Essays in Corporate Finance, Shareholder Litigation, and Politics
Bibliographic record
Abstract
When firms seek to curry the favor of politicians, it inevitably leads to political corruption. Political spending totaled US$14.4 Billion in the 2020 US election cycle—and this total does not include dark money donations. Firms naturally never donate to politicians without wanting a return on their investment, so clearly political corruption is a multi-billion-dollar problem in the United States. Recently, a strand of literature examines political corruption in the US from a corporate finance perspective. Another recent strand of finance literature concerns the effects of political ideology on the outcomes of US securities-related shareholder litigation. This thesis aims to first combine and expand upon these two emerging strands of literature by analyzing the relationships of a comprehensive variety of US political and judicial variables with the outcomes of securities fraud and related shareholder litigation. We then extend our framework to a refined exploration of corporate governance as it relates to shareholder litigation. \n \nIn the first essay, we study the relationship between a number of political and judicial variables in the United States with the outcomes of litigation for firms that have been sued by their shareholders. Consistent with our hypothesis, we find that a crucial factor in shareholder litigation dismissal has been the passage of the Citizens United v. FEC Supreme Court campaign finance ruling of 2010. Furthermore, we find evidence that political campaign contributions afford firms the requisite connections that will benefit them in current or future lawsuits. Also, we quantify the impact of the size and timing of the political campaign contributions. In addition, we confirm hypotheses that the fate of shareholder class action litigation against these firms is also affected by the political ideologies of some of the trusted authorities who write, administer, and interpret the laws pertinent to firms facing such litigation. These authorities are federal politicians and judges, who are ideally independent arbiters—but the great powers they are given appear to create agency and bias issues, respectively.\t \n \nIn the second essay, we use the knowledge and framework attained from our conclusions from the first essay to examine various corporate governance variables with respect to their role in shareholder litigation outcomes in this new light—variables which can be categorized as board, executive, and firm ownership characteristics. We confirm hypotheses generally based on the principle that variables reflecting better corporate governance will tend to be associated with a higher lawsuit dismissal likelihood. This likelihood tends to increase with a firm’s board of directors who are older, more independent, less busy, and have a larger network size. Furthermore, the likelihood of litigation dismissal increases with greater analyst coverage of the firm, with a firm’s CEO who is older than the board of directors, with greater institutional ownership, and with a larger number of blockholders owning stakes in the firm. As well as finding results consistent with such hypotheses for our corporate governance variables, we also find some novel, unexpected interactions between political variables and corporate governance variables.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".