Principled Identification of Structural Dynamic Models

TL;DR

This paper introduces OASIS, a new identification scheme for structural dynamic models that optimizes a correlation-based objective, improving over traditional methods in accuracy and applicability.

Contribution

It develops a principled, objective-based approach for identifying structural models, unifying and extending existing identification schemes like recursive Cholesky and Proxy SVARs.

Findings

OASIS systematically achieves closer correlation to true shocks than recursive orderings.

Revisiting 22 SVARs shows weak correlation of reduced-form innovations, explaining robustness of recursive schemes.

Applying OASIS to proxy applications reveals shock leakage and impacts substantive conclusions.

Abstract

We take a new perspective on identification in structural dynamic models: rather than imposing restrictions alone, we optimize an objective. While definitive structural identification ultimately requires exogenous economic insight, a weighted correlation-maximizing objective yields an Order- and Scale-Invariant Scheme (OASIS) that selects the orthogonal rotation most aligned with designated target variables. In traditional SVARs, these targets are the reduced-form innovations, making OASIS a natural reference rotation. We show that recursive Cholesky identification is a constrained version of the same objective and that OASIS is systematically closer to perfect correlation, closing roughly twice as much of the gap as recursive orderings, both theoretically and empirically. The same framework also provides a principled estimation strategy for Proxy VARs (IV-SVARs), where the weighted criterion is essential for resolving overdetermination in multi-proxy systems while symmetrically accommodating proxy leakage. Revisiting 22 published SVARs, we find that reduced-form innovations are typically only weakly correlated, helping explain the historical robustness of recursive schemes. Applying OASIS to seminal proxy applications, however, reveals economically important leakage across shocks and shows that accounting for such leakage can materially alter substantive conclusions.