auction2nd_tariff {trade}

Tariff Simulation With A Second Score Procurement Auction Game

Description

Simulate the effect of tariffs when firms play a second score procurement auction game and consumer demand is Logit.

Usage

auction2nd_tariff(
  demand = c("logit"),
  prices,
  quantities,
  margins,
  owner = NULL,
  mktElast = NA_real_,
  diversions,
  tariffPre = rep(0, length(quantities)),
  tariffPost = rep(0, length(quantities)),
  priceStart,
  parmStart,
  control.slopes,
  control.equ,
  labels = paste("Prod", 1:length(quantities), sep = ""),
  ...
)

Arguments

demand

A character vector indicating which demand system to use. Currently allows logit (default).

prices

A length k vector product prices.

quantities

A length k vector of product quantities.

margins

A length k vector of product margins. All margins must be in levels (not w.r.t to price), or NA.

owner

EITHER a vector of length k whose values indicate which firm produced a product before the tariff OR a k x k matrix of pre-merger ownership shares.

mktElast

A negative number equal to the industry pre-merger price elasticity. Default is NA .

diversions

A k x k matrix of diversion ratios with diagonal elements equal to -1. Default is missing, in which case diversion according to revenue share is assumed.

tariffPre

A vector of length k where each element equals the current ad valorem tariff (expressed as a proportion of the consumer price) imposed on each product. Default is 0, which assumes no tariff.

tariffPost

A vector of length k where each element equals the new ad valorem tariff (expressed as a proportion of the consumer price) imposed on each product. Default is 0, which assumes no tariff.

priceStart

For aids, a vector of length k who elements equal to an initial guess of the proportional change in price caused by the merger. The default is to draw k random elements from a [0,1] uniform distribution. For ces and logit, the default is prices.

parmStart

aids only. A vector of length 2 whose elements equal to an initial guess for each "known" element of the diagonal of the demand matrix and the market elasticity.

control.slopes

A list of optim control parameters passed to the calibration routine optimizer (typically the calcSlopes method).

control.equ

A list of BBsolve control parameters passed to the non-linear equation solver (typically the calcPrices method).

labels

A k-length vector of labels.

...

Additional options to feed to the BBsolve optimizer used to solve for equilibrium prices.

Details

Let k denote the number of products produced by all firms. Using price, and quantity, information for all products in each market, as well as margin information for at least one products in each market, auction2ndtariff is able to recover the slopes and intercepts of a Logit, CES, demand system. These parameters are then used to simulate the price effects of an ad valorem tariff under the assumption that the firms are playing a 2nd score auction.

Value

auction2ndtariff returns an instance of class Tariff2ndLogit

References

Simon P. Anderson, Andre de Palma, Brent Kreider, Tax incidence in differentiated product oligopoly, Journal of Public Economics, Volume 81, Issue 2, 2001, Pages 173-192.

See Also

bertrand_tariff to simulate the effects of a tariff under a Bertrand pricing game and monopolistic_competition_tariff to simulate the effects of a tariff under monopolistic competition.

Examples

## Calibration and simulation results from a 10% tariff on non-US beers "OTHER-LITE"
## and "OTHER-REG"
## Source: Epstein/Rubenfeld 2004, pg 80

prodNames <- c("BUD","OLD STYLE","MILLER","MILLER-LITE","OTHER-LITE","OTHER-REG")
owner <-c("BUD","OLD STYLE","MILLER","MILLER","OTHER-LITE","OTHER-REG")
price    <- c(.0441,.0328,.0409,.0396,.0387,.0497)
quantities   <- c(.066,.172,.253,.187,.099,.223)*100
margins <- c(.3830,.5515,.5421,.5557,.4453,.3769) # margins in terms of price
margins <- margins*price # dollar margins
tariff <- c(0,0,0,0,.1,.1)

names(price) <-
 names(quantities) <-
 names(margins) <-
 prodNames


result.2nd <- auction2nd_tariff(demand = "logit",prices=price,quantities=quantities,
                                margins = margins,owner=owner,
                                 tariffPost = tariff, labels=prodNames)

print(result.2nd)           # return predicted price change
summary(result.2nd)         # summarize merger simulation