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Record W1764037781

Does Inflation Targeting Reduce Inflation? An Analysis for the OECD Industrial Countries

2004· preprint· en· W1764037781 on OpenAlexaboutno aff
Thomas Wu

Bibliographic record

VenueRePEc: Research Papers in Economics · 2004
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsInflation (cosmology)Real interest rateInflation targetingMonetary policyMonetary economicsEmpirical evidenceInflation rateQuarter (Canadian coin)MacroeconomicsInterest rate
DOInot available

Abstract

fetched live from OpenAlex

Despite of its popularity, empirical studies have failed to find evidence of the causal effect of a country's adoption of the Inflation Targeting regime on that country's inflation rate decline. This paper applies the multi-period differences-in-differences estimation to the quarterly CPI inflation rates from the first quarter of 1985 until the third quarter of 2002 to the 22 OECD industrial countries and finds two basic sets of results. The first set of evidences is that countries that have officially adopted Inflation Targeting experience a decrease in their average inflation rates that is not only due to a reversion to mean process. The second set of results is that (1) there seems to be no evidence that Inflation Targeting countries experienced a significant increase in the level of their real interest rates after they adopted the new regime and that (2) even after controlling for the level of real interest rates there is still a causal effect from the adoption of Inflation Targeting to the reduction in inflation rates. In other words, the empirical evidence rejects the idea that the better performance in the inflation rates of the Inflation Targeting countries is only due to a more "aggressive" monetary policy.

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 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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.110
GPT teacher head0.325
Teacher spread0.215 · 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 teacher head, not a consensus.

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

Citations34
Published2004
Admission routes1
Has abstractyes

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