A sample of 632 American production units

datasets

Maximum likelihood estimation of random utility discrete
choice models. The software is described in Croissant (2020)
<doi:10.18637/jss.v095.i11> and the underlying methods in
Train (2009) <doi:10.1017/CBO9780511805271>.

Yves Croissant

mlogit

Multinomial Logit Models

NOx function

A dataframe containing:<ul>
<li>chid: the plant id,</li>
<li>alt: the alternative,</li>
<li>id: the owner id,</li>
<li>choice: the
chosen alternative,</li>
<li>available: a dummy indicating that the alternative is
available,</li>
<li>env: the regulatory environment, one of <code>'regulated'</code>,
<code>'deregulated'</code> and <code>'public'</code>,</li>
<li>post: dummy for post-combustion polution control technology,</li>
<li>cm: dummy for combustion modification technology,</li>
<li>lnb: dummy for low NOx burners technology,</li>
<li>age: age of the plant (in deviation from the mean age).,</li>
<li>vcost: variable cost,</li>
<li>kcost: capital cost.</li>
</ul>

NOx: Technologies to reduce NOx emissions

Description

Arguments

Format

References