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含近单位根解释变量的回归模型中的最优推断AI 解读

This paper considers the problem of conducting inference on the regression coefficient in a bivariate regression model with a highly persistent regressor. Gaussian asymptotic power envelopes are obtained for a class of testing procedures that satisfy a conditionality restriction. In addition, the paper proposes testing procedures that attain these power envelopes whether or not the innovations of the regression model are normally distributed.

利用利差预测美国衰退的结构突变门限 VARAI 解读

Abstract This paper proposes a model to predict recessions that accounts for non‐linearity and a structural break when the spread between long‐ and short‐term interest rates is the leading indicator. Estimation and model selection procedures allow us to estimate and identify time‐varying non‐linearity in a VAR. The structural break threshold VAR (SBTVAR) predicts better the timing of recessions than models with constant threshold or with only a break. Using real‐time data,…

利率期限结构与宏观经济的联合模型AI 解读

Abstract We present and estimate a continuous time term structure model that incorporates observable macroeconomic variables and latent variables with a clear macroeconomic interpretation. Our model is able to accurately describe the joint dynamics for US macroeconomic variables and the yield curve. However, the observable variables do not explain the long end of the term structure. Central tendencies of these macroeconomic variables do a much better job in this respect.…

多变量不可观测成分模型的季节整合与协整检验AI 解读

Abstract This paper considers tests of seasonal integration and cointegration for multivariate unobserved component models. First, the locally best invariant (LBI) test of the null hypothesis of a deterministic seasonal pattern against the alternative of seasonal integration is derived for a model with Gaussian i.i.d. disturbances and deterministic trend. Then the null hypothesis of seasonal cointegration is considered and a test for common nonstationary components at the…

广义长记忆过程、协整检验失效与汇率动态AI 解读

Abstract This paper presents evidence that the equilibrium relationship in a system of nominal exchange rates is best described as a stationary GARMA process. The implementation of the GARMA methodology helps explain conflicting and puzzling results from the use of linear cointegration and fractional cointegration methods. Furthermore, we use Monte Carlo analysis to document problems with standard cointegration tests when the attraction process is distributed as a long…

长程依赖序列的序贯 Bahadur–Kiefer 与 Vervaat 误差过程强不变原理AI 解读

In this paper we study strong approximations (invariance principles) of the sequential uniform and general Bahadur–Kiefer processes of long-range dependent sequences. We also investigate the strong and weak asymptotic behavior of the sequential Vervaat process, that is, the integrated sequential Bahadur–Kiefer process, properly normalized, as well as that of its deviation from its limiting process, the so-called Vervaat error process. It is well known that the Bahadur–Kiefer…

若干异方差时间序列模型中的误差分布拟合AI 解读

This paper addresses the problem of fitting a known distribution to the innovation distribution in a class of stationary and ergodic time series models. The asymptotic null distribution of the usual Kolmogorov–Smirnov test based on the residuals generally depends on the underlying model parameters and the error distribution. To overcome the dependence on the underlying model parameters, we propose that tests be based on a vector of certain weighted residual empirical…

有限过去预测系数的显式表示及其应用AI 解读

We consider the finite-past predictor coefficients of stationary time series, and establish an explicit representation for them, in terms of the MA and AR coefficients. The proof is based on the alternate applications of projection operators associated with the infinite past and the infinite future. Applying the result to long memory processes, we give the rate of convergence of the finite predictor coefficients and prove an inequality of Baxter-type.

协方差结构的识别AI 解读

The issue of identification of covariance structures, which arises in a number of different contexts, has been so far linked to conditions on the true parameters to be estimated. In this paper, this limitation is removed.As done by Johansen (1995, Journal of Econometrics 69, 112–132) in the context of linear models, the present paper provides necessary and sufficient conditions for the identification of a covariance structure that depends only on the constraints and can…

非线性平滑转换误差修正模型中的协整检验AI 解读

This paper proposes a new testing procedure to detect the presence of a cointegrating relationship that follows a globally stationary smooth transition process. In the context of nonlinear smooth transition error correction models (ECMs) we provide two simple operational versions of the tests. First, we obtain the associated nonlinear ECM-based tests. Second, we derive the nonlinear analogue of the residual-based test for cointegration in linear models. We derive the…

长跨度下的方差比统计量AI 解读

We make three contributions to using the variance ratio statistic at large horizons. Allowing for general heteroskedasticity in the data, we obtain the asymptotic distribution of the statistic when the horizon k is increasing with the sample size n but at a slower rate so that k/n → 0. The test is shown to be consistent against a variety of relevant mean reverting alternatives when k/n → 0. This is in contrast to the case when k/n → δ > 0, where the statistic has been…

货币政策变化如何影响银行贷款：奥地利银行数据分析AI 解读

Abstract Using a panel of Austrian bank data we show that the lending decisions of the smallest banks are more sensitive to interest rate changes, and that for all banks, sensitivity changes over time. We propose to estimate the groups of banks that display similar lending reactions by means of a group indicator which, after estimation, indicates each bank's classification. Additionally, we estimate a state indicator that indicates the periods during which the lending…

多元线性过程时间可逆性札记AI 解读

We derive some readily verifiable necessary and sufficient conditions for a multivariate non-Gaussian linear process to be time-reversible, under two sets of conditions on the contemporaneous dependence structure of the innovations. One set of conditions concerns the case of independent-component innovations, in which case a multivariate non-Gaussian linear process is time-reversible if and only if the coefficients consist of essentially asymmetric columns with…

谱密度的收缩估计量AI 解读

We propose a shrinkage estimator for spectral densities based on a multilevel normal hierarchical model. The first level captures the sampling variability via a likelihood constructed using the asymptotic properties of the periodogram. At the second level, the spectral density is shrunk towards a parametric time series model. To avoid selecting a particular parametric model for the second level, a third level is added which induces an estimator that averages over a class of…

基于多项式系数密度的聚合AR(1)模型AI 解读

This paper develops a new kind of aggregation model. We extend the work of Linden (1999) to allow the AR coefficient to be drawn from a polynomial density function. The polynomial density incorporates a wealth of multi-modal density functions as special cases. Given the aggregate data, we provide estimation methods for the coefficients and the order of the polynomial density. A test for the functional form of the polynomial is provided. We apply the model to the consumption…

异质面板平稳性的均值组检验AI 解读

This paper proposes a panel-based mean group test for the null of stationarity against the alternative of unit roots in the presence of both heterogeneity across cross-section units and serial correlation across time periods. Using both sequential and joint asymptotic analyses the proposed test statistic is shown to be distributed as standard normal under the null for large N (number of groups) and large T (number of time periods). Monte Carlo results support the use of…

动态相关性的状态切换模型AI 解读

We propose a new model for the variance between multiple time series, the Regime Switching Dynamic Correlation. We decompose the covariances into correlations and standard deviations and the correlation matrix follow a regime switching model; it is constant within a regime but different across regimes. The transitions between the regimes are governed by a Markov chain. This model does not suffer from a curse of dimensionality and it allows analytic computation of multi-step…

金融因子、宏观信息与利率期限结构的预期理论AI 解读

In this paper we develop on the VAR framework, originally proposed by Campbell and Shiller (J. Political Econom 95 (1987) 1062) to evaluate the Expectations Theory, along three dimensions: the use of a testing method based on a real-time procedure, the measurement of the risk premium, the specification of the implicit monetary policy maker’s reaction function. We use financial factors and macroeconomic information to construct a test of the theory based on simulating…

摘要暂缺

摘要暂缺

基于超额质量泛函的局部平稳时间序列判别AI 解读

Discrimination of time series is an important practical problem with applications in various scientific fields. We propose and study a novel approach to this problem. Our approach is applicable to cases where time series in different categories have a different “shape.” Although based on the idea of feature extraction, our method is not distance-based, and as such does not require aligning the time series. Instead, features are measured for each time series, and…

非平稳时间序列模型的结构断点估计AI 解读

This article considers the problem of modeling a class of nonstationary time series using piecewise autoregressive (AR) processes. The number and locations of the piecewise AR segments, as well as the orders of the respective AR processes, are assumed unknown. The minimum description length principle is applied to compare various segmented AR fits to the data. The goal is to find the “best” combination of the number of segments, the lengths of the segments, and the orders of…

基于排序的依赖 Dirichlet 过程AI 解读

In this article we propose a new framework for Bayesian nonparametric modeling with continuous covariates. In particular, we allow the nonparametric distribution to depend on covariates through ordering the random variables building the weights in the stick-breaking representation. We focus mostly on the class of random distributions that induces a Dirichlet process at each covariate value. We derive the correlation between distributions at different covariate values and use…