data_rec

<p>Data from 2000 individuals from the Value of Nature to Canadians (VNC) survey.
The travel costs are calculated using the approach described in Lloyd-Smith (2020)</p>

datasets

Estimates and simulates Kuhn-Tucker demand models with individual heterogeneity. The package implements the multiple-discrete continuous extreme value (MDCEV) model and the Kuhn-Tucker specification common in the environmental economics literature on recreation demand. Latent class and random parameters specifications can be implemented and the models are fit using maximum likelihood estimation or Bayesian estimation. All models are implemented in Stan, which is a C++ package for performing full Bayesian inference (see Stan Development Team, 2019) <http://mc-stan.org>. The package also implements demand forecasting (Pinjari and Bhat (2011) <https://repositories.lib.utexas.edu/handle/2152/23880>) and welfare calculation (Lloyd-Smith (2018) <doi.org/10.1016/j.jocm.2017.12.002>) for policy simulation.

Patrick Lloyd-Smith

rmdcev

Kuhn-Tucker and Multiple Discrete-Continuous Extreme Value
Models

Trustees of Columbia University

data_rec function

<p>A tibble with 34000 rows and 8 variables</p>

data_rec: Recreation data from Value of Nature to Canadians Survey

Description

Usage

Arguments

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References