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Record W1579116926

Commentary on The real effects of U.S. banking deregulation

2003· article· en· W1579116926 on OpenAlexvenueno aff
David C. Wheelock

Bibliographic record

VenueCanadian parliamentary review · 2003
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsDeregulationEconomicsCompetition (biology)Monetary economicsMarket economy
DOInot available

Abstract

fetched live from OpenAlex

JULY/AUGUST 2003 129 P hil Strahan and various coauthors have written a series of significant papers on the impact of interstate banking and intrastate branching deregulation. His present paper summarizes and extends much of that research.1 I suspect that most economists would agree that draconian restrictions on branch banking or on the ability of bank holding companies to cross state lines make no sense. Geographic restrictions historically left the U.S. banking system vulnerable to regional economic shocks, limited banks’ ability to exploit economies of scale and scope, sheltered weak banks from competition, and imposed costs on the consumers of banking services. Strahan’s work attempts to quantify the impact of the removal of such restrictions on economic growth and entrepreneurial activity at the state level. His estimates are striking—for example, the removal of restrictions on branching appears to have increased the growth rate of state per capita incomes by about one-third, and the effect is persistent. He also estimates a marked increase in the rate of new business incorporations following deregulation, as well as a large decline in the volatility of state-level business cycles after interstate banking was permitted. Economists and economic historians have long debated the effects of a country’s financial system on its economic development. This commentary relates Strahan (2003) to other studies on the effects of geographic restrictions on banks, with a focus on historical comparisons. In addition, I raise some specific questions about Strahan’s empirical analysis in the traditional discussant’s role as devil’s advocate.

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)0.006
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.068
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0060.005
Scholarly communication0.0060.006
Open science0.0050.002
Research integrity0.0440.033
Insufficient payload (model declined to judge)0.0080.004

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 head0.022
GPT teacher head0.225
Teacher spread0.203 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2003
Admission routes1
Has abstractyes

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