Three essays dealing with open economy models based on the portfolio balance tradition
Bibliographic record
Abstract
This thesis consists of three papers on open economy models in the portfolio balance tradition. The first paper presents a dynamic stock-flow consistent model for three economies with both fixed and floating exchange rates. The model is applied to simulate the impact of internal and external shocks, and short-run and long-run effects of changes in the U.S. fiscal position on the economies of the three countries---the U.S., China and Euroland. The simulation results show that the compensation principle still holds in an open overdraft economy. The second paper investigates the effect of the diversification of China's foreign reserves using the three-country model. The simulation results show that with the diversification of China's foreign reserves, the euro appreciates against the dollar and the RMB. China and the U.S. can benefit from the diversification, while the Euroland economy slows down. What is interesting is that the model generates some kind of path dependence. How the central bank of China will achieve its target diversification rate has an impact on the steady state values of the model. The third paper examines the portfolio balance model for the determination of the nominal exchange rate of the Canadian dollar against the US dollar using the VAR model. One cointegration equation is found. Through the impulse response and the variance decomposition analyses, we find that the Canadian demand for the US bills and bonds play an important role in the dynamic changes of the exchange rate. The empirical test results indicate that it is difficult for the reduced form portfolio-balance models to consistently beat the random walk model.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".