论文检索

函数型自回归过程中的协整AI 解读

This article defines the class of ${\cal H}$ -valued autoregressive (AR) processes with a unit root of finite type, where ${\cal H}$ is a possibly infinite-dimensional separable Hilbert space, and derives a generalization of the Granger–Johansen Representation Theorem valid for any integration order $d = 1,2, \ldots$ . An existence theorem shows that the solution of an AR process with a unit root of finite type is necessarily integrated of some finite integer order d ,…

含高阶单整变量的联立协整方程系统识别条件AI 解读

This paper discusses identification of systems of simultaneous cointegrating equations with integrated variables of order two or higher, under constraints on the cointegration parameters. Rank and order conditions for identification are provided for general linear constraints, covering both cross-equation and equation-by-equation restrictions.

具有共同周期特征的向量自回归过程刻画AI 解读

This paper presents necessary and sufficient conditions for the existence of common cyclical features in Vector Auto Regressive (VAR) processes integrated of order 0, 1, 2, where the common cyclical features correspond to common serial correlation (CS), commonality in the final equations (CE) and co-dependence (CD). The results are based on local rank factorizations of the reversed AR polynomial around the poles of its inverse. All processes with CS structures are found to…

协整系统的调整速度AI 解读

This paper discusses summary measures for the speed of adjustment in possibly cointegrated Vector Autoregressive Processes (VAR). In particular we propose long-run half-lives, based on interim and total multipliers. We discuss their relation with Granger-noncausality and other types of half-life, which are shown to convey different information, except in the univariate AR(1) case. We present likelihood-based inference on long-run half-lives, regarded as discrete functions of…

I(2) VAR 系统中的共同趋势与周期AI 解读

This paper discusses common cycles in I(2) vector autoregressive (VAR) systems. Both static and dynamic cofeatures are considered. We consider application of these notions to different choices of stationary variables extracted from a VAR, including deviations from equilibria. This extension is based on the equilibrium dynamics representation of the system, which is introduced in this paper. Inference on the number of common features is addressed via reduced rank regression,…

VAR(1) 过程的 I(2) 模型：第 20 卷第 3 期问题 04.3.1 解答AI 解读

Let α * be any basis of col(Π) and β * be any basis of col(Π′); we note col(α ⊥ ) = col(α *⊥ ), col(β ⊥ ) = col(β *⊥ ) so no distinction is made between α ⊥ and α *⊥ , β ⊥ and β *⊥ in the following discussion.

VAR(1) 过程的 I(2) 模型：问题 04.3.1AI 解读

This problem discusses an I (2) model in the VAR(1) case. The I (2) representation theorem of Johansen (1992) (JRT) holds also for VAR(1) processes. The I (2) model for VAR( k ) processes has been discussed for k ≥ 2 in Johansen (1996, Ch. 9; 1997). We here discuss a parametrization for the I (2) case of VAR(1) that differs from the VAR( k ) model.

协整 I(2) VAR 系统中移动平均影响矩阵的渐近推断AI 解读

This paper provides asymptotic standard errors for the moving average (MA) impact matrix for the second differences of a vector autoregressive (VAR) process integrated of order 2, I (2). Standard errors of the row space of the MA impact matrix are also provided; bases of this row space define the common I (2) trends linear combinations. These standard errors are then used to formulate Wald-type tests. The MA impact matrix is shown to be linked to impact factors that measure…

I(2) 系统中两阶段估计量的渐近效率AI 解读

This paper derives the distribution of the two stage estimator of cointegrating parameters in I (2) systems, abbreviated 2SI2, under several assumptions regarding the drift of the process. The asymptotic distribution is compared with that of the maximum likelihood (ML) estimator derived in Johansen (1997, Scandinavian Journal of Statistics 24, 433–462). It is found that the two asymptotic distributions are the same, thus showing that the 2SI2 estimator is asymptotically as…

摘要暂缺

协整分析中的两个混合正态密度AI 解读

We derive explicitly the exact density functions of two key mixed normal variates that arise from cointegration analysis. We also plot them, and analyze their analytical features and implications.

协整 I(1) VAR 系统中移动平均影响矩阵的渐近推断AI 解读

This paper addresses the problem of inference on the moving average impact matrix and on its row and column spaces in cointegrated 1(1) VAR processes. The choice of bases (i.e., the identification) of these spaces, which is of interest in the definition of the common trend structure of the system, is discussed. Maximum likelihood estimators and their asymptotic distributions are derived, making use of a relation between properly normalized bases of orthogonal spaces, a…