Tax Elasticity Estimates for Capital Stocks in Canada
Why this work is in the frame
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Bibliographic record
Abstract
The paper provides estimates of the long-run, tax-adjusted, user cost elasticity of capital (UCE) in a small open economy, exploiting three sources of variation in Canadian tax policy: across provinces, industries, and years. Estimates of the UCE with Canadian data are less prone to the endogeneity problems arising from the effects of tax policy changes on the interest rate or on the price of capital equipment. Reductions in the federal corporate income tax rate during the early 2000s for service industries but not for manufacturing, which already benefited from a preferential tax rate, contribute to the identification of the UCE. To capture the long-run relationship between the capital stock and the user cost of capital, an error correction model (ECM) is estimated. Supplementary results are obtained from a distributed lag model in first differences (DLM). With the ECM, our baseline UCE for machinery and equipment (M&E) is -1.312. The corresponding semi-elasticity of the stock of M&E with respect to the METR is about -0.2, suggesting, for example, that a 5 percentage point reduction in the METR, say from 15 to 10 percent, would in the long run generate an increase of 1.0 percent in the stock of M&E. The UCE for non-residential construction is statistically insignificantly different from zero.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it