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Geopolitical Risk and the Cost of Capital

2020· article· en· W3045599577 on OpenAlex
Richard W. Carney, Omrane Guedhami, Sadok El Ghoul, Helen Wang

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

VenueAcademy of Management Proceedings · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicState Capitalism and Financial Governance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeopoliticsCost of equityEmerging marketsCost of capitalEquity (law)Equity capital marketsBusinessEconomicsCapital (architecture)Capital marketPrivate equityMonetary economicsFinancial economicsFinanceMarket economyGeographyPolitical science

Abstract

fetched live from OpenAlex

One of the most fundamental determinants of firm competitiveness is the cost of capital. Existing research has focused on firm- and country-level factors, but largely overlooked a highly salient systemic factor – geopolitical risk. We posit that geopolitical events that elevate investor risk will prompt equity investors to shift their capital away from emerging markets to safer mature markets, raising the cost of equity capital for firms located in emerging economies. Based on a sample of 10,916 observations spanning 18 countries from 1990 to 2015, we find that higher geopolitical risk increases the cost of equity capital, on average. These results are robust to alternative measures for the cost of equity, to a variety of robustness tests, and to the inclusion of an extended range of control variables. We also find that this relationship is moderated by constraints on executive power, the strength of legal and regulatory institutions, a common law legal tradition, and cross-listing in the United States.

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 score0.814
Threshold uncertainty score0.406

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.213
Teacher spread0.198 · 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