Abstract
We investigate how borrower consent clause (BCC) is used in private debt contracts as a contract design mechanism to protect borrower interests. We find that the probability of including a BCC in debt contracts increases in the intensity of creditor control rights measured by number of financial covenants. Furthermore, we document that performance covenants result in higher likelihood of BCC inclusion than capital covenants do. For robustness checks, we use alternative proxies for creditor control rights, and employ simultaneous equation and propensity score matching to address endogeneity. The baseline results still hold. Exploiting Anti-Recharacterization Law (ARL) as a quasi-natural experiment for strengthened creditor rights, we find that adoption of ARL increases the likelihood of BCC inclusion. Using credit default swap (CDS) trading as a setting of weakened creditor control rights, we document the inception of CDS trading is associated with lower likelihood of including BCC. Furthermore, we find that the association between creditor control rights and BCC is more pronounced for borrowing firms with good quality and more conservative financial reporting.
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Notes
There are other types of assignment clauses in loan contracts in addition to BCC, including lead lender consent, buyer eligibility, minimum holding, minimum assignment, and Institutional Investor OK clause, which we discuss in detail in Sect. 3.2. We focus on BCC in this study.
Borrowers often renegotiate their credits to adjust the terms of their loans or to manage the maturity they have left in their credits ((Roberts and Sufi 2009b; Mian and Santos 2018). Consistent with the view that transferring control rights through loan assignments is a source of concern for borrowers, Bord and Santos (2012) state that such transfers may “hinder the ability of corporate borrowers to renegotiate their loans after they have been issued. This difficulty may arise not only because the borrower will have to renegotiate with more investors but also because the universe of investors acquiring corporate loans is more heterogeneous.”.
Ferreira et al. (2018) finds that even the combination of a borrowing firm’s board of directors might change in reaction to a covenant violation. They find that the number of independent directors increases by about 24% following a violation. Most of the new directors have links to creditors.
The results are qualitatively similar using facility-level analysis or using weighted average of facility-level variable. The analysis of probability of loan trading is conducted at the facility level.
The covenant violation data is available at http://finance.wharton.upenn.edu/~mrrobert/styled-9/styled-11/index.html.
We also report the results based on probit model as a robustness test.
We obtain the measure from Professor Peter Demerjian’s website: http://faculty.washington.edu/pdemerj/data.html.
Performance covenants include cash interest coverage ratio, debt service coverage ratio, level of earnings before interest, taxes, depreciation, and amortization (EBITDA), fixed charge coverage ratio, interest coverage ratio, ratio of debt to EBITDA, and ratio of senior debt to EBITDA covenants). Capital covenants include quick ratio, current ratio, debt-to-equity ratio, loan-to-value ratio, ratio of debt to tangible net worth, leverage ratio, senior leverage ratio, and net worth requirement.
Because the analysis in Table 4 intends to compare whether performance vs. capital covenants is associated with higher likelihood of including BCC in debt contracts, we only include loans with financial covenants in the analysis. As a sensitivity test to evaluate whether performance or capital covenants is associated with higher likelihood of BCC inclusion than debt contracts without any financial covenants, we also include loans without any financial covenants in the analysis. The untabuluated results show that in the full sample analysis, while the intensity of both performance and capital covenants are associated with higher likelihood of BCC inclusion, the magnitude of the impact of the performance covenants is larger than that of the capital covenants, consistent with our results in Table 4 using the sample of observations with at least one financial covenant. The results are available upon request.
We include the number of financial covenants to control for the effect of financial covenants that is not accounted for by the inception of CDS trading. We interpret the coefficient on Post_CDS as capturing borrowers’ reactions to reduced demand for creditor control rights due to CDS trading.
We use the dichotomous variable Hcov instead of the continuous variable FinCov to estimate the probit model in Eq. (4).
Although the creditor rights arisen from ARL and the intensity of financial covenants are different, they both represent the rights enjoyed by creditors with the former representing rights in liquidation process and the latter allowing creditors to take over control during technical default.
Mississippi is a neighbor state of both Louisiana and Alabama, but Louisiana and Alabama have different ARL implementation year. Therefore, Mississippi is excluded.
As in Sect. 4.1.1, firm-specific characteristics include firm size, market-to-book, tangibility, profitability, leverage, and financial constraint indicator; loan-specific characteristics include loan-to-asset, maturity, revolver loan indicator, leveraged loan indicator, and collateral indicator. We thank the referee for suggesting the additional robustness test.
Because the intensity of financial covenants used in debt contracts could be different due to observable firm and loan characteristics during the sample period, the matched sample is a more appropriate for this analysis. We thank the referee for suggesting this additional test.
WW index is from Whited and Wu (2006), which is defined as—0.091 × Cash flow + 0.062 × Dividend dummy + 0.021 × Long-term debt—0.044 × Size + 0.10VI2 × Industry sales growth—0.035 × Sales growth.
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Acknowledgements
We thank Anthony Saunders and Mehdi Beyhaghi for their helpful comments. We also thank Yang Wang (the discussant) and participants at 2021 Financial Management Association Virtual European conference, Adam Usman (the discussant) and participants at 2019 Financial Management Association Annual Meeting, the City University of Hong Kong, and 2019 American Accounting Association Annual Meetings for their comments and suggestions. Yutao Li thanks the Social Sciences and Humanities Research Council of Canada (SSHRC, grant number 430-2017-00708) and CPA Alberta for their financial support. All errors are solely ours.
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Appendix 1: Variable definitions
Appendix 1: Variable definitions
Variables | Definitions |
|---|---|
BCC | An indicator variable that equals one if a loan deal contains a borrower consent clause and zero otherwise |
Min Assi | An indicator variable that equals one if a loan deal contains a minimum assignment clause and zero otherwise |
Lead lender consent | An indicator variable that equals one if a loan deal contains a lead lender consent clause and zero otherwise |
Restriction on buyer type | An indicator variable that equals one if a loan deal contains a restriction on buyer type clause and zero otherwise |
Institutional Investor OK | An indicator variable that equals one if a loan deal contains an institutional investor OK clause and zero otherwise |
Min Holding | An indicator variable that equals one if a loan deal contains a minimum holding clause and zero otherwise |
FinCov | The total number of fin covenants contained in a loan deal |
Increase_Chargeoff | The number of lead lenders with an increase in the net chargeoff in the quarter prior to loan syndication |
Predicted_FinCov | The number of predicted financial covenants obtained from the first-stage regression model (Eq. (2)) in the instrumental variable estimation. The instrument is Increase_Chargeoff |
SIC2_BCC | The percentage of loans with BCCs syndicated in the borrowing firm’s SIC 2-digit industry and in the year prior to the firm’s loan year |
Predicted_BCC | The predicted probability of including BCC in debt contracts from the first stage regression model (Eq. (2) in the instrumental variable estimation. The instrument is the percentage of loans with BCC syndicated in a firm's SIC two-digit industry and the year prior to the firm's loan year (SIC2_BCC) |
PerfCov | The number of performance covenants in a loan deal based on Christensen and Nikolaev’s (2012) classification, including (1) Cash interest coverage ratio, (2) Debt service coverage ratio, (3) Level of EBITDA, (4) Fixed charge coverage ratio, (5) Interest coverage ratio, (6) Ratio of debt to EBITDA, and (7) Ratio of senior debt to EBITDA |
CapCov | The number of capital covenants in a loan deal based on Christensen and Nikolaev’s (2012) classification: (1) Quick ratio, (2) Current ratio, (3) Debt-to-equity ratio, (4) Loan-to-value ratio, (5) Ratio of debt to tangible net worth, (6) Leverage ratio, (7) Senior leverage ratio, and (8) Net worth requirement |
FinCov_Tightness | The aggregated measure of covenant tightness based on all financial covenants (Demerjian and Owens 2016) |
PerfCov_Tightness | The aggregated measure of covenant tightness based on all performance covenants (Demerjian and Owens 2016) |
CapCov_Tightness | The aggregated measure of covenant tightness based on capital covenants (Demerjian and Owens 2016) |
Post_CDS | An indicator variable that equals one if a loan deal is initiated after the inception of CDS trading and zero otherwise |
Log(Assets) | Natural logarithm of total assets |
Mkbk | Market-to-book ratio |
Tang | Tangible assets (ppent/at) |
Roa | Return on assets (ni/at) |
Inv Grade | An indicator variable that equals one if a borrower has an S&P long-term debt rating of BBB or above, and zero otherwise |
Non-Inv Grade | An indicator variable that equals one if a borrower has an S&P long-term debt rating of below BBB or does not have a credit rating, and zero otherwise |
Levg | Leverage (dltt/at) |
Fc | An indicator variable for financial constraint that equals one if a firm’s Whited and Wu (2006) financial constraint index is greater than the sample median, and zero otherwise. Whited and Wu (2006) index = − 0.091 * cash – 0.062 * dvt + 0.021 * dltt/at – 0.044 * log(at) + 0.102 * industry_sale_growth – 0.035 * sale_growth |
Not_Rated | An indicator variable that equals one if a firm has S&P long-term credit rating and zero otherwise |
Secured | An indicator variable that equals one if a loan deal contains collateral requirement and zero otherwise |
Deal/Assets | deal mount/total assets |
Log(Maturity) | Natural logarithm of loan maturity. The longest maturity of all tranches in a loan deal is used for the loan deal |
Leveraged loans | An indicator variable that equals one if a firm’s credit rating is below BBB or a firm does not have a credit rating, and zero otherwise |
Revolver | An indicator variable that equals one if a deal contains at least one revolver loan and zero otherwise |
ARL | An indicator variable that equals 1 if a loan deal is syndicated in 1995–1996 or 1998–1999 for a borrower headquartered in Texas or Louisiana or syndicated in 1999–2000 or 2002–2003 for a borrower headquartered in Alabama; and 0 if a loan is syndicated for a borrower headquartered in one of the non-adopting neighboring states |
Post | An indicator variable that equals 1 if a loan is borrowed by a firm in Texas, Louisiana or their neighboring states (Alabama or its neighboring states) in 1998–1999 (2002–2003) and 0 otherwise |
AT1 and Hat1 | A measure of accounting conservatism based on the Basu (1997) model in which accounting earnings (epsx/pricet−1) is regressed on stock returns (Rit), an indicator variable for negative Rit (D), and an interaction term D × Rit. The coefficient on D × Rit represents the relative speed of economic losses are recognized into earnings (AT1). The higher the coefficient on D × Rit, the more timely the losses are recognized into earnings. The firm-year accounting conservatism measure is obtained by estimating the regression for each two-digit NAICS industry over a five-year period prior to the loan syndication year. Each industry with the number of firm-years less than 200 and the number of firms less than 20 is removed from the estimation to avoid small sample bias. Hat1 is an indicator variable that equals 1 if AT1 is greater than the sample median, and 0 otherwise |
AT2 and Hat2 | A measure of accounting conservatism based on the Ball and Shivakumar (1997) model in which accounting total accruals ((ib-oancf)/att−1) is regressed on cash flow (CFO: oancf/att−1), an indicator variable for negative cash flow (DCFO), and an interaction term DCFO × CFO. The coefficient on DCFO × CFO represents the relative speed of economic losses are recognized into accruals (AT2). The higher the coefficient on DCFO × CFO, the more timely the losses are recognized into accruals. The firm-year accounting conservatism measure is obtained by estimating the regression for each two-digit NAICS industry over a five-year period prior to the loan syndication year. Each industry with the number of firm-years less than 200 and the number of firms less than 20 is removed from the estimation to avoid small sample bias. Hat2 is an indicator variable that equals 1 if AT2 is greater than the sample median, and 0 otherwise |
AT3 and Hat3 | A measure of accounting conservatism based on the Ball and Shivakumar (1997) model in which accounting change in net income (∆Eit) is regressed on change in net income in year t−1(∆Et−1), an indicator variable for the negative change in net income in year t−1 (D∆Et−1), and an interaction term D∆Et−1 × ∆Et−1. A more negative coefficient on D∆Et−1 × ∆Et−1 implies more timely recognition of the losses that are transitory and reverse sooner (AT3). The firm-year accounting conservatism is estimated same as the AT1 for each 2-digit NAICS industry. Hat3 is an indicator variable that equals 1 if AT3 is negative, and 0 otherwise |
High_Mkbk | An indicator variable that equals 1 if firms' market to book ratio is greater than the sample median and 0 otherwise |
Rated | An indicator variable that equals 1 if a firm has long-term S&P debt rating and 0 otherwise |
Large | An indicator variable that equals 1 if firms' assets is greater than the sample median and 0 otherwise |
Unconstrained | An indicator variable that equals 1 if a firm's WW financial constraint index smaller than the sample median and 0 otherwise |
Institutional | An indicator variable set to one if the loan is designed to be sold to institutional investors, and zero otherwise |
CAR | Cumulative abnormal returns adjusted for value weighted market returns around loan announcement or loan initiation |
Log(Maturity) | The natural logarithm of the number of days between the quarter end date to the loan maturity date |
Mkbkq | Market-to-book ratio at quarter end |
Roaq | Quarterly Return on Assets |
Log(assetsq) | log(at) at quarter end |
Traded | An indicator variable that equals one if a loan is traded in a quarter and zero otherwise |
Log(loan age) | Natural logarithm of the days between loan initiation and the quarter end date |
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Deng, S., Li, Y. Creditor control rights and borrower protection: the role of borrower consent clause in private debt contracts. Rev Quant Finan Acc 61, 357–394 (2023). https://doi.org/10.1007/s11156-023-01151-6
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DOI: https://doi.org/10.1007/s11156-023-01151-6