Valuing Nature with Travel Cost Models
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Valuing Nature with Travel Cost Models

A Manual

Frank A. Ward and Diana Beal

The book presents a self-contained treatment of TCM along with a wide range of applications to natural resource and environmental policy questions.
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Chapter 5: Design Principles for TCMs

Frank A. Ward and Diana Beal


Page 128 5—  Design Principles for TCMs We study history to learn from past experience. To a recreation demand modeler this means we build TCMs to analyse what visitors did, so we can learn what they  will do in the future. But we don't build a TCM just to predict what visitors will do if current trends continue. We build it to find out what they will do under one or  more proposed policies. Then, if we are good listeners and good communicators, we explain those predictions to decisionmakers so that they can formulate an  appropriate set of decisions among the many possible choices they face. Building models ensures that our data are organized so that we can exploit its relationships. We then use our knowledge of those historical relationships to predict the  past and thus check the usefulness of the model by comparing the predictions with our knowledge of what actually occurred. If the predictions are good, we are able  to design better futures provided the structure doesn't change. This book assumes that models will normally be quantitative and estimated through regression models. What it means to predict the past accurately needs little  elaboration. We use the independent variables of our TCM regression model in conjunction with its algebraic function to predict the behavior we actually saw. We  want to estimate a TCM for which price, income, site characteristics and demographic factors predict recorded trips. We can use the model then to construct  counterfactual histories of the past by...

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