1st Edition
Stated Preference Methods Using R
Introduction
Stated preference methods and the role of R
Objective of this book
Overview of CV, DCEs, and BWS
Random utility theory and discrete choice models
Summary of the rest of this book
Contingent Valuation
Introduction
Overview of contingent valuation
An R package for analyzing SBDC and DBDC CV data
Parametric estimation of WTP
Nonparametric estimation of WTP
Concluding remarks
Discrete Choice Experiments
Introduction
Overview of DCEs
R functions for DCEs
Example DCEs using R
Concluding remarks
Best–Worst Scaling
Introduction
Outline of BWS
R functions for BWS
Example BWS using R
Concluding remarks
Basic Operations in R
Introduction
Getting started with R
Enhancing R
Importing and exporting data
Manipulating vectors and matrices
Data and object types
Implementing linear regression
Drawing figures
Appendix A: Other Packages Related to This Book
Appendix B: Examples of Contrivance in Empirical Studies
Bibliography
Index
Biography
Hideo Aizaki, Tomoaki Nakatani, Kazuo Sato
"This is a very useful introduction to the econometrics of stated preference methods. A very significant strength of the book is the use of R. I have been teaching this type of course for many years without the benefit of this book. I wish I had it many years ago."
—Bengt Kriström, Professor and Chair, Department of Forest Economics, Swedish University of Agricultural Sciences (SLU), and Research Director, Centre for Environmental and Resource Economics (CERE)"It is wonderful to finally see a book on how to use R to estimate the welfare measures commonly used in nonmarket valuation studies. The authors provide a set of R functions for some of the procedures most commonly used with stated preference data. Just as important, like almost all R functions, the user can see how these functions were coded as a way of understanding how they work and how new functions can be created. Using R opens up a very wide range of statistical procedures and visualization tools that will allow researchers to look at their stated preference data in new ways."
—Richard T. Carson, Professor, Department of Economics, University of California, San Diego"There are a number of very expensive statistical packages that can be used to analyze stated preference data. R is free so it is wonderful for teaching undergraduate students and others who don’t have access to expensive packages. Aizaki, Nakatani, and Sato have provided a valuable reference book for stated preference researchers and teachers who want to use R. I used the book to install R and the contingent valuation package in a few minutes. I was estimating CVM models soon afterwards. I’m especially excited that the package contains an easy-to-use nonparametric willingness to pay estimator that is superior to the spreadsheet methods I’ve been using for years. The package includes very well-known (Exxon Valdez) and less well-known (Albemarle-Pamlico) contingent valuation data. These data allow the user to play around with the package and compare results to what has been published in the literature. This book is an ideal reference for advanced undergraduate and graduate courses in environmental valuation."
—John C. Whitehead, Professor, Department of Economics, Appalachian State University
