Transcript
  • 00:00    |    
    Initial credits
  • 00:18    |    
    Background behind the Victoria Gaming Machine Auction
    • Gaming machine history in Victoria
    • Creating a large auction-type system
    • Auction set-up
  • 09:50    |    
    Auction details
    • Purpose: Allocation of gaming machines in Victoria, Australia
    • The origin of policy constraints
    • Multidimensional system based on classic economic principles
  • 16:17    |    
    Auction system basics
    • Induced preferences: Two person auction
    • Predicting the result of a competition: The law of supply and demand
    • Lagrange multipliers: A constrained optimization problem
    • Convergence to the competitive equilibrium
    • Principles that reproduce over scales
  • 26:38    |    
    New auction system methods
    • Using bid functions instead of numbers
    • Determining efficient allocations
    • Using rounds vs. continuous systems: The stopping rule and efficient information processing
    • Forcing bid functions up: The bidding screen
  • 32:31    |    
    Nature of the demand function
  • 33:31    |    
    Key procedures and rules
  • 35:26    |    
    Revealing the slope of the demand curve
  • Revelation at the margin principle
  • 40:35    |    
    Adjusting policies into the testbed
    • Arithmetical description of the problem
    • Computing efficient allocation
    • The actual bidding page
    • Economist model of allocation
  • 45:07    |    
    Experimental testbeds
    • Studying and learning from simple cases
    • Experimental models
    • Describing competitive equilibrium revenue
    • Predicting price and quantity through models
    • Reaching competitive equilibrium
  • 51:47    |    
    The real auction
    • Auction venue and characters
    • Price discovery and total revenue
    • Observing competitive equilibrium
    • Maximum demand at a certain price
    • The demand curve revealed
    • Depiction of a constrained market
    • Area derived demands
    • The general equilibrium effect
  • 01:05:45    |    
    Lessons learned from the auction
  • Study of objections and comments
  • 01:09:20    |    
    Questions and comments section
    • Was the supply determined (politically) by bureaucrats?
    • Did machine operators pay taxes according to revenue?
    • What was involved in the political process that led to cutting the supply?
    • Did politicians want to stop the auction because of gambling concerns?
    • Was there competition across regions?
    • How many bidders were allowed per station?
    • What happens when a single owner has more than one venue?
  • 01:16:50    |    
    Final credits


Large Constrained Auctions: The Victoria Gaming Machine Auction

New Media  | 21 de febrero de 2014  | Vistas: 2734

Charles R. Plott retells his experience during the creation and implementation process of the Gaming-Machine Auction held in Victoria, Australia, in May 2010. In an attempt to achieve a more competitive allocation of gaming machine rights among the user industry, the Australian government hired Plott to create an unprecedented, large auction system. His task was to create a single-day, 10-hour auction that would ensure an effective distribution of machine rights, equally among hotel/casinos and clubs, according to strict area constraints and under rigorous political vigilance.

Plott describes the complexity of the auction set-up, and the considerations involved in making this a functional, transparent arrangement that met all of these goals. By returning to basic economics and the law of supply and demand, he explains the core principles behind the creation of the auction system. New methods of measurement and the use of bid-functions ultimately reveal a demand function at the margin, and result in one of the first-ever observations of the dynamic convergence of a system to the classical competitive equilibrium.

Despite few, irrelevant objections, the Victoria Gaming Machine Auction was completed successfully, complying with all the stringent time and policy constraints, generating predictable revenue, and serving as a crucial model in the history of experimental economics.







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