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Record W2615075005 · doi:10.3386/w19025

Market Deregulation and Optimal Monetary Policy in a Monetary Union

2013· preprint· en· W2615075005 on OpenAlexaff
Matteo Cacciatore, Giuseppe Fiori, Fabio Ghironi

Bibliographic record

VenueNational Bureau of Economic Research · 2013
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsHEC Montréal
FundersNational Science Foundation
KeywordsDeregulationMonetary policyMonetary hegemonyEconomicsMonetary economicsInternational economicsBusinessMarket economy

Abstract

fetched live from OpenAlex

The wave of crises that began in 2008 reheated the debate on market deregulation as a tool to improve economic performance. This paper addresses the consequences of increased flexibility in goods and labor markets for the conduct of monetary policy in a monetary union. We model a two-country monetary union with endogenous product creation, labor market frictions, and price and wage rigidities. Regulation affects producer entry costs, employment protection, and unemployment benefits. We first characterize optimal monetary policy when regulation is high in both countries and show that the Ramsey allocation requires significant departures from price stability both in the long run and over the business cycle. Welfare gains from the Ramsey-optimal policy are sizable. Second, we show that the adjustment to market reform requires expansionary policy to reduce transition costs. Third, deregulation reduces static and dynamic inefficiencies, making price stability more desirable. International synchronization of reforms can eliminate policy tradeoffs generated by asymmetric deregulation.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.153
GPT teacher head0.401
Teacher spread0.248 · 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 designTheoretical or conceptual
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

Citations18
Published2013
Admission routes1
Has abstractyes

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