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备择为趋势突变平稳过程时的单位根检验AI 解读

of break under the alternative evolves according to the crash, changing growth, and mixed models. It is shown that serious power distortions occur if the form of break is misspecified, and thus the practitioner should use the mixed model as the appropriate alternative in empirical applications. The mixed model may reveal useful information regarding the location and form of break. The maximum F statistic for the joint null of a unit-root and no breaks is shown to have…

多重结构变化模型的计算与分析AI 解读

Abstract In a recent paper, Bai and Perron ( 1998 ) considered theoretical issues related to the limiting distribution of estimators and test statistics in the linear model with multiple structural changes. In this companion paper, we consider practical issues for the empirical applications of the procedures. We first address the problem of estimation of the break dates and present an efficient algorithm to obtain global minimizers of the sum of squared residuals. This…

时变参数随机波动率均值模型的矩与动态结构AI 解读

This paper introduces and discusses some of the statistical properties of a time-varying parameter stochastic volatility (SV) in mean model. We derive the autocovariance function of an observed series, under the assumption that the conditional variance follows a flexible parameterization, which nests the autoregressive SV and the exponential GARCH specifications. Furthermore, the mean parameter can be time varying. We also present the autocovariance functions of higher…

含删失与协变量测量误差的非线性混合效应联合模型：艾滋病研究应用AI 解读

In recent years AIDS researchers have shown great interest in the study of HIV viral dynamics. Nonlinear mixed-effects models (NLMEs) have been proposed for modeling intrapatient and interpatient variations in viral load measurements. The interpatient variation often receives great attention and may be partially explained by time-varying covariates, such as CD4 cell counts. Statistical analyses in these studies are complicated by the following problems: (a) the viral load…

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室内环境源邻近效应的带标记点过程模型AI 解读

In indoor air quality studies, discrepancies between personal and stationary indoor air quality monitors arise because of the source proximity effect, in which pollutant sources near the respondent cause elevated and highly variable exposures. In a set of experiments in a home, concentrations of a continuously emitting tracer gas were simultaneously monitored at different distances from the tracer gas source. Concentration time series are modeled at collinear monitoring…

STAR 与 STAR-GARCH 模型的极大似然估计：理论与蒙特卡洛证据AI 解读

Abstract Theoretical and practical interest in non‐linear time series models, particularly regime switching models, have increased substantially in recent years. Given the abundant research activity in analysing time‐varying volatility through Generalized Autoregressive Conditional Heteroscedasticity (GARCH) processes (see Engle, 1982 ; Bollerslev, 1986 ), it is important to analyse regime switching models with GARCH errors. A popular specification in this class is the…

金融市场波动率动态中的多重结构突变检测AI 解读

Abstract The paper evaluates the performance of several recently proposed tests for structural breaks in the conditional variance dynamics of asset returns. The tests apply to the class of ARCH and SV type processes as well as data‐driven volatility estimators using high‐frequency data. In addition to testing for the presence of breaks, the statistics identify the number and location of multiple breaks. We study the size and power of the new tests for detecting breaks in the…

摘要暂缺

线性回归结构变化的最优相似检验AI 解读

This paper analyzes similar tests for structural change for the normal linear regression model in finite samples. Using the approach of Wald (1943, American Mathematical Society Transactions 54, 426–482), Hillier (1987, Econometric Theory 3, 1–44), Andrews and Ploberger (1994, Econometrica 62, 1382–1414), and Andrews, Lee, and Ploberger (1996, Journal of Econometrics 70, 9–36), we characterize a class of optimal similar tests for the existence of (possibly multiple)…

股票市场收益中的条件跳跃动态AI 解读

This article develops a new conditional jump model to study jump dynamics in stock market returns. We propose a simple filter to infer ex post the distribution of jumps. This permits construction of the shock affecting the time t conditional jump intensity and is the main input into an autoregressive conditional jump intensity model. The model allows the conditional jump intensity to be time-varying and follows an approximate autoregressive moving average (ARMA) form. The…

外汇收益中的波动率、动量与时变偏度AI 解读

This article tests a stochastic volatility model of exchange rates that links both the level of volatility and its instantaneous covariance with returns to pathwise properties of the currency. In particular, the model implies that the return-volatility covariance behaves like a weighted average of recent returns and hence switches signs according to the direction of trends in the data. This implies that the skewness of the finite-horizon return distribution likewise switches…

具有时变相关性的多元广义自回归条件异方差模型AI 解读

In this article we propose a new multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) model with time-varying correlations. We adopt the vech representation based on the conditional variances and the conditional correlations. Whereas each conditional-variance term is assumed to follow a univariate GARCH formulation, the conditional-correlation matrix is postulated to follow an autoregressive moving average type of analog. Our new model retains the…

动态条件相关AI 解读

Time varying correlations are often estimated with multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation models is proposed. These have the flexibility of univariate GARCH models coupled with parsimonious parametric models for the correlations. They are not linear but can often be estimated very simply with…

灵活的加性—乘性风险率模型AI 解读

We present a new additive‐multiplicative hazard model which consists of two components. The first component contains additive covariate effects through an additive Aalen model while the second component contains multiplicative covariate effects through a Cox regression model. The Aalen model allows for time‐varying covariate effects, while the Cox model allows only a common time‐dependence through the baseline. Approximate maximum likelihood estimators are derived by solving…

观测误差下的变点、边界与前沿估计AI 解读

A range of problems in economics and statistics involve calculation of the boundary, or frontier, of the support of a distribution. Several practical and attractive solutions exist if the sampled distribution has a sharp discontinuity at the frontier, but accuracy can be greatly diminished if the data are observed with error. Indeed, if the error is additive and has variance σ2 then inaccuracies are usually of order σ, for small σ. In this article we suggest an elementary…

纵向边际模型中的非参数回归AI 解读

We consider nonparametric regression in a longitudinal marginal model of generalized estimating equation (GEE) type with a time-varying covariate in the situation where the number of observations per subject is finite and the number of subjects is large. In such models, the basic shape of the regression function is affected only by the covariate values and not otherwise by the ordering of the observations. Two methods of estimating the nonparametric function can be…

阈值模型最小绝对偏差估计的说明AI 解读

This paper develops the limit law for the least absolute deviation estimator of the threshold parameter in linear regression. In this respect, we extend the literature of threshold models. The existing literature considers only the least squares estimation of the threshold parameter (see Chan, 1993, Annals of Statistics 21, 520–533; Hansen, 2000, Econometrica 68, 575–605). This result is useful because in the case of heavy-tailed errors there is an efficiency loss resulting…

结构变化与表面未识别的结构方程AI 解读

This paper introduces structural equations that do not satisfy the rank and/or order condition(s) for identification but still are identifiable. These equations are called seemingly unidentified structural equations. The key to the identifiability of these equations is that the right-hand-side endogenous variables undergo structural changes with respect to the exogenous and/or predetermined variables. To estimate the seemingly unidentified structural equations, this paper…

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…

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.…

重复测量分析中的变系数模型与基函数近似AI 解读

A global smoothing procedure is developed using basis function approximations for estimating the parameters of a varying‐coefficient model with repeated measurements. Inference procedures based on a resampling subject bootstrap are proposed to construct confidence regions and to perform hypothesis testing. Conditional biases and variances of our estimators and their asymptotic consistency are developed explicitly. Finite sample properties of our procedures are investigated…