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Record W4366811071 · doi:10.4236/tel.2023.132019

Revisiting the AA-DD Model in Zero Lower Bound

2023· article· en· W4366811071 on OpenAlex
Charles Olivier Mao Takongmo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTheoretical Economics Letters · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsZero lower boundEconomicsExchange rateGovernment spendingZero (linguistics)Monetary economicsInterest rateEconometricsWelfare

Abstract

fetched live from OpenAlex

This paper proposes a simple model of a mechanism through which exchange rate can affect the link between output and government spending in zero lower bound (ZLB) periods. In our proposed model, the expected near-future interest rate is added as an endogenous variable. Unlike existing AA-DD models in ZLB, the nominal exchange rate is no longer constant. Our model predicts that the output effect of an increase in government spending in a ZLB period is deflected by an appreciation of the current exchange rate. The AA-DD model is taught in almost all economic departments. The model is also generally used by many central banks and governments. The existing AA-DD model can be misleading. Our new AA-DD model may help to update the existing model in ZLB periods. Our AA-DD model is also consistent with recent dynamic stochastic general equilibrium models in open economies in ZLB periods.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.412
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.005

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.

Opus teacher head0.044
GPT teacher head0.224
Teacher spread0.180 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it