Type: Package
Title: Estimate Entry Models
Version: 0.2.1
Maintainer: Guilherme Jardim <gnjardim1@gmail.com>
Description: Tools for measuring empirically the effects of entry in concentrated markets, based in Bresnahan and Reiss (1991) https://www.jstor.org/stable/2937655.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: stats, magrittr, dplyr, readr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2020-05-06 12:53:59 UTC; gjardim
Author: Guilherme Jardim [aut, cre], Arthur Bragança [ctb], Pedro Fernandes [ctb]
Repository: CRAN
Date/Publication: 2020-05-06 13:20:03 UTC

Build our auxiliary matrices to estimate entry models

Description

Build our auxiliary matrices to estimate entry models

Usage

aux_matrix(data, y, N_max, n)

Arguments

data

A data.frame object containing your data

y

A string indicating the outcome variable

N_max

An integer indicating the maximum number of competitors

n

Number of observations in data

Value

A list of the auxiliary matrices

Build our optimization function

Description

Build our optimization function

Usage

br1(params, n, N_max, l_params, A1, A2, S, N)

Arguments

params

Parameters to construct function

n

Number of observations in data

N_max

An integer indicating the maximum number of competitors

l_params

Length of parameters vector

A1

Auxiliary matrix A1

A2

Auxiliary matrix A2

S

Size of the market

N

Vector of zeros

Value

The function to be optimized

Build our optimization function

Description

Build our optimization function

Usage

br2(params, n, N_max, A1, A2, S1, S2, N)

Arguments

params

Parameters to construct function

n

Number of observations in data

N_max

An integer indicating the maximum number of competitors

A1

Auxiliary matrix A1

A2

Auxiliary matrix A2

S1

First variable for size of the market

S2

Second variable for size of the market

N

Vector of zeros

Value

The function to be optimized

Two-Variable Entry Model

Description

Estimate entry model with two variables for the market size.

Usage

em_2var(data, Sm1, Sm2, y, N_max = 5, alpha0 = rep(0.1, N_max),
  gamma0 = rep(1, N_max))

Arguments

data

A data.frame object containing your data

Sm1

A string indicating the main market size variable, present in data

Sm2

A string indicating the second market size variable, present in data

y

A string indicating the outcome variable, present in data

N_max

An integer indicating the maximum number of competitors. Defaults to 5.

alpha0

A vector of type numeric and length N_max indicating the initial condition for alpha. Defaults to a vector of 0.1's.

gamma0

A vector of type numeric and length N_max indicating the initial condition for gamma. Defaults to a vector of 1's.

Value

A tibble with critical market sizes and estimated parameters, as explained in Bresnahan and Reiss (1991)

Author(s)

Guilherme N. Jardim, Department of Economics, Pontifical Catholic University of Rio de Janeiro

References

Bresnahan, T. F., & Reiss, P. C. (1991). Entry and competition in concentrated markets. Journal of political economy, 99(5), 977-1009.

Examples

tb <- data.frame(Sm1 = 1:5, Sm2 = 1:5, y = 1:5)

# estimate default model
em_n5 <- em_2var(tb, "Sm1", "Sm2", "y")

# estimate model with 3 competitors only
em_n3 <- em_2var(tb, "Sm1", "Sm2", "y", N_max = 3)


## Not run: 
# estimate model with different initial conditions
em_difc <- em_2var(tb, "Sm1", "Sm2", "y", alpha0 = rep(0.2, 5), gamma0 = rep(1.1, 5))

# estimate model with example data
tb <- load_example_data()
em <- em_2var(tb, "Populacao", "RendaPerCapita", "n_agencias")

## End(Not run)

Basic Entry Model

Description

Estimate basic entry model with only one variable for the market size.

Usage

em_basic(data, Sm, y, N_max = 5, alpha0 = rep(0.1, N_max),
  gamma0 = rep(1, N_max))

Arguments

data

A data.frame object containing your data

Sm

A string indicating the market size variable, present in data

y

A string indicating the outcome variable, present in data

N_max

An integer indicating the maximum number of competitors. Defaults to 5.

alpha0

A vector of type numeric and length N_max indicating the initial condition for alpha. Defaults to a vector of 0.1's.

gamma0

A vector of type numeric and length N_max indicating the initial condition for gamma. Defaults to a vector of 1's.

Value

A tibble with critical market sizes and estimated parameters, as explained in Bresnahan and Reiss (1991)

Author(s)

Guilherme N. Jardim, Department of Economics, Pontifical Catholic University of Rio de Janeiro

References

Bresnahan, T. F., & Reiss, P. C. (1991). Entry and competition in concentrated markets. Journal of political economy, 99(5), 977-1009.

Examples

tb <- data.frame(Sm = 1:5, y = 1:5)

# estimate default model
em_n5 <- em_basic(tb, "Sm", "y")

# estimate model with 3 competitors only
em_n3 <- em_basic(tb, "Sm", "y", N_max = 3)


## Not run: 
# estimate model with different initial conditions
em_difc <- em_basic(tb, "Sm", "y", alpha0 = rep(0.2, 5), gamma0 = rep(1.1, 5))

# estimate model with example data
tb <- load_example_data()
em <- em_basic(tb, "Populacao", "n_agencias")

## End(Not run)

Load example dataset

Description

Load example dataset

Usage

load_example_data()

Value

Example dataset as tibble

Author(s)

Guilherme N. Jardim, Department of Economics, Pontifical Catholic University of Rio de Janeiro

mirror server hosted at Truenetwork, Russian Federation.