Lecturenotesongametheory

Total Page:16

File Type:pdf, Size:1020Kb

Lecturenotesongametheory Lecture Notes on Game Theory Theory and Examples Xiang Sun August 22, 2015 ii Contents Acknowledgement vii 1 Introduction 1 1.1 Timeline of the main evolution of game theory ................................ 1 1.2 Nobel prize laureates .............................................. 16 1.3 Potential Nobel prize winners ......................................... 19 1.4 Rational behavior ................................................ 20 1.5 Common knowledge .............................................. 20 2 Strategic games with complete information 23 2.1 Strategic games ................................................. 23 2.2 Nash equilibrium ................................................ 24 2.3 Examples .................................................... 25 2.4 Existence of a Nash equilibrium ........................................ 41 2.5 Strictly competitive games (zero-sum games) ................................. 43 2.6 Existence of a Nash equilibrium: games with discontinuous payoff functions ................ 44 3 Contest 47 4 Bayesian games (strategic games with incomplete information) 49 4.1 Bayes’ rule (Bayes’ theorem) .......................................... 49 4.2 Bayesian games ................................................. 50 4.3 Examples .................................................... 54 4.4 Comments on Bayesian games ......................................... 70 5 Auction 73 i Contents ii 5.1 Preliminary ................................................... 73 5.2 The symmetric model ............................................. 75 5.3 Second-price sealed-bid auction ........................................ 75 5.4 First-price sealed-bid auction ......................................... 76 5.5 Revenue comparison .............................................. 84 5.6 Reserve prices ................................................. 86 5.7 The revenue equivalence principle ....................................... 89 5.8 All-pay auction ................................................. 90 5.9 Third-price auction ............................................... 91 5.10 Uncertain number of bidders ......................................... 92 6 Mixed-strategy Nash equilibrium 95 6.1 Mixed-strategy Nash equilibrium ....................................... 95 6.2 Examples .................................................... 97 6.3 Interpretation of mixed-strategy Nash equilibrium .............................. 100 6.3.1 Purification .............................................. 101 7 Correlated equilibrium 105 7.1 Motivation ................................................... 105 7.2 Correlated equilibrium ............................................. 106 7.3 Examples .................................................... 108 8 Rationalizability 113 8.1 Rationalizability ................................................ 113 8.2 Iterated elimination of never-best response .................................. 117 8.3 Iterated elimination of strictly dominated actions .............................. 118 8.4 Examples .................................................... 120 8.5 Iterated elimination of weakly dominated actions .............................. 124 9 Knowledge model 125 9.1 A model of knowledge ............................................. 125 9.2 Common knowledge .............................................. 130 9.3 Common prior ................................................. 131 9.4 “Agree to disagree” is impossible ........................................ 132 9.5 No-trade theorem ............................................... 134 9.6 Speculation ................................................... 135 Contents iii 9.7 Characterization of the common prior assumption .............................. 137 9.8 Unawareness .................................................. 138 10 Interactive epistemology 141 10.1 Epistemic conditions for Nash equilibrium .................................. 141 10.2 Epistemic foundation of rationalizability ................................... 144 10.3 Epistemic foundation of correlated equilibrium ............................... 145 10.4 The electronic mail game ............................................ 145 11 Extensive games with perfect information 149 11.1 Extensive games with perfect information .................................. 149 11.2 Subgame perfect equilibrium ......................................... 151 11.3 Examples .................................................... 154 11.4 Three notable games .............................................. 161 11.5 Iterated elimination of weakly dominated strategies ............................. 163 11.6 Forward induction ............................................... 164 12 Bargaining games 167 12.1 A bargaining game of alternating offers .................................... 167 12.2 Bargaining games with finite horizon ..................................... 168 12.3 Bargaining games with infinite horizon .................................... 169 12.4 Properties of subgame perfect equilibria in Rubinstein bargaining games .................. 172 12.5 Bargaining games with cost .......................................... 173 12.6 n-person bargaining games .......................................... 173 13 Repeated games 177 13.1 Infinitely repeated games ............................................ 177 13.2 Trigger strategy equilibrium .......................................... 182 13.3 Tit-for-tat strategy equilibrium ........................................ 187 13.4 Folk theorem .................................................. 188 13.5 Nash-threats folk theorem ........................................... 189 13.6 Perfect folk theorem .............................................. 190 13.7 Finitely repeated games ............................................ 193 14 Extensive games with imperfect information 195 14.1 Extensive games with imperfect information ................................. 195 Contents iv 14.2 Mixed and behavioral strategies ........................................ 197 14.3 Subgame perfect equilibrium ......................................... 200 14.4 Perfect Bayesian equilibrium .......................................... 206 14.5 Sequential equilibrium ............................................. 211 14.6 Trembling hand perfect equilibrium ...................................... 214 15 Information economics 217 15.1 Adverse selection ................................................ 218 15.2 Signalling .................................................... 220 15.2.1 The market for “lemons” ....................................... 229 15.2.2 Job-market signaling ......................................... 232 15.2.3 Cheap talk ............................................... 234 15.3 Screening .................................................... 239 15.3.1 Pricing a single indivisible good ................................... 239 15.3.2 Nonlinear pricing ........................................... 240 15.4 Moral hazard and the principle-agent problem ................................ 244 15.4.1 Complete information ......................................... 244 15.4.2 Asymmetric information ....................................... 245 16 Social choice theory 247 16.1 Social choice .................................................. 247 16.2 Arrow’s impossibility theorem ......................................... 248 16.3 Borda count, simple plurality rule, and two-round system .......................... 252 16.4 Gibbard-Satterthwaite theorem ........................................ 255 17 Mechanism design 261 17.1 Envelope theorem ............................................... 262 17.2 A general mechanism design setting ..................................... 263 17.3 Dominant strategy mechanism design .................................... 265 17.3.1 Revelation principle for dominant strategies ............................. 265 17.3.2 Payoff equivalence theorem ...................................... 266 17.3.3 Gibbard-Satterthwaite theorem .................................... 267 17.3.4 VCG mechanism ........................................... 267 17.3.5 Pivot mechanism ........................................... 269 17.3.6 Balancing the budget ......................................... 272 Contents v 17.4 Bayesian mechanism design .......................................... 273 17.5 Characterization of incentive compatibility .................................. 274 17.6 Bilateral trade .................................................. 275 18 Auction: mechanism design approach 279 18.1 The revelation principle for Bayesian equilibrium .............................. 280 18.2 Incentive compatibility and individual rationality .............................. 282 18.3 Optimal auction ................................................ 285 18.4 Maximizing welfare .............................................. 289 18.5 VCG mechanism ................................................ 291 18.6 AGV mechanism ................................................ 293 19 Implementation theory 295 19.1 Implementation ................................................ 295 19.2 Implementation in dominant strategies .................................... 297 19.3 Nash implementation ............................................. 300 20 Coalitional games 305 20.1 Coalitional game ................................................ 305 20.2 Core ....................................................... 306 20.3 Shapley value .................................................
Recommended publications
  • Game Theory 2: Extensive-Form Games and Subgame Perfection
    Game Theory 2: Extensive-Form Games and Subgame Perfection 1 / 26 Dynamics in Games How should we think of strategic interactions that occur in sequence? Who moves when? And what can they do at different points in time? How do people react to different histories? 2 / 26 Modeling Games with Dynamics Players Player function I Who moves when Terminal histories I Possible paths through the game Preferences over terminal histories 3 / 26 Strategies A strategy is a complete contingent plan Player i's strategy specifies her action choice at each point at which she could be called on to make a choice 4 / 26 An Example: International Crises Two countries (A and B) are competing over a piece of land that B occupies Country A decides whether to make a demand If Country A makes a demand, B can either acquiesce or fight a war If A does not make a demand, B keeps land (game ends) A's best outcome is Demand followed by Acquiesce, worst outcome is Demand and War B's best outcome is No Demand and worst outcome is Demand and War 5 / 26 An Example: International Crises A can choose: Demand (D) or No Demand (ND) B can choose: Fight a war (W ) or Acquiesce (A) Preferences uA(D; A) = 3 > uA(ND; A) = uA(ND; W ) = 2 > uA(D; W ) = 1 uB(ND; A) = uB(ND; W ) = 3 > uB(D; A) = 2 > uB(D; W ) = 1 How can we represent this scenario as a game (in strategic form)? 6 / 26 International Crisis Game: NE Country B WA D 1; 1 3X; 2X Country A ND 2X; 3X 2; 3X I Is there something funny here? I Is there something funny here? I Specifically, (ND; W )? I Is there something funny here?
    [Show full text]
  • Best Experienced Payoff Dynamics and Cooperation in the Centipede Game
    Theoretical Economics 14 (2019), 1347–1385 1555-7561/20191347 Best experienced payoff dynamics and cooperation in the centipede game William H. Sandholm Department of Economics, University of Wisconsin Segismundo S. Izquierdo BioEcoUva, Department of Industrial Organization, Universidad de Valladolid Luis R. Izquierdo Department of Civil Engineering, Universidad de Burgos We study population game dynamics under which each revising agent tests each of his strategies a fixed number of times, with each play of each strategy being against a newly drawn opponent, and chooses the strategy whose total payoff was highest. In the centipede game, these best experienced payoff dynamics lead to co- operative play. When strategies are tested once, play at the almost globally stable state is concentrated on the last few nodes of the game, with the proportions of agents playing each strategy being largely independent of the length of the game. Testing strategies many times leads to cyclical play. Keywords. Evolutionary game theory, backward induction, centipede game, computational algebra. JEL classification. C72, C73. 1. Introduction The discrepancy between the conclusions of backward induction reasoning and ob- served behavior in certain canonical extensive form games is a basic puzzle of game the- ory. The centipede game (Rosenthal (1981)), the finitely repeated prisoner’s dilemma, and related examples can be viewed as models of relationships in which each partic- ipant has repeated opportunities to take costly actions that benefit his partner and in which there is a commonly known date at which the interaction will end. Experimen- tal and anecdotal evidence suggests that cooperative behavior may persist until close to William H.
    [Show full text]
  • Lecture Notes
    GRADUATE GAME THEORY LECTURE NOTES BY OMER TAMUZ California Institute of Technology 2018 Acknowledgments These lecture notes are partially adapted from Osborne and Rubinstein [29], Maschler, Solan and Zamir [23], lecture notes by Federico Echenique, and slides by Daron Acemoglu and Asu Ozdaglar. I am indebted to Seo Young (Silvia) Kim and Zhuofang Li for their help in finding and correcting many errors. Any comments or suggestions are welcome. 2 Contents 1 Extensive form games with perfect information 7 1.1 Tic-Tac-Toe ........................................ 7 1.2 The Sweet Fifteen Game ................................ 7 1.3 Chess ............................................ 7 1.4 Definition of extensive form games with perfect information ........... 10 1.5 The ultimatum game .................................. 10 1.6 Equilibria ......................................... 11 1.7 The centipede game ................................... 11 1.8 Subgames and subgame perfect equilibria ...................... 13 1.9 The dollar auction .................................... 14 1.10 Backward induction, Kuhn’s Theorem and a proof of Zermelo’s Theorem ... 15 2 Strategic form games 17 2.1 Definition ......................................... 17 2.2 Nash equilibria ...................................... 17 2.3 Classical examples .................................... 17 2.4 Dominated strategies .................................. 22 2.5 Repeated elimination of dominated strategies ................... 22 2.6 Dominant strategies ..................................
    [Show full text]
  • The Monty Hall Problem in the Game Theory Class
    The Monty Hall Problem in the Game Theory Class Sasha Gnedin∗ October 29, 2018 1 Introduction Suppose you’re on a game show, and you’re given the choice of three doors: Behind one door is a car; behind the others, goats. You pick a door, say No. 1, and the host, who knows what’s behind the doors, opens another door, say No. 3, which has a goat. He then says to you, “Do you want to pick door No. 2?” Is it to your advantage to switch your choice? With these famous words the Parade Magazine columnist vos Savant opened an exciting chapter in mathematical didactics. The puzzle, which has be- come known as the Monty Hall Problem (MHP), has broken the records of popularity among the probability paradoxes. The book by Rosenhouse [9] and the Wikipedia entry on the MHP present the history and variations of the problem. arXiv:1107.0326v1 [math.HO] 1 Jul 2011 In the basic version of the MHP the rules of the game specify that the host must always reveal one of the unchosen doors to show that there is no prize there. Two remaining unrevealed doors may hide the prize, creating the illusion of symmetry and suggesting that the action does not matter. How- ever, the symmetry is fallacious, and switching is a better action, doubling the probability of winning. There are two main explanations of the paradox. One of them, simplistic, amounts to just counting the mutually exclusive cases: either you win with ∗[email protected] 1 switching or with holding the first choice.
    [Show full text]
  • Pricing Rule in a Clock Auction
    Decision Analysis informs ® Vol. 7, No. 1, March 2010, pp. 40–57 issn 1545-8490 eissn 1545-8504 10 0701 0040 doi 10.1287/deca.1090.0161 © 2010 INFORMS Pricing Rule in a Clock Auction Peter Cramton, Pacharasut Sujarittanonta Department of Economics, University of Maryland, College Park, Maryland 20742 {[email protected], [email protected]} e analyze a discrete clock auction with lowest-accepted-bid (LAB) pricing and provisional winners, as Wadopted by India for its 3G spectrum auction. In a perfect Bayesian equilibrium, the provisional winner shades her bid, whereas provisional losers do not. Such differential shading leads to inefficiency. An auction with highest-rejected-bid (HRB) pricing and exit bids is strategically simple, has no bid shading, and is fully efficient. In addition, it has higher revenues than the LAB auction, assuming profit-maximizing bidders. The bid shading in the LAB auction exposes a bidder to the possibility of losing the auction at a price below the bidder’s value. Thus, a fear of losing at profitable prices may cause bidders in the LAB auction to bid more aggressively than predicted, assuming profit-maximizing bidders. We extend the model by adding an anticipated loser’s regret to the payoff function. Revenue from the LAB auction yields higher expected revenue than the HRB auction when bidders’ fear of losing at profitable prices is sufficiently strong. This would provide one explanation why India, with an expressed objective of revenue maximization, adopted the LAB auction for its upcoming 3G spectrum auction, rather than the seemingly superior HRB auction. Key words: auctions; clock auctions; spectrum auctions; behavioral economics; market design History: Received on April 16, 2009.
    [Show full text]
  • Statistical Mechanics of Evolutionary Dynamics
    Statistical Mechanics of Evolutionary Dynamics Kumulative Dissertation zur Erlangung des Doktorgrades der Mathematisch-Naturwissenschaftlichen Fakult¨at der Christian-Albrechts-Universit¨at zu Kiel vorgelegt von Torsten Rohl¨ Kiel 2007 Referent: Prof. Dr. H. G. Schuster Koreferent(en): Prof. Dr. G. Pfister Tagderm¨undlichenPr¨ufung: 4.Dezember2007 ZumDruckgenehmigt: Kiel,den12.Dezember2007 gez. Prof. Dr. J. Grotemeyer (Dekan) Contents Abstract 1 Kurzfassung 2 1 Introduction 3 1.1 Motivation................................... 3 1.1.1 StatisticalPhysicsandBiologicalSystems . ...... 3 1.1.1.1 Statistical Physics and Evolutionary Dynamics . ... 4 1.1.2 Outline ................................ 7 1.2 GameTheory ................................. 8 1.2.1 ClassicalGameTheory. .. .. .. .. .. .. .. 8 1.2.1.1 TheMatchingPenniesGame . 11 1.2.1.2 ThePrisoner’sDilemmaGame . 13 1.2.2 From Classical Game Theory to Evolutionary Game Theory.... 16 1.3 EvolutionaryDynamics. 18 1.3.1 Introduction.............................. 18 1.3.2 ReplicatorDynamics . 22 1.3.3 GamesinFinitePopulations . 25 1.4 SurveyofthePublications . 29 1.4.1 StochasticGaininPopulationDynamics. ... 29 1.4.2 StochasticGaininFinitePopulations . ... 31 1.4.3 Impact of Fraud on the Mean-Field Dynamics of Cooperative Social Systems................................ 36 2 Publications 41 2.1 Stochasticgaininpopulationdynamics . ..... 42 2.2 Stochasticgaininfinitepopulations . ..... 47 2.3 Impact of fraud on the mean-field dynamics of cooperative socialsystems . 54 Contents II 3 Discussion 63 3.1 ConclusionsandOutlook . 63 Bibliography 67 Curriculum Vitae 78 Selbstandigkeitserkl¨ arung¨ 79 Abstract Evolutionary dynamics is an essential component of a mathematical and computational ap- proach to biology. In recent years the mathematical description of evolution has moved to a description of any kind of process where information is being reproduced in a natural envi- ronment. In this manner everything that lives is a product of evolutionary dynamics.
    [Show full text]
  • Competition and Efficiency of Coalitions in Cournot Games
    1 Competition and Efficiency of Coalitions in Cournot Games with Uncertainty Baosen Zhang, Member, IEEE, Ramesh Johari, Member, IEEE, Ram Rajagopal, Member, IEEE, Abstract—We investigate the impact of coalition formation on Electricity markets serve as one motivating example of the efficiency of Cournot games where producers face uncertain- such an environment. In electricity markets, producers submit ties. In particular, we study a market model where firms must their bids before the targeted time of delivery (e.g., one day determine their output before an uncertain production capacity is realized. In contrast to standard Cournot models, we show that ahead). However, renewable resources such as wind and solar the game is not efficient when there are many small firms. Instead, have significant uncertainty (even on a day-ahead timescale). producers tend to act conservatively to hedge against their risks. As a result, producers face uncertainties about their actual We show that in the presence of uncertainty, the game becomes production capacity at the commitment stage. efficient when firms are allowed to take advantage of diversity Our paper focuses on a fundamental tradeoff revealed in to form groups of certain sizes. We characterize the tradeoff between market power and uncertainty reduction as a function such games. On one hand, in the classical Cournot model, of group size. In particular, we compare the welfare and output efficiency obtains as the number of individual firms approaches obtained with coalitional competition, with the same benchmarks infinity, as this weakens each firm’s market power (ability to when output is controlled by a single system operator.
    [Show full text]
  • CONTENT2 2.Pages
    DRAFT PROPOSITIONAL CONTENT in SIGNALS (for Special Issue Studies in the History and Philosophy of Science C ) Brian Skyrms and Jeffrey A. Barrett Introduction We all think that humans are animals, that human language is a sophisticated form of animal signaling, and that it arises spontaneously due to natural processes. From a naturalistic perspective, what is fundamental is what is common to signaling throughout the biological world -- the transfer of information. As Fred Dretske put it in 1981, "In the beginning was information, the word came later." There is a practice of signaling with information transfer that settles into some sort of a pattern, and eventually what we call meaning or propositional content crystallizes out. The place to start is to study the evolution, biological or cultural, of information transfer in its most simple and tractable forms. But once this is done, naturalists need first to move to evolution of more complex forms of information transfer. And then to an account of the crystallization process that gives us meaning. There often two kinds of information in the same signal: (1) information about the state of the world that the signaler observes (2) information about the act that the receiver will perform on receiving the signal. [See Millikan (1984), Harms (2004), Skyrms (2010)]. The meaning that crystalizes out about the states, we will single out here as propositional meaning. The simplest account that comes to mind will not quite do, as a general account of this kind of meaning, although it may be close to the mark in especially favorable situations.
    [Show full text]
  • Tough Talk, Cheap Talk, and Babbling: Government Unity, Hawkishness
    Tough Talk, Cheap Talk, and Babbling: Government Unity, Hawkishness and Military Challenges By Matthew Blake Fehrs Department of Political Science Duke University Date:_____________________ Approved: ___________________________ Joseph Grieco, Supervisor __________________________ Alexander Downes __________________________ Peter Feaver __________________________ Chris Gelpi __________________________ Erik Wibbels Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Political Science in the Graduate School of Duke University 2008 ABSTRACT Tough Talk, Cheap Talk, and Babbling: Government Unity, Hawkishness and Military Challenges By Matthew Blake Fehrs Department of Political Science Duke University Date:_____________________ Approved: ___________________________ Joseph Grieco, Supervisor __________________________ Alexander Downes __________________________ Peter Feaver __________________________ Chris Gelpi __________________________ Erik Wibbels An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Political Science in the Graduate School of Duke University 2008 Copyrighted by Matthew Blake Fehrs 2008 Abstract A number of puzzles exist regarding the role of domestic politics in the likelihood of international conflict. In particular, the sources of incomplete information remain under-theorized and the microfoundations deficient. This study will examine the role that the unity of the government and the views of the government towards the use of force play in the targeting of states. The theory presented argues that divided dovish governments are particularly likely to suffer from military challenges. In particular, divided governments have difficulty signaling their intentions, taking decisive action, and may appear weak. The theory will be tested on a new dataset created by the author that examines the theory in the context of international territorial disputes.
    [Show full text]
  • Incomplete Information I. Bayesian Games
    Bayesian Games Debraj Ray, November 2006 Unlike the previous notes, the material here is perfectly standard and can be found in the usual textbooks: see, e.g., Fudenberg-Tirole. For the examples in these notes (except for the very last section), I draw heavily on Martin Osborne’s excellent recent text, An Introduction to Game Theory, Oxford University Press. Obviously, incomplete information games — in which one or more players are privy to infor- mation that others don’t have — has enormous applicability: credit markets / auctions / regulation of firms / insurance / bargaining /lemons / public goods provision / signaling / . the list goes on and on. 1. A Definition A Bayesian game consists of 1. A set of players N. 2. A set of states Ω, and a common prior µ on Ω. 3. For each player i a set of actions Ai and a set of signals or types Ti. (Can make actions sets depend on type realizations.) 4. For each player i, a mapping τi :Ω 7→ Ti. 5. For each player i, a vN-M payoff function fi : A × Ω 7→ R, where A is the product of the Ai’s. Remarks A. Typically, the mapping τi tells us player i’s type. The easiest case is just when Ω is the product of the Ti’s and τi is just the appropriate projection mapping. B. The prior on states need not be common, but one view is that there is no loss of generality in assuming it (simply put all differences in the prior into differences in signals and redefine the state space and si-mappings accordingly).
    [Show full text]
  • Information Games and Robust Trading Mechanisms
    Information Games and Robust Trading Mechanisms Gabriel Carroll, Stanford University [email protected] October 3, 2017 Abstract Agents about to engage in economic transactions may take costly actions to influence their own or others’ information: costly signaling, information acquisition, hard evidence disclosure, and so forth. We study the problem of optimally designing a mechanism to be robust to all such activities, here termed information games. The designer cares about welfare, and explicitly takes the costs incurred in information games into account. We adopt a simple bilateral trade model as a case study. Any trading mechanism is evaluated by the expected welfare, net of information game costs, that it guarantees in the worst case across all possible games. Dominant- strategy mechanisms are natural candidates for the optimum, since there is never any incentive to manipulate information. We find that for some parameter values, a dominant-strategy mechanism is indeed optimal; for others, the optimum is a non- dominant-strategy mechanism, in which one party chooses which of two trading prices to offer. Thanks to (in random order) Parag Pathak, Daron Acemoglu, Rohit Lamba, Laura Doval, Mohammad Akbarpour, Alex Wolitzky, Fuhito Kojima, Philipp Strack, Iv´an Werning, Takuro Yamashita, Juuso Toikka, and Glenn Ellison, as well as seminar participants at Michigan, Yale, Northwestern, CUHK, and NUS, for helpful comments and discussions. Dan Walton provided valuable research assistance. 1 Introduction A large portion of theoretical work in mechanism design, especially in the world of market design applications, has focused on dominant-strategy (or strategyproof ) mechanisms — 1 those in which each agent is asked for her preferences, and it is always in her best interest to report them truthfully, no matter what other agents are doing.
    [Show full text]
  • Forward Guidance: Communication, Commitment, Or Both?
    Forward Guidance: Communication, Commitment, or Both? Marco Bassetto July 25, 2019 WP 2019-05 https://doi.org/10.21033/wp-2019-05 *Working papers are not edited, and all opinions and errors are the responsibility of the author(s). The views expressed do not necessarily reflect the views of the Federal Reserve Bank of Chicago or the Federal Federal Reserve Bank of Chicago Reserve Federal Reserve System. Forward Guidance: Communication, Commitment, or Both?∗ Marco Bassettoy July 25, 2019 Abstract A policy of forward guidance has been suggested either as a form of commitment (\Odyssean") or as a way of conveying information to the public (\Delphic"). I an- alyze the strategic interaction between households and the central bank as a game in which the central bank can send messages to the public independently of its actions. In the absence of private information, the set of equilibrium payoffs is independent of the announcements of the central bank: forward guidance as a pure commitment mechanism is a redundant policy instrument. When private information is present, central bank communication can instead have social value. Forward guidance emerges as a natural communication strategy when the private information in the hands of the central bank concerns its own preferences or beliefs: while forward guidance per se is not a substitute for the central bank's commitment or credibility, it is an instrument that allows policymakers to leverage their credibility to convey valuable information about their future policy plans. It is in this context that \Odyssean forward guidance" can be understood. ∗I thank Gadi Barlevy, Jeffrey Campbell, Martin Cripps, Mariacristina De Nardi, Fernando Duarte, Marco Del Negro, Charles L.
    [Show full text]