Bibliographic record
Abstract
How are macroeconomic fluctuations in open economies affected by international\nbusiness cycles? To shed some light on this question, I develop and estimate\na medium scale DSGE model for a small open economy. The model incorporates\ni) international markets for firm-to-firm trade in production inputs, and ii) producer\nheterogeneity where technology and price setting constraints vary across industries.\nUsing 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\nhorizons. Second, productivity is the most important driver of business cycles.\nInvestment efficiency shocks on the other hand have counterfactual implications for\ninternational spillover. Third, the relevance of foreign shocks accumulates over time.\nFourth, business cycles display strong co-movement across countries, even though\nshocks are uncorrelated and the trade balance is countercyclical. Fifth, exchange\nrate pass-through to aggregate CPI inflation is moderate, while pass-through at the\nsector level is positively linked to the frequency of price changes. Few of these features\nhave been accounted for in existing open economy DSGE literature, but all are\nconsistent with reduced form evidence. The model presented here offers a structural\ninterpretation of the results.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| 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) | 0.001 | 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".