Quick Start

This page shows the constrained-program API. Read the returned constraint violation together with the estimates, because MPEC’s structural interpretation requires the Bellman constraint to be satisfied.

The public MPEC surface is the full estimator API. Create an estimator, call estimate, and read the returned summary object.

from econirl.environments.rust_bus import RustBusEnvironment
from econirl.estimation.mpec import MPECEstimator, MPECConfig
from econirl.preferences.linear import LinearUtility
from econirl.simulation import simulate_panel

env = RustBusEnvironment(
    operating_cost=0.01,
    replacement_cost=2.0,
    num_mileage_bins=20,
    discount_factor=0.99,
    seed=42,
)
panel = simulate_panel(env, n_individuals=100, n_periods=50, seed=123)
utility = LinearUtility.from_environment(env)

model = MPECEstimator(config=MPECConfig(solver="sqp"), verbose=False)
summary = model.estimate(
    panel=panel,
    utility=utility,
    problem=env.problem_spec,
    transitions=env.transition_matrices,
)

print([float(x) for x in summary.parameters])
print([float(x) for x in summary.standard_errors])
print(summary.policy.shape)
print(summary.metadata["final_constraint_violation"])

Output

[0.017559314146637917, 2.244328022003174]
[0.003141143824905157, 0.07669873535633087]
(20, 2)
9.265894274079756e-09

After fitting, the summary provides structural parameters, standard errors, a policy, a value function, a likelihood, and constrained-optimizer diagnostics.

Attribute	Meaning
`parameters`	Estimated structural reward parameters.
`standard_errors`	Standard errors for the structural parameters.
`policy`	Estimated action probabilities by state.
`value_function`	Estimated value function by state.
`log_likelihood`	Maximized constrained choice log likelihood.
`metadata`	Solver status and Bellman constraint diagnostics.

Counterfactual Example

MPEC does not currently expose the same one-call dataframe wrapper counterfactual method as NFXP and CCP. The counterfactual evidence is therefore produced through the simulation harness, which re-solves oracle Type A, Type B, and Type C counterfactuals against the recovered structural object.

See Counterfactuals for the reported counterfactual cases and Simulation Study for the generator and results file links.

Full Estimator API

Use econirl.estimation.mpec.MPECEstimator when you need direct control over panel objects, utility objects, transition tensors, constrained optimizer options, Bellman constraint tolerance, or diagnostic metadata.