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向量自回归与因果性AI 解读

A limit theory for Wald tests of Granger causality in levels vector autoregressions (VAR's) and error correction models (ECM's) is developed, which allows for stochastic trends and cointegration. Earlier work is extended to the general case, thereby characterizing when these Wald tests are asymptotically valid as 'x'(superscript 2) criteria. Our results for inference from unrestricted levels VAR are not encouraging: the limit theory often involves nuisance parameters and…

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单位根对向量自回归的伪影响AI 解读

This paper analyzes whether inclusion of a statistically independent random walk in a vector autoregression can result in spurious inference. The problem was raised originally by Ohanian (1988). In a Monte Carlo simulation based on the VAR's estimated by Sims (1980, 1982), Ohanian found that ‘block exogeneity’ of the genuine variables with respect to an artificially generated random walk variable was rejected too often. In the present paper we attempt a full analytical study…

非线性动态结构AI 解读

Methods for nonlinear impulse response analysis are introduced. The methods are based on conditional moment profiles defined for a stationary time series. Comparing conditional moment profiles to baseline profiles is the nonlinear analog of conventional impulse-response analysis. The bootstrap may be used for statistical inference. Profile bundles may be examined for evidence of damping or persistence. Application to bivariate NYSE price and volume series from 1928 to 1987…

估计线性动态模型的脉冲响应、阶跃响应与方差分解的渐近分布AI 解读

Formulas are derived for computing asymptotic covariance matrices of sets of impulse responses, step responses, or variance decompositions of estimated dynamic simultaneous-equations models in vector autoregressive moving-average (VARMA) form. Computed covariances would be used to test linear restrictions on sets of impulse responses, step responses, or variance decompositions. The results unify and extend previous formulas to handle any model in VARMA form, provide accurate…

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配置系统中理论约束与自相关的联合检验AI 解读

Abstract In the context of allocation models with vector autoregressive errors we propose a convenient procedure, based on the Lagrange multiplier principle, for testing any possible combination of absence of serial correlation, homogeneity, and symmetry against any possible alternative which specifies autocorrelation of an arbitrary given order. We also derive generic expressions for the maximum likelihood estimation of the models under six possible combinations of…

一阶自回归／单位根模型的精确中位无偏估计AI 解读

First-order autoregressive/unit root models with independent identically distributed normal errors are considered, including those without an intercept, those with an intercept, and those with an intercept and time trend. The autoregressive parameter is allowed to lie in the interval (-1, 1], which includes the unit root case. Exactly median-unbiased estimators and exact confidence intervals of the autoregressive parameter are introduced. Corresponding exactly…

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多元ARMA模型中两个变量向量之间的因果性检验AI 解读

In the analysis of economic time series, a question often raised is whether a vector of variables causes another one in the sense of Granger. Most of the literature on this topic is concerned with bivariate relationships or uses finite-order autoregressive specifications. The purpose of this article is to develop a causality analysis in the sense of Granger for general vector autoregressive moving average (ARMA) models. We give a definition of Granger noncausality between…

总量冲击与宏观经济波动：贝叶斯方法AI 解读

Abstract This paper describes Bayesian techniques for analysing the effects of aggregate shocks on macroeconomic time‐series. Rather than calculate point estimates of the response of a time‐series to an aggregate shock, we calculate the whole probability density function of the response and use Monte‐Carlo or Gibbs sampling techniques to evaluate its properties. The proposed techniques impose identification restrictions in a way that includes the uncertainty in these…

多元动态线性变量误差模型的可识别性AI 解读

This article considers multivariate causal transfer function systems with latent stationary inputs and outputs. Their observation is assumed to be disturbed by errors in variables (EV). The main identification results for such models so far consist of structure theory. Derived are descriptions of classes of EV transfer function systems compatible with given covariance structures of the observed variables under various causality constraints. The case of unique determination…

多变量动态线性变量测量误差模型的可识别性AI 解读

This article considers multivariate causal transfer function systems with latent stationary inputs and outputs. Their observation is assumed to be disturbed by errors in variables (EV). The main identification results for such models so far consist of structure theory. Derived are descriptions of classes of EV transfer function systems compatible with given covariance structures of the observed variables under various causality constraints. The case of unique determination…

改进的异方差与自相关一致协方差矩阵估计量AI 解读

This paper considers a new class of heteroskedasticity and autocorrelation consistent (HAC) covariance matrix estimators. The estimators considered are prewhitened kernel estimators with vector autoregressions employed in the prewhitening stage. The paper establishes consistency, rate of convergence, and asymptotic truncated mean squared error (MSE) results for the estimators when a fixed or automatic bandwidth procedure is employed. Conditions are obtained under which…

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二阶单整向量自回归过程的表示AI 解读

We investigate vector autoregressive processes and find the condition under which the processes are I (2). A representation theorem forsuch processes is proved and the interpretation of the AR model as an error correction model is discussed.

用自助法辅助选择向量时间序列的近似表示AI 解读

In this article, a procedure is presented to use the bootstrap in choosing the best approximation in terms of forecasting performance for the equivalent state-space representation of a vector autoregressive model. It is found that the proposed procedure, which uses each approximator's forecasting performance, can enhance considerably an approach based simply on the estimated Hankel singular values.

用最小二乘识别向量线性过程的阶梯规范形式AI 解读

In this paper a method of identifying stationary and invertible vector autoregressive moving-average time series is proposed. The models are presumed to be represented in (reversed) echelon canonical form. Consideration is given to both parameter estimation and the determination of structural indices, the evaluations being based on the use of closed form least squares calculations. Consistency of the technique is shown and the operational characteristics of the procedure…

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通过向量自回归模型估计正交化脉冲响应AI 解读

Impulse response functions from time series models are standard tools for analyzing the relationship between economic variables. The asymptotic distribution of orthogonalized impulse responses is derived under the assumption that finite order vector autoregressive (VAR) models are fitted to time series generated by possibly infinite order processes. The resulting asymptotic distributions of forecast error variance decompositions are also given.

高斯向量自回归模型中协整向量的估计与假设检验AI 解读

This paper contains the likelihood analysis of vector autoregressive models allowing for cointegration. The author derives the likelihood ratio test for cointegrating rank and finds it asymptotic distribution. He shows that the maximum likelihood estimator of the cointegrating relations can be found by reduced rank regression and derives the likelihood ratio test of structural hypotheses about these relations. The author shows that the asymptotic distribution of the maximum…

线性去趋势向量自回归中的伪推断札记AI 解读

A simulation study is designed to evaluate the sensitivity of inference in a Vector Autoregression in which the variables of interest (GNP, the money stock, the price level, and a short-term interest rate) are treated as trend stationary processes. Using the normal asymptotic theory, the authors find that an artificially generated random walk Granger-causes the genuine variables in the model as often as 60% of the time for a 5% level test. They also observe substantial bias…

日元兑美元外汇市场风险溢价的时间序列性质AI 解读

Abstract In this paper a VAR model is employed to construct a measure of the conditional expectations of the future yen/dollar spot rate. This measure allows us to examine the dynamics of an ex‐ante time‐series for the risk premium in the market. The VAR model produces ‘better’ forecasts than the survey responses for turbulent periods such as 1981–1982 and 1984–1985. The VAR‐generated expectations are then used to construct a risk premium time‐series. This risk premium…