the loan quality and their commitment to mitigating the adverse selection and moral hazard problems. This study sheds new light on the mixed evidence of TARP on lending and contributes to the research and policy debates on the role of stringent supervisory scrutiny in lending.

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Participants include banks and institutional investors including sponsors of structured products (Ivashina and Scharfstein 2010). Our sample shows an average loan amount of $840 million and an average 13 lenders take a portion of a syndicated loan. Among the 13 lenders, four are banks that are relatively large with average total assets of $578 billion.

In addition to the typical agency problems in a lending relationship that exist between the borrower and the lender, moral hazard takes place in the syndicated loan market between the lead arranger and the other syndicate members within the syndicate. See Dennis and Mullineaux (2000) for more details about the scope of agency problems associated with syndication.

Note Ivashina (2009) points out that the lead bank is uniquely exposed to idiosyncratic risk, and thus its portfolio is not perfectly diversified.

Adverse selection and moral hazard occur if the lead arranger chooses to syndicate the most risky loan and loosely monitors the borrower after the loan is originated because of their limited stake, respectively.

Similarly, Holmstrom (1982) highlights that either monitoring or rewards that are consistent with responsibilities can promote team collaborations.

FDIC law 32.3 (lending limits) indicates that the maximum size of a loan to a single borrower is 15% of the bank’s capital and surplus. Specifically, “Loan Concentration Limit” mandates that banks limit their exposure from each deal. The loan syndication facilitates portfolio diversification and limits the individual lender’s exposure to the overall credit risk that regulators would always recommend.

Cornett et al. (2013) argue that the bailout funding worked as a relatively cheap resource for its recipient banks and find that many relatively weak banks used TARP funding to make low quality loans.

They employ within-loan estimations to assess the impact of bank capital on lending in the syndicated loan market and find that the capital levels of banks significantly increase the bank allocation shares to the same syndicated loan. To mitigate the endogeneity concerns, the authors use TARP as a quasi-natural experiment and present evidence on the causal effect of bank capital on lending.

The DID analysis assumes a uniform date for the post-TARP dummy, while the actual TARP enrollment dates vary across TARP recipients. We follow the same approach as in Black and Hazelwood (2013) to identify our TARP variables that allows heterogeneity in TARP enrollment dates.

Ross (2010) finds favorable market reactions to the announcement of a dominant bank’s involvement in the syndicated loan. Similarly, Gopalan et al. (2011) study the behaviors of lending partners in the case of borrowers’ bankruptcies. Further, the complex nature of loan syndication requires lenders to be experts in the borrower’s industry (Francois and Missonier-Piera 2007).

The literature uses either the BHC level (Berger and Roman 2015) or commercial bank level (Li 2013) as the unit of measurement. The use of financial information at the consolidated level is consistent with the practice of bank supervision where the bank’s risk exposure is aggregated at the BHC level.

Using TARP funding as a natural experiment to address endogeneity of bank capital, Chu et al. (2019) also perform baseline within-loan analysis to examine the TARP effect on overall bank shares and the shares of participant banks. When examining overall bank shares, their within-loan estimations exclude single-lender loans in the sample that 50% of lead bank observations is missing. When examining participant bank shares, their subsampling designs are not superior than ours. A split sample analysis allows for all the covariates to differ and the coefficients to vary, unlike our analysis using an interaction term to allow only the interacted variable to have different coefficients for the groups by lender type.

Our sample includes 1,424 unique borrowers and 131 unique bank lenders. The clustering choice at the bank level or borrower level accounts for the correlation between multiple loans made by the same bank or borrowed by the same borrowers, respectively. Our results remain the same if we cluster the standard errors at the bank level.

We also use various TARP infusion rates by replacing the denominator with either Tier 1 regulatory capital, total regulatory capital, or total equity, all of which show consistent results.

To provide a perspective of economic magnitude, for an average bank with average total assets of $578 billion in our sample, the TARP injection equals about $1.69 billion ($578.06*0.732 (RWA share) *0.4% (TARP infusion rate)).

They argue all three channels: shocks to borrowers, shocks to bank capital, and variation in investor sentiment will require lead banks to hold larger shares of the loans originated in response to an economic downturn, thus amplifying credit cycles.

Their opposite results are based on within-loan estimations without borrower and loan characteristics, using a smaller and only including participant bank sample. Compared to their sample size of 1,533 observations; 322 for lead banks and 1,201 for participant banks, we use a relatively larger sample of 5,325 observations: 639 and 4,686 for lead banks and participant banks, respectively. Also, our finding of reduced shares of participant banks is in line with our hypothesis because of their fewer responsibilities and no incentive to monitor their borrowers than their peer lead banks in a syndicate. Our unreported analysis also shows a greater number of participant lenders when a TARP recipient participates in the syndicate. These findings imply increased risk-sharing among syndicated members when participant banks received TARP.

In banking, an NPL is a loan after being in default in 90 days. In general, a bank with low level of impaired loans indicates its higher ability to increase lending, or greater risk appetite. Although one may argue that high level of NPLs could in principle to follow a logic of gamble for resurrection, thus inducing banks to lend more, there is scant empirical study in this regard (Accornero et al. 2017).

Starting in May 2009, the banks with total assets greater than $100 billion are assessed in greater detail for their capital needs from a forward-looking perspective under the SCAP. According to Bayazitova and Shivdasani (2012), banks under SCAP face more rigorous regulatory surveillance to certify their well-being to the investing public in order to raise the necessary funding.

Using an alternative measure of size, the sample median of a bank’s total deposits, we find the same results at significance level of 1%.

See Acharya et al. (2018) for a detailed discussion of the potential impacts of stress tests on lending. Consistent with our findings, they find that lead banks subject to stress tests significantly decrease lending, particularly to riskier borrowers, to reduce their credit risk.

To save space, we report only the TARP recipient dummy results, as the TARP infusion rate results are qualitatively similar.

First, Fed director is a dummy variable equal to one if one of the bank's directors was on the board of directors of one of the 12 Federal Reserve Banks or a branch of the FRB in 2008 or 2009. Second, Subcomm_on FI is a dummy variable equal to one if the bank is headquartered in a district of a US House member who served on the Subcommittee on Financial Institutions and Consumer Credit in 2008 or 2009. Third, Democracy is a dummy variable equal to one if the bank's local representative was a democrat in the 2007–2008 election cycle. Last, Local FIRE Donation is the percentage of campaign contributions from local fire industries in total contributions received by a representative in the 2007–2008 election cycle.

Valid instruments should be correlated to the TARP recipient dummy but uncorrelated to the bank share and omitted variables. The research on TARP finds that these political and regulatory connections as instruments used in our model can affect the bank’s probability of receiving TARP funds (Blau et al. 2013). Because Duchin and Sosyura (2014) argue that macro-political representations follow election cycles with high turnovers, it is reasonable to conjecture that these instrument variables are not directly related to an individual bank’s share in the syndicated loan.

The instrument variables are significantly related to the TARP recipient dummy variable. The Chi-square tests indicate the hypothesis that coefficients on the four political and regulatory variables are jointly zero is rejected at the 1% level of significance that confirms the strength of the instrument.

The selection bias includes unobservable and nonrandom TARP applicants (i.e., banks choosing whether to apply and the Treasury choosing whether to invest).

The results for the analyses can be made available by request.

There are eight involuntary participants: Citi group, JP Morgan, Wells Fargo, Morgan Stanley, Goldman Sachs, Bank of New York, Bank of America, and State Street Bank. As an immediate action to stabilize the financial system, TARP mandated that these banks receive funding without their initiatives.

We consider that systemically important banks have a higher chance for bailouts because of the too-big-to-fail factor. We consider that relatively healthy and undercapitalized banks are the banks that were targeted by TARP. To balance the sample, for example, we drop treated TARP recipients with total assets larger than the maximum value of the control group, and control group observations with total assets below the minimum value of the treated group. Similarly, we repeat the same trimming method for the bank’s total deposits and ROA. We change the Tier 1 capital thresholds to the maximum value of the treated TARP group, and the minimum value of the control group to consider of TARP targeting undercapitalized banks.

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Titel: The effect of TARP on lending: Evidence from the lead bank’s share in syndicated loans
verfasst von: Bolortuya Enkhtaivan
Wenling Lu
Publikationsdatum: 05.05.2021
Verlag: Springer US
Erschienen in: Review of Quantitative Finance and Accounting / Ausgabe 4/2021
Print ISSN: 0924-865X
Elektronische ISSN: 1573-7179
DOI: https://doi.org/10.1007/s11156-021-00974-5

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