摘要
为了提高高维动态因子模型识别的有效性,借鉴SVAR模型的结构分析方法,提出了通过隐性因子的新息ε_t来推断和识别动态因子模型正交结构冲击的分析过程.并且,根据动态因子模型的似然函数表示,通过信息矩阵推导出了动态因子模型识别的秩条件.秩条件仅仅依赖于因子的个数以及约束条件,而不依赖于数据的维数,易于在实际应用中验证动态因子模型的识别性.
In order to improve the identification effectiveness of high-dimensional dynamic factor model, analogously to structural VAR analysis, this paper proposes to infer and identify the dynamic factors structural shocks using the innovations of the factor variables. And according to the likelihood function of the dynamic factor models, we establish a kind of identification rank condition through the information matrix. The rank condition depends only on the number of factors and constraints of models without depending on the dimension of the data, and easy to verify the identification of the dynamic factor model in practical applications.
引文
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1.根据Stock&Watson(2005)、Bai&Ng(2002)、Bai(2003)以及Forni et al.(2000)等人的研究结论,这一结论是合理的.
2.在SVAR模型中的K-模型的结构识别假设和本文的假设1具有相同的形式.
3.对x为任-q(q-1)/2维向量,D_qx=vecW, W为某一斜对称矩阵,即D_qx为某一斜对称矩阵的向量化形式.由于N_q=(I_q2+K_q2),且K_q2变换矩阵,容易验证D_qx为N_qy=0的通解.