Fabrizio Cafaggi, Antonio Nicita, Ugo Pagano

Legal Orderings and Economic Institutions (eBook, PDF)

• Format: PDF

Produktbeschreibung

This book addresses the lively interaction between the disciplines of law and economics. The traditional boundaries of these two disciplines have somehow inhibited a full understanding of the functioning of and the evolution of economic and legal systems. It has often been the case that these boundaries have had to be reshaped, and sometimes abolis

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 368
• Erscheinungstermin: 3. Mai 2007
• Englisch
• ISBN-13: 9781134331000
• Artikelnr.: 42981549

Autorenporträt

Fabrizio Cafaggi, Antonio Nicita, Ugo Pagano

Inhaltsangabe

Introduction 1. Law, Economics and Institutional Complexity: An
Introduction Part 1: Complexity in Law and Economics 2. Economics in the
Future of the Law 3. Law and Economics in Historic Perspective 4. Legal
Positions and Institutional Complementarities 5. Legislate Today or Wait
Until Tomorrow?: An Investment Approach to Lawmaking Part 2: Private
Orderings, Efficiency and the Role of the State 6. The Enforcement of
Contracts and the Role of the State 7. Minimal Liberty and the `Coasean
Liberal¿: Setting Boundaries and Complementarities between the State and
the Market 8. Private Orderings and Intellectual Property: What is it the
Best Incentive System? 9. Fairness and Welfare: are they Really Competing
Values? Part 3: Contractual Incompleteness and the Nature of Endogenous
Enforcement 10. Costly Contingent Contracts: A Failure of the Coase Theorem
11. Game-Theoretic Solutions to Endogenous Contractual Incompleteness
12.Customary Contracts 13.Group Relations and Industrial Districts Part 4:
Governance Models and Corporate Ethics 14. What is a Corporation?: The
Corporate Personality Controversy and Comparative Corporate Governance 15.
Fiduciary Duties, Models of Firms and Organizational Theories in the
Context of Relational Interdependencies 16. Incomplete Contracts and
Corporate Ethics: A Game Theoretical Model under Fuzzy Information