Abstract
We reformulate the quality ladder model of Pakes and McGuire, Rand Journal of Economics, 25(4), 555–589 (1994) as a dynamic stochastic game with random moves in which each period one firm is picked at random to make an investment decision. Contrasting this model to the standard version with simultaneous moves illustrates the computational advantages of random moves. In particular, the quality ladder model with random moves avoids the curse of dimensionality in computing firms’ expectations over all possible future states and is therefore orders of magnitude faster to solve than its counterpart with simultaneous moves when there are more than just a few firms. Perhaps unexpectedly, the equilibria of the quality ladder model with random moves are practically indistinguishable from those of the model with simultaneous moves.
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