The outcomes of corporate prosecutions can devastate even the largest multinational corporations and set long-lasting judicial precedents that affect how businesses operate. For example, the 2002 guilty verdict against Arthur Andersen (AA), one of the “Big 5” accounting firms with over 28,000 employees, resulted in the loss of AA’s license to act as a certified public accountant. Earlier, the New York Central and Hudson River Railroad v. United States ruling of 1909 established that corporations are responsible for the actions of their employees.
Increases in the average fines imposed by judges,from about $500 Million in the 1990s to over $4.5 billion in recent years, can also shift companies’ priorities, particularly if these changes are concentrated among certain types of crimes (e.g., the violation of labor regulations). In our study, titled “Are Judges Like Umpires? Political Affiliation and Corporate Prosecutions”, we assess whether the political affiliation of judges influences the outcomes of corporate prosecutions and the monetary penalties imposed on companies.
Although concerns about judicial bias tend to focus on social issues such as abortion and guns, judicial political affiliations could also be important for corporate criminal prosecutions and the broader economy. For example, if Republican judges are more likely to view the hiring of illegal workers as an essential legal violation, the average outcome and resulting precedents of corporate immigration cases could be influenced by the recent increase in Republican-appointed judges. Likewise, if Democrat-appointed judges are more likely to view the protection of the environment as vital, the outcomes of cases involving corporate pollution could shift as well. Any such shift in the expected penalties for violating various regulations (e.g., immigration and pollution laws) could then influence how companies operate (e.g., by changing firms’ hiring practices or investment choices).
To assess whether judicial political affiliations affect the outcomes of corporate prosecutions, we construct a novel dataset on federal corporate prosecutions and the political affiliation of federal judges. We begin by using the Corporate Prosecutions Registry, which provides information on the universe of all federal criminal corporate prosecutions in the US from 1993 to 2018, and augment this dataset by extracting additional information from each case’s docket using Python. Our data include information on the filing date, resolution date, underlying charges, outcomes (e.g., trial conviction, acquittal, plea deal, etc., and monetary damages assessed, if any), and most importantly, the judge’s name. We then match each judge’s name to the political affiliation (Republican versus Democrat) of the president that nominated the judge. This allows us to assess whether the political affiliation of US federal judges, as measured by the political affiliation of the appointing president, is associated with the outcome of cases they preside over.
Our analysis focuses on whether case outcomes depend on the combination of a judge’s political affiliation and how partisan political views are concerning the underlying crime being prosecuted. We classify two types of crimes in our sample as being related to highly partisan issues: immigration crimes (e.g., a firm hired illegal immigrants) and violations of labor and environmental regulations (e.g., a firm polluted a local river). According to the Pew Research Center’s Ideological Consistency Scale, liberals tend to take a more positive view of labor and environmental regulations, while conservatives tend to place a larger emphasis on enforcing immigration laws. Therefore, if judicial political affiliations matter, we might see less favorable outcomes for companies accused of labor or environmental crimes when a Democrat-appointed judge oversees the case, and more favorable outcomes if the case instead involves immigration crimes.
Our findings show that the identity of the political party making these judicial appointments does matter. In corporate prosecutions, the average fine imposed on companies can vary considerably depending on the political affiliation of the assigned judge and the underlying crime. In particular, cases randomly assigned to Democrat-appointed judges have fines that are, on average, 184 percent larger if the underlying crime involves violating labor or environmental regulations and 91 percent smaller if related to violating immigration laws. The difference in fines imposed across these different types of crime conforms to the typical priorities associated with each political party. These differences in fines across Republican and Democratic judges are even more significant during time periods of greater partisan polarization and are not driven by other judge-level characteristics—such as race, age, and experience—that might be correlated with a judge’s political affiliation.
These findings have numerous implications for companies. Judicial rulings can set long-lasting precedents regarding the enforcement of various business regulations, and the penalties imposed by judges for violating existing laws can be a deterrent affecting the broader economy. For example, Oregon Senator Jeff Merkley argued in 2012 that the lack of significant penalties imposed on large banks following the 2008 financial crisis was sending a message that some firms are simply “too big to jail.”
To the extent that judicial political affiliations contribute to the amount of penalties companies can expect to incur for violations, a shift in the composition of judges also has the potential to shift companies’ priorities. For example, if the recent push to confirm President Trump’s nominees results in firms expecting to incur smaller fines for environmental violations but larger fines for hiring illegal workers, then companies may prioritize abiding by immigration laws rather than environmental regulations, which could influence both the types of workers they hire and the investments they make. This potential impact of judicial political affiliations on the real economy presents an interesting direction for future research.