Size, Productivity and Profitability: Canada's Natural Resource Industries in the Twentieth Century
Bibliographic record
Abstract
Size, Productivity and Profitability: Canada’s Natural Resource Industries in the Twentieth Century At the end of the twentieth century Canada’s natural resource industries continued to play a substantial role in the growth and development of the domestic economy. Relative to the aggregate economy (and the manufacturing sector), the resource industries were large and growing, they were more capital intensive, and they enjoyed more rapid total factor productivity growth. Despite the strength of these “economic fundamentals” it is not clear that we should adopt an unambiguously optimistic perspective when we assess the long run economic performance of Canada’s resource intensive industries. Among participants on Canada’s equity markets, for example, pessimism may not have been uniform across time periods or sectors, but investors were clearly not bullish about the long run performance of domestic energy, forestry and mining producers. In this paper I investigate the relationship between the size of Canada’s twentieth century resource industries as measured by output, value added and employment the productivity of these industries as measured by labour and total factor productivity and the profitability of these industries as measured by the generation of resource rents and common stock prices. I present evidence that is generally supportive of the theoretical predictions made by natural resource and finance theory with respect to the relationship among performance indicators. In particular, T.F.P., output, capital intensity and relative prices were all significant determinants of resource rents, and in turn, resource rents were a significant determinant of stock market performance. The empirical support for these theoretical predictions suggests that we should look beyond productivity and size when assessing economic performance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".