Applications of Simulation Methods in Environmental and by Kenneth Train, Melvyn Weeks (auth.), Riccardo Scarpa, Anna

By Kenneth Train, Melvyn Weeks (auth.), Riccardo Scarpa, Anna Alberini (eds.)

Simulation tools are revolutionizing the perform of utilized monetary research. This quantity collects eighteen chapters written by way of prime researchers from prestigious learn associations across the world. the typical denominator of the papers is their relevance for utilized study in environmental and source economics.

The subject matters diversity from discrete selection modeling with heterogeneity of personal tastes, to Bayesian estimation, to Monte Carlo experiments, to structural estimation of Kuhn-Tucker call for structures, to overview of simulation noise in greatest simulated chance estimates, to dynamic usual source modeling. Empirical instances are used to teach the sensible use and the consequences introduced forth via the several methods.

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Extra info for Applications of Simulation Methods in Environmental and Resource Economics

Example text

They performed out-of-sample analysis and concluded that their model in WTP space fits better out-of-sample, even though it fits worse in-sample. To examine this issue, we divided our sampled respondents into two equalsized sub-samples, estimated each model on one sub-sample, and evaluated the log-likelihood of the estimated models on the other sub-sample. In each comparison (estimation on first half with evaluation on the second half, and estimation on the second half with evaluation on the first half), the model in preference space obtained a higher log-likelihood than the model in WTP space on the out-of-estimation sub-sample.

For example, if the coefficient of an attribute is distributed normally, then WTP for that attribute, which is the attribute’s coefficient divided by the price coefficient, is also normally distributed. The mean and standard deviation of WTP are simply the mean and standard deviation of the attribute coefficient scaled by the inverse of the (fixed) price coefficient. The restriction also facilitates estimation. As Ruud (1996) points out, a model with all random coefficients, including the price coefficient, can be practically unidentified empirically, especially in datasets with only one observed choice for each decision-maker.

4. Model in WTP Space with Uncorrelated WTP’s Attribute Price in $10,000’s Operating cost in $/month Range in 100’s of miles Electric engine Hybrid engine High performance Medium or high performance Mini car Small car Large car Small SUV Midsize SUV Large SUV Compact pickup Full-sized pickup Minivan Log likelihood at convergence Parameter Estimate St. 13 tinction is that the means and especially the standard deviations of WTP’s are smaller for the model in WTP space than the model in preference space.

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