Applications of Simulation Methods in Environmental and Resource Economics

Simulation methods are revolutionizing the practice of applied economic analysis. This volume collects eighteen chapters written by leading researchers from prestigious research institutions the world over. The common denominator of the papers is their relevance for applied research in environmental and resource economics.

The topics range from discrete choice modeling with heterogeneity of preferences, to Bayesian estimation, to Monte Carlo experiments, to structural estimation of Kuhn-Tucker demand systems, to evaluation of simulation noise in maximum simulated likelihood estimates, to dynamic natural resource modeling. Empirical cases are used to show the practical use and the results brought forth by the different methods.

Useful for practioners and students wishing to apply simulation methods for estimation and optimization purposes Discusses interpretation issues, similarities and differences across alternative models, propose practical solutions for the choice of the model and programming Caters to a wide variety of models and applications

Contenu
Discrete Choice Models in Preference Space and Willingness-to-Pay Space.- Using Classical Simulation-Based Estimators to Estimate Individual WTP Values.- The Cost of Power Outages to Heterogeneous Households.- Capturing Correlation and Taste Heterogeneity with Mixed GEV Models.- Analysis of Agri-Environmental Payment Programs.- A Comparison Between Multinomial Logit and Probit Models.- Mixed Logit with Bounded Distributions of Correlated Partworths.- Kuhn-Tucker Demand System Approaches to Non-Market Valuation.- Hierarchical Analysis of Production Efficiency in a Coastal Trawl Fishery.- Bayesian Approaches to Modeling Stated Preference Data.- Bayesian Estimation of Dichotomous Choice Contingent Valuation with Follow-Up.- Modeling Elicitation Effects in Contingent Valuation Studies.- Performance of Error Component Models for Status-Quo Effects in Choice Experiments.- DPSIM Modelling: Dynamic Optimization in Large Scale Simulation Models.- An Exposition of Structural Estimation of Discrete Dynamic Decision Processes.- Monte Carlo Methods in Environmental Economics.- Gaussian Quadrature Versus Simulation for the Estimation of Random Parameters.- Simulation Noise and the Estimation of Land Use Decisions in Kenya.