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.