Learn R Programming

antitrust (version 0.99.10)

CES-class: Class “CES”

Description

The “CES” class contains all the information needed to calibrate a CES demand system and perform a merger simulation analysis under the assumption that firms are playing a differentiated Bertrand pricing game.

Arguments

Objects from the Class

Objects can be created by using the constructor function ces.

Slots

Let k denote the number of products produced by all firms.

slopes:

A list containing the coefficient on the numeraire (`alpha'), the coefficient on price (‘gamma’), and the vector of mean valuations (‘meanval’)

priceOutside:

The price of the outside good. Default is 1.

Extends

Class '>Logit, directly. Class '>Bertrand, by class '>Logit, distance 2. Class '>Antitrust, by class '>Bertrand, distance 3.

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.

calcShares

signature(object, preMerger = TRUE,revenue=FALSE)

Compute either pre-merger or post-merger equilibrium revenue shares under the assumptions that consumer demand is CES 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 CES demand parameters. Assumes that firms are currently at equilibrium in a differentiated product Bertrand Nash pricing game.
CV

signature(object, revenueInside)

Calculates compensating variation. If ‘revenueInside’ is missing, then CV returns compensating variation as a percent of the representative consumer's income. If ‘revenueInside’ equals the total expenditure on all products inside the market, then CV returns compensating variation in levels.
elast

signature(object, preMerger = TRUE)

Computes a k x k matrix of own and cross-price elasticities.

Examples

Run this code
# NOT RUN {
showClass("CES")           # get a detailed description of the class
showMethods(classes="CES") # show all methods defined for the class
# }

Run the code above in your browser using DataLab