bertrand_calibrate: Bertrand model calibration

In mergersim: Merger Simulation and Calibration

Bertrand model calibration

Description

Bertrand model calibration

Usage

bertrand_calibrate(
  param,
  own,
  price,
  shares,
  cost,
  weight = NA,
  returnOutcomes = FALSE
)

Arguments

param	Price coefficient alpha parameter to calibrate
own	Ownership matrix
price	Price
shares	Observed market shares
cost	Marginal costs for each product
weight	Weighting vector of length equal to number of margins provided
returnOutcomes	logical; should equilibrium objects be returned (mean value parameter, prices, shares, costs) as a list.

Details

This function calculate the first-order conditions from a Bertrand price-setting model of competition. This function is only for standard logit demand. For nested logit or generalized nested logit, see bertrand_calibrate_gnl().

Value

Distance between observed values and model predicted values for prices and shares

Examples

alpha  <- -0.9
delta <- c(.81,.93,.82)
c_j <- c(.05,.31,.30)

own_pre = diag(3)

p0 <- c_j*1.1

share1 <- (exp(delta + alpha*p0))/(1+sum(exp(delta + alpha*p0)))
x00 <- c(-1)
wt_vector <- c(1,1,1)

bertrand_calibrate( param = x00,
                    own = own_pre, price = p0,
                    shares = share1, cost  = c_j,
                    weight = wt_vector)

mergersim documentation built on July 21, 2026, 5:09 p.m.