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Research Article
Open Access

Data Science and Political Economy: Application to Financial Regulatory Structure

Sharyn O’Halloran, Sameer Maskey, Geraldine McAllister, David K. Park, Kaiping Chen
RSF: The Russell Sage Foundation Journal of the Social Sciences November 2016, 2 (7) 87-109; DOI: https://doi.org/10.7758/RSF.2016.2.7.06
Sharyn O’Halloran
aGeorge Blumenthal Professor of Political Economy and professor of international and public affairs at Columbia University
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Sameer Maskey
bAssistant professor at Columbia University
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Geraldine McAllister
cSenate director at Columbia University
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David K. Park
dDean of Strategic Initiatives at Columbia University
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Kaiping Chen
eDoctoral student at Stanford University
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  • Article
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RSF: The Russell Sage Foundation Journal of the Social Sciences: 2 (7)
RSF: The Russell Sage Foundation Journal of the Social Sciences
Vol. 2, Issue 7
1 Nov 2016
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Data Science and Political Economy: Application to Financial Regulatory Structure
Sharyn O’Halloran, Sameer Maskey, Geraldine McAllister, David K. Park, Kaiping Chen
RSF: The Russell Sage Foundation Journal of the Social Sciences Nov 2016, 2 (7) 87-109; DOI: 10.7758/RSF.2016.2.7.06

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Data Science and Political Economy: Application to Financial Regulatory Structure
Sharyn O’Halloran, Sameer Maskey, Geraldine McAllister, David K. Park, Kaiping Chen
RSF: The Russell Sage Foundation Journal of the Social Sciences Nov 2016, 2 (7) 87-109; DOI: 10.7758/RSF.2016.2.7.06
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  • Article
    • Abstract
    • DELEGATION, DISCRETION, AND FINANCIAL REGULATORY DESIGN
    • FINANCIAL REGULATORY STRUCTURE: AN OBSERVATIONAL STUDY
    • NEW MACHINE LEARNING TECHNIQUES TO ANALYZE FINANCIAL REGULATION DATA
    • CONCLUSION
    • FOOTNOTES
    • REFERENCES
  • Figures & Data
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Keywords

  • big data
  • natural language processing
  • machine learning
  • political economics
  • financial regulation
  • banking and financial services sector

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