Identifiability and estimation of possibly non-invertible SVARMA Models: The normalised canonical WHF parametrisation
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可能不可逆 SVARMA 模型的识别与估计：规范化典范 WHF 参数化
- 研究问题
- 对于可能不可逆、包含移动平均结构的 SVARMA 模型，如何实现参数化、识别和似然估计，并刻画经济主体与观察者的信息不对称？
- 方法与思路
- 作者用 Wiener–Hopf 分解表示移动平均多项式矩阵，研究最大或准最大似然估计，并在宏观应用中比较隐含脉冲响应。
- 材料陈述的贡献
- 摘要称，方法容纳不可逆性，给出估计量渐近正态性的底层条件及得分和信息矩阵表达式，并提供文档化的 R 包。
- 阅读关注点
- 应核对规范化如何解决识别问题、不可逆结构与信息不对称的对应关系、似然估计条件，以及应用中脉冲响应差异的来源。
- 阅读边界
- 仅依据所给 OpenAlex 摘要；具体识别条件、模型选择及应用数值未说明，不能据此认定该模型普遍优于 SVAR 或 DSGE。
原文摘要
This article focuses on the parametrisation, identifiability, and (quasi-) maximum likelihood (QML) estimation of possibly non-invertible structural vector autoregressive moving average (SVARMA) models. SVAR models are routinely adopted due to their well-known implementation strategy. However, for various economic and statistical reasons, multivariate SVARMA settings are often more suitable. These settings introduce complexity in the analysis, primarily due to the presence of the moving average (MA) polynomial. We propose a novel representation of the MA polynomial matrix using the Wiener–Hopf factorization (WHF). A significant advantage of the WHF is its ability to handle possible non-invertibility and thus models with informational asymmetry between economic agents and outside observers. Since solutions of Dynamic Stochastic General Equilibrium (DSGE) models often involve this informational asymmetry, SVARMA models in WHF parametrisation can be considered data-driven alternatives to DSGE models and used for their evaluation. Furthermore, we provide low-level conditions for the asymptotic normality of the (Q)ML estimator and analytic expressions for the score and information matrix. As application, we estimate the Blanchard and Quah model, and compare our results and implied impulse response function with the ones in the SVAR model by Blanchard and Quah and a non-invertible SVARMA model by Gouriéroux and co-authors. Importantly, we have implemented this novel method in a well-documented R-package, making it readily accessible for researchers and practitioners.