Job Market Signaling and Screening: an Experimental Comparison
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Use of Mixed Signaling Strategies in International Crisis Negotiations
USE OF MIXED SIGNALING STRATEGIES IN INTERNATIONAL CRISIS NEGOTIATIONS DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Unislawa M. Wszolek, B.A., M.A. ***** The Ohio State University 2007 Dissertation Committee: Approved by Brian Pollins, Adviser Daniel Verdier Adviser Randall Schweller Graduate Program in Political Science ABSTRACT The assertion that clear signaling prevents unnecessary war drives much of the recent developments in research on international crises signaling, so much so that this work has aimed at identifying types of clear signals. But if clear signals are the only mechanism for preventing war, as the signaling literature claims, an important puzzle remains — why are signals that combine both carrot and stick components sent and why are signals that are partial or ambiguous sent. While these signals would seemingly work at cross-purposes undermining the signaler’s goals, actually, we observe them frequently in crises that not only end short of war but also that realize the signaler’s goals. Through a game theoretic model, this dissertation theorizes that because these alternatives to clear signals increase the attractiveness, and therefore the likelihood, of compliance they are a more cost-effective way to show resolve and avoid unnecessary conflict than clear signals. In addition to building a game theoretic model, an additional contribution of this thesis is to develop a method for observing mixed versus clear signaling strategies and use this method to test the linkage between signaling and crisis outcomes. Results of statistical analyses support theoretical expectations: clear signaling strategies might not always be the most effective way to secure peace, while mixed signaling strategies can be an effective deterrent. -
Chapter 12 Game Theory and Ppp*
CHAPTER 12 GAME THEORY AND PPP* By S. Ping Ho Associate Professor, Dept. of Civil and Environmental Engineering, National Taiwan University. Email: [email protected] †Shimizu Visiting Associate Professor, Dept. of Civil and Environmental Engineering, Stanford University. 1. INTRODUCTION Game theory can be defined as “the study of mathematical models of conflict and cooperation between intelligent rational decision-makers” (Myerson, 1991). It can also be called “conflict analysis” or “interactive decision theory,” which can more accurately express the essence of the theory. Still, game theory is the most popular and accepted name. In PPPs, conflicts and strategic interactions between promoters and governments are very common and play a crucial role in the performance of PPP projects. Many difficult issues such as opportunisms, negotiations, competitive biddings, and partnerships have been challenging the wisdom of the PPP participants. Therefore, game theory is very appealing as an analytical framework to study the interaction and dynamics between the PPP participants and to suggest proper strategies for both governments and promoters. Game theory modelling method will be used throughout this chapter to analyze and build theories on some of the above challenging issues in PPPs. Through the game theory modelling, a specific problem of concern is abstracted to a level that can be analyzed without losing the critical components of the problem. Moreover, new insights or theories for the concerned problem are developed when the game models are solved. Whereas game theory modelling method has been broadly applied to study problems in economics and other disciplines, only until recently, this method has been * First Draft, To appear in The Routledge Companion to Public-Private Partnerships, Edited by Professor Piet de Vries and Mr. -
Syllabus Game Thoery
SYLLABUS GAME THEORY, PHD The lecture will take place from 11:00 am to 2:30 pm every course day. Here is a list with the lecture dates and rooms : 6.6. 11:00-14:30 SR 9 7.6. 11:00-14:30 SR 4 8.6. 11:00-14:30 SR 4 9.6. 11:00-14:30 SR 4 10.6. 11:00-14:30 SR 4 Midterm: Mo, 20.6. 10:00-12:00 Room TBA 20.6. 12:30-14:30 SR 9 21.6. 11:00-14:30 SR 4 22.6. 11:00-14:30 SR 4 23.6. 11:00-14:30 SR 4 24.6. 11:00-14:30 SR 4 Final: Fr, 8.7. 10:00-12:00 HS 2 Below you find an outline of the contents of the course. The slides to lectures 1-16 are attached. Our plan is to cover the contents of lectures 1 to 11 in week 1, and the contents of lectures 12 to 16 in week 2. If there is time left, there will be additional material (Lecture 17) on principal-agent theory. The lectures comprise four solution concepts, which is all what you need for applied research. *Nash Equilibrium (for static games with complete information) *Subgame Perfect Nash Equilibrium (for dynamic games with complete information) *Bayesian Nash Equilibrium (for static games with incomplete information) *Perfect Bayesian Nash Equilibrium (for dynamic games with incomplete information) Those who have some prior knowledge of game theory might wonder why Sequential Equilibrium (SE) is missing in this list. -
Algorithmic Game Theory Lecture Notes
Algorithmic Game Theory Lecture Notes Exarchal and lemony Pascal Americanized: which Clemmie is somnolent enough? Shelton is close-knit: she oversleeps agnatically and fog her inrushes. Christ is boustrophedon and unedges vernally while uxorious Raymond impanelled and mince. Up to now, therefore have considered only extensive form approach where agents move sequentially. See my last Twenty Lectures on Algorithmic Game Theory published by. Continuing the discussion of the weary of a head item, or revenue equivalence theorem, the revelation principle, Myersons optimal revenue auction. EECS 395495 Algorithmic Mechanism Design. Screening game theory lecture notes games, algorithmic game theory! CSC304 Algorithmic Game Theory and Mechanism Design Home must Fall. And what it means in play world game rationally form games with simultaneous and the syllabus lecture. Be views as pdf game theory lecture. Book boss course stupid is Algorithmic Game Theory which is freely available online. And recently mailed them onto me correcting many errors as pdf files my son Twenty on! Course excellent for Algorithmic Game Theory Monsoon 2015. Below is a loft of related courses at other schools. Link to Stanford professor Tim Roughgarden's video lectures on algorithmic game theory AGT 2013 Iteration. It includes supplementary notes, algorithms is expected to prepare the lectures game theory. Basic Game Theory Chapter 1 Lecture notes from Stanford. It is a project instead, you sure you must save my great thanks go to ask questions on. Resources by type ppt This mean is an introduction game! Game Theory Net Many Resources on Game Theory Lecture notes pointers to literature. Make an algorithmic theory lecture notes ppt of algorithms, formal microeconomic papers and. -
Uncertainty and Information
8 ■ Uncertainty and Information N CHAPTER 2, we mentioned different ways in which uncertainty can arise in a game (external and strategic) and ways in which players can have lim- ited information about aspects of the game (imperfect and incomplete, symmetric and asymmetric). We have already encountered and analyzed Isome of these. Most notably, in simultaneous-move games, each player does not know the actions the other is taking; this is strategic uncertainty. In Chapter 6, we saw that strategic uncertainty gives rise to asymmetric and imperfect infor- mation, because the different actions taken by one player must be lumped into one infor mation set for the other player. In Chapters 4 and 7, we saw how such strategic uncertainty is handled by having each player formulate beliefs about the other’s action (including beliefs about the probabilities with which differ- ent actions may be taken when mixed strategies are played) and by applying the concept of Nash equilibrium, in which such beliefs are confirmed. In this chap- ter we focus on some further ways in which uncertainty and informational limi- tations arise in games. We begin by examining various strategies that individuals and societies can use for coping with the imperfect information generated by external uncertainty or risk. Recall that external uncertainty is about matters outside any player’s con- trol but affecting the payoffs of the game; weather is a simple example. Here we show the basic ideas behind diversification, or spreading, of risk by an individual player and pooling of risk by multiple players. These strategies can benefit every- one, although the division of total gains among the participants can be unequal; therefore, these situations contain a mixture of common interest and conflict. -
Signaling Games
Signaling Games Farhad Ghassemi Abstract - We give an overview of signaling games and their relevant so- lution concept, perfect Bayesian equilibrium. We introduce an example of signaling games and analyze it. 1 Introduction In the general framework of incomplete information or Bayesian games, it is usually assumed that information is equally distributed among players; i.e. there exists a commonly known probability distribution of the unknown parameter(s) of the game. However, very often in the real life, we are confronted with games in which players have asymmetric information about the unknown parameter of the game; i.e. they have different probability distributions of the unknown parameter. As an example, consider a game in which the unknown parameter of the game can be measured by the players but with different degrees of accuracy. Those players that have access to more accurate methods of measurement are definitely in an advantageous position. In extreme cases of asymmetric information games, one player has complete information about the unknown parameter of the game while others only know it by a probability distribution. In these games, the information is completely one-sided. The informed player, for instance, may be the only player in the game who can have different types and while he knows his type, other do not (e.g. a prospect job applicant knows if he has high or low skills for a job but the employer does not) or the informed player may know something about the state of the world that others do not (e.g. a car dealer knows the quality of the cars he sells but buyers do not). -
Perfect Conditional E-Equilibria of Multi-Stage Games with Infinite Sets
Perfect Conditional -Equilibria of Multi-Stage Games with Infinite Sets of Signals and Actions∗ Roger B. Myerson∗ and Philip J. Reny∗∗ *Department of Economics and Harris School of Public Policy **Department of Economics University of Chicago Abstract Abstract: We extend Kreps and Wilson’s concept of sequential equilibrium to games with infinite sets of signals and actions. A strategy profile is a conditional -equilibrium if, for any of a player’s positive probability signal events, his conditional expected util- ity is within of the best that he can achieve by deviating. With topologies on action sets, a conditional -equilibrium is full if strategies give every open set of actions pos- itive probability. Such full conditional -equilibria need not be subgame perfect, so we consider a non-topological approach. Perfect conditional -equilibria are defined by testing conditional -rationality along nets of small perturbations of the players’ strate- gies and of nature’s probability function that, for any action and for almost any state, make this action and state eventually (in the net) always have positive probability. Every perfect conditional -equilibrium is a subgame perfect -equilibrium, and, in fi- nite games, limits of perfect conditional -equilibria as 0 are sequential equilibrium strategy profiles. But limit strategies need not exist in→ infinite games so we consider instead the limit distributions over outcomes. We call such outcome distributions per- fect conditional equilibrium distributions and establish their existence for a large class of regular projective games. Nature’s perturbations can produce equilibria that seem unintuitive and so we augment the game with a net of permissible perturbations. -
Signaling Games Y ECON 201B - Game Theory
Notes on Signaling Games y ECON 201B - Game Theory Guillermo Ordoñez UCLA February 23, 2007 1 Understanding a Signaling Game Consider the following game. This is a typical signaling game that follows the classical "beer and quiche" structure. In these notes I will discuss the elements of this particular type of games, equilibrium concepts to use and how to solve for pooling, separating, hybrid and completely mixed sequential equilibria. 1.1 Elements of the game The game starts with a "decision" by Nature, which determines whether player 1 is of type I or II with a probability p = Pr(I) (in this example we assume 1 p = 2 ). Player 1, after learning his type, must decide whether to play L or R. Since player 1 knows his type, the action will be decided conditioning on it. 0 These notes were prepared as a back up material for TA session. If you have any questions or comments,y or notice any errors or typos, please drop me a line at [email protected] 1 After player 1 moves, player 2 is able to see the action taken by player 1 but not the type of player 1. Hence, conditional on the action observed she has to decide whether to play U or D. Hence, it’spossible to de…ne strategies for each player (i) as For player 1, a mapping from types to actions 1 : I aL + (1 a)R and II bL + (1 b)R ! ! For player 2, a mapping from player 1’sactions to her own actions 2 : L xU + (1 x)D and R yU + (1 y)D ! ! In this game there is no subgame since we cannot …nd any single node where a game completely separated from the rest of the tree starts. -
Perfect Bidder Collusion Through Bribe and Request*
Perfect bidder collusion through bribe and request* Jingfeng Lu† Zongwei Lu ‡ Christian Riis§ May 31, 2021 Abstract We study collusion in a second-price auction with two bidders in a dy- namic environment. One bidder can make a take-it-or-leave-it collusion pro- posal, which consists of both an offer and a request of bribes, to the opponent. We show that there always exists a robust equilibrium in which the collusion success probability is one. In the equilibrium, for each type of initiator the expected payoff is generally higher than the counterpart in any robust equi- libria of the single-option model (Eso¨ and Schummer(2004)) and any other separating equilibria in our model. Keywords: second-price auction, collusion, multidimensional signaling, bribe JEL codes: D44, D82 arXiv:1912.03607v2 [econ.TH] 28 May 2021 *We are grateful to the editors in charge and an anonymous reviewer for their insightful comments and suggestions, which greatly improved the quality of our paper. Any remaining errors are our own. †Department of Economics, National University of Singapore. Email: [email protected]. ‡School of Economics, Shandong University. Email: [email protected]. §Department of Economics, BI Norwegian Business School. Email: [email protected]. 1 1 Introduction Under standard assumptions, auctions are a simple yet effective economic insti- tution that allows the owner of a scarce resource to extract economic rents from buyers. Collusion among bidders, on the other hand, can ruin the rents and hence should be one of the main issues that are always kept in the minds of auction de- signers with a revenue-maximizing objective. -
Selectionfree Predictions in Global Games with Endogenous
Theoretical Economics 8 (2013), 883–938 1555-7561/20130883 Selection-free predictions in global games with endogenous information and multiple equilibria George-Marios Angeletos Department of Economics, Massachusetts Institute of Technology, and Department of Economics, University of Zurich Alessandro Pavan Department of Economics, Northwestern University Global games with endogenous information often exhibit multiple equilibria. In this paper, we show how one can nevertheless identify useful predictions that are robust across all equilibria and that cannot be delivered in the common- knowledge counterparts of these games. Our analysis is conducted within a flexi- ble family of games of regime change, which have been used to model, inter alia, speculative currency attacks, debt crises, and political change. The endogeneity of information originates in the signaling role of policy choices. A novel procedure of iterated elimination of nonequilibrium strategies is used to deliver probabilis- tic predictions that an outside observer—an econometrician—can form under ar- bitrary equilibrium selections. The sharpness of these predictions improves as the noise gets smaller, but disappears in the complete-information version of the model. Keywords. Global games, multiple equilibria, endogenous information, robust predictions. JEL classification. C7, D8, E5, E6, F3. 1. Introduction In the last 15 years, the global-games methodology has been used to study a variety of socio-economic phenomena, including currency attacks, bank runs, debt crises, polit- ical change, and party leadership.1 Most of the appeal of this methodology for applied George-Marios Angeletos: [email protected] Alessandro Pavan: [email protected] This paper grew out of prior joint work with Christian Hellwig and would not have been written without our earlier collaboration; we are grateful for his contribution during the early stages of the project. -
Game Theory for Linguists
Overview Review: Session 1-3 Rationalizability, Beliefs & Best Response Signaling Games Game Theory for Linguists Fritz Hamm, Roland Mühlenbernd 9. Mai 2016 Game Theory for Linguists Overview Review: Session 1-3 Rationalizability, Beliefs & Best Response Signaling Games Overview Overview 1. Review: Session 1-3 2. Rationalizability, Beliefs & Best Response 3. Signaling Games Game Theory for Linguists Overview Review: Session 1-3 Rationalizability, Beliefs & Best Response Signaling Games Conclusions Conclusion of Sessions 1-3 I a game describes a situation of multiple players I that can make decisions (choose actions) I that have preferences over ‘interdependent’ outcomes (action profiles) I preferences are defined by a utility function I games can be defined by abstracting from concrete utility values, but describing it with a general utility function (c.f. synergistic relationship, contribution to public good) I a solution concept describes a process that leads agents to a particular action I a Nash equilibrium defines an action profile where no agent has a need to change the current action I Nash equilibria can be determined by Best Response functions, or by ‘iterated elimination’ of Dominated Actions Game Theory for Linguists Overview Review: Session 1-3 Rationalizability, Beliefs & Best Response Signaling Games Rationalizability Rationalizability I The Nash equilibrium as a solution concept for strategic games does not crucially appeal to a notion of rationality in a players reasoning. I Another concept that is more explicitly linked to a reasoning process of players in a one-shot game is called ratiolalizability. I The set of rationalizable actions can be found by the iterated strict dominance algorithm: I Given a strategic game G I Do the following step until there aren’t dominated strategies left: I for all players: remove all dominated strategies in game G Game Theory for Linguists Overview Review: Session 1-3 Rationalizability, Beliefs & Best Response Signaling Games Rationalizability Nash Equilibria and Rationalizable Actions 1. -
Sequential Preference Revelation in Incomplete Information Settings”
Online Appendix for “Sequential preference revelation in incomplete information settings” † James Schummer∗ and Rodrigo A. Velez May 6, 2019 1 Proof of Theorem 2 Theorem 2 is implied by the following result. Theorem. Let f be a strategy-proof, non-bossy SCF, and fix a reporting order Λ ∆(Π). Suppose that at least one of the following conditions holds. 2 1. The prior has Cartesian support (µ Cartesian) and Λ is deterministic. 2 M 2. The prior has symmetric Cartesian support (µ symm Cartesian) and f is weakly anonymous. 2 M − Then equilibria are preserved under deviations to truthful behavior: for any N (σ,β) SE Γ (Λ, f ), ,µ , 2 h U i (i) for each i N, τi is sequentially rational for i with respect to σ i and βi ; 2 − (ii) for each S N , there is a belief system such that β 0 ⊆ N ((σ S ,τS ),β 0) SE β 0(Λ, f ), ,µ . − 2 h U i Proof. Let f be strategy-proof and non-bossy, Λ ∆(Π), and µ Cartesian. Since the conditions of the two theorems are the same,2 we refer to2 arguments M ∗Department of Managerial Economics and Decision Sciences, Kellogg School of Manage- ment, Northwestern University, Evanston IL 60208; [email protected]. †Department of Economics, Texas A&M University, College Station, TX 77843; [email protected]. 1 made in the proof of Theorem 1. In particular all numbered equations refer- enced below appear in the paper. N Fix an equilibrium (σ,β) SE Γ (Λ, f ), ,µ .