We present a dynamic extension of the classic static model of Bertrand price competition that allows competing duopolists to undertake cost-reducing investments in an attempt to “leapfrog” their rival to attain low-cost leadership – at least temporarily. We show that leapfrogging occurs in...

We define a class of dynamic Markovian games that we call directional dynamic games (DDG) in which directionality is represented by a partial order on the state space. We propose a fast and robust state recursion algorithm that can find a Markov perfect equilibrium (MPE) via backward induction...

Dynamic programming (DP) is a powerful tool for solving a wide class of sequential decision-making problems under uncertainty. In principle, it enables us to compute optimal decision rules that specify the best possible decision in any situation. This article reviews developments in DP and...

This chapter explores the numerical methods for solving dynamic programming (DP) problems. The DP framework has been extensively used in economics because it is sufficiently rich to model almost any problem involving sequential decision making over time and under uncertainty. The chapter focuses...

This chapter summarizes the ability of the models to track the shift in departure rates induced by the 1982 window plan. All forecasts were based on the estimated utility function parameters using data prior to 1982. Using these parameters, predictions were generated from all four models after...

Are the serves of the world’s best tennis pros consistent with the theoretical predictions of Nash equilibrium in mixed strategies? We analyze their serve direction choices (to the receiver’s left, right or body) with data from an online database called the Match Charting Project. Using a...