Three Essays on the Effect of External Business Environment on Corporate Investment
Bibliographic record
Abstract
This dissertation consists of three related essays on corporate investment.In Essay I, I examine how the characteristics of the country in which firms operate affect firm's "fourth quarter effect".In Essay II, I study how firm's local risk preference influence their acquiring decisions.And in Essay III, I investigate the relation between country laws and institutions and corporate pension underfunding, as well as the effect of pension underfunding on corporate investment and valuation.Essay I: It is documented that companies and government agencies in the United States invest more in the fourth fiscal quarter without having higher investment opportunities.While previous studies focus on the agency conflicts and information asymmetry within organizations, we are motivated by Scharfstein and Stein's (2000) two-tiered agency model, and examine how firms' external business environment affects the "fourth quarter effect".We implement our study in a sample of 41 countries, and observe similar seasonality in firm investment as documented in the U.S. market.More importantly, using country characteristics, we find that firms from countries with better investor rights and protection, and more developed financial markets show less severe over-investment in the fourth fiscal quarter.Essay II: This essay studies how managers' risk aversion, captured by the local religious beliefs prevailing in the locations of their firms, could affect firms' merger and acquisition activities.We find that firms headquartered in areas with higher Catholics-to-Protestants (CP) ratio, reflective of stronger gambling preferences, tend to conduct more acquisitions.Moreover, these acquisitions are more likely to be international and conglomerate, and more likely to involve targets with high stock return volatility and R&D spending.The acquisitions are also associated with value destruction from the perspective of the acquiring firm's shareholders and the effect is magnified in an environment of weaker corporate governance.When we interact CP ratio with executive's career risk, we find that local gambling preference significantly promotes managerial risk-taking in mergers and acquisitions.iii Essay III: Financial crises, low interest rate, and extended life expectancy cast doubt on whether corporate defined benefit (DB) pensions are sufficiently funded to cover their liabilities.We study the effect of pension underfunding on corporate investment using international data involving 29 countries at heterogeneous economic development stages and different regulatory environments.We document that corporate pensions are significantly underfunded in most countries of our sample in the period of 2001 to 2015.Pension assets are on average less than 50% of pension liabilities among firms that provide DB pension plans.To the extent of pension underfunding effect on corporate investment, we find that the (inverse) relationship is subject to variation in country characteristics.Specifically, firm's investment is more severely constrained by pension underfunding in countries with stronger labor union power and less developed financial market.Finally, while substantial pension underfunding has a negative impact on firm value, our results show that offering more DB pension plans do not reduce firm value.Overall, our findings suggest that DB pension plans could still play a useful role in creating firm value.discussions.All people, especially Haim and Chauncey, have been excellent colleagues and office mates.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".