Robust structural analysis when theoretical information is scarce

理论信息匮乏时的稳健结构分析

• 批准号: 504720211
• 负责人: Professor Dr. Helmut Herwartz
• 金额: --
• 依托单位: Lehrstuhl für Ökonometrie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/504720211?language=en
• 关键词: Robust; structural; analysis; when; theoretical

The identification of structural relations in dynamic systems requires external information (e.g. theory-based restrictions, instrumental variables). To support structural analysis in cases where such information is scant or hardly available, a viable literature has emerged on data-based identification that relies on stochastic characteristics of orthogonal shocks, e.g. heteroskedasticity or independence of non-Gaussian shocks. To detect independent components, several suggestions have been made that differ, for instance, with regard to parametric rigour. The pseudo-maximum-likelihood approach of Gourieroux, Monfort and Renné (2017) is of particular appeal, as it allows robust estimation of structural relations under conditions that regulate, for instance, the “extent” of misspecification. Yet, the fact remains that actual misspecification is always unknown to the analyst. In this project we first develop kernel-maximum-likelihood estimation of structural parameters as an alternative to parametric pseudo-maximum-likelihood that promises robust estimation under much weaker conditions. Second, the new approach will be used to unravel the scope of both deterministic (structural breaks) and stochastic changes (Markov switching) in the transmission from latent shocks to observables. Third, we suggest kernel-maximum-likelihood as a conceptual framework to account for singular systems, in which observables are driven by a smaller number of (independent) shocks. Fourth, in addition to econometric advances, this project contributes to important topics of current macroeconomic research. On the one hand, each developed econometric tool is employed to achieve an improved understanding of global oil market shocks and their effects. On the other hand, we employ an ensemble of the planned econometric advances to identify information effects of monetary policy announcements of the central bank. Finally, the ensemble approach will serve as a core yardstick for the development of a novel software package that summarizes relevant information contained in central banks announcements in (almost) real-time to unravel the state of monetary policy (both in the US and the Euro-Area) and its potential macroeconomic implications.

动态系统中结构关系的识别需要外部信息（例如基于理论的限制，工具变量）。为了在这种信息很少或难以获得的情况下支持结构分析，出现了一种基于数据的识别的可行文献，这种识别依赖于正交冲击的随机特性，例如非高斯冲击的异方差性或独立性。为了检测独立分量，已经提出了几个不同的建议，例如，关于参数的严格性。Gourieroux，Monfort和Renné（2017）的伪最大似然方法特别有吸引力，因为它允许在调节条件下对结构关系进行鲁棒估计，例如，错误指定的“程度”。然而，事实仍然是，实际的错误规范总是未知的分析师。在这个项目中，我们首先开发核最大似然估计的结构参数作为替代参数的伪最大似然，承诺在更弱的条件下的鲁棒估计。第二，新的方法将被用来解开的范围内的确定性（结构性突变）和随机变化（马尔可夫转换）的传输从潜在的冲击，以观察。第三，我们建议核最大似然作为一个概念框架来解释奇异系统，其中可观的是由较少数量的（独立）冲击。第四，除了计量经济学的进步，这个项目有助于当前宏观经济研究的重要课题。一方面，每一个发达的计量经济学工具，以实现更好地了解全球石油市场的冲击及其影响。另一方面，我们采用计划的计量经济学进步的合奏，以确定中央银行的货币政策公告的信息效应。最后，集成方法将作为开发一个新软件包的核心尺度，该软件包（几乎）实时总结中央银行公告中包含的相关信息，以揭示货币政策（美国和欧元区）的状况及其潜在的宏观经济影响。