计量经济分析 = Econometric analysis

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

The power of feedback.

Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

Estimation and Inference in Econometrics

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

Quality monitoring in infrastructural Design-Build projects

Influence of course characteristics, student characteristics, and behavior in learning management systems on student performance: Neural Information Processing Systems (NIPS) Workshop on Machine Learning for Education 2016

Research on online reputation systems has shown that, in general, a higher reputation score increases trust in the seller in the sense that those with a higher reputation score get better prices for their goods (the “reputation premium”) and may be more likely to attract buyers (a higher probability of a sale). Likewise, negative feedback from buyers reduces trust in the seller. In this chapter, we analyze whether and how sellers who are confronted with negative feedback can rebuild trust by reacting appropriately.We also assess the monetary value of textual feedback, as compared to the value of the numerical reputation score. Data obtained in an online choice-based experiment allows us to analyze both the effects of buyers’ feedback text comments on the trust of a buyer in eBay sellers and the effect of a seller’s textual reaction on rebuilding trust. Our results show that textual feedback from buyers can indeed strongly affect the purchasing decisions of other buyers. Sellers can counteract the effect of negative comments, but only when the appropriate trust-rebuilding strategy is chosen in formulating the reply. The monetary value of adequate textual feedback is surprisingly high when compared to the value of the reputation score.

Online reputation in eBay auctions : Damaging and rebuilding trustworthiness through feedback comments from buyers and sellers

Humans increasingly interact with AI systems, and successful interactions rely on individuals trusting such systems (when appropriate). Considering that trust is fragile and often cannot be restored quickly, we focus on how trust develops over time in a human-AI-interaction scenario. In a 2x2 between-subject experiment, we test how model accuracy (high vs. low) and type of explanation (human-like vs. not) affect trust in AI over time. We study a complex decision-making task in which individuals estimate jail time for 20 criminal law cases with AI advice. Results show that trust is significantly higher for high-accuracy models. Also, behavioral trust does not decline, and subjective trust even increases significantly with high accuracy. Human-like explanations did not generally affect trust but boosted trust in high-accuracy models.

https://dl.acm.org/doi/pdf/10.1145/3581641.3584058

It Seems Smart, but It Acts Stupid: Development of Trust in AI Advice in a Repeated Legal Decision-Making Task

In 1998, Thomas Fararo and Patrick Doreian edited The Problem of Solidarity: Theories and Models as a companion volume to JMS. Their volume featured influential contributions to the development of formal theoretical models for the analysis of solidarity in groups of different sizes and in society as a whole. The present special issue of JMS complements this perspective by focusing on theory‐guided empirical studies of solidarity in dyadic relations. The fields of application in the present special issue are solidarity between partners in households (Bruderl and Kalter; Komter), in informal social relations between kin and friends (Komter), between business firms (Blumberg), and in abstract experimental settings (Snijders and Buskens).

Chris Snijders

Papers

Quality monitoring in infrastructural Design-Build projects

Influence of course characteristics, student characteristics, and behavior in learning management systems on student performance: Neural Information Processing Systems (NIPS) Workshop on Machine Learning for Education 2016

Online reputation in eBay auctions : Damaging and rebuilding trustworthiness through feedback comments from buyers and sellers

It Seems Smart, but It Acts Stupid: Development of Trust in AI Advice in a Repeated Legal Decision-Making Task

Solidarity in social relations: Theory‐guided empirical studies