Applications of Simulation Methods in Environmental and Resource Economics

ISBN-13: 9789048169306 / Angielski / Miękka / 2010 / 410 str.

Riccardo Scarpa; Anna Alberini

Opis

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.

Spis treści

Introduction. Anna Alberini and Riccardo Scarpa.- 1. Models in preference space and WTP space. Kenneth Train and Melvyn Weeks.- 2. Classical simulation-based estimators to estimate individual WTP. William H. Greene et al.- 3. Heterogeneity in the cost of power outages. David F. Layton and Klaus Molmer.- 4. Capturing correlation and taste heterogeneity with mixed GEV models. Stephane Hess et al.- 5. Analysis of agri-environmental payment programs. Joseph Cooper.- 6. Multinomial logit vs. probit models. Andreas Ziegler.- 7. Mixed logit with bounded distributions of correlated partworths. Kenneth Train and Garrett Sonnier.- 8. Kuhn-Tucker demand system approaches to non market valuation. Roger H. van Haefen, Daniel J. Paneuf.- 9. Hierarchical analysis of production efficiency. Garth Halloway et al.- 10. Bayesian approaches to modeling stated preference data. David F. Layton and Richard A. Levine.- 11. Bayesian estimation of DC CV with follow-up. Jorge E. Araña and Carmelo J. León.- 12. Modeling elicitation effects in contingent valuation studies. Margarita Genius and Elisabetta Strazzera.- 13. Performance of error component models for status-quo effects. Riccardo Scarpa et al.- 14. Dynamic Optimization in large scale simulation models. Richard T. Woodward et al.- 15. Estimation of discrete dynamic decision processes. Bill Provencher and Kenneth A. Baerenklau.- 16. Monte Carlo methods in environmental economics. Giovanni Baiocchi.- 17. Gaussian quadrature versus simulation. William S. Breffle et al.- 18. Simulation noise and the estimation of land use decisions. John McPeak.- References. Index.