MétaCan
Menu
Back to cohort

Monetary Policy and Corporate Investment: Evidence from Chinese Micro Data

2012· article· en· W2105104655 on OpenAlexaboutno aff
Ying Huang, Frank M. Song, Yizhong Wang

Bibliographic record

VenueChina & World Economy · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsMonetary policyMonetary economicsQuarter (Canadian coin)Market liquidityEconomicsAsset (computer security)Investment (military)LiabilitySample (material)BusinessFinance

Abstract

fetched live from OpenAlex

Abstract This paper investigates how a firm's characteristics restrict the influence of monetary policy changes on its investment behavior. Focusing on China's listed companies for a sample period from the first quarter of 2002 to the first quarter of 2011, we find that quantity‐oriented and price‐based monetary policies have heterogeneous impacts on corporate investment behavior, but the influence of monetary policies is constrained by the liquidity, inventory, size and asset–liability ratio of a firm. Firms with higher liquidity, lower inventory level and lower asset–liability ratios are less sensitive to the impact from two kinds of monetary policies. The larger the size of the firm, the less it is subject to influence from quantity‐oriented monetary policy; it responds more to price‐based monetary policy. The policy implication is that the monetary authorities should pay attention to the importance of policy‐making based on the monetary demand of microeconomic entities.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.237
Teacher spread0.192 · 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 designObservational
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

Citations29
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueChina & World EconomySame topicCorporate Finance and GovernanceFrench-language works237,207