This dissertation formulates, solves and estimates dynamic stochastic games to answer various questions that arise in Industrial Organization. First chapter is a "theoretic" investigation of learning-by-doing and organizational forgetting that shows them to be distinct economic forces whose interplay gives rise to aggressive pricing behavior, market dominance, and multiple equilibria. The homotopy method is used to identify multiple equilibria in a systematic fashion. Second chapter is an empirical study that structurally estimates a dynamic model of the drug development process in the pharmaceutical industry, and uses counterfactual experiments to evaluate the effects of various policy interventions aimed at increasing the introduction rate of new drugs within a specific therapeutic area. I find that policies affecting the earlier stages of the drug development are less effective than those aimed at the later stages; this phenomenon stems from strategic response to policy-induced changes, and would not be observable outside a game framework. Final chapter introduces the homotopy path-following as a new method of exploring parameter space and identifying multiple equilibria in dynamic games; we believe that wider adoption of this method will substantially increase the quality of research in the field.

Last modified

• 09/07/2018

Creator

• Yaroslav Kryukov

DOI

• https://doi.org/10.21985/N2QF1W

Subject

• Economics

Keyword

• dynamic
• organization
• game
• industrial
• stochastic
• MPE

Date created

• 2008-05-09

Resource type

• Dissertation

Rights statement

• In Copyright