# stackelberg_solver: Stackelberg Duopoly with numeric solution In Recon: Computational Tools for Economics

## Description

This function numerically finds the equilibrium in a Stackelberg duopoly model with linear functions. For guaranteed existence of equilibrium, cost parameters should be non-negative. The general functional form for a function of argument x is f(x) = p_0 + p_1 x. Parameters p refer to the inverse demand function. The firm indexed by "l" is the leader, and the one indexed by "f" is the follower.

## Usage

 ```1 2``` ```stackelberg_solver(leader = c(0, 1), follower = c(0, 1), demand = c(0, -1), l0 = 0, f0 = 0) ```

## Arguments

 `leader` vector of coefficients of the leader's cost function which in order must be: intercept of leader's cost function and linear term's parameter of leader's cost function `follower` vector of coefficients of the follower's cost function which in order must be: intercept of intercept of follower's cost function linear term's parameter of follower's cost function `demand` vector of coefficients of the market demand curve. Must be, in order, intercept and linear coefficient. `l0` Initial guess for leader's output. Defaults to 0. Strongly advised not to set this parameter unless you are very aware of what you're doing. `f0` Initial guess for follower's output. Defaults to 0. Strongly advised not to set this parameter unless you are very aware of what you're doing.

## Value

A list with market price, firm output, profits and market share

## Author(s)

Pedro Cavalcante Oliveira, Department of Economics, Fluminense Federal University pedrocolrj@gmail.com

## Examples

 ```1 2 3 4``` ```l = c(100, 4) f = c(120, 5) p = c(300, -10) stackelberg_solver(leader = l, follower = f, demand = p) ```

Recon documentation built on July 30, 2019, 9:03 a.m.