What Explains the Rising Profit Share in Canada
Bibliographic record
Abstract
The distribution of the gains of economic growth among workers and corporations has evolved over time. While an extensive body of literature has studied the fall in the share of labour income in the gross domestic product (GDP), less attention has been paid to the development of the components of its counterpart, the capital share. In the system of National Accounts, the capital share of income can be broken down into net operating surplus and net mixed income (which includes corporate profits before taxes, net interest paid, net other payments and inventory valuation adjustment, and net mixed income) and capital consumption allowances (CCA). This report contributes to the discussion on the rising capital share by studying the evolution of the Canadian corporate profit share in the past three decades using both financial and national accounts data. We analyze trends at the aggregate and sectoral level and compare the aggregate trends to those in the United States during the same period. We also provide an overview of the structural factors affecting the corporate profit share in Canada. According to national accounts data, the corporate profit share before tax in Canada rose 3.8 percentage points between the 1961-1999 and 2000-2017 periods, an increment that significantly enhanced the surge in the capital share of income. Similarly, the financial corporate profit share of income increased by 7.2 percentage points between 1997 and 2017. This development was widespread, with the profit share increasing in all sectors except mining, quarrying and oil, and gas extraction. It was also concentrated. We find that the financial sector, which accounts for less than one tenth of GDP, was responsible for 33 per cent of the increase in the corporate profit share. Complete time series of the profits data used in this report can be found in a profits database developed as part of this research project.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".