structural-modeling

Structural econometric estimation uses NFXP inner-loop contraction mapping or single-step MPEC formulations to translate model primitives into executable pipelines. This Skill provides end-to-end templates for both approaches, allowing you to run estimations on sample datasets.

Debugging BLP or CCP estimation requires running diagnostic checks like convergence verification and sensitivity analysis. This workflow provides structured diagnostic steps to isolate failures during the inner and outer loop estimation of dynamic structural models.

Deriving moment conditions for structural econometric models requires defining agents, information, timing, payoffs, and equilibrium concepts before coding. This workflow provides a step-by-step model specification process to formalize these primitives into moment conditions.

Yes, this workflow explicitly supports structural estimation and debugging for Rust dynamic discrete choice, BLP, CCP, and auction models. It applies model specification, moment condition derivation, and diagnostic checks across these specific econometric paradigms.

Computing standard errors after structural estimation is handled through the workflow's diagnostics and robustness phase. It performs sensitivity analysis and standard error computation to ensure reliable inference after your NFXP or MPEC estimation converges.