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Record W3129242329 · doi:10.3386/w24353

Protectionism and the Business Cycle

2018· preprint· en· W3129242329 on OpenAlexaff
Alessandro Barattieri, Matteo Cacciatore, Fabio Ghironi

Bibliographic record

VenueNational Bureau of Economic Research · 2018
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsBank of CanadaHEC MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsProtectionismBusiness cycleBusinessInternational tradeEconomicsKeynesian economics

Abstract

fetched live from OpenAlex

We study the consequences of protectionism for macroeconomic fluctuations. First, using high-frequency trade policy data, we present fresh evidence on the dynamic effects of temporary trade barriers. Estimates from country-level and panel VARs show that protectionism acts as a supply shock, causing output to fall and inflation to rise in the short run. Moreover, protectionism has at best a small positive effect on the trade balance. Second, we build a small open economy model with firm heterogeneity, endogenous selection into trade, and nominal rigidity to study the channels through which protectionism affects aggregate fluctuations. The model successfully reproduces the VAR evidence and highlights the importance of aggregate investment dynamics and micro-level reallocations for the contractionary effects of tariffs. We then use the model to study scenarios where temporary trade barriers have been advocated as potentially beneficial, including recessions with binding constraints on monetary policy easing or in the presence of a fixed exchange rate. Our main conclusion is that, in all the scenarios we consider, protectionism is not an effective tool for macroeconomic stimulus.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.610
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.412
GPT teacher head0.436
Teacher spread0.024 · 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

Citations45
Published2018
Admission routes1
Has abstractyes

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