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多期预测中的变量选择、估计与推断AI 解读

This paper conducts a broad-based comparison of iterated and direct multi-period forecasting approaches applied to both univariate and multivariate models in the form of parsimonious factor-augmented vector autoregressions. To account for serial correlation in the residuals of the multi-period direct forecasting models we propose a new SURE-based estimation method and modified Akaike information criteria for model selection. Empirical analysis of the 170 variables studied by…

含短期与长期约束的 VAR 模型选择、估计与预测AI 解读

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. A Monte Carlo study explores the finite sample performance of this procedure and evaluates the…

结合低频与高频方法的大维波动矩阵推断AI 解读

It is increasingly important in financial economics to estimate volatilities of asset returns. However, most of the available methods are not directly applicable when the number of assets involved is large, due to the lack of accuracy in estimating high-dimensional matrices. Therefore it is pertinent to reduce the effective size of volatility matrices in order to produce adequate estimates and forecasts. Furthermore, since high-frequency financial data for different assets…

短面板向量自回归中脉冲响应函数的渐近分布AI 解读

This paper establishes the asymptotic distributions of the impulse response functions in panel vector autoregressions with a fixed time dimension. It also proves the asymptotic validity of a bootstrap approximation to their sampling distributions. The autoregressive parameters are estimated using the GMM estimators based on the first differenced equations and the error variance is estimated using an extended analysis-of-variance type estimator. Contrary to the time series…

VAR 学习动态下前瞻模型的模拟检验AI 解读

In this paper we propose a simulation-based technique to investigate the finite sample performance of likelihood ratio (LR) tests for the nonlinear restrictions that arise when a class of forward-looking (FL) models typically used in monetary policy analysis is evaluated with vector autoregressive (VAR) models. We consider ‘one-shot’ tests to evaluate the FL model under the rational expectations hypothesis and sequences of tests obtained under the adaptive learning…

利用贝叶斯降秩多元模型预测大型数据集AI 解读

The paper addresses the issue of forecasting a large set of variables using multivariate models. In particular, we propose three alternative reduced rank forecasting models and compare their predictive performance for US time series with the most promising existing alternatives, namely, factor models, large-scale Bayesian VARs, and multivariate boosting. Specifically, we focus on classical reduced rank regression, a two-step procedure that applies, in turn, shrinkage and…

含分段线性趋势的I(2)协整模型AI 解读

This paper presents likelihood analysis of the I(2) cointegrated vector autoregression which allows for piecewise linear deterministic terms. Limiting behaviour of the maximum likelihood estimators are derived, which is used to further derive the limiting distribution of the likelihood ratio statistic for the cointegration ranks, extending Nielsen and Rahbek. The provided asymptotic theory extends also the results in Johansen et al. where asymptotic inference is discussed in…

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…

无限维 VAR 与因子模型AI 解读

This paper proposes a novel approach for dealing with the 'curse of dimensionality' in the case of infinite-dimensional vector autoregressive (IVAR) models. It is assumed that each unit or variable in the IVAR is related to a small number of neighbors and a large number of non-neighbors. The neighborhood effects are fixed and do not change with the number of units (N), but the coefficients of non-neighboring units are restricted to vanish in the limit as N tends to infinity.…

含随机波动率的贝叶斯向量自回归实时密度预测AI 解读

Central banks and other forecasters are increasingly interested in various aspects of density forecasts. However, recent sharp changes in macroeconomic volatility, including the Great Moderation and the more recent sharp rise in volatility associated with increased variation in energy prices and the deep global recession—pose significant challenges to density forecasting. Accordingly, this paper examines, with real-time data, density forecasts of U.S. GDP growth,…

通过贝叶斯随机搜索选择多元随机波动率模型AI 解读

We propose a Bayesian stochastic search approach to selecting restrictions on multivariate regression models where the errors exhibit deterministic or stochastic conditional volatilities. We develop a Markov chain Monte Carlo (MCMC) algorithm that generates posterior restrictions on the regression coefficients and Cholesky decompositions of the covariance matrix of the errors. Numerical simulations with artificially generated data show that the proposed method is effective…

含噪声与高维尺度下的低秩及近低秩矩阵估计AI 解读

We study an instance of high-dimensional inference in which the goal is to estimate a matrix Θ∗∈ℝm1×m2 on the basis of N noisy observations. The unknown matrix Θ∗ is assumed to be either exactly low rank, or “near” low-rank, meaning that it can be well-approximated by a matrix with low rank. We consider a standard M-estimator based on regularization by the nuclear or trace norm over matrices, and analyze its performance under high-dimensional scaling. We define the notion of…

衡量房价在空间与时间上的扩散AI 解读

How fast and how long (and to what magnitude) does a change in housing prices in one region affect its neighbors? In this paper, I apply a time series technique for measuring impulse response functions from local projections to a spatial autoregressive model of housing prices. For a dynamic panel of California counties, the data reveal that the diffusion of regional housing prices across space lasts up to two and half years. This result, and the econometric techniques…

协整与长期资产配置AI 解读

We show that economic restrictions of cointegration between asset cash flows and aggregate consumption have important implications for return dynamics and optimal portfolio rules, particularly at long investment horizons. When cash flows and consumption share a common stochastic trend (i.e., are cointegrated), temporary deviations between their levels forecast long-horizon dividend growth rates and returns, and consequently, alter the term profile of risks and expected…

长记忆分数阶单整过程的脉冲响应AI 解读

Fractionally integrated time series, which have become an important modeling tool over the last two decades, are obtained by applying the fractional filter $(1 - L)^{ - d} = \sum\nolimits_{n = 0}^\infty {b_n } L^n$ to a weakly dependent (short memory) sequence. Weakly dependent sequences are characterized by absolutely summable impulse response coefficients of their Wold representation. The weights b n decay at the rate n d −1 and are not absolutely summable…

条件异方差下的协整秩检验AI 解读

We analyze the properties of the conventional Gaussian-based cointegrating rank tests of Johansen (1996, Likelihood-Based Inference in Cointegrated Vector Autoregressive Models) in the case where the vector of series under test is driven by globally stationary, conditionally heteroskedastic (martingale difference) innovations. We first demonstrate that the limiting null distributions of the rank statistics coincide with those derived by previous authors who assume either…

协整向量自回归模型中的若干识别问题AI 解读

The paper analyses some identification problems in the cointegrated vector autoregressive model. A criteria for identification by linear restrictions on individual relations is given. The asymptotic distribution of the estimators of [alpha] and [beta] is derived when they are identified by linear restrictions on [beta], and when they are identified by linear restrictions on [alpha]. It it shown that, in the latter case, a component of is asymptotically Gaussian. Finally we…

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…

协整、长期结构建模与弱外生性：两个英国经济模型AI 解读

Cointegration ideas as introduced by Granger in 1981 are commonly embodied in empirical macroeconomic modelling through the vector error correction model (VECM). It has become common practice in these models to treat some variables as weakly exogenous, resulting in conditional VECMs. This paper studies the consequences of different approaches to weak exogeneity for the dynamic properties of such models, in the context of two models of the UK economy, one a national-economy…

非平稳波动率向量自回归中的协整检验AI 解读

Many key macroeconomic and financial variables are characterized by permanent changes in unconditional volatility. In this paper we analyse vector autoregressions with non-stationary (unconditional) volatility of a very general form, which includes single and multiple volatility breaks as special cases. We show that the conventional rank statistics computed as in (Johansen, 1988) and (Johansen, 1991) are potentially unreliable. In particular, their large sample distributions…

向量自回归模型中多项式协分数关系的表示理论AI 解读

We extend the representation theory of the autoregressive model in the fractional lag operator of Johansen (2008, Econometric Theory 24, 651–676). A recursive algorithm for the characterization of cofractional relations and the corresponding adjustment coefficients is given, and it is shown under which condition the solution of the model is fractional of order d and displays cofractional relations of order d − b and polynomial cofractional relations of order d − 2 b ,…, d −…

欧洲东部与西部对货币政策冲击的响应比较AI 解读

Abstract This paper compares impulse responses to monetary policy shocks in the euro area countries before the EMU and in the New Member States (NMS) from central–eastern Europe. We mitigate the small‐sample problem, which is especially acute for the NMS, by using a Bayesian estimation that combines information across countries. The impulse responses in the NMS are broadly similar to those in the euro area countries. There is some evidence that in the NMS, which have had…

使用时变参数动态Nelson–Siegel模型分析利率期限结构AI 解读

In this article we introduce time-varying parameters in the dynamic Nelson–Siegel yield curve model for the simultaneous analysis and forecasting of interest rates of different maturities. The Nelson–Siegel model has been recently reformulated as a dynamic factor model with vector autoregressive factors. We extend this framework in two directions. First, the factor loadings in the Nelson–Siegel yield model depend on a single loading parameter that we treat as the fourth…

共爆炸过程分析AI 解读

A vector autoregressive model allowing for unit roots as well as an explosive characteristic root is developed. The Granger-Johansen representation shows that this results in processes with two common features: a random walk and an explosively growing process. Cointegrating and coexplosive vectors can be found that eliminate these common factors. The likelihood ratio test for a simple hypothesis on the coexplosive vectors is analyzed. The method is illustrated using data…