External Sector Rebalancing and Endogenous Trade Imbalance Models
Bibliographic record
Abstract
I discuss the need for trade models to incorporate endogenous trade imbalances both to more adequately capture the reality of a global economy with large imbalances and pressures from the financial crisis for countries to reduce imbalances.Conventional general equilibrium trade models implicitly incorporate monetary neutrality and either have zero trade balance as a property of equilibrium, or have a fixed and exogenous trade imbalance.Models which are discussed here have a variety of forms.In one, central banks fix exchange rates and operate a non accommodative monetary policy and accumulate reserves.Changes in both trade and monetary policies change reserve accumulative and with the external sector imbalances.This is a reflection of China's current policy regime.In another intertemporal preferences allow for simultaneous inter commodity and intertemporal trade across countries, and with changed intertemporal trade changed external sector imbalances within the period.These formulations are each applied to potential tax initiatives to aid in rebalancing. Endogenous Trade Imbalance ModelsConventional real side trade models (see Dixit & Norman (1980)) sit as a subclass of general equilibrium models of pure barter form, which if taken to a simple monetized extension via a simple quantity theory of money approach exhibit neutrality of money.In these, in 2 country form, once domestic money supplies are determined exchange rates are endogenously determined in such a way that changes in monetary policy only affect exchange rates with no real effects.In such models, in addition, trade balance by country is either zero as a property of equilibrium; or meets an exogenously given inter country transfer, which is fixed and given and implies an exogenous trade imbalance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".