Main entry point for BLP demand estimation.
Usage
blp_problem(
product_formulations,
product_data,
agent_formulation = NULL,
agent_data = NULL,
integration = NULL,
rc_types = NULL,
epsilon_scale = 1,
costs_type = "linear",
add_exogenous = TRUE
)Arguments
- product_formulations
List of BLPFormulation objects (1-3)
- product_data
Data frame with market_ids, shares, prices, etc.
- agent_formulation
Optional demographics formulation
- agent_data
Optional agent data frame
- integration
Optional BLPIntegration object
- rc_types
Character vector of random coefficient types
- epsilon_scale
Epsilon scaling (default 1)
- costs_type
"linear" or "log"
- add_exogenous
Whether to add exogenous regressors to instruments
Examples
if (FALSE) { # \dontrun{
# Logit model
f1 <- blp_formulation(~ prices + sugar + mushy)
problem <- blp_problem(list(f1), product_data)
results <- problem$solve()
# Random coefficients
f2 <- blp_formulation(~ prices + sugar + mushy)
problem <- blp_problem(list(f1, f2), product_data,
integration = blp_integration("product", 5))
results <- problem$solve(sigma = diag(3))
} # }