Artificial Economics - The Generative Method in Economics

Acknowledgements

Preface

Contents

List of Contributors

Part I Macroeconomics

1 A Potential Disadvantage of a Low Interest Rate Policy: the Instability of Banks Liquidity

1.1 Introduction

1.2 The Bank

1.2.1 Profitability and Liquidity

1.2.2 An Idealization of the Bank Activity

1.2.3 The Lending Activity

1.3 Simulations

1.4 Comparative Static, Dynamics and Credit Rationing

1.5 Conclusions

References

2 Keynes in the Computer Laboratory. An Agent-Based Model with MEC, MPC, LP

2.1 Introduction

2.2 The Model

2.2.1 Methodological Premises

2.2.2 Modelling the Market Sentiment

2.2.3 The Marginal Efficiency of Capital

2.2.4 The Marginal Propensity to Consume

2.2.5 The Liquidity Preference

2.2.6 Aggregate Supply

2.3 Simulations Results

2.3.1 GDP Series

2.3.2 GDP and its Components

2.4 Conclusions

References

3 Pride and Prejudice on a Centralized Academic Labor Market

3.1 Introduction

3.2 Related Work

3.3 The French Academic Labor Market

3.3.1 The Hiring Process

3.3.2 Empirical Evidence

3.4 Academic Labor Market Modelling

3.4.1 Agent Preferences

3.4.2 Multi-Agent Based Model

3.4.2.1 Candidates

3.4.2.2 Universities

3.4.2.3 Interaction Rules

3.5 Simulation Results

3.5.1 Methodology and Experimental Settings

3.5.2 No Learning Setting

3.5.3 Learning Universities Setting

3.6 Conclusion

References

Part II Industrial Organization

4 U. S. Defense Market Concentration: An Analysis of the Period 1996–2006

4.1 Introduction

4.2 Analysis of U. S. Defense Market Structure 1996–2006

4.2.1 Data Sources

4.2.2 Market Description & Unique Factors

4.2.3 Results and Findings

4.3 Two Simple Computational Models

4.4 Conclusion and Further Research

References

5 Operator's Bidding Strategies in the Liberalized Italian Power Market

5.1 Introduction

5.2 ACE Model

5.2.1 Market Model

5.2.2 Grid Model

5.2.3 Agent Model

5.2.4 Learning Model

5.3 Results

5.4 Conclusions

References

6 Selection Processes in a Monopolistic Competition Market

6.1 Motivation

6.2 A Formal Model of a Differentiated Industry

6.2.1 Consumer Behavior

6.2.2 Evolutionary Firm Behavior

6.3 Selection and Monopolistic Competition

6.3.1 Homogeneous Product Competition

6.3.2 Differentiated Product Competition

6.3.3 Heterogeneity and Other Model Parameters

6.4 Conclusions

References

Part III Market Dynamics and Auctions

7 Symmetric Equilibria in Double Auctionswith Markdown Buyers and Markup Sellers

7.1 Introduction

7.2 The Model

7.2.1 The Environment

7.3 Call Market

7.3.1 General Markup and Markdown Coefficients

7.3.2 Ex Ante Equilibria

7.4 Bilateral Trading

7.5 Continuous Double Auction

7.6 Conclusions

References

8 Multi-Unit Auction Analysis by Means of Agent-Based Computational Economics

8.1 Introduction

8.2 The Ausubel Auction

8.3 The Agent-Based Model

8.4 The Experimental Results

8.4.1 Decreasing Marginal Values

8.4.2 Increasing Marginal Values

8.5 Conclusions

References

9 Social Learning and Pricing Obfuscation

9.1 Introduction

9.2 Model Architecture

9.2.1 Obfuscation Game and Dimensions of Intervention

9.2.2 Recursive Companies

9.2.3 Adaptive Customers

9.3 Experiments

9.3.1 Baseline Behaviors

9.3.2 Efficiency of Market Intervention

9.4 Conclusions

References

Part IV Finance

10 Mutual Funds Flows and the ``Sheriff of Nottingham'' Effect

10.1 Introduction

10.2 A Simple Example and One Analytical Result

10.3 A Computational Model

10.3.1 Results

10.4 Conclusion

References

11 Foundations for a Framework for Multiagent-Based Simulation of Macrohistorical Episodes in Financial Markets

11.1 Introduction

11.2 What is Wrong with MABS?

11.2.1 Barriers to MABS for Macrohistorial Researchin Finance

11.3 Proposal for a MABS Framework

11.3.1 A Bird's Eye View of the Framework

11.3.2 The Modelling Process

11.4 Conclusions

References

12 Explaining Equity Excess Return by Means of an Agent-Based Financial Market

12.1 Introduction

12.2 The Model

12.2.1 Firms

12.2.2 Households

12.2.3 The Banking Sector

12.2.4 The Government

12.3 Simulation Results

12.4 Conclusions

References

Part V Financial Markets

13 Bubble and Crash in the Artificial Financial Market

13.1 Introduction

13.2 An Artificial Financial Market

13.2.1 Market Settings

13.2.2 Trading Agents

13.2.2.1 Expectation formation and time discounting

13.2.2.2 The Algorithm for Buying and Selling Decision-Making

13.2.3 Transaction System

13.3 Results

13.3.1 Simulation Results

13.3.2 Definition of Price Bubble

13.3.3 Sensibility Analysis

13.4 Conclusion

References

14 Computation of the Ex-Post Optimal Strategy for the Trading of a Single Financial Asset

14.1 Introduction

14.2 Elements of the Game and Formalizations

14.2.1 Initial Simplification

14.2.2 A Linear Programming Method For the Identification of S*

14.2.3 Embedding the Identification of S* in aGraph Structure

14.2.4 The S*-determination Algorithm

14.3 Numerical Illustrations and Conclusive Remarks

References

15 A Generative Approach on the Relationship between Trading Volume, Prices, Returns and Volatility of Financial Assets

15.1 Introduction

15.2 Historical Precedents and Motivation

15.3 Methodology

15.3.1 The ISS-ASM Model

15.3.2 Dataset.

15.3.3 Cross-Correlations and Causal Relation

15.4 Conclusions - Results

15.4.1 Price-Volume Relationship

15.4.2 Return-Volume Relationship

15.4.3 Volatility-Volume Relationship

15.4.4 Causal Relationship

15.5 Summary

References

Part VI Information and Learning

16 Comparing Laboratory Experiments and Agent-Based Simulations: The Value of Information and Market Efficiency in a Market with Asymmetric Information

16.1 Introduction

16.2 Market Model

16.3 Experimental Implementation and Simulation

16.4 Results

16.4.1 Distribution of Returns

16.4.2 Market Efficiency

16.5 Conclusion

References

17 Asset Return Dynamics under Alternative Learning Schemes

17.1 Introduction

17.2 The Model

17.2.1 The Market Setting

17.2.2 The Portfolio Model

17.2.3 The Learning Process

17.2.3.1 The IID Setting

17.2.3.2 The HMM Setting

17.2.4 Statistical Measures of Population Heterogeneity

17.3 Calibration and Results

17.3.1 Simulation Parameters

17.3.2 Comparison between the Learning Models

References

18 An Attempt to Integrate Path-Dependencyin a Learning Model

18.1 Introduction

18.2 Study of CPR Based on Information Issue

18.2.1 Lack of Information and Over-Exploitation

18.2.2 Dealing with Scarce Information in ABM

18.3 The Model

18.3.1 Main Assumptions and General Framework

18.3.2 Resource Dynamics and Probabilistic Choice of Effort

18.4 Simulations

18.5 Results

18.6 Discussions

18.7 Conclusion

References

Part VII Methodological Issues

19 A Model-to-Model Analysis of the Repeated Prisoners' Dilemma: Genetic Algorithms vs. Evolutionary Dynamics

19.1 Introduction

19.2 The Analytical Model

19.2.1 The Replicator Dynamics Analysis

19.3 The Computational Model

19.4 Conclusions

References

20 Impact of Tag Recognition in Economic Decisions

20.1 Introduction

20.2 Cognitive Foundations

20.3 The Model

20.4 The Model with One Agent Type

20.4.1 Replication

20.4.2 Introduction of a New Decision Rule

20.4.3 Introduction of a Variable Payoff Matrix

20.5 The Model with Two Agent Types (the ``Tag'' Model)

20.6 Conclusions

References

21 Simulation of Effects of Culture on Trade Partner Selection

21.1 Introduction

21.2 Hofstede's Dimensions and Trade Partner Selection

21.3 Representation in Agents

21.4 Simulation Results

21.5 Conclusion

References