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Record W4405996661 · doi:10.1017/s0212610924000168

Hedges of the Second Republic: firms, equity investors and political uncertainty in a nascent democracy, 1930–1936

2025· article· en· W4405996661 on OpenAlexfundno aff
Stefano Battilossi, Stefan Houpt

Bibliographic record

VenueRevista de Historia Económica / Journal of Iberian and Latin American Economic History · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPolitical Influence and Corporate Strategies
Canadian institutionsnot available
FundersUniversidad Carlos III de MadridQueen's UniversityQueen's University Belfast
KeywordsDemocracyEquity (law)PoliticsEconomicsFinancial economicsMarket economyPolitical scienceBusinessLaw

Abstract

fetched live from OpenAlex

Abstract We study how Spanish equity investors assessed firms’ exposure to political risk during the regime change of the 1930s. We show that shifts in political uncertainty regularly predicted a general deterioration of future investment opportunities in the stock market. However, we also find that firms differed in their sensitivity to uncertainty, reflecting important differences in their perceived exposures to political risk. The negative impact of uncertainty was significantly milder for firms with political connections to republican parties. The price of some stocks increased in periods of heightened uncertainty, thus allowing investors to hedge against reinvestment risk. In the case of firms that became targets of hostile political actions, we observe that investors frequently adjusted their assessment of individual stocks to changes in firm-specific political circumstances. Over the whole period of the Second Republic, investors’ systematic preference for safer equity hedges led to a continuous decline in the price of stocks perceived as more exposed to political risk.

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)0.003
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 score0.018
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.018
GPT teacher head0.245
Teacher spread0.227 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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Same venueRevista de Historia Económica / Journal of Iberian and Latin American Economic HistorySame topicPolitical Influence and Corporate StrategiesFrench-language works237,207