We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

Statistics for Spatial Data.

Impatti, adattamento e vulnerabilita Le cause e le responsabilita dei cambiamenti climatici sono state trattate sul numero di ottobre della rivista Cda. Approfondiamo l’argomento presentando il documento: “Cambiamenti climatici 2007: impatti, adattamento e vulnerabilita” votato ad aprile 2007 dal secondo gruppo di lavoro del Comitato Intergovernativo sui Cambiamenti Climatici (Intergovernmental Panel on Climate Change). Si tratta del secondo di tre documenti che compongono il quarto rapporto sui cambiamenti climatici.

/pdf/climate-change-2007-impacts-adaptation-and-vulnerability-31xc1cf4d3.pdf

Climate Change 2007: Impacts, Adaptation and Vulnerability.

Preface 1. Decision-Theoretic Foundations 1.1 Game Theory, Rationality, and Intelligence 1.2 Basic Concepts of Decision Theory 1.3 Axioms 1.4 The Expected-Utility Maximization Theorem 1.5 Equivalent Representations 1.6 Bayesian Conditional-Probability Systems 1.7 Limitations of the Bayesian Model 1.8 Domination 1.9 Proofs of the Domination Theorems Exercises 2. Basic Models 2.1 Games in Extensive Form 2.2 Strategic Form and the Normal Representation 2.3 Equivalence of Strategic-Form Games 2.4 Reduced Normal Representations 2.5 Elimination of Dominated Strategies 2.6 Multiagent Representations 2.7 Common Knowledge 2.8 Bayesian Games 2.9 Modeling Games with Incomplete Information Exercises 3. Equilibria of Strategic-Form Games 3.1 Domination and Ratonalizability 3.2 Nash Equilibrium 3.3 Computing Nash Equilibria 3.4 Significance of Nash Equilibria 3.5 The Focal-Point Effect 3.6 The Decision-Analytic Approach to Games 3.7 Evolution. Resistance. and Risk Dominance 3.8 Two-Person Zero-Sum Games 3.9 Bayesian Equilibria 3.10 Purification of Randomized Strategies in Equilibria 3.11 Auctions 3.12 Proof of Existence of Equilibrium 3.13 Infinite Strategy Sets Exercises 4. Sequential Equilibria of Extensive-Form Games 4.1 Mixed Strategies and Behavioral Strategies 4.2 Equilibria in Behavioral Strategies 4.3 Sequential Rationality at Information States with Positive Probability 4.4 Consistent Beliefs and Sequential Rationality at All Information States 4.5 Computing Sequential Equilibria 4.6 Subgame-Perfect Equilibria 4.7 Games with Perfect Information 4.8 Adding Chance Events with Small Probability 4.9 Forward Induction 4.10 Voting and Binary Agendas 4.11 Technical Proofs Exercises 5. Refinements of Equilibrium in Strategic Form 5.1 Introduction 5.2 Perfect Equilibria 5.3 Existence of Perfect and Sequential Equilibria 5.4 Proper Equilibria 5.5 Persistent Equilibria 5.6 Stable Sets 01 Equilibria 5.7 Generic Properties 5.8 Conclusions Exercises 6. Games with Communication 6.1 Contracts and Correlated Strategies 6.2 Correlated Equilibria 6.3 Bayesian Games with Communication 6.4 Bayesian Collective-Choice Problems and Bayesian Bargaining Problems 6.5 Trading Problems with Linear Utility 6.6 General Participation Constraints for Bayesian Games with Contracts 6.7 Sender-Receiver Games 6.8 Acceptable and Predominant Correlated Equilibria 6.9 Communication in Extensive-Form and Multistage Games Exercises Bibliographic Note 7. Repeated Games 7.1 The Repeated Prisoners Dilemma 7.2 A General Model of Repeated Garnet 7.3 Stationary Equilibria of Repeated Games with Complete State Information and Discounting 7.4 Repeated Games with Standard Information: Examples 7.5 General Feasibility Theorems for Standard Repeated Games 7.6 Finitely Repeated Games and the Role of Initial Doubt 7.7 Imperfect Observability of Moves 7.8 Repeated Wines in Large Decentralized Groups 7.9 Repeated Games with Incomplete Information 7.10 Continuous Time 7.11 Evolutionary Simulation of Repeated Games Exercises 8. Bargaining and Cooperation in Two-Person Games 8.1 Noncooperative Foundations of Cooperative Game Theory 8.2 Two-Person Bargaining Problems and the Nash Bargaining Solution 8.3 Interpersonal Comparisons of Weighted Utility 8.4 Transferable Utility 8.5 Rational Threats 8.6 Other Bargaining Solutions 8.7 An Alternating-Offer Bargaining Game 8.8 An Alternating-Offer Game with Incomplete Information 8.9 A Discrete Alternating-Offer Game 8.10 Renegotiation Exercises 9. Coalitions in Cooperative Games 9.1 Introduction to Coalitional Analysis 9.2 Characteristic Functions with Transferable Utility 9.3 The Core 9.4 The Shapkey Value 9.5 Values with Cooperation Structures 9.6 Other Solution Concepts 9.7 Colational Games with Nontransferable Utility 9.8 Cores without Transferable Utility 9.9 Values without Transferable Utility Exercises Bibliographic Note 10. Cooperation under Uncertainty 10.1 Introduction 10.2 Concepts of Efficiency 10.3 An Example 10.4 Ex Post Inefficiency and Subsequent Oilers 10.5 Computing Incentive-Efficient Mechanisms 10.6 Inscrutability and Durability 10.7 Mechanism Selection by an Informed Principal 10.8 Neutral Bargaining Solutions 10.9 Dynamic Matching Processes with Incomplete Information Exercises Bibliography Index

博弈论 : 矛盾冲突分析 = Game theory : analysis of conflict

The measurement of meaning

The assumption that people possess a repertoire of strategies to solve the inference problems they face has been raised repeatedly. However, a computational model specifying how people select strategies from their repertoire is still lacking. The proposed strategy selection learning (SSL) theory predicts a strategy selection process on the basis of reinforcement learning. The theory assumes that individuals develop subjective expectations for the strategies they have and select strategies proportional to their expectations, which are then updated on the basis of subsequent experience. The learning assumption was supported in 4 experimental studies. Participants substantially improved their inferences through feedback. In all 4 studies, the best-performing strategy from the participants' repertoires most accurately predicted the inferences after sufficient learning opportunities. When testing SSL against 3 models representing extensions of SSL and against an exemplar model assuming a memory-based inference process, the authors found that SSL predicted the inferences most accurately.

SSL: a theory of how people learn to select strategies.

At a time when suicides by microfinance borrowers in Andhra Pradesh are extensively discussed, this paper makes an initial tentative exploration into the impact of microfinance on suicides. Does MF reduce or increase suicides? Data limitations imply methodological limitations and provisional conclusions. The literature review, starting with Emile Durkheim, of research on suicides brings out the importance of psychological factors, divorce, and unemployment. We investigate time series data on suicides in India and find a just significantly positive correlation with male suicide rates and slightly negative correlations (not significant) with female suicide rates – but no relation between microfinance and total suicides. Cross-sectional data of Indian states indicates a significant positive correlation of total suicides with number of SHGs loans outstanding to Banks, higher than with microfinance loans provided by MFIs, which only shows a weak correlation. Going beyond India, a global country-wise analysis indicates that there is no correlation between microfinance and male or female suicides, yet regression analysis of 31 countries (weakly) indicates that microfinance penetration among the poor is a causal factor for increased suicides. Three related questions are discussed. First, do rapid growth and sustainability aims make MFis forget the human angle? Second, is social pressure necessary to make people repay? Third, if Microfinance increases suicides, is this impact to be differentiated between women and men possibly due to changing roles? Based on these, we tentatively propose policy recommendations.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1775705_code473010.pdf?abstractid=1715442&mirid=1&type=2

Does Microfinance Cause or Reduce Suicides? Policy Recommendations for Reducing Borrower Stress

SUMMARY

If a previously unpaid activity (e.g. donating blood) is paid, then we often observe that this activity is reduced. In this paper, it is hypothesized that the price offered is taken as a proxy for the “value” of the activity. Depending on how the actor valued the activity previously, crowding-out or crowding-in is implied, an effect with or without persistence after stopping the payment. The model can be adapted to a number of similar situations, including those where a high price signals high costs instead of high values. Our “naive” explanation is confronted with Benabou and Tirole's (2003) Principal-Agent model. A questionnaire study supports our basic hypothesis as well as some of the derived consequences, and contradicts Benabou and Tirole's model.

A Price Is a Signal: on Intrinsic Motivation, Crowding-out, and Crowding-in

a b s t r a c t Economic theory provides a number of often complementary suggestions for modeling social motives related to altruistic behavior. Questionnaire research on altruism (Rushton et al., 1981) can enable iden- tification of "facets" of altruism. But can we match these facets with pro-social behavior, stated reasons for such behavior, and theoretical concepts for modeling altruism? In this paper, we show that such matching is possible and plausible. Our questionnaire results suggest that overall altruism is related to charity giving, but not to blood-donation behavior. Only when investigating different facets of altruism separately can we link specific motives to specific behaviors.

Multiple facets of altruism and their influence on blood donation

In this paper, we introduce a new spatial model that incorporates heteroscedastic variance depending on neighbouring locations. The proposed process is considered as the spatial equivalent to the temporal autoregressive conditional heteroscedasticity (ARCH) model. We also show how the newly introduced spatial ARCH model can be used in spatiotemporal settings. In contrast to the temporal ARCH model, in which the distribution is known given the full information set for the prior periods, the distribution is not straightforward in the spatial and spatiotemporal setting. However, the model parameters can be estimated using the maximum-likelihood approach. Via Monte Carlo simulations, we demonstrate the performance of the estimator for a specific spatial weighting matrix. Moreover, we combine the known spatial autoregressive model with the spatial ARCH model assuming heteroscedastic errors. Eventually, the proposed autoregressive process is illustrated by an empirical example. Specifically, we model lung cancer mortality in 3108 U.S. counties and compare the newly introduced model with four benchmark approaches.

Philipp E. Otto

Papers

SSL: a theory of how people learn to select strategies.

Does Microfinance Cause or Reduce Suicides? Policy Recommendations for Reducing Borrower Stress

A Price Is a Signal: on Intrinsic Motivation, Crowding-out, and Crowding-in

Multiple facets of altruism and their influence on blood donation

Generalised spatial and spatiotemporal autoregressive conditional heteroscedasticity