Provincial Public Infrastructure Spending and Financing in Alberta: Searching for a Better Course
Bibliographic record
Abstract
Alberta’s provincial government investment and capital stocks have followed a rather varied and unusual path since 1961, a path characterized by large swings in both. This paper seeks to understand those developments better and suggest directions for improvement. Relative to other provinces, Alberta has a low level of provincial net capital stock relative to GDP but a high level of capital stock and investment per person. Investigation here shows that the reason for this seeming anomaly is that the Alberta economy is different in notable and generally unappreciated ways from the economies in other provinces. The results indicate that interprovincial comparisons to GDP can often be misleading. Also, household income, not GDP, appears to be the major determinant of public infrastructure. Since 2008, the Alberta government has relied increasingly on debt finance. There is a need for caution because what appear to be (inter-provincially) moderate levels of debt relative to GDP are large relative to provincial government revenue (which is argued to be a more meaningful comparator). Utilizing public investment to help stabilize the economy has been mixed in Alberta over the long term. However, the overall surplus/deficit pattern has been much more counter-cyclic. More emphasis has been placed on stabilization since 2000 and especially so during the 2009 and 2015 downturns. While both those downturns are linked to long-term resource revenue setbacks (the lasting drop in natural gas prices and the drop in oil prices that is expected to diminish the provincial government’s resource revenues for some time), they have been treated as if caused by cyclic rather than structural changes. The result is that reserve funds have been drained and the province has dramatically increased debt (largely it is argued to support capital investment) and continues to do so even as the economy gradually improves. Provincial finances need adjustment to the longer-term realities. More stable capital funding would be a component. Possibilities are noted and suggestions are offered.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".