2017 Joint Department of Economics/CMSS Seminar by Rajiv Sarin

Speaker: Rajiv Sarin (University of Exeter)

Title of the talk: “A Model of Satisficing”

Date, Time and Venue: Thursday, 17 August 2017,  2:00-3:00 pm, room 260-323 [Business School Building, Level 3]

Abstract: “We build a model of satisficing behaviour. We explicitly introduce the payoff the decision maker expects from a strategy, where this expectation is adaptively formed. This valuation of a strategy is differentiated from her satisficing level which is taken to be the payoff the agent expects from her best outside option. If the agent receives a payoff above her satisficing level she continues with the current action, updating her valuation of the action. If she receives a payoff below her satisficing level and her valuation of the action falls below her satisficing level she updates both her satisficing level and what she expects from the strategy. We show that in the long run, all players satisfice. In individual decision problems, satisficing behaviour results in cautious, maximin choice. In games like the Prisoner’s Dilemma and Stag Hunt, they converge to cooperative outcomes. In other games, such as canonical public good games, they converge to (selfish) Nash equilibria.”

Bio: Rajiv Sarin is Professor of Economics at the University of Exeter. He is a theorist whose research has appeared in such leading journals as American Economic Review, International Economic Review, Games and Economic Behavior and Journal of Economic Theory.

Everyone welcome!

2017 CMSS Seminar Simona Fabrizi

Speaker: Simona Fabrizi (Department of Economics, University of Auckland)

Title of the talk: “The Good, The Bad, and The Not So Ugly: Unanimity Voting with Ambiguous Information” based on a joint paper with Addison Pan

Date, Time and Venue: Thursday, 3 August 2017,  2:00-3:00 pm, [Room Change!] now room 260-307 [Business School Building, Level 3]

Abstract: “Collective decision-making leads to poorer quality decisions under the unanimity voting rule than under majority voting especially as the size of the group grows larger, due to the tendency for strategic decision-makers to vote more often against their private information. In jury trials, for instance, it is well-established that strategic voting is responsible for the paradoxical result that the more demanding the hurdle for conviction is, the more likely it is that a jury will convict an innocent defendant. We challenge these findings, by exploring collective decision-making under alternative voting rules when decision-makers face an ambiguous information structure. Specifically, we investigate voting behaviour by ambiguity-averse voters, who are MaxMin Expected Utility Maximizers, demonstrating that unanimity voting is compatible with instances of informative voting, outperforming other voting rules, such as majority voting.”

Everyone welcome!

2017 CMSS Seminars: Thomas Pfeiffer

SpeakerThomas Pfeiffer  (New Zealand Institute for Advanced Study, Massey University)

Title of the talk: “Decision markets in theory, experiment, and practical applications”

Date, Time and Venue: Wednesday, 31 May 2017,  2:00-3:00 pm, 260-307 [Business School Building, Level 3]

What this talk is going to be about, in Thomas’ words: “Knowledge in society is often dispersed, with different individuals holding different pieces of information. Decision markets are novel mechanisms to harness this knowledge for decision-making. They combine scoring rules to reward individuals for accurate forecasts with decision rules to translate aggregated forecasts into decisions. Because of this combination, decision markets can also be viewed as voting mechanisms that tie votes on actions to forecasts of their consequences.

In preparation for a full Marsden proposal on decision markets, I would like to discuss some promising open questions on this topic:

  • What are the most interesting theoretical aspects of the proposal?
    • What really is the relation between decision markets and voting mechanisms – i.e. what framework in voting theory is best suited to compare decision markets with other voting mechanisms?
    • The decision rules in proper decision markets are stochastic – what is the most relevant literature on stochastic voting systems?
    • The forecasting functionality of decision markets resembles (to some degree) signalling of candidates intentions prior to an election. Is there theory on campaign promises and voting?
  • What are the most interesting aspects in terms of human-subjects experiments
    • Proof-of-concept: we currently don’t really have a solid one – what is the best possible experiment for this (e.g. compare to Plott’s XYZ prediction market experiments)?
    • What would be a good lab setup/scenario to compare voting and decision markets?
  • What are the most relevant implications of such a proposal
    • Can decision markets help strengthening evidence-based decision-making in a “post-truth” world?

This is really intended as “sparring” session – I’ll prepare material for about 15 min (max), and would be very grateful for critical feedback, discussion, and pointers to the literature.”

Everyone welcome!

2017 CMSS Seminars: Jiamou Liu

SpeakerJiamou Liu  (University of Auckland & CMSS Member)

Title of the talk: “How to Build Your Network? – A Structural Analysis” joint work with Anastasia Moskvina (AUT)

Date, Time and Venue: Wednesday, 5 April 2017,  2:00-3:00 pm, 260-307 [Business School Building, Level 3]

What this talk is going to be about, in Jaimou’s own words: “Creating new ties in a social network facilitates knowledge exchange and affects positional advantage. We study the process of establishing ties between a single node and an existing network in order to reach certain structural goals. We motivate this problem from two perspectives. The first perspective is socialization: we ask how a newcomer can forge relationships with an existing network to place herself at the center. The second perspective is network expansion: we investigate how a network may preserve or reduce its diameter through linking with a new node, hence ensuring small distance between its members. We then extend our discussion to the problem of network integration, which refers to the process of building links between two networks so that they dissolve into a single unified network.”

Everyone welcome!

2017 CMSS Seminars: Nina Anchugina

Speaker: Nina Anchugina (PhD Candidate, University of Auckland)

Title of the talk: “A Puzzle of Mixing Discount Functions” joint work with Matthew Ryan (AUT) and Arkadii Slinko (University of Auckland)

Date, Time and Venue: Wednesday, 15 March 2017,  2:00-3:00 pm, 206-202 [Arts 1 Building, Level 2]

What this talk is going to be about, in Nina’s own words: “This talk will introduce the concept of a “discount function” from decision theory, and discuss some results on mixtures of discount functions.  These results suggest a puzzle that we are struggling to resolve.  Your help is sought!

In decision-theory, intertemporal preferences are modelled using “discount functions”, which attach weights to different points in time at which costs or benefits might be experienced.  In reliability theory, “survival functions” describe the probability that a component survives beyond any given point in time.  Discount functions and survival functions have similar mathematical properties.  If S(t) is a survival function, its “failure rate” is given by -S'(t)/S(t).  For discount functions, the analogous quantity is known as the “time preference rate”.  For exponential functions, this rate is constant.  For hyperbolic functions, which have become popular for modelling intertemporal preferences, this rate is strictly decreasing – a phenomenon known as strictly decreasing impatience (DI).  It is well known that mixing – that is, forming convex combinations – of exponentials produces a function that exhibits strictly DI.  (The analogous result is also well known in reliability theory.) We study generalisations of this phenomenon, from which a puzzle emerges.  For example, we have not been able to prove (or disprove) that mixing an exponential function with a non-exponential function that exhibits DI will always produce a mixture that exhibits strictly DI.  Are we missing something, or do these mixtures behave very strangely?”

Everyone welcome!