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Record W3122883649 · doi:10.21034/wp.741

Small and Large Firms over the Business Cycle

2017· preprint· en· W3122883649 on OpenAlex
Nicolas Crouzet, Neil Mehrotra

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsKellogg's (Canada)
FundersColby CollegeInter-American Development Bank
KeywordsBusiness cycleRecessionMonetary economicsInvestment (military)DebtEconomicsRest (music)SkewnessBusinessEconometricsFinanceMacroeconomics

Abstract

fetched live from OpenAlex

Drawing from confidential firm-level data of US manufacturing firms, we provide new evidence on the cyclicality of small and large firms. We show that the cyclicality of sales and investment declines with firm size. The effect is primarily driven by differences between the top 0.5% of firms and the rest. Moreover, we show that, due to the skewness of sales and investment, the higher cyclicality of small firms has a negligible influence on the behavior of aggregates. We argue that the size asymmetry is unlikely to be driven by financial frictions given 1) the absence of statistically significant differences in the behavior of production inputs or debt in recessions, 2) the survival of the size effect after directly controlling for proxies of financial strength, and 3) the predictions of a simple financial frictions model, in which unconstrained (large) firms contract more in recessions than constrained (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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.727
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.055
GPT teacher head0.236
Teacher spread0.180 · 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

Quick stats

Citations28
Published2017
Admission routes1
Has abstractyes

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