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强自相关时间序列的阈值自回归模型AI 解读

In some cases the unit root or near unit root behavior of linear autoregressive models fitted to economic time series is not in accordance with the underlying economic theory. To accommodate this feature we consider a threshold autoregressive (TAR) process with the threshold effect only in the intercept term. Although these processes are stationary, their realizations switch between different regimes and can therefore closely resemble those of (near) integrated processes for…

基于扩散指数的宏观经济预测AI 解读

This article studies forecasting a macroeconomic time series variable using a large number of predictors. The predictors are summarized using a small number of indexes constructed by principal component analysis. An approximate dynamic factor model serves as the statistical framework for the estimation of the indexes and construction of the forecasts. The method is used to construct 6-, 12-, and 24-month ahead forecasts for eight monthly U.S. macroeconomic time series using…

含近不可逆移动平均成分模型的自助法推断AI 解读

This article proposes a bootstrap method for constructing two-sided confidence intervals for the moving average (MA) parameter in nearly noninvertible models. The confidence intervals are obtained by inverting the acceptance region of the likelihood ratio (LR) test reflecting the asymmetry of the likelihood near the noninvertibility boundary. The limiting distribution of the LR statistic is nonpivotal and its quantiles are parameterized as a function of the MA parameter and…

利率的状态切换AI 解读

We examine the econometric performance of regime-switching models for interest rate data from the United States, Germany, and the United Kingdom. Regime-switching models forecast better out-of-sample than single-regime models, including an affine multifactor model, but do not always match moments very well. Regime-switching models incorporating international short-rate and term spread information forecast better, match sample moments better, and classify regimes better than…

时间序列模型测量误差问题的统一方法AI 解读

The measurement error problem that we consider in this paper is concerned with the situation where time series data of various kinds—short memory, long memory, and random walk processes—are contaminated by white noise. We suggest a unified approach to testing for the existence of such noise. It is found that the power of our test crucially depends on the underlying process.

时间序列筛自助法的不变原理AI 解读

This paper establishes an invariance principle applicable for the asymptotic analysis of sieve bootstrap in time series. The sieve bootstrap is based on the approximation of a linear process by a finite autoregressive process of order increasing with the sample size, and resampling from the approximated autoregression. In this context, we prove an invariance principle for the bootstrap samples obtained from the approximated autoregressive process. It is of the strong form…

结构断点的稳健估计AI 解读

This paper proposes robust M -estimators of dynamic linear models with a structural break of unknown location. Rates of convergence and limiting distributions for the estimated shift point and the estimated regression parameters are derived. The analysis is carried out in the framework of possibly dependent observations and also with trending regressors. The asymptotic distribution of the break location estimator is obtained both for fixed magnitude of shift and for shift…

未知时点水平变化下的时间序列单位根检验AI 解读

Unit root tests for time series with level shifts of general form are considered when the timing of the shift is unknown. It is proposed to estimate the nuisance parameters of the data generation process including the shift date in a first step and apply standard unit root tests to the residuals. The estimation of the nuisance parameters is done in such a way that the unit root tests on the residuals have the same limiting distributions as for the case of a known break date.…

一种在计量经济学中具有应用价值的分块求逆公式AI 解读

In this paper a novel partitioned inversion formula is obtained in terms of the orthogonal complements of off-diagonal blocks, with the emblematic matrix of unit-root econometrics emerging as the leading diagonal block of the inverse. The result paves the way to a straightforward derivation of a key result of vector autoregressive econometrics.

协整向量线性约束检验：Wald 与似然比检验的有限样本大小和功效AI 解读

The Wald test for linear restrictions on cointegrating vectors is compared in finite samples using the Monte Carlo method. The Wald test is calculated within the vector error-correction based estimation methods of Bewley, Orden, Yang, and Fisher (1994, Journal of Econometrics 64, 3–27) and of Johansen (1991, Econometrica 59, 1551–1580), the canonical cointegration method of Park (1992, Econometrica 60, 119–143), the dynamic ordinary least squares method of Phillips and…

在不可观测成分框架中用微分差分方程刻画周期行为AI 解读

This paper considers a continuous time unobserved components model in which the cyclical component follows a differential-difference equation whereas the trend and seasonal components follow more standard differential equations. Estimation of the parameters of the model with either a stock or a flow variable is analyzed using a frequency domain Gaussian estimator whose asymptotic properties are derived paying particular attention to the role of a truncation parameter that…

部分观测时间序列的非线性检验札记AI 解读

We have implemented a Lagrange multiplier test for the alternative hypothesis of a nonlinear continuous‐time autoregressive model with the instantaneous mean having multiple degrees of nonlinearity. This test is an extension of a Lagrange multiplier test proposed by Tsai & Chan (2000), with the alternative model analogous to the model used in Tsay's (1986) discrete‐time work. The performance of the test in the finite‐sample case is compared with several existing tests for…

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购买力平价偏离半衰期的不确定性量化AI 解读

Abstract We propose a Bayesian framework in which the uncertainty about the half‐life of deviations from purchasing power parity can be quantified. Based on the responses to a survey study, we propose a prior probability distribution for the half‐life under the recent float intended to capture widely held views among economists. We derive the posterior probability distribution of the half‐life under this consensus prior and confirm the presence of substantial uncertainty…

可谐过程的谱分析AI 解读

Spectral estimation of nonstationary but harmonizable processes is considered. Given a single realization of the process, periodogram-like and consistent estimators are proposed for spectral mass estimation when the spectral support of the process consists of lines. Such a process can arise in signals of a moving source from array data or multipath signals with Doppler stretch from a single receiver. Such processes also include periodically correlated (or cyclostationary)…

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分数阶系统中的协整秩确定AI 解读

This paper develops methods of investigating the existence and extent of cointegration in fractionally integrated systems. We focus on stationary series, with some discussion of extension to nonstationarity. The setting is semiparametric, so that modelling is effectively confined to a neighbourhood of frequency zero. We first discuss the definition of fractional cointegration. The initial step of cointegration analysis entails partitioning the vector series into subsets with…

时间序列的回归分位数AI 解读

In this paper we study nonparametric estimation of regression quantiles for time series data by inverting a weighted Nadaraya–Watson (WNW) estimator of conditional distribution function, which was first used by Hall, Wolff, and Yao (1999, Journal of the American Statistical Association 94, 154–163). First, under some regularity conditions, we establish the asymptotic normality and weak consistency of the WNW conditional distribution estimator for α-mixing time series at both…

看似随机游走的平稳过程：离散与连续时间有界随机游走AI 解读

Several economic and financial time series are bounded by an upper and lower finite limit (e.g., interest rates). It is not possible to say that these time series are random walks because random walks are limitless with probability one (as time goes to infinity). Yet, some of these time series behave just like random walks. In this paper we propose a new approach that takes into account these ideas. We propose a discrete-time and a continuous-time process (diffusion process)…

ARCH(∞) 模型的平稳性AI 解读

We continue investigation of the ARCH(∞) model begun in Giraitis, Kokoszka, and Leipus (2000, Econometric Theory 16, 3–22). Nonrestrictive conditions for the existence of a strictly stationary solution are established. The paper generalizes the results of Nelson (1990, Econometric Theory 6, 318–334) and Bougerol and Picard (1992, Journal of Econometrics 52, 115–127) to the ARCH(∞) model.

线性过程的不变性原理及其应用AI 解读

Let X t be a linear process defined by X t = [sum ] k=0 ∞ ψ k ε t − k , where {ψ k , k ≥ 0} is a sequence of real numbers and {ε k , k = 0,±1,±2,...} is a sequence of random variables. Two basic results, on the invariance principle of the partial sum process of the X t converging to a standard Wiener process on [0,1], are presented in this paper. In the first result, we assume that the innovations ε k are independent and identically distributed random variables but do not…

平稳多元长记忆过程的样本均值、自协方差与线性回归AI 解读

We develop an asymptotic theory for the first two sample moments of a stationary multivariate long memory process under fairly general conditions. In this theory the convergence rates and the limits (the fractional Brownian motion, the Rosenblatt process, etc.) all depend intrinsically on the degree of long memory in the process. The theory of the sample moments is then applied to the multiple linear regression model. An interesting finding is that, even though all the…

多类 GARCH 与随机波动率模型的混合性和矩性质AI 解读

This paper first provides some useful results on a generalized random coefficient autoregressive model and a generalized hidden Markov model. These results simultaneously imply strict stationarity, existence of higher order moments, geometric ergodicity, and β-mixing with exponential decay rates, which are important properties for statistical inference. As applications, we then provide easy-to-verify sufficient conditions to ensure β-mixing and finite higher order moments…