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Can credit default swaps exert an enduring monitoring influence on political integrity?

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Abstract

Exploiting the launch of U.S. state credit default swaps (CDS) to study how financial market monitoring affects local political integrity, we show that CDS-referenced states are associated with reduced corruption conviction rates of local government officials by about 28% post-launch compared to non-CDS-referenced states. The effect on curbing corruption persists up to six years after CDS issuance. Improved transparency of government fiscal information is the primary mechanism through which CDS inception affects corruption. We conclude that credit market innovation creates positive and enduring externalities for political integrity.

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Notes

  1. Corruption can disrupt investment and growth, distort public policies, and hamper efficient allocation of resources (see, e.g., Shleifer and Vishny 1993; Mauro 1995; Bliss and Di Tella 1997; Ehrlich and Lui 1999).

  2. The empty creditor problem arising at the inception of CDS trading may increase the bargaining power of lenders in default negotiations or lessen incentives to monitor borrowers, which in turn increases the probability of bankruptcy (Bolton and Oehmke 2011; Subrahmanyam et al. 2014). States, however, are sovereign and not subject to bankruptcy. That is, a state entity typically does not have the legal ability to declare bankruptcy (Ang and Longstaff 2013). Thus, this change in the debtor-creditor relation should not affect the behavior of state officials.

  3. Municipal securities issuers are not subject to most federal securities laws, including the registration and reporting requirements of the Securities Act of 1933 and the Exchange Act of 1934. In addition, state and local governments take about five and a half months to disclosure annual audited financial statements (GASB 2018).

  4. Non-state municipal entities can seek Chapter 9 protection under the U.S. Bankruptcy Code, similar to Chapter 11 for corporations.

  5. The results remain unchanged if we cluster the standard errors by state.

  6. Mauro (1995) indicates a negative relation between corruption and economic growth.

  7. There are 26 observations for each CDS-referenced state, including one CDS-referenced state and 25 non-CDS-referenced states. Thus, the total number of observations is 6,500 (= 26 × 25 CDS-referenced states × 10 years). We also use the propensity-score-matching approach to select a non-CDS-referenced as a control sample for each CDS-referenced state. In this case, there are 500 observations in the analysis. The empirical results are reported in the latter part.

  8. We do not include CDS_Tradingt−3 in this equation because of multicollinearity.

  9. A state’s explanatory variables include fiscal deficit, total taxes, debt outstanding, total revenue, cash and security holdings, total expenditure divided by total revenue, unemployment rate, logarithm of population, logarithm of per capita gross domestic production, logarithm of per capita personal income, and credit rating. Data on state per capita gross domestic production and state per capita personal income are obtained from the U.S. Bureau of Economic Analysis. Data on state unemployment rates and ratings are obtained from the U.S. Bureau of Labor Statistics and S&P Capital IQ, respectively. Data on the other variables are obtained from the U.S. Census Bureau.

  10. The conclusion remains unchanged if (1) we require that the maximum difference between the propensity score of the non-CDS-referenced state and the propensity score of the CDS-referenced state should not exceed 10% in absolute value, or (2) we use two non-CDS-referenced states with the closest propensity scores to the CDS-referenced state.

  11. We also conduct a placebo test with CDS_Tradingt−6, CDS_Tradingt−5, and CDS_Tradingt−4 set equal to zero and with CDS_Tradingt−3, CDS_Tradingt−2, and CDS_Tradingt−1 set equal to one. The DiD coefficient on CDS_Trading is again statistically insignificant.

  12. As the data are available only from 1975 through 2003 and our sample period starts from 2001, we use the average value of Attorney over 2001–2003 to proxy for the efforts of law enforcement.

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Funding

Ministry of Science and Technology, Taiwan, MOST 107-2410-H-004-026-MY3, Sheng-Syan Chen, MOST110-2410-H-468-006-MY2, Hsien-Yi Chen.

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Authors and Affiliations

  1. Department of Finance, College of Management, Providence University, Taichung, Taiwan

    Hsien-Yi Chen

  2. Department of Finance, College of Management, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd, Taipei, Taiwan

    Sheng-Syan Chen

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  1. Hsien-Yi Chen
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Correspondence to Sheng-Syan Chen.

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Part of this research was done while Sheng-Syan Chen was a professor of finance at National Chengchi University. We gratefully acknowledge financial support from Ministry of Science and Technology in Taiwan (MOST 107-2410-H-004-026-MY3 and MOST 110-2410-H-468-006-MY2).

Appendix: Variable definitions and data sources

Appendix: Variable definitions and data sources

Variable

Definition

Source

Corruption

Number of federal corruption convictions of public officials per 10,000 government employees in a state

U.S. Department of Justice

Gini

Gini index

U.S. Census Bureau

LnPCPI

Natural logarithm of state per capita personal income

U.S. Bureau of Economic Analysis

LnPopu

Natural logarithm of state population

U.S. Census Bureau

Bachelor

Percent of the population with a bachelor’s degree or higher

U.S. Census Bureau

LnHI

Natural logarithm of state median household income

U.S. Census Bureau

Urban

Share of urban population to state population

U.S. Census Bureau

Govemploy

Share of employment in government and government enterprise to total state employment

U.S. Bureau of Economic Analysis

Midwest

A binary variable that equals one if a state is located in the Midwestern U.S., and zero otherwise

U.S. Census Bureau

Northeast

A binary variable that equals one if a state is located in the Northeastern U.S., and zero otherwise

U.S. Census Bureau

South

A binary variable that equals one if a state is located in the Southern U.S., and zero otherwise

U.S. Census Bureau

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Chen, HY., Chen, SS. Can credit default swaps exert an enduring monitoring influence on political integrity?. Rev Quant Finan Acc 60, 445–469 (2023). https://doi.org/10.1007/s11156-022-01100-9

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