| The factors which speed and slow technological innovation have been of interest to policy makers since at least the mid 1960's. Since that time, many theoretical models of innovation at the firm level and at the industry level have been proposed. Due to limitations in computational complexity, nearly all of these models have assumed a single, representative firm type. Very few have systematically investigated the implications of markets with a variety of firm types. With increases in computing power and the advent of agent-based modeling, interactions between agent types can now be explored. In this thesis, a computational model of innovative firms in competitive markets is presented. Firms devote resources to R&D which can lead to new, improved products allowing firms to steal market share from their competitors. Initially, two types of firms, differentiated by the strategies they use in pursuing new innovations, are allowed to coexist. One type pursues exclusively radical innovations, while the other pursues exclusively incremental innovations. It will be demonstrated that under certain conditions, a synergy exists between firms of different types which allows heterogeneous populations of firms to earn more than homogeneous ones. Later, firms capable of making optimal decisions are added.; Next, pollution and a government which monitors, taxes and limits pollution are added. It will be demonstrated that the model agrees qualitatively with established results from the economics of pollution control literature. In addition it will be shown that government can control pollution more effectively when firms are given time to prepare for the onset of pollution regulations rather than being surprised by them. Finally, an endogenous pollution regulation mechanism is proposed. It is demonstrated that the effects of pollution controls can vary widely across firm types. |
