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利用伪似然比检验进行协整检验AI 解读

This paper considers pseudomaximum likelihood estimators for vector autoregressive models. These estimators are used to determine the cointegration rank of a multivariate time series process using pseudolikelihood ratio tests. The asymptotic distributions of these tests depend on nuisance parameters if the pseudolikelihood is non-Gaussian. This even holds if the likelihood is correctly specified. The nuisance parameters have a natural interpretation and can be consistently…

基于因果式残差正交化的向量自回归脉冲响应函数AI 解读

A data-determined method for testing structural models of the errors in vector autoregressions is discussed. The method can easily be combined with prior economic knowledge and a subjective analysis of data characteristics to yield valuable information concerning model selection and specification. In one dimension, it turns out that standard t statistics can be used to test the various overidentifying restrictions that are implied by a model. In another dimension, the method…

含协整与标量分量的向量自回归模型推断AI 解读

For the partially nonstationary vector autoregressive model of Ann and Reinsel, I further assume that the first differenced series has scalar components of lower order and study estimation of these models along with asymptotic properties of the estimators. It is shown that Gaussian reduced rank estimation can be easily carried out by simple modification of the Ahn and Reinsel's method. The asymptotic distribution for the estimator of the nonstationary parameter is a locally…

贝叶斯 VAR 模型估计与推断的数值方法AI 解读

In Bayesian analysis of vector autoregressive models, and especially in forecasting applications, the Minnesota prior of Litterman is frequently used. In many cases other prior distributions provided better forecasts and are preferable from a theoretical standpoint. Several of these priors require numerical methods in order to evaluate the posterior distribution. Different ways of implementing Monte Carlo integration are considered. It is found that Gibbs sampling performs…

协整时间序列的主成分分析AI 解读

This paper considers the analysis of cointegrated time series using principal components methods. These methods have the advantage of requiring neither the normalization imposed by the triangular error correction model nor the specification of a finite-order vector autoregression. An asymptotically efficient estimator of the cointegrating vectors is given, along with tests forcointegration and tests of certain linear restrictions on the cointegrating vectors. An illustrative…

含稳定过程的矩阵随机积分弱收敛AI 解读

This paper generalizes the univariate results of Chan and Tran (1989, Econometric Theory 5, 354–362) and Phillips (1990, Econometric Theory 6, 44–62) to multivariate time series. We develop the limit theory for the least-squares estimate of a VAR(l) for a random walk with independent and identically distributed errors and for I(1) processes with weakly dependent errors whose distributions are in the domain of attraction of a stable law. The limit laws are represented by…

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…

具有随机波动的贝叶斯向量自回归AI 解读

This paper proposes a Bayesian approach to a vector autoregression with stochastic volatility, where the multiplicative evolution of the precision matrix is driven by a multivariate beta variate. Exact updating formulas are given to the nonlinear filtering of the precision matrix. Estimation of the autoregressive parameters requires numerical methods: an importance-sampling-based approach is explained here.

GARCH 模型中条件波动率的脉冲响应函数AI 解读

This paper defines and analyzes the impulse response function for conditional volatility in GARCH models. It first derives the function from a vector autoregressive and moving average representation of the GARCH models and obtains the corresponding standard errors from the first-order derivatives of the function and the covariance matrix of the estimated parameters. The paper then employs a Monte Carlo study to assess the finite sample properties of the standard errors and…

永久性冲击、暂时性冲击与英国经济周期AI 解读

In this paper the business cycle properties of UK data are investigated using a VAR technique. A Real Business Cycle (RBC) model is formulated. The model includes both permanent and transitory shocks to technology. The business cycle properties of the data and the model are investigated by deriving the expected changes over various forecast horizons from a VAR model. It is found, contrary to evidence in Rotemberg and Woodford (1996), that the model can account for many…

永久与暂时冲击及英国经济周期AI 解读

In this paper the business cycle properties of UK data are investigated using a VAR technique. A Real Business Cycle (RBC) model is formulated. The model includes both permanent and transitory shocks to technology. The business cycle properties of the data and the model are investigated by deriving the expected changes over various forecast horizons from a VAR model. It is found, contrary to evidence in Rotemberg and Woodford (1996), that the model can account for many…

无限阶协整向量自回归过程AI 解读

Estimation of cointegrated systems via autoregressive approximation is considered in the framework developed by Saikkonen (1992, Econometric Theory 8, 1-27). The asymptotic properties of the estimated coefficients of the autoregressive error correction model (ECM) and the pure vector autoregressive (VAR) representations are derived under the assumption that the autoregressive order goes to infinity with the sample size. These coefficients are often used for analyzing the…

无需预先确定平稳化方式的股票价格建模：计算更正AI 解读

In “Modeling Stock Prices without Knowing How to Induce Stationarity” (1994, Econometric Theory 10, 701–719), we used posterior-odds calculations to evaluate restrictions imposed by a present-value model of stock prices across the equations of a VAR representation of stock prices and dividends. The results we reported are tainted by the omission of two factors: the Jacobians induced by the mapping of our priors over VAR parameters β into the restricted sample spaces relevant…

长序列向量一般线性过程的快速似然近似：分数差分应用AI 解读

The quadratic form appearing in the likelihood function of a Gaussian stationary and invertible vector general linear process is considered in this paper. A new expression for this quadratic form is developed, which allows repeated computations to be performed very efficiently by possibly using forecast and backcast values of the series. While the quadratic form itself involves the inverse of the covariance matrix, the new expression uses the autocovariances of the…

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协整系统的预测表现评估AI 解读

This paper examines the forecast performance of a cointegrated system relative to the forecast performance of a comparable VAR that fails to recognize that the system is characterized by cointegration. The cointegrated system we examine is composed of three vectors, a money demand representation, a Fisher equation, and a risk premium captured by an interest rate differential. The forecasts produced by the vector error correction model (VECM) associated with this system are…

截距修正与结构变化AI 解读

Analyses of forecasting that assume a constant, time-invariant data generating process (DGP), and so implicitly rule out structural change or regime shifts in the economy, ignore an aspect of the real world responsible for some of the more dramatic historical episodes of predictive failure. Some models may offer greater protection against unforeseen structural breaks than others, and various tricks may be employed to robustify forecasts to change. We show that in certain…

计量经济模型的确定AI 解读

This paper is concerned with model determination methods and their use in the prediction of economic time series. The methods are Bayesian but they can be justified by classical arguments as well. The paper continues some recent work on Bayesian asymptotic, develops embedding techniques for vector martingales, and implements the modeling ideas in a multivariate regression framework that includes Bayesian vector autoregression (BVAR's) and reduced rank regressions (RRR's). It…

非线性协方差结构模型估计量的小样本性质AI 解读

This study examines the small sample properties of generalized method of moments (GMM) and maximood likelihood estimators of nonlinear models of covariance structure. It considers the properties of estimates for a simple factor model, the Hall and Mishkin (1982) model of consumption and income, and a simple structural vector-autoregression-type error model. This analysis establishes three basic results. First, optimally weighted GMM estimation yields some biased parameter…

季节性过程中的冲击持续性AI 解读

The paper addresses the issue of measuring the persistence of shocks on seasonally integrated processes observed at quarterly intervals. We show that the amplitude of the limiting cycle described by the cumulated impulse response function provides a parametric measure of persistence and that Cochrane's normalized variance ratio can correspondingly be extended as a non-parametric counterpart. For illustrative purposes the latter is applied to the Italian GDP and to the output…

宏观经济理论视角下的应用协整分析AI 解读

Cointegration analyses of macroeconomic time series are often not based on fully specified theoretical models. We use a theoretical model to scrutinize common procedures in applied cointegration analysis. Monte Carlo experiments show that 1) some tests of the cointegration vectors do not work well on series generated by an equilibrium cycle model; (2) cointegration restrictions add little to forecasting; (3) structural VAR models based on weak long-run restrictions seem to…

季节性过程中的冲击持续性AI 解读

The paper addresses the issue of measuring the persistence of shocks on seasonally integrated processes observed at quarterly intervals. We show that the amplitude of the limiting cycle described by the cumulated impulse response function provides a parametric measure of persistence and that Cochrane's normalized variance ratio can correspondingly be extended as a non-parametric counterpart. For illustrative purposes the latter is applied to the Italian GDP and to the output…

从宏观经济理论审视应用协整分析AI 解读

Cointegration analyses of macroeconomic time series are often not based on fully specified theoretical models. We use a theoretical model to scrutinize common procedures in applied cointegration analysis. Monte Carlo experiments show that 1) some tests of the cointegration vectors do not work well on series generated by an equilibrium cycle model; (2) cointegration restrictions add little to forecasting; (3) structural VAR models based on weak long-run restrictions seem to…

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