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Record W3210957285 · doi:10.5539/ijef.v13n11p77

Monetary and Fiscal Policies Interaction in a Large Emerging Economy: Which Is the Leader Policy?

2021· article· en· W3210957285 on OpenAlexvenueno aff
Ricardo Ramalhete Moreira, Edson Zambon Monte

Bibliographic record

VenueInternational Journal of Economics and Finance · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsFiscal policyMonetary policyInflation (cosmology)Budget constraintMonetary economicsConstraint (computer-aided design)MacroeconomicsInterest rate channelInflation targetingKeynesian economicsCredit channelMicroeconomics

Abstract

fetched live from OpenAlex

This article analyzed the intertemporal interaction between monetary and fiscal policies in Brazil. We aimed at identifying if structural innovations to the real interest rate were able to induce unexpected effects on fiscal and inflation dynamics. To do so, we estimated Structural Vector Autoregressive (SVAR) models over the period from Jan/2004 to Apr/2019. Moreover, we filtered out the time series’ long-memory component through a fractional integration approach, so that we did not build our analysis on traditional unit root tests. The findings showed that monetary policy shocks robustly activated an unconventional transmission channel based on the Fiscal Theory of the Price Level, i.e., an unexpected and induced change in primary surpluses, through a wealth effect, as mechanism to satisfy the Government’s intertemporal budget constraint. Such a result is strongly linked to another evidence, that is, the monetary policy`s role as a leader in shaping inflation over time.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.042
GPT teacher head0.261
Teacher spread0.218 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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