Investment under Uncertainty, Debt and Taxes
Bibliographic record
Abstract
It is common practice in financial derivative valuation to use a discount factor based on the riskless debt rate. But, to what extent is this discount factor appropriate for cash flows emerging in capital budgeting? To answer this question, we introduce a framework for real asset valuation that considers both personal and corporate taxation. We first discuss broad circumstances under which personal taxes do not affect valuation. We show that the appropriate discount rate for equity‐financed flows in a risk‐neutral setting is an equity rate that differs from the riskless debt rate by a tax wedge due to the presence of personal taxation. We extend this result to the valuation of the interest tax shield for exogenous debt policy with default risk. Interest tax shields, which accrue at a net rate corresponding to the difference between the corporate tax rate and a tax rate related to the personal tax rates, can have either positive or negative values. We also provide an illustrative real options application of our valuation approach to the case of an option to delay investment in a project, showing that the application of Black and Scholes formula may be incorrect in presence of personal taxes.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".