Bibliographic record
Abstract
How and to what extent are small open economies affected by international shocks? I develop and estimate a medium scale DSGE model that addresses both questions. The model incorporates i) international markets for firm-to-firm trade in production inputs, and ii) producer heterogeneity where technology and price setting constraints vary across industries. Using Bayesian techniques on Canadian and US data, I document several macroeconomic regularities in the small open economy, all attributed to international disturbances. First, foreign shocks are crucial for domestic fluctuations at all forecasting horizons. Second, productivity is the most important driver of business cycles. Investment efficiency shocks on the other hand have counterfactual implications for international spillover. Third, the relevance of foreign shocks accumulates over time. Fourth, business cycles display strong co-movement across countries, even though shocks are uncorrelated and the trade balance is countercyclical. Fifth, exchange rate pass-through to aggregate CPI inflation is moderate, while pass-through at the sector level is positively linked to the frequency of price changes. Few of these features have been accounted for by existing open economy DSGE literature, but all are consistent with reduced form evidence. The model presented here offers a structural interpretation of the results.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".