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Record W2388922665 · doi:10.1111/caje.12361

Learning, prices and firm dynamics

2018· article· en· W2388922665 on OpenAlexvenueno aff
Paulo Bastos, Daniel A. Dias, Olga A. Timoshenko

Bibliographic record

VenueCanadian Journal of Economics/Revue canadienne d économique · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsCounterfactual thinkingEconomicsRevenueVolatility (finance)Quality (philosophy)WelfareDestinationsMicroeconomicsMonetary economicsEconometricsMarket economy

Abstract

fetched live from OpenAlex

Abstract We document new facts about the evolution of firm performance and prices in international markets and propose a theory of firm dynamics emphasizing the interaction between learning about demand and quality choice to explain the observed patterns. Using data from the Portuguese manufacturing sector, we find that: (1) firms with longer spells of activity in export destinations tend to ship larger quantities at lower prices; (2) older exporters tend to use more expensive inputs; (3) the volatility of output and input prices tends to decline with export experience; and (4) input prices and quantities tend to increase with revenue growth within firms. We develop a model of endogenous input and output quality choices in a learning environment that is able to account for these patterns. Counterfactual simulations reveal that minimum quality standards on traded goods reduce welfare by lowering entry in export markets and reallocating resources from old and large towards young and small firms.

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)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.160
GPT teacher head0.171
Teacher spread0.012 · 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 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

Citations21
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Economics/Revue canadienne d économiqueSame topicGlobal trade and economicsFrench-language works237,207