jamesbrandecon

using Plots
using StatsPlots, Turing 
using Distributions, LinearAlgebra, Random, FillArrays

Random.seed!(12334455)

# -------------------------------------------------------
# Models/functions for OLS and IV 
# Only implemented with a single RHS variable -- easy 
# to extend to multiple 

jamesbrandecon

# Basic implementation of Bayesian Logit and BLP 
# In both cases, we model the observed market shares as coming from 
# a logit model with measurement error.

using Plots
using StatsPlots
using DataFrames
using Turing, FillArrays
using LinearAlgebra, DynamicHMC

jamesbrandecon

# This file contains a basic implementation of the FKRB estimator for the random coefficients logit model in Julia. 
# In particular, it implements a constrained elastic net version of the estimator with aggregate data. 
#  -- Fox, Kim, Ryan, and Bajari (2011) https://onlinelibrary.wiley.com/doi/abs/10.3982/QE49

# Written by James Brand, 2023

# The main components of the code include:
# - The `logexpratio` function, which calculates market shares for a given parameter vector.
# - The `FKRBProblem` struct, which represents the FKRB problem and stores relevant data and results.
# - The `define_problem` function, which defines the FKRB problem based on input data and variables.