| Applications of Simulation Methods in Environmental and Resource Economics 2005 Edition Contributor(s): Scarpa, Riccardo (Editor), Alberini, Anna (Editor) |
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ISBN: 1402036833 ISBN-13: 9781402036835 Publisher: Springer OUR PRICE: $161.49 Product Type: Hardcover - Other Formats Published: August 2005 Annotation: 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. |
| Additional Information |
| BISAC Categories: - Business & Economics | Econometrics - Science | Environmental Science (see Also Chemistry - Environmental) - Business & Economics | Economics - Macroeconomics |
| Dewey: 339.49 |
| LCCN: 2006615273 |
| Series: Economics of Non-Market Goods and Resources |
| Physical Information: 1" H x 6.14" W x 9.21" (1.76 lbs) 410 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |