Overview
- 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
Part of the book series: The Economics of Non-Market Goods and Resources (ENGO, volume 6)
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Table of contents (18 chapters)
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Front Matter
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Back Matter
Keywords
About this book
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.
Editors and Affiliations
Bibliographic Information
Book Title: Applications of Simulation Methods in Environmental and Resource Economics
Editors: Riccardo Scarpa, Anna Alberini
Series Title: The Economics of Non-Market Goods and Resources
DOI: https://doi.org/10.1007/1-4020-3684-1
Publisher: Springer Dordrecht
eBook Packages: Business and Economics, Economics and Finance (R0)
Copyright Information: Springer Science+Business Media B.V. 2005
Hardcover ISBN: 978-1-4020-3683-5Published: 12 August 2005
Softcover ISBN: 978-90-481-6930-6Published: 28 October 2010
eBook ISBN: 978-1-4020-3684-2Published: 15 December 2005
Series ISSN: 1571-487X
Edition Number: 1
Number of Pages: XXXVI, 410
Topics: Macroeconomics/Monetary Economics//Financial Economics, Environmental Economics, Econometrics, Environmental Management