BLS Working Papers An Anticipative Feedback Solution for the Infinite-Horizon

BLS Working Papers An Anticipative Feedback Solution for the Infinite-Horizon by Baoline Chen is published by CreateSpace Independent Publishing Platform in August 2013. This 32-page work is presented in English and explores the application of dynamic Stackelberg games, particularly focusing on infinite-horizon, linear-quadratic dynamic Stackelberg (LQDS) games. The book discusses how these games serve as effective tools for analyzing economic behavior in equilibrium settings where a dominant player exists.
Readers will find a detailed examination of the use of LQDS games in various economic contexts, including non-competitive market behavior and macroeconomic policy design. The text references notable studies in the field, illustrating the anticipative feedback solution within a hypothetical industry setting. This work is relevant for those interested in business and economics, particularly in understanding the dynamics of economic interactions and policy implications.
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Dynamic Stackelberg (or leader-follower) games are useful tools for studying dynamic economic behavior in equilibrium settings in which some player is dominant. Because of their tractability, infinite- horizon, linear-quadratic, dynamic, Stackelberg (LQDS) games have received particular attention. LQDS games have been used to study non- competitive behavior in specific markets and to evaluate and design macroeconomic policies. For example, Sargent (1985) contains studies of energy markets based on LQDS games; Kydland and Prescott (1977) and Fischer (1980) studied optimal tax policy using DS games; Canzoneri and Gray (1985), Miller and Salmon (1985), and Turnovsky, Basar, and d’Orey (1988) studied international macroeconomic policy coordination using DS games; section 4 illustrates the present anticipative feedback solution in a LQDS game of a hypothetical industry. The anticipative feedback solution could be applied to the LQ approximation of any dynamic economic setting with a dominant agent.
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