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含单位根的部分线性模型AI 解读

This paper studies the asymptotic properties of a nonstationary partially linear regression model. In particular, we allow for covariates to enter the unit root (or near unit root) model in a nonparametric fashion, so that our model is an extension of the semiparametric model analyzed in Robinson (1988, Econometrica 56, 931–954). It is proved that the autoregressive parameter can be estimated at rate N even though part of the model is estimated nonparametrically. Unit root…

参数不稳定下嵌套模型选择的最优检验AI 解读

This paper develops optimal tests for model selection between two nested models in the presence of underlying parameter instability. These are joint tests for both parameter instability and a null hypothesis on a subset of the parameters. They modify the existing tests for parameter instability to allow the parameter vector to be unknown. These test statistics are useful if one is interested in testing a null hypothesis on some parameters but is worried about the possibility…

短记忆与长记忆高斯过程的 Stein–James 估计量AI 解读

We investigate the mean squared error of the Stein–James estimator for the mean when the observations are generated from a Gaussian vector stationary process with dimension greater than two. First, assuming that the process is short-memory, we evaluate the mean squared error, and compare it with that for the sample mean. Then a sufficient condition for the Stein–James estimator to improve upon the sample mean is given in terms of the spectral density matrix around the…

最小绝对偏差估计的条件异方差时间序列模型诊断AI 解读

The recent paper by Peng & Yao (2003) gave an interesting extension of least absolute deviation estimation to generalised autoregressive conditional heteroscedasticity, GARCH, time series models. The asymptotic distributions of absolute residual autocorrelations and squared residual autocorrelations from the GARCH model estimated by the least absolute deviation method are derived in this paper. These results lead to two useful diagnostic tools which can be used to check…

复合似然推断与模型选择札记AI 解读

A composite likelihood consists of a combination of valid likelihood objects, usually related to small subsets of data. The merit of composite likelihood is to reduce the computational complexity so that it is possible to deal with large datasets and very complex models, even when the use of standard likelihood or Bayesian methods is not feasible. In this paper, we aim to suggest an integrated, general approach to inference and model selection using composite likelihood…

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存在平滑非参数趋势时的长记忆估计AI 解读

We consider semiparametric estimation of the long-memory parameter of a stationary process in the presence of an additive nonparametric mean function. We use a semiparametric Whittle-type estimator, applied to the tapered, differenced series. Because the mean function is not necessarily a polynomial of finite order, no amount of differencing will completely remove the mean. We establish a central limit theorem for the estimator of the memory parameter, assuming that a slowly…

线性回归的自助法标准误估计AI 解读

Standard errors of parameter estimates are widely used in empirical work. The bootstrap often can provide a convenient means of estimating standard errors. The conditions under which bootstrap standard error estimates are theoretically justified have not received much attention, however. This article establishes conditions for the consistency of the moving blocks bootstrap estimators of the variance of the least squares estimator in linear dynamic models with dependent data.…

线性自回归模型中的测量误差AI 解读

Time series data are often subject to measurement error, usually the result of needing to estimate the variable of interest. Although it is often reasonable to assume that the measurement error is additive (i.e., the estimator is conditionally unbiased for the missing true value), the measurement error variances often vary as a result of changes in the population/process over time and/or changes in sampling effort. In this article we address estimation of the parameters in…

美国制造业部门的多层面板平滑转换自回归模型AI 解读

Abstract We introduce a multi‐level smooth transition model for a panel of time series, which can be used to examine the presence of common nonlinear business cycle features across many variables. The model is positioned in between a fully pooled model, which imposes such common features, and a fully heterogeneous model, which allows for unrestricted nonlinearity. We introduce a second‐stage model linking the parameters that determine the timing of the switches between…

利用二阶整合协整技术检验购买力平价AI 解读

Abstract This paper contributes to the empirical literature on the purchasing power parity (PPP) over the post‐Bretton Woods period by providing a time‐series based interpretation of the controversial evidence characterizing the dynamics of real exchange rates. It is shown that the persistence of deviations from the PPP between a set of European countries and the United States may be empirically attributed to the presence of I(2) stochastic trends in prices using Consumer…

含平稳外生回归变量的协整检验：分布近似AI 解读

Abstract The distribution of a functional of two correlated vector‐Brownian motions is approximated by a Gamma distribution. This functional represents the limiting distribution for cointegration tests with stationary exogenous regressors, but also for cointegration tests based on a non‐Gaussian likelihood. The approximation is accurate, fast and easy to use in comparison with both tabulated critical values and simulated p ‐values. The proposed procedure is applied to a UK…

相依序列样本分位数的 Bahadur 表示AI 解读

We establish the Bahadur representation of sample quantiles for linear and some widely used nonlinear processes. Local fluctuations of empirical processes are discussed. Applications to the trimmed and Winsorized means are given. Our results extend previous ones by establishing sharper bounds under milder conditions and thus provide new insight into the theory of empirical processes for dependent random variables.

分数单整的精确局部 Whittle 估计AI 解读

An exact form of the local Whittle likelihood is studied with the intent of developing a general-purpose estimation procedure for the memory parameter (d) that does not rely on tapering or differencing prefilters. The resulting exact local Whittle estimator is shown to be consistent and to have the same $N(0,\frac{1}{4})$ limit distribution for all values of d if the optimization covers an interval of width less than $\frac{9}{2}$ and the initial value of the process is…

谱密度具有未知极点的平稳过程半参数估计AI 解读

We consider the estimation of the location of the pole and memory parameter, λ0 and α, respectively, of covariance stationary linear processes whose spectral density function f(λ) satisfies f(λ)∼C|λ−λ0|−α in a neighborhood of λ0. We define a consistent estimator of λ0 and derive its limit distribution Zλ0. As in related optimization problems, when the true parameter value can lie on the boundary of the parameter space, we show that Zλ0 is distributed as a normal random…

平稳与非平稳分数阶时间序列推断的效率改进AI 解读

We consider a time series model involving a fractional stochastic component, whose integration order can lie in the stationary/invertible or nonstationary regions and be unknown, and an additive deterministic component consisting of a generalized polynomial. The model can thus incorporate competing descriptions of trending behavior. The stationary input to the stochastic component has parametric autocorrelation, but innovation with distribution of unknown form. The model is…

门限自回归模型中的子抽样推断AI 解读

This paper discusses inference in self exciting threshold autoregressive (SETAR) models. Of main interest is inference for the threshold parameter. It is well-known that the asymptotics of the corresponding estimator depend upon whether the SETAR model is continuous or not. In the continuous case, the limiting distribution is normal and standard inference is possible. In the discontinuous case, the limiting distribution is non-normal and cannot be estimated consistently. We…

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非平稳价格下的需求系统AI 解读

Relative prices are nonstationary and standard root-T inference is invalid for demand systems. But demand systems are nonlinear functions of relative prices, and standard methods for dealing with nonstationarity in linear models cannot be used. Demand system residuals are also frequently found to be highly persistent, further complicating estimation and inference. We propose a variant of the translog demand system, the NTLOG, and an associated estimator that can be applied…

股票收益的非平稳性AI 解读

The paper outlines a methodology for analyzing daily stock returns that relinquishes the assumption of global stationarity. Giving up this common working hypothesis reflects our belief that fundamental features of the financial markets are continuously and significantly changing. Our approach approximates the nonstationary data locally by stationary models. The methodology is applied to the S&P 500 series of returns covering a period of over seventy years of market activity.…

冲击矩阵两种表达式的等价性AI 解读

This note gives a proof of the equivalence between two expressions of the moving-average impact matrix; one is given by Johansen (1995, Likelihood-Based Inference in Cointegrated Vector Autoregressive Models ) and Paruolo (1997, Econometric Theory 13, 79–118), and the other appears in Phillips (1998, Journal of Econometrics 83, 21–56) as the limit of the impulse response function. Because these expressions are shown to be parametrically equivalent, we can make the same…

不规则间隔观测的平稳性检验及采样频率对功效的影响AI 解读

In this article, starting from continuous-time local level unobserved components models for stock and flow data we derive locally best invariant (LBI) stationarity tests for data available at potentially irregularly spaced points in time. We demonstrate that the form of the LBI test differs between stock and flow variables. In cases where the data are observed at regular intervals throughout the sample we show that the LBI tests for stock and flow data both reduce to the…