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Kuhn-Tucker and Multiple Discrete-Continuous Extreme Value Model Estimation and Simulation in R: The rmdcev Package

Date

2020

Authors

Lloyd-Smith, Patrick

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The R Foundation

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Article

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Abstract

This paper introduces the package rmdcev in R for estimation and simulation of Kuhn-Tucker demand models with individual heterogeneity. The models supported by rmdcev are the multiple-discrete continuous extreme value (MDCEV) model and 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. The rmdcev package also implements demand forecasting and welfare calculation for policy simulation. The purpose of this paper is to describe the model estimation and simulation framework and to demonstrate the functionalities of rmdcev using real datasets.

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Starting from 2017, all published articles are licensed under the Creative Commons Attribution 4.0 International license (CC BY 4.0, http://creativecommons.org/licenses/by/4.0.

Keywords

rmdcev, R programming, Kuhn-Tucker demand model, multiple-discrete continuous extreme value (MDCEV) model, policy simulation

Citation

lloyd-smith (2020). Kuhn-Tucker and Multiple Discrete-Continuous Extreme Value Model Estimation and Simulation in R: The rmdcev Package. The R Journal, Vol. 12/2. ISSN 2073-4859

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Citation

lloyd-smith (2020). Kuhn-Tucker and Multiple Discrete-Continuous Extreme Value Model Estimation and Simulation in R: The rmdcev Package. The R Journal, Vol. 12/2. ISSN 2073-4859

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