Getting Real: A Shadow Federal Budget for 2017
Bibliographic record
Abstract
The 2017 edition of the C.D. Howe Institute’s annual Shadow Federal Budget urges Ottawa to set out a path back toward balance to inspire confidence among savers and investors, accompanied by tax and spending measures to boost economic growth and opportunities. To reassure Canadians that federal finances are under control, and correct unrealistic expectations about spending encouraged by lack of discipline on the bottom line, this Shadow Budget ensures that, even with cautious economic forecasts and prudence cushions, the ratio of federal debt to gross domestic product will stabilize immediately. Among the measures that produce this result are continued restraint on transfers to other levels of government, and containment of Ottawa’s compensation costs. This Shadow Budget also contributes to fiscal discipline through improved accountability: clearer and more prominent presentation of the key revenue and spending numbers in the budget and the Estimates, and fair-value presentation of the federal government’s massive pension obligations. To boost economic growth and opportunities for Canadians, this Shadow Budget includes a variety of measures. Changes to the tax system focus on modernization, with recommendations to replace ongoing preferential tax treatment for small businesses with temporary preferential treatment for young businesses, and to tax returns on intellectual property investments at a lower rate to reflect their spillover effects to the broader economy. To enhance Canada’s international competitiveness, it proposes to replace aviation fuel taxes and other potential CO2-related levies with a new GST rate on fuels, and proposes to roughly double the threshold for the top personal tax rate. It also proposes to level the playing field for domestic producers of digital services relative to untaxed competitors abroad. It would raise the threshold for sales tax and customs duties levied on imports, and begin the phase-out of all import tariffs. And it would encourage business investment and equity relative to debt finance by establishing an allowance for corporate equity that relieves ordinary returns to capital from corporate income tax. On the spending side, this Shadow Budget prioritizes infrastructure projects Ottawa can drive on its own. It proposes to dispose of non-core assets and increase private investment in infrastructure by selling selected airport leases. Other measures would improve Canada’s job market, and support higher student achievement. Additional measures to boost Canada’s economy include updated mandates for Crown lenders, a backstop for catastrophic insurance, and reforms to help Canadians saving for retirement in RRSPs or target-benefit pension plans, and protect them against outliving their savings. In summary, this Shadow Budget marks a transition from the rhetoric of campaigning and the hesitations of a new government, to a package of concrete measures that will give Canadians confidence in the future of their country as a place to learn, work, and retire, and as a place to save and invest.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.077 | 0.055 |
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".