Three essays in regional economic impact analysis

This research examines regional economic impact analysis in the context of existing methods and innovations that contribute to the current body of research. As such, it represents a progression of knowledge in regional impact analysis. This is accomplished through a series of three related essays. The first essay identifies sectors of the economy that are most likely to be affected by blooms of harmful algae commonly referred to as red tide. It also develops a methodology for analyzing impacts of red tide events on local economies, and discusses problems and limitations. Three activities were identified as important components of the Galveston economy that were most likely to be affected by a red tide event: tourism, commercial oyster harvests, and beach cleanup costs.;In the second essay a simulation model of a local economy is created to explore the effects of probabilistic impacts on key demographic variables. The model represents the "next step" in the evolution of regional impact models. It integrates a regional input-output model with an econometric model and incorporates stochastic elements in such a way as to allow for the probabilistic analysis of demographic and labor changes in a local economy. The model represents an improvement over conventional methods in regional analysis, because the assumption of a static impact can be relaxed in a controlled manner; the effects of increased impact variability are presented in a probabilistic context.;In the third essay an existing, static model of local economies in Texas is adapted, and converted to a simulation model. Issues of stochastic relevance are explored, and a formal sensitivity analysis is performed on the primary input variables. The model represents a step toward realizing a stochastic fiscal estimation tool that can be used to explore the effects of change on local economies in Texas. The model also included a business failure module and made use of response surface methodologies. These are innovations in regional impact modeling that have not been previously explored.