The “LogitNests” class contains all the information needed to
calibrate a nested Logit
demand system and perform a merger simulation analysis under the assumption that
firms are playing a differentiated products Bertrand pricing game.
Arguments
Objects from the Class
Objects can be created by using the constructor function logit.nests.
Slots
Let k denote the number of products produced by all firms.
nests:
A length k vector identifying the nest that each
product belongs to.
parmsStart:
A length k vector who elements equal an
initial guess of the nesting parameter values.
constraint:
A length 1 logical vector that equals TRUE
if all nesting parameters are constrained to equal the same value
and FALSE otherwise. Default is TRUE.
Extends
Class '>Logit, directly.
Class '>Bertrand, by class '>Logit, distance 2.
Methods
For all of methods containing the ‘preMerger’ argument, ‘preMerger’ takes
on a value of TRUE or FALSE, where TRUE invokes the method using the
pre-merger ownership structure, while FALSE invokes the method using
the post-merger ownership structure.
Compute either pre-merger or post-merger equilibrium
shares under the assumptions that consumer demand is Logit and firms play a differentiated product
Bertrand Nash pricing game. ‘revenue’ takes
on a value of TRUE or FALSE, where TRUE calculates revenue shares,
while FALSE calculates quantity shares.
calcSlopes
signature(object)
Uncover nested Logit demand
parameters. Assumes that firms are currently at equilibrium in a
differentiated product Bertrand Nash pricing game.
# NOT RUN {showClass("LogitNests") # get a detailed description of the classshowMethods(classes="LogitNests") # show all methods defined for the class# }