Download Applications of Simulation Methods in Environmental and by Riccardo Scarpa, Anna Alberini PDF

By Riccardo Scarpa, Anna Alberini

Simulation tools are revolutionizing the perform of utilized financial research. during this ebook, major researchers from world wide speak about interpretation concerns, similarities and modifications throughout substitute versions, and suggest functional options for the alternative of the version and programming. Case reports convey the sensible use and the implications introduced forth via the several tools.

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Additional resources for Applications of Simulation Methods in Environmental and Resource Economics (The Economics of Non-Market Goods and Resources)

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We estimated a model in preference space with correlated coefficients and a model in WTP space with correlated WTP’s. The model in preference space incorporates random scale, since it allows correlation between all coefficients. The two models (in preference space and WTP space) are therefore the same in allowing for random scale and differ only in the distributional assumptions for coefficients and WTP. Both models assume a log-normal price coefficient. The model in preference space assumes normal and log-normal non-price coefficients, which implies that WTP’s are distributed as the ratio of a normal or log-normal to a log-normal.

2003). The difference can perhaps be explained by the fact that we used a somewhat 16 APPLICATIONS OF SIMULATION METHODS different method to evaluate out-of-sample fit than they did. We estimated on half the respondents using all of their choice situations and then calculated the log-likelihood for all the choice situations for the other half of the respondents, while they estimated the model on all but one choice situation for each respondent and then calculated the log-likelihood for this one “hold-out” choice situation for each respondent.

The mixed-logit model is one choice specification with this capability which we use as the model for a classical inference. 3. The Mixed Logit Model To illustrate the “mixed logit”5 model we start by assuming that a sampled individual (q = 1, . . , Q) faces a choice among J alternatives in each of T choice situations. Individual q is assumed to consider the full set of offered alternatives in choice situation t and to choose the alternative with the highest utility. 1) where xjtq is the full vector of explanatory variables, including attributes of the alternatives, socio-economic characteristics of the individual and descriptors of the decision context and choice task itself in choice situation t.

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