This study analyzes the economic and geographic effects of alternative locations on risky investment decisions in a probabilistic framework. Historically, alternative locations for multi-million dollar investments are often evaluated with deterministic models that rely on expected values or best case/worst case scenarios. Stochastic simulation was used to estimate the probability distribution for select key output variables, including net present value (NPV), of a proposed biomass to ethanol production facility in three alternative regions in Texas. The simulated NPV probability distributions were compared using Stochastic Efficiency with Respect to a Function (SERF) to predict the location preference of decision makers with alternative levels of risk aversion. Risk associated with input availability and costs were analyzed for the proposed plant locations so each location resulted in different levels of economic viability and risk that would not have been observed with a traditional deterministic analysis. For all analyzed scenarios, the projected financial feasibility results show a positive NPV over the 16 year planning horizon with a small probability of being negative. The SERF results indicate the Central Region of Texas is preferred for risk averse decision makers compared to the Panhandle and Coastal Bend Regions. Risk premiums were calculated for the alternative locations and are consistent for all risk averse decision makers, indicating the ranking of alternative locations are robust. Positive community impacts and sensitivity elasticities for key variables were estimated in the model. The estimated positive economic gains for the local economy are quite large and indicate locating a production facility in the region could substantially impact the local economy. The calculated sensitivity elasticities show ethanol price, ethanol yield, and hydrogen price are the three variables that have the greatest affect on the feasibility of a biomass to ethanol production facility.
