
We propose the backward indifference derivation (BID) algorithm, a new method to numerically approximate the pure strategy Nash equilibrium (PSNE) bidding functions in asymmetric first-price auctions. The BID algorithm constructs a sequence of finite-action PSNE that converges to the continuum-action PSNE by finding where bidders are indifferent between actions. Consequently, our approach differs from prevailing numerical methods that consider a system of poorly behaved differential equations. After proving convergence (conditional on knowing the maximum bid), we evaluate the numerical performance of the BID algorithm on four examples, two of which have not been previously addressed.
Auctions, bargaining, bidding and selling, and other market models, first-price auctions, Applications to the sciences, asymmetric auctions, numerical solutions, simulation
Auctions, bargaining, bidding and selling, and other market models, first-price auctions, Applications to the sciences, asymmetric auctions, numerical solutions, simulation
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