Bibliographic record
Abstract
I develop a model that improves upon the recent literature in open economy macroeconomics in that it lends itself more directly to empirical investigation. I solve the stationarity problem that characterizes many existing models by adopting an overlapping generations structure la Weil (1989). I model nominal rigidity by assuming that firms face explicit costs of output price inflation volatility. The specification generates an endogenous markup that fluctuates over the business cycle. I identify the two economies in my model with Canada--a small open economy--and the United States--taken as an approximation of the rest-of-the-world economy. In the second part of the paper, I present a plausible strategy for estimating the structural parameters of the Canadian economy. I do so by using nonlinear least squares at the single-equation level. Estimates of most parameters are characterized by small standard errors and are in line with the findings of other studies. I also develop a plausible way of constructing measures for nonobservable variables. To verify if multiple-equation regressions yield significantly different estimates, I run full information maximum likelihood, system-wide regressions. The results of the two procedures are similar. Finally, I illustrate a practical application of the model, showing how a shock to the U.S. economy is transmitted to Canada under an inflation-targeting monetary regime.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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; both teacher heads agree on what is shown here.
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".