Local public corruption and corporate debt concentration: evidence from US firms

Abstract

Using debt structure data from a large sample of US non-financial companies during the period 2002–2016 combined with the US Department of Justice (DOJ) data on local public corruption, we examine the effect of public corruption on the degree of debt concentration in a firm’s debt structure. The results imply that firms in corrupt areas tend to use several debt types simultaneously, decreasing in that way debt concentration. These findings remain robust to tests that control for endogeneity. In further analysis, we show that these results are stronger for more informationally transparent firms, i.e. investment grade rated and publicly listed firms, that have easier access to capital debt markets. Lastly, in terms of debt choices, we find that firms in corrupt areas issue more commercial paper, senior bonds and capital leases, while they borrow less from banks. The study provides useful policy implications for combating corruption, as informationally opaque firms face increased barriers to debt financing.

KEYWORDS:

• Public corruption
• debt concentration
• information asymmetry
• financing policy

JEL Codes:

• G30
• G32
• G38
• D73

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Firms are more likely to react to changes in the environment where they operate (i.e. corruption), by adapting their balance sheet and debt policies rather than moving headquarters, which is costly and not very common.

2 The database provides comprehensive information only from 2002 and onwards, and thus in line with previous studies (Colla, Ippolito, and Li 2013), we start our analysis from this year to enhance the validity of our estimations.

3 Revolving credit facilities are also known as drawn credit lines. In line with previous studies, operating leases are not included due to not being categorized as debt on the balance sheet. Other debt consists of any other unclassified short-term borrowings.

4 We source the relevant data to transfer ZIP codes to county Federal Information Processing Standard (FIPS) codes from the Missouri Data Center: http://mcdc.missouri.edu/applications/geocorr2000.html.

5 https://www.usmarshals.gov/district/county.htm

6 Compustat only reports the most recent headquarter location. The Augmented 10-X Header data, which captures all the information in the header section in the 10-K for each fiscal year, is available here: https://sraf.nd.edu/data/augmented-10-x-header-data/

7 In line with several previous studies (Smith 2016; Hossain, Kryzanowski, and Ma 2020; Huang and Yuan 2021; Hassan, Karim, and Kozlowski 2022) that have analysed the effect of public corruption on firm-level characteristics, we include industry and year fixed effects in our baseline model. The use of industry fixed effects – as opposed to firm fixed effects – is critical to our study. Corruption exhibits high variation between firms located in different states and little variation across firms located within the same state. Additionally, firms do not change headquarters during the period of the study. Hence, since corruption is quite persistent and firms do not alter their location, within-firm estimation – i.e. firm fixed effects – would increase the potential bias on the estimation of the coefficients of the explanatory variables in our regression model (Gormley and Matsa 2014), thereby making it difficult to draw valid conclusions from our results. To this end, we opt for industry and year fixed effects in our baseline estimations.

8 In this study, we do not have lender-level data to empirically control for supply-side considerations regarding the effect of corruption on debt concentration. However, the use of year fixed effects along with macroeconomic factors in our estimations capture, to a certain extent, the business cycle and therefore the supply of private and public funding at the US level.

Additional information

Notes on contributors

Theodora Bermpei

Theodora Bermpei is an associate professor in finance at IESEG School of Management in France. He joined IESEG in September 2023. Theodora's previous academic appointments were at the University of Essex (senior lecturer in finance) and the University of Nottingham Trent (lecturer in finance). She has also served as the equality and diversity lead of Essex Business School. Theodora has published in several journals such as Journal of Business Ethics, Journal of Financial Stability, Journal of International Money and Finance, and others. Theodora obtained her Ph.D. in banking from the University of Sussex.

José M. Liñares-Zegarra

José M. Liñares-Zegarra is a senior lecturer (associate professor) in finance at Essex Business School (UK) and an affiliated researcher at the Centre for Responsible Banking & Finance (CRBF). He also holds an honorary position at the University of St Andrews, Scotland. With more than 15 years of experience in teaching and research, José's specializations include banking, corporate finance, financial technology (FinTech), and entrepreneurship. His research has been published in international journals such as the British Journal of Management, Journal of Corporate Finance, European Journal of Finance, and Small Business Economics, among others. Prior to his current roles, José held positions at various national and international institutions, including the Federal Reserve Bank of Boston, the University of Alicante, the University of Illinois, Florida State University, and the Institute of European Finance at Bangor University.