Do corruption perceptions impact the pricing and access of euro area corporations to bond markets?

Abstract

Public sector corruption affects economic and financial outcomes, such as GDP growth, foreign direct investment, and government funding costs. Less is known about the spillovers from perceptions of public sector corruption on the private sector corporate bond market. In this paper, we assess the role of public sector corruption perception on corporate bond market variables in Europe using data of both country-level corporate bond indexes and firm-level corporate bond market issuances. At the aggregate country level, we find some evidence that country indices of corporate bonds' yields and coupons are higher in countries with more corruption. While we do not find effects of corruption on coupon rates at the individual firm level, we show that higher government corruption perception increases their yield to maturity and reduces the amounts raised by corporations through their bond issuances.

KEYWORDS:

• Corruption
• transparency
• corporate debt
• yields
• issuances

JEL CLASSIFICATIONS:

• D73
• G10
• F30
• G12
• G15
• G20
• G24

Acknowledgements

The authors thank the referees and EUMODFRAUD, the European Research group and Observatório de Economia e Gestão de Fraude (OBEGEF).

Disclosure statement

No potential conflict of interest was reported by the author(s). Views expressed in this paper are those of the authors and do not necessarily reflect the position of the Spanish Ministry of Economy and Digital Transformation.

Notes

1 The Bloomberg Euro-Aggregate country corporate statistic index is a broad-based benchmark that measures the investment grade, euro-denominated, fixed-rate corporate bond market for each country. The index is weighted at market value with a monthly rebalanced frequency.

2 Tickets I02063, I02067, I02071, I02075, I02083, I02087, I02091, I02095, I02099, I02103 and I02079.

3 The correlation between the CRR and CPI indices for all the observations in our sample is 0.951. Figure A1 in the Appendix shows comparative graphs of the two indices, as a composite and by country. The correlation of the mean CCR and CPI by year of all countries (first left panel of Figure A1) is 0.7258. When we disaggregate by countries and take the means by country and year, the average of the correlation between the CCR and CPI of the 11 countries is 0.9536.

^[4] Credit to Non-financial corporations from all sectors at market value - percentage of GDP - adjusted for breaks.

^[5] Table A1 in the Appendix lists all the main variables used in our analyses.

^[6] Figures 2 and 3 show graphically the YTM and coupon rate variation by country. Note that the variation if higher for YTM than for coupon. It is also noticeable the differences in variation across countries.

^[7] Note the low time variation by country in Figure 1. Also, non-tabulated results show that the average standard deviation of CPI in each country is 0.38.

^[8] In any case for robustness we run an alternative model with country fixed effects, the results available upon request do not change our conclusions.

^[9] Standard errors clustered by year.

^[10] Results reported in tables 6 and 7 are clustered by firm and year. For robustness we also cluster by firm, country and year the results, not reported but available upon request, are similar. Also results reported in table 5 are clustered by year in columns 1 to 3, for robustness we also cluster by country and find similar results (Results for table 5 with cluster by country are available upon request).

4 Credit to Non-financial corporations from all sectors at market value - percentage of GDP - adjusted for breaks.

5 Table A1 in the Appendix lists all the main variables used in our analyses.

6 Figures 2 and 3 show graphically the YTM and coupon rate variation by country. Note that the variation if higher for YTM than for coupon. It is also noticeable the differences in variation across countries.

7 Note the low time variation by country in Figure 1. Also, non-tabulated results show that the average standard deviation of CPI in each country is 0.38.

8 In any case for robustness we run an alternative model with country fixed effects, the results available upon request do not change our conclusions.

9 Standard errors clustered by year.

10 Results reported in tables 6 and 7 are clustered by firm and year. For robustness we also cluster by firm, country and year the results, not reported but available upon request, are similar. Also results reported in table 5 are clustered by year in columns 1 to 3, for robustness we also cluster by country and find similar results (Results for table 5 with cluster by country are available upon request).

Additional information

Funding

This work was supported by Spanish Ministry of Science and Innovation [grant number ECO2018-98139].

Notes on contributors

Marta Alonso

Marta Alonso is a PhD student at the University of Navarra. Her dissertation lies in the area of Corporate Governance and she has published in the Journal of Institutional Economics.

Judith Arnal

Judith Arnal is the Chief of Staff of the Minister of Economy and Digital Transformation of the Spanish Government. She holds a Phd from the University of Navarra. Her dissertation focused on banks and financial markets.

Andrés Mesa-Toro

Andrés Mesa-Toro is an Assistant Professor of Finance at the University of Navarra. His research is focused on financial institutions and he has published in the Journal of Financial Stability, and the Annals of Public and Cooperative Economics.

Antonio Moreno

Antonio Moreno is a Professor of Economics and Finance at the University of Navarra. He holds a PhD in Economics from Columbia University. His research is in the intersection of Macroeconomics and Finance, and he has published in outlets such as the Journal of Monetary Economics, the Journal of Money, Credit and Banking, and the Journal of Banking & Finance.