Do Financial Frictions Amplify Fiscal Policy? Evidence from Business Investment Stimulus∗
Bibliographic record
Abstract
We estimate the causal effect of temporary tax incentives on equipment investment using a difference-in-differences design and policy shifts in accelerated depreciation. Ana-lyzing data for over 120,000 US firms from 1993 to 2010, we present three findings. First, bonus depreciation raised investment by 18.5 percent on average between 2001 and 2004 and 31.2 percent between 2008 and 2010. Second, financially constrained firms respond more than unconstrained firms. And third, firms respond strongly when the policy gener-ates immediate cash flows, but do not respond at all when the policy only benefits them in the future. The results provide an estimate of the discount rate firms apply to future cash flows: constrained firms act as if $1 next year is worth 38 cents today. The estimated discount rate is too high to match the predictions of a frictionless model, nor can it be explained entirely by costly external finance, unless firms also neglect financial constraints binding in the future.
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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 | 0.003 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".