SSRN Author: Philipp StrackPhilipp Strack SSRN Content
https://privwww.ssrn.com/author=1337995
https://privwww.ssrn.com/rss/en-usThu, 06 Aug 2020 01:07:42 GMTeditor@ssrn.com (Editor)Thu, 06 Aug 2020 01:07:42 GMTwebmaster@ssrn.com (WebMaster)SSRN RSS Generator 1.0REVISION: Optimal Control of an Epidemic through Social DistancingWe analyze how to optimally engage in social distancing (SD) in order to minimize the spread of an infectious disease. We identify conditions under which the optimal policy is single-peaked, i.e., ﬁrst engages in increasingly more social distancing and subsequently decreases its intensity. We show that the optimal policy might delay measures that decrease the transmission rate substantially to create “herd-immunity” and that engaging in social distancing sub-optimally early can increase the number of fatalities. Finally, we ﬁnd that optimal social distancing can be an eﬀective measure in substantially reducing the death rate of a disease.
https://privwww.ssrn.com/abstract=3583186
https://privwww.ssrn.com/1928701.htmlWed, 05 Aug 2020 09:34:59 GMTREVISION: Optimal Auctions for Dual Risk Averse Bidders: Myerson meets YaariWe derive the revenue maximizing mechanism for a risk-neutral seller who<br>faces Yaari's [1987] dual risk-averse bidders. The optimal mechanism offers "full-<br>insurance" in the sense that each agent's utility is independent of other agents'<br>reports. The seller excludes less types than under risk neutrality, and awards the<br>object randomly to intermediate types. Subjecting intermediate types to a risky<br>allocation while compensating them when losing allows the seller to collect larger<br>payments from higher types. Relatively high types are anyway willing to pay more,<br>and their allocation is efficient. Finally, a first-price auction maximizes revenue<br>within the class of standard auctions.
https://privwww.ssrn.com/abstract=3547437
https://privwww.ssrn.com/1927748.htmlMon, 03 Aug 2020 14:09:00 GMTREVISION: Optimal Control of an Epidemic through Social DistancingWe analyze how to optimally engage in social distancing (SD) in order to minimize the spread of an infectious disease. We identify conditions under which the optimal policy is single-peaked, i.e., first engages in increasingly more social distancing and subsequently decreases its intensity. We show that the optimal policy might delay measures that decrease the transmission rate substantially to create "herd-immunity' and that engaging in social distancing sub-optimally early can increase the number of fatalities. Finally, we find that optimal social distancing can be an effective measure in substantially reducing the death rate of a disease.
https://privwww.ssrn.com/abstract=3581295
https://privwww.ssrn.com/1926398.htmlWed, 29 Jul 2020 10:42:37 GMTREVISION: Optimal Control of an Epidemic through Social DistancingWe analyze how to optimally engage in social distancing (SD) in order to minimize the spread of an infectious disease. We identify conditions under which the optimal policy is single-peaked, i.e., first engages in increasingly more social distancing and subsequently decreases its intensity. We show that the optimal policy might delay measures that decrease the transmission rate substantially to create "herd-immunity' and that engaging in social distancing sub-optimally early can increase the number of fatalities. Finally, we find that optimal social distancing can be an effective measure in substantially reducing the death rate of a disease.
https://privwww.ssrn.com/abstract=3581295
https://privwww.ssrn.com/1904891.htmlThu, 04 Jun 2020 14:31:04 GMTREVISION: Limit Points of Endogenous Misspecified LearningWe study how a misspecified agent learns from endogenous data when their prior belief does not impose restrictions on the distribution of outcomes, but can assign probability 0 to a neighborhood of the true model. We characterize the stable actions, which have a very high probability of being the long-run outcome for some initial beliefs, and the positively attracting actions, which have a positive probability of being the long-run outcome for any initial full support belief. A Berk-Nash equilibrium is uniformly strict if the equilibrium action is a strict best response to all the outcome distributions that minimize the Kullback-Leibler divergence from the truth, and uniform if the action is a best response to all those distributions. Uniform Berk-Nash equilibria are the unique possible limit actions under a myopic policy. All uniformly strict Berk-Nash equilibria are stable. They are positively attractive under causation neglect, where the agent believes that their action does not ...
https://privwww.ssrn.com/abstract=3553363
https://privwww.ssrn.com/1901293.htmlTue, 26 May 2020 14:29:28 GMTREVISION: Limit Points of Endogenous Misspecified LearningWe study how a misspecified agent learns from endogenous data when their prior belief does not impose restrictions on the distribution of outcomes, but can assign probability 0 to a neighborhood of the true model. We characterize the stable actions, which have a very high probability of being the long-run outcome for some initial beliefs, and the positively attracting actions, which have a positive probability of being the long-run outcome for any initial full support belief. A Berk-Nash equilibrium is uniformly strict if the equilibrium action is a strict best response to all the outcome distributions that minimize the Kullback-Leibler divergence from the truth, and uniform if the action is a best response to all those distributions. Uniform Berk-Nash equilibria are the unique possible limit actions under a myopic policy. All uniformly strict Berk-Nash equilibria are stable. They are positively attractive under causation neglect, where the agent believes that their action does not ...
https://privwww.ssrn.com/abstract=3553363
https://privwww.ssrn.com/1898570.htmlMon, 18 May 2020 16:19:44 GMTREVISION: Optimal Control of an Epidemic through Social DistancingWe analyze how to optimally engage in social distancing (SD) in order to minimize the spread of an infectious disease. We identify conditions under which the optimal policy is single-peaked, i.e., ﬁrst engages in increasingly more social distancing and subsequently decreases its intensity. We show that the optimal policy might delay measures that decrease the transmission rate substantially to create “herd-immunity” and that engaging in social distancing sub-optimally early can increase the number of fatalities. Finally, we ﬁnd that optimal social distancing can be an eﬀective measure in substantially reducing the death rate of a disease.
https://privwww.ssrn.com/abstract=3583186
https://privwww.ssrn.com/1889178.htmlThu, 23 Apr 2020 15:15:25 GMTREVISION: Limits Points of Endogenous Misspecified LearningWe study how a misspecified agent learns from endogenous data when their prior belief does not impose restrictions on the distribution of outcomes, but can assign probability 0 to a neighborhood of the true model. We characterize the stable actions, which have a very high probability of being the long-run outcome for some initial beliefs, and the are positively attracting actions, which have positive probability of being the long-run outcome for any initial full support belief. A Berk-Nash equilibrium is uniformly strict if the equilibrium action is a strict best response to all the outcome distributions that minimize the Kullback-Leibler divergence from the truth, and uniform if the action is a best response to all those distributions. Uniform Berk-Nash equilibria are the unique possible limit actions under a myopic policy. All uniformly strict Berk-Nash equilibria are stable. They are positively attractive under causation neglect, where the agent believes that their action does ...
https://privwww.ssrn.com/abstract=3553363
https://privwww.ssrn.com/1888102.htmlTue, 21 Apr 2020 09:37:16 GMTREVISION: Extreme Points and Majorization: Economic ApplicationsWe characterize the set of extreme points of monotone functions that are either majorized by a given function f or themselves majorize f. Any feasible element in a majorization set can be expressed as an integral with respect to a measure supported on the extreme points of that set. We show that these extreme points play a crucial rule in mechanism design, Bayesian persuasion, optimal delegation and many other models of decision making with expected and non-expected utility. Our main results show that each extreme point is uniquely characterized by a countable collection of intervals. Outside these intervals the extreme point equals the original function f and inside the function is constant. Further consistency conditions need to be satisfied pinning down the value of the extreme points in each interval where it is constant. Finally, we apply these insights to a varied set of economic problems.
https://privwww.ssrn.com/abstract=3551258
https://privwww.ssrn.com/1882354.htmlMon, 06 Apr 2020 09:09:19 GMTREVISION: Extreme Points and Majorization: Economic ApplicationsWe characterize the set of extreme points of monotone functions that are either majorized by a given function f or themselves majorize f. Any feasible element in a majorization set can be expressed as an integral with respect to a measure supported on the extreme points of that set. We show that these extreme points play a crucial rule in mechanism design, Bayesian persuasion, optimal delegation and many other models of decision making with expected and non-expected utility. Our main results show that each extreme point is uniquely characterized by a countable collection of intervals. Outside these intervals the extreme point equals the original function f and inside the function is constant. Further consistency conditions need to be satisfied pinning down the value of the extreme points in each interval where it is constant. Finally, we apply these insights to a varied set of economic problems.
https://privwww.ssrn.com/abstract=3551258
https://privwww.ssrn.com/1882156.htmlFri, 03 Apr 2020 17:39:09 GMTREVISION: Limits Points of Endogenous Misspecified LearningWe study how a misspecified agent learns from endogenous data when their prior belief does not impose restrictions on the distribution of outcomes, but can assign probability 0 to a neighborhood of the true model. We characterize the stable actions, which have a very high probability of being the long-run outcome for some initial beliefs, and the are positively attracting actions, which have positive probability of being the long-run outcome for any initial full support belief. A Berk-Nash equilibrium is uniformly strict if the equilibrium action is a strict best response to all the outcome distributions that minimize the Kullback-Leibler divergence from the truth, and uniform if the action is a best response to all those distributions. Uniform Berk-Nash equilibria are the unique possible limit actions under a myopic policy. All uniformly strict Berk-Nash equilibria are stable. They are positively attractive under causation neglect, where the agent believes that their action does ...
https://privwww.ssrn.com/abstract=3553363
https://privwww.ssrn.com/1882153.htmlFri, 03 Apr 2020 17:34:47 GMTNew: A Theory of Auctions with Endogenous ValuationsWe derive the revenue maximizing allocation of m units among n symmetric agents who have unit demand, and who take costly actions that influence their values before participating in the mechanism. The allocation problem with costly actions can be represented by a reduced form model where agents have convex, non-expected utility preferences over the interim probability of receiving an object. Both the uniform m + 1 price auction and the discriminatory pay-your-bid auction with reserve price constitute symmetric revenue maximizing mechanisms. Contrasting the case with exogenous valuations, the optimal reserve price reacts to both demand and supply, i.e., it depends both on the number of objects m and on number of agents n. The main tool in our analysis is an integral inequality involving majorization, super-modularity and convexity due to Fan and Lorentz (1954).
https://privwww.ssrn.com/abstract=3547465
https://privwww.ssrn.com/1879608.htmlFri, 27 Mar 2020 10:21:07 GMTREVISION: Optimal Auctions for Dual Risk Averse Bidders: Myerson meets YaariWe derive the revenue maximizing mechanism for a risk-neutral seller who faces Yaari's [1987] dual risk-averse bidders. Revenue equivalence fails and the optimal mechanism offers "full-insurance" in the sense that each agent's utility is independent of other agents' reports. The optimal mechanism solves a variational obstacle problem where the main role is played by a majorization constraint on the "reduced form auction". The seller excludes less types than under risk neutrality, and awards the object randomly to intermediate types. Subjecting intermediate types to a risky allocation while compensating them when losing allows the seller to collect larger payments from higher types. Relatively high types are anyway willing to pay more, and their allocation is efficient. We also show that a first-price auction maximizes revenue within the class of standard auctions.
https://privwww.ssrn.com/abstract=3547437
https://privwww.ssrn.com/1879607.htmlFri, 27 Mar 2020 10:19:51 GMTNew: Progressive ParticipationA single seller faces a sequence of buyers with unit demand. The buyers are forward-looking and long-lived but vanish (and are replaced) at a constant rate. The arrival time and the valuation is private information of each buyer and unobservable to the seller. Any incentive compatible mechanism has to induce truth-telling about the arrival time and the evolution of the valuation. <br> <br>We derive the optimal stationary mechanism, characterize its qualitative structure, and derive a closed-form solution. As the arrival time is private information, the buyer can choose the time at which he reports his arrival. The truth-telling constraint regarding the arrival time can be represented as an optimal stopping problem. The stopping time determines the time at which the buyer decides to participate in the mechanism. The resulting value function of each buyer cannot be too convex and must be continuously diﬀerentiable everywhere, reflecting the option value of delaying participation. The ...
https://privwww.ssrn.com/abstract=3528161
https://privwww.ssrn.com/1862277.htmlFri, 31 Jan 2020 15:24:11 GMTNew: Bitcoin: An Impossibility Theorem for Proof-of-Work Based ProtocolsBitcoin’s main innovation lies in allowing a decentralized system that relies on anonymous, proﬁt driven miners who can freely join the system. We formalize these properties in three axioms: anonymity of miners, no incentives for miners to consolidate, and no incentive to assuming multiple fake identities. This novel axiomatic formalization allows us to characterize which other protocols are feasible: Every protocol with these properties must have the same reward scheme as Bitcoin. This implies an impossibility result for risk-averse miners: no protocol satisﬁes the aforementioned constraints simultaneously without giving miners a strict incentive to merge. Furthermore, any protocol either gives up on some degree of decentralization or its reward scheme is equivalent to Bitcoin’s.
https://privwww.ssrn.com/abstract=3487355
https://privwww.ssrn.com/1842123.htmlFri, 15 Nov 2019 13:31:26 GMTNew: Bitcoin: An Impossibility Theorem for Proof-of-Work based ProtocolsA key part of decentralized consensus protocols is a procedure for random selection, which is the source of the majority of miners cost and wasteful energy consumption in Bitcoin. We provide a simple economic model for random selection mechanism and show that any PoW protocol with natural desirable properties is outcome equivalent to the random selection mechanism used in Bitcoin.
https://privwww.ssrn.com/abstract=3467058
https://privwww.ssrn.com/1832173.htmlThu, 10 Oct 2019 16:42:00 GMTREVISION: Too Proud to Stop: Regret in Dynamic DecisionsRegret and its anticipation aﬀect a wide range of decisions. Job-seekers reject oﬀers while waiting for an oﬀer to match their best past oﬀer; investors hold on to badly performing stocks; and managers throw good money after bad projects. We analyze behavior of a decision-maker with regret preferences in a dynamic context and show that regret agents have a disposition to gamble until they receive a payoﬀ matching the best past oﬀer. Results from a lab experiment conﬁrm that many subjects exhibit such behavior and are reluctant to stop below the past peak.<br>
https://privwww.ssrn.com/abstract=2465840
https://privwww.ssrn.com/1826868.htmlMon, 23 Sep 2019 12:26:44 GMTREVISION: Identifying Present-Bias from the Timing of ChoicesTiming decisions are common: when to file your taxes, finish a referee report, or complete a task at work. We ask whether time preferences can be inferred when only task completion is observed. To answer this question, we analyze the following model: each period a decision maker faces the choice whether to complete the task today or to postpone it to later. Cost and benefits of task completion cannot be directly observed by the analyst, but the analyst knows that net benefits are drawn independently between periods from a time-invariant distribution and that the agent has time-separable utility. Furthermore, we suppose the analyst can observe the agent's exact stopping probability. We establish that for any agent with quasi-hyperbolic β,δ-preferences and given level of partial naivete, the probability of completing the task conditional on not having done it earlier increases towards the deadline. And conversely, for any given preference parameters β,δ and (weakly increasing) profile ...
https://privwww.ssrn.com/abstract=3386017
https://privwww.ssrn.com/1816888.htmlTue, 20 Aug 2019 07:30:50 GMTNew: Progressive ParticipationA single seller faces a sequence of buyers with unit demand. The buyers are forward-looking and long-lived but vanish (and are replaced) at a constant rate. The arrival time and the valuation is private information of each buyer and unobservable to the seller. Any incentive-compatible mechanism has to induce truth-telling about the arrival time and the evolution of the valuation.<br><br>We derive the optimal stationary mechanism, characterize its qualitative structure and derive a closed-form solution. As the arrival time is private information, the agent can choose the time at which he reports his arrival. The truth-telling constraint regarding the arrival time can be represented as an optimal stopping problem. The stopping time determines the time at which the agent decides to participate in the mechanism. The resulting value function of each agent can not be too convex and has to be continuously diﬀerentiable everywhere, reflecting the option value of delaying participation. The ...
https://privwww.ssrn.com/abstract=3437559
https://privwww.ssrn.com/1815593.htmlThu, 15 Aug 2019 10:26:02 GMT