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Bank Information and Firm Growth: Microeconomic Evidence from the US Credit Market

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Abstract

We examine the effect of bank information on the growth of borrowing firms by using matched bank-firm data from the US credit market. Exploiting the structure of lending syndicates to construct proxies for banks’ information acquisition, we find consistent evidence that bank monitoring spurs firms’ investments in tangible and intangible assets, promoting higher growth. Conversely, little evidence exists of banks exploiting informational monopolies that could deter firm investments, even when banks hold significant credit market power. Banks’ information does not appear to bias firm growth toward capital-intensive investments, but does also foster employment growth.

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Notes

  1. Due to data availability, when using this expanded sample, we focus on the effects of bank information acquisition on firm short-term growth.

  2. There are 335 lead arrangers in the baseline sample.

  3. Section 5.1 will provide a detailed discussion.

  4. Moreover, hold-up issues can especially inhibit innovation opportunities, and hence growth, when bank information on existing technologies is not transferable to new ones (Minetti 2011).

  5. However, a strand of empirical studies has found a beneficial effect of relationship banks on firm access to credit during financial crises. For a sample of Italian firms during the last financial crisis, Sette and Gobbi (2015) find that relationship lenders granted more loans than other banks, and at a lower cost. Bolton et al. (2016) show that firms operating with relationship banks were less likely to default on their loans during the crisis. Beck et al. (2018) find that relationship lending mitigates credit constraints during a cyclical downturn, especially for small and informationally opaque firms.

  6. The exact number of observations on which we perform our estimations depends on the data availability for the single variables used in the analysis.

  7. The borrowing firm pays an up-front arrangement fee to the lead arranger for its role in coordinating the loan syndication.

  8. Clearly, if the monitoring effort were verifiable for third parties, this issue would not arise. However, monitoring is hardly verifiable in courts.

  9. In the empirical analysis, to tease out the contribution of bank consultancy services, we interact these loan-level and bank-level indicators for the relevance of consultancy services with our proxy for bank monitoring.

  10. We isolate changes in the credit supply by including bank-year fixed effects.

  11. Garmaise and Moskowitz (2006) and Favara and Giannetti (2017) use the $1billion threshold to identify mergers unrelated to local geographic conditions. This exogeneity argument is plausible when applied to the syndicated loan market (see, e.g., Agarwal and Hauswald 2019).

  12. The F-test values are well above the threshold values for weak instruments indicated by Stock (2002). Observe that in the first stage the negative coefficient on the merger indicator could suggest that banks that expand their loan portfolio information through a merger may need to retain a lower loan share to perform monitoring.

  13. For related studies on the effect of lending relationships on firm performance, see also, e.g., Sufi (2007) and Delis et al. (2022).

  14. In the case of other firm growth indicators the coefficients are estimated more imprecisely, although the signs are in line with those obtained for assets and employment.

  15. The degree of product complexity of the firm could also reinforce hold-up issues. Firms with complex products could find more difficult to establish relationships with other banks. Therefore, these firms could be more exposed to be extracted rents from their main banks.

  16. To measure the complexity of the products of a sector, Rauch (1999) computes the share of products that are heterogeneous, that is, neither reference priced nor sold on an organized exchange.

  17. In Panel B of Table 8, we also experiment with interacting our main proxy for hold-up issues with the proxy for credit market power. The estimated coefficients for the interaction term are generally not statistically significant at conventional levels.

  18. In further untabulated tests, we also find that our main results hold in both recessionary and non-recessionary periods (where recessionary periods are captured by NBER recessions).

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Authors and Affiliations

  1. KU Leuven, Leuven, Belgium

    Hans Degryse

  2. University of Essex, Essex, England

    Sotirios Kokas

  3. Michigan State University, East Lansing, MI, 48824, Michigan, USA

    Raoul Minetti

  4. Sapienza University of Rome, Rome, Italy

    Valentina Peruzzi

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  1. Hans Degryse
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  2. Sotirios Kokas
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  3. Raoul Minetti
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  4. Valentina Peruzzi
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Correspondence to Raoul Minetti.

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We thank the editors, two anonymous referees and a discussant for their comments. We also thank conference participants at the 2022 ICMAIF conference (Crete) as well as several seminar and conference participants for helpful comments and conversations. All remaining errors are ours.

Appendix

Appendix

Table 10 Bank monitoring and firm growth: Product complexity
Full size table
Table 11 Bank monitoring and firm growth: Collateral
Full size table
Table 12 Further robustness tests. The table reports coefficients and t-statistics (in parentheses)
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Degryse, H., Kokas, S., Minetti, R. et al. Bank Information and Firm Growth: Microeconomic Evidence from the US Credit Market. J Financ Serv Res (2023). https://doi.org/10.1007/s10693-023-00410-w

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