A Simple and Flexible Dynamic Approach to Foreign Direct Investment Growth: Did Canada Benefit From the Free Trade Agreements with the United States?
Bibliographic record
Abstract
This paper asks a simple question: Did Wilfred Laurier’s dream of free trade with the United States, when it came to fruition in 1989, also have a benefit by increasing foreign direct investment (FDI) into Canada by US multinationals? This paper introduces a dynamic framework, rather than the literature’s traditional static framework, and uses a structural break framework, rather than modelling policy changes as an intercept shift alone. Its conclusions are (a) The signing of the free trade agreements between Canada and the United States increased the responsiveness of growth in the Canadian economy on the US FDI decision by a factor of two. (b) Limited dynamics are found in the form of lagged effect of changes in the real Canadian interest rate. (c) The effect of the change in the exchange rate is static and constant over the whole 1955 to 2000 period and was unaffected by the introduction of free trade between the United States and Canada.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".