Package 'entrymodels'

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

---