antitrust (version 0.99.10)

LogLin-class: Class “LogLin”

Description

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

Objects from the Class

Objects can be created by using the constructor function loglin.

Slots

symmetry:

If TRUE, requires the matrix of demand slope coefficients to be consistent with utility maximization theory Default is FALSE

Extends

Class '>Linear, directly. Class '>Bertrand, by class '>Linear, 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.

calcPrices

signature(object, preMerger = TRUE)

Compute either pre-merger or post-merger equilibrium prices under the assumptions that consumer demand is Log-Linear and firms play a differentiated product Bertrand Nash pricing game.

calcPriceDeltaHypoMon

signature(object,prodIndex,...)

Calculates the price changes that a Hypothetical Monopolist would impose on its products relative to pre-merger prices.

calcQuantities

signature(object, preMerger = TRUE)

Compute either pre-merger or post-merger equilibrium quantities under the assumptions that consumer demand is Log-Linear and firms play a differentiated product Bertrand Nash pricing game.

calcSlopes

signature(object)

Uncover slopes and intercept from a Log-Linear demand system. Assumes that firms are currently at equilibrium in a differentiated product Bertrand Nash pricing game.

elast

signature(object, preMerger = TRUE)

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

Examples

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