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Record W2771887932 · doi:10.3386/w16941

Macroeconomic Conditions and Capital Raising

2011· preprint· en· W2771887932 on OpenAlexaff
Isil Erel, Brandon Julio, Woojin Kim, Michael S. Weisbach

Bibliographic record

VenueNational Bureau of Economic Research · 2011
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Policy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRaising (metalworking)EconomicsCapital (architecture)Monetary economicsMathematicsGeography

Abstract

fetched live from OpenAlex

Do macroeconomic conditions affect firms' abilities to raise capital? If so, how do they affect the manner in which the capital is raised? We address these questions using a large sample of publicly-traded debt issues, seasoned equity offers, bank loans and private placements of equity and debt. Our results suggest that a borrower's credit quality significantly affects its ability to raise capital during macroeconomic downturns. For noninvestment-grade borrowers, capital raising tends to be procyclical while for investment-grade borrowers, it is countercyclical. Moreover, proceeds raised by investment grade firms are more likely to be held in cash in recessions than in expansions. Poor market conditions also affect the structure of securities offered, shifting them towards shorter maturities and more security. Overall, our results suggest that macroeconomic conditions influence the securities that firms issue to raise capital, the way in which these securities are structured and indeed firms' ability to raise capital at all. This influence likely occurs primarily through the effect of macroeconomic conditions on the supply of capital.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.466
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.362
GPT teacher head0.464
Teacher spread0.102 · 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; both teacher heads agree on what is shown here.

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

Citations22
Published2011
Admission routes1
Has abstractyes

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