Foreign competition and income distribution in Canada: A dynamic microsimulation CGE Model Analysis
Bibliographic record
Abstract
Since Canada is a very open economy, globalisation and increased foreign competition may entail significant long-run labour market and distributional implications. Indeed, with increased foreign competition and China’s accession to the World Trade Organisation (WTO) in 2001, Canada is facing the shock of declining prices and exports of manufactured goods. The long-run distributional effects of these changes remain ambiguous. While export-oriented sectors face a competitive challenge when their export prices fall along with the prices of competing imports, consumers and firms may benefit from cheaper manufactured goods. In this paper, a dynamic microsimulation computable general equilibrium model (CGE) is developed for the Canadian economy to analyse the impact of increased foreign competition on labour markets, low-income families and income distribution. A Dynamic microsimulation computable general equilibrium model (CGE). The model is calibrated with Canadian data for 2003. Matching and balancing techniques are used to integrate the 29, 846 economic families from the Survey of Labour and Income Dynamics into the general equilibrium framework. The main findings of the simulations conducted in this study are that the decline in world prices of imports and exports of the manufacturing goods induces small increases in low-income rates and inequality in the short run as well as contractions in the export-oriented manufacturing sectors. In the long run, however, it enhances capital accumulation, particularly in the primary and service sectors, increases real GDP and reduces low-income rates especially among families with two persons or more.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".