| Title: | A Graphical User Interface for Antitrust and Trade Practitioners |
|---|---|
| Description: | A graphical user interface for simulating the effects of mergers, tariffs, and quotas under an assortment of different economic models. The interface is powered by the 'Shiny' web application framework from 'RStudio'. |
| Authors: | Charles Taragin [aut, cre], Kenneth Rios [aut], Paulette Wolak [aut] |
| Maintainer: | Charles Taragin <[email protected]> |
| License: | CC0 |
| Version: | 0.7.1 |
| Built: | 2024-11-20 03:19:59 UTC |
| Source: | https://github.com/luciu5/competitiontoolbox |
Launch a shiny interface to simulate the effects of tariffs and mergers
antitrust_shiny()antitrust_shiny()
antitrust_shiny calls ct_shiny, which is a shiny interface for the antitrust
and trade package. See ct_shiny for further details.
Launch a shiny interface to simulate the effects of tariffs and mergers
ct_shiny()ct_shiny()
ct_shiny launches a shiny interface for the antitrust and trade packages.
The shiny interface provides users with the ability to calibrate model parameters and simulate
tariff effects using many of the supply and demand models included in the trade package. It
also provides users with the ability to calibrate different consumer demand systems and simulate the
effects of mergers under different competitive regimes included in the antitrust package.
Charles Taragin, Paulette Wolak
if(interactive()){ct_shiny()}if(interactive()){ct_shiny()}
A dataset containing the summary statistics necessary to make boxplots according to supply, demand, and percent of outside share for horizontal mergers. This allows for examination of the relationship between industry price changes and commonly used merger indices.
indicboxdataindicboxdata
A data frame with 2,303 rows and 10 variables
Firm Count, HHI, Delta HHI, UPP, CMCR, Harm 2nd, Party Gap
axis units depending on Cut_type
outside share threshold in percent (20–70)
pooled, bertrand, cournot, auction
pooled, log, logit, aids, ces, linear
maximum
minimum
25th percentile boxplot line
50th percentile boxplot line
75th percentile boxplot line
Taragin, C., & Loudermilk, M. (2019). Using measures of competitive harm for optimal screening of horizontal mergers. mimeo.doi:10.13140/RG.2.2.30872.85760/1.
A dataset containing the information necessary to calculate the number of merger simulations used to generate the plots for the "Indices" tab of "Numerical Simulations" for Horizontal Mergers based on the index of interest.
indicboxmktCntindicboxmktCnt
A data frame with 35 rows and 3 variables
Firm Count, HHI, Delta HHI, UPP, CMCR, Harm 2nd, Party Gap
number of horizontal merger simulations (25,890 – 184,254)
outside share threshold in percent (20–70)
Taragin, C., & Loudermilk, M. (2019). Using measures of competitive harm for optimal screening of horizontal mergers. mimeo.doi:10.13140/RG.2.2.30872.85760/1.
A dataset containing the summary statistics necessary to make boxplots according to supply, demand, and percent of outside share for horizontal mergers so as to examine the distribution of outcomes.
sumboxdatasumboxdata
A data frame with 210 rows and 10 variables
log, logit, aids, ces, linear
cournot:log, cournot: linear, bertrand:aids, bertrand:logit, bertrand:ces, auction:logit
post-Merger index of interest (Industry Price Change (percent), Merging Party Price Change (percent), Consumer Harm (dollars), Producer Benefit (dollars), Net Harm (dollars)
bertrand, cournot, auction
maximum
minimum
25th percentile boxplot line
50th percentile boxplot line
75th percentile boxplot line
outside share threshold in percent (20–70)
Taragin, C., & Loudermilk, M. (2019). Using measures of competitive harm for optimal screening of horizontal mergers. mimeo.doi:10.13140/RG.2.2.30872.85760/1.
A dataset containing the summary statistics necessary to make boxplots according to supply, demand, and tariff percentage for tariffs so as to examine the distribution of outcomes.
sumboxdata_tradesumboxdata_trade
A data frame with 162 rows and 10 variables
Linear, CES, Logit
Cournot:Linear, Bertrand:CES, Bertrand:Logit, Auction2nd:Logit, Bargaining:Logit, Monopolistic Competition:CES, Monopolistic Competition:Logit
Consumer Harm, Domestic Firm Benefit, Foreign Firm Harm, Industry Price Change, Net Domestic Harm, Net Total Harm, Domestic Firm Price Change, Foreign Firm Price Change
Cournot, Bertrand, Auction2nd, Bargaining, Monopolistic Competition
maximum
minimum
25th percentile boxplot line
50th percentile boxplot line
75th percentile boxplot line
tariff threshold in percent (10–30)
Taragin, C., & Loudermilk, M. (2019). Using measures of competitive harm for optimal screening of horizontal mergers. mimeo.doi:10.13140/RG.2.2.30872.85760/1.
A dataset containing the information necessary to calculate the number of merger simulations used to generate the plots for the Summary tab of Numerical Simulations for Horizontal Mergers.
sumboxmktCntsumboxmktCnt
A data frame with 30 rows and 3 variables
post-Merger indice of interest (Industry Price Change (percent), Merging Party Price Change (percent), Consumer Harm (dollars), Producer Benefit (dollars), Net Harm (dollars)
number of horizontal merger simulations
outside share threshold in percent (20–70)
Taragin, C., & Loudermilk, M. (2019). Using measures of competitive harm for optimal screening of horizontal mergers. mimeo.doi:10.13140/RG.2.2.30872.85760/1.
A dataset containing the information necessary to calculate the number of tariffs used to generate the plots for the Summary tab of Numerical Simulations for Tariffs.
sumboxmktCnt_tradesumboxmktCnt_trade
A data frame with 24 rows and 3 variables
Consumer Harm, Domestic Firm Benefit, Foreign Firm Harm, Industry Price Change, Net Domestic Harm, Net Total Harm, Domestic Firm Price Change, Foreign Firm Price Change
number of tariffs simulated
tariff threshold in percent (10–30)
Taragin, C., & Loudermilk, M. (2019). Using measures of competitive harm for optimal screening of horizontal mergers. mimeo.doi:10.13140/RG.2.2.30872.85760/1.
Launch a shiny interface to simulate the effects of tariffs and mergers
trade_shiny()trade_shiny()
trade_shiny calls ct_shiny, which is a shiny interface for the antitrust
and trade package. See ct_shiny for further details.