The Role of Public Infrastructure Investment: its Development and Contributions to Economic Growth
Bibliographic record
Abstract
Canada's response to the recent global economic crisis reflected that of many Western nations - one that centred on fiscal stimulus packages with large funds allocated towards infrastructure development. This paper uses modified-Wald tests in bivariate autoregressive models to examine whether factor inputs, specifically public fixed capital investment and other determinants of economic growth, are complements (or substitutes). National accounting data is used at the provincial, national, and international levels to test for complementary relationships. Test results could not produce any robust evidence of any one-way or dual causal relationships in the levels or growth rates among any of these subsets. However despite no evidence of these short-run relationships, the Johansen cointegration test identifies long-run relationships between Canada's public and private investments, employment, and labour productivity. Furthermore the impact of Canadian public investment growth on output growth demonstrates a dual causal relationship, running positively from investment to output, but negatively in the reverse causation. This study supports the notion of functional finance in the Canadian context, in that increases to public infrastructure growth contribute to increased output growth, but that increased output growth leads decreases in public investment growth. I conclude with an exploratory discussion involving the development of specific industries in a Kaldorian context, highlighting the shift of Canada's industry sectors from manufacturing to natural resources, which may indeed be a source of our declining productivity growth.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".