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将赤池信息准则扩展至混合回归模型AI 解读

We examine the problem of jointly selecting the number of components and variables in finite mixture regression models. We find that the Akaike information criterion is unsatisfactory for this purpose because it overestimates the number of components, which in turn results in incorrect variables being retained in the model. Therefore, we derive a new information criterion, the mixture regression criterion (MRC), that yields marked improvement in model selection due to what…

采用两类邻接关系条件自回归先验的牙周数据空间分析AI 解读

Attachment loss, the extent of a tooth's root (in millimeters) that is no longer attached to surrounding bone by periodontal ligament, is often used to measure the current state of a patient's periodontal disease and monitor disease progression. Attachment loss data can be analyzed using a conditionally autoregressive (CAR) prior distribution that smooths fitted values toward neighboring values. However, it may be desirable to have more than one class of neighbor relation in…

一种简单的风险调整指数加权移动平均AI 解读

In such contexts as medical monitoring there is a need for a simple procedure to estimate the level of a smoothly changing dynamic process while adjusting for risk factors associated with heterogeneous nonnormal observations. Standard methods exist for when the data are normal, and simple methods have been developed for nonnormal data without covariates. The dynamic generalized linear model (DGLM) may be considered a standard for nonnormal data with covariates, but perhaps…

日度电力现货价格的周期季节性 Reg-ARFIMA–GARCH 模型AI 解读

Novel periodic extensions of dynamic long-memory regression models with autoregressive conditional heteroscedastic errors are considered for the analysis of daily electricity spot prices. The parameters of the model with mean and variance specifications are estimated simultaneously by the method of approximate maximum likelihood. The methods are implemented for time series of 1,200–4,400 daily price observations in four European power markets. Apart from persistence,…

利用半参数贝叶斯方法预测美国癌症死亡人数AI 解读

We present two models for the short-term prediction of the number of deaths arising from common cancers in the United States. The first is a local linear model, in which the slope of the segment joining the number of deaths for any two consecutive time periods is assumed to be random with a nonparametric distribution, which has a Dirichlet process prior. For slightly longer prediction periods, we present a local quadratic model. This extension of the local linear model…

分数单位根的有效 Wald 检验AI 解读

In this article we introduce efficient Wald tests for testing the null hypothesis of the unit root against the alternative of the fractional unit root. In a local alternative framework, the proposed tests are locally asymptotically equivalent to the optimal Robinson Lagrange multiplier tests. Our results contrast with the tests for fractional unit roots, introduced by Dolado, Gonzalo, and Mayoral, which are inefficient. In the presence of short range serial correlation, we…

多元回归中结构变化的估计与检验AI 解读

This paper considers issues related to estimation, inference, and computation with multiple structural changes that occur at unknown dates in a system of equations. Changes can occur in the regression coefficients and/or the covariance matrix of the errors. We also allow arbitrary restrictions on these parameters, which permits the analysis of partial structural change models, common breaks that occur in all equations, breaks that occur in a subset of equations, and so…

存在截面依赖时的简单面板单位根检验AI 解读

Abstract A number of panel unit root tests that allow for cross‐section dependence have been proposed in the literature that use orthogonalization type procedures to asymptotically eliminate the cross‐dependence of the series before standard panel unit root tests are applied to the transformed series. In this paper we propose a simple alternative where the standard augmented Dickey–Fuller (ADF) regressions are augmented with the cross‐section averages of lagged levels and…

非平稳面板的子抽样假设检验：汇率与股票价格应用AI 解读

Abstract This paper studies subsampling hypothesis tests for panel data that may be nonstationary, cross‐sectionally correlated, and cross‐sectionally cointegrated. The subsampling approach provides approximations to the finite sample distributions of the tests without estimating nuisance parameters. The tests include panel unit root and cointegration tests as special cases. The number of cross‐sectional units is assumed to be finite and that of time‐series observations…

意大利内部迁移的长期趋势：存在个体依赖的面板协整研究AI 解读

Abstract The objective of this paper is to examine the long‐run determinants of internal migrations from southern Italy. In order to accomplish this task, the paper develops a bootstrap test for panel cointegration analysis with dependent units. Monte Carlo simulations show that the test, based on the Continuous‐Path Block bootstrap, has good power and size properties and is robust to both short‐ and long‐run dependence across units. The empirical analysis points to income…

面板单位根检验与空间依赖AI 解读

Abstract This paper studies the performance of panel unit root tests when spatial effects are present that account for cross‐section correlation. Monte Carlo simulations show that there can be considerable size distortions in panel unit root tests when the true specification exhibits spatial error correlation. These tests are applied to a panel data set on net real income from the 1000 largest French communes observed over the period 1985–1998. Copyright © 2007 John Wiley &…

面板单位根检验中截面依赖的动态因子提取AI 解读

Abstract Recently, considerable emphasis has been placed on the problems arising out of cross‐sectional dependence in panel unit root tests. This paper adopts the factor‐based cross‐sectional dependence paradigm of Bai and Ng ( 2005 ) but suggests alternative factor extraction methods. Some theoretical results for these methods are provided. Further, a detailed Monte Carlo study of these methods for multiple and persistent factors is undertaken. It is found that results are…

面板数据模型中的异质性与截面依赖：理论与应用专题导言AI 解读

Abstract The papers included in this special issue are primarily concerned with the problem of cross section dependence and heterogeneity in the analysis of panel data models and their relevance in applied econometric research. Cross section dependence can arise due to spatial or spill over effects, or could be due to unobserved (or unobservable) common factors. Much of the recent research on non‐stationary panel data have focussed on this problem. It was clear that the…

社会资本、生产壁垒与资本份额：非平稳面板中的参数异质性AI 解读

Abstract Recent advances in the growth literature have proposed that difficult‐to‐quantify concepts such as social capital may play an important role in explaining the degree of persistent income disparity that is observed among countries. Other recently explored possibilities include institutional mechanisms which generate barriers to aggregate production. An important limitation for empirical work in this area stems from the fact that it is difficult to distinguish sources…

利用多分辨率近似对分形过程进行推断AI 解读

We consider Bayesian inference via Markov chain Monte Carlo for a variety of fractal Gaussian processes on the real line. These models have unknown parameters in the covariance matrix, requiring inversion of a new covariance matrix at each Markov chain Monte Carlo iteration. The processes have no suitable independence properties so this becomes computationally prohibitive. We surmount these difficulties by developing a computational algorithm for likelihood evaluation based…

多个时间序列片段的对齐AI 解读

We consider a local least-squares criterion for aligning multiple time series fragments differing by locations and show the consistency of the time-lag estimator and the asymptotic normality of the location estimator. We apply the criterion to the problem of aligning 50 glacial varve fragments and construct a 3000-year surrogate for global temperature.

通过平滑样条自动估计多变量谱AI 解读

The classical method for estimating the spectral density of a multivariate time series is to first calculate the periodogram, and then smooth it to obtain a consistent estimator. Typically, to ensure the estimate is positive definite, all the elements of the periodogram are smoothed the same way. There are, however, many situations for which different components of the spectral matrix have different degrees of smoothness, and hence require different smoothing parameters in…

分析非正态非线性时间序列的广义阈值混合模型：哈萨克斯坦鼠疫应用AI 解读

We introduce the generalized threshold mixed model for piecewise-linear stochastic regression with possibly nonnormal time-series data. It is assumed that the conditional probability distribution of the response variable belongs to the exponential family, and the conditional mean response is linked to some piecewise-linear stochastic regression function. We study the particular case where the response variable equals zero in the lower regime. Some large-sample properties of…

利用 lasso 收缩与选择回归系数及自回归阶数AI 解读

Summary The least absolute shrinkage and selection operator (‘lasso’) has been widely used in regression shrinkage and selection. We extend its application to the regression model with autoregressive errors. Two types of lasso estimators are carefully studied. The first is similar to the traditional lasso estimator with only two tuning parameters (one for regression coefficients and the other for autoregression coefficients). These tuning parameters can be easily calculated…

离散采样 Lévy 过程的波动率估计AI 解读

This paper studies the estimation of the volatility parameter in a model where the driving process is a Brownian motion or a more general symmetric stable process that is perturbed by another Lévy process. We distinguish between a parametric case, where the law of the perturbing process is known, and a semiparametric case, where it is not. In the parametric case, we construct estimators which are asymptotically efficient. In the semiparametric case, we can obtain…

非线性协整型模型中的非参数估计AI 解读

We derive an asymptotic theory of nonparametric estimation for a time series regression model Zt=f(Xt)+Wt, where {Xt} and {Zt} are observed nonstationary processes and {Wt} is an unobserved stationary process. In econometrics, this can be interpreted as a nonlinear cointegration type relationship, but we believe that our results are of wider interest. The class of nonstationary processes allowed for {Xt} is a subclass of the class of null recurrent Markov chains. This…

非独立同分布观测下后验分布的收敛速度AI 解读

We consider the asymptotic behavior of posterior distributions and Bayes estimators based on observations which are required to be neither independent nor identically distributed. We give general results on the rate of convergence of the posterior measure relative to distances derived from a testing criterion. We then specialize our results to independent, nonidentically distributed observations, Markov processes, stationary Gaussian time series and the white noise model. We…

未知形式条件异方差下时间序列条件均值模型的改进广义谱检验AI 解读

Dynamic economic theories usually have implications on and only on the conditional mean dynamics of economic processes. Using a generalized spectral derivative approach, Hong and Lee (2005, Review of Economic Studies 72, 499–541) recently proposed a new class of omnibus nonparametric specification tests for linear and nonlinear time series conditional mean models, where the dimension of the conditioning information set may be infinite. The tests can detect a wide range of…

维纳–柯尔莫哥洛夫滤波、频率选择滤波与多项式回归AI 解读

Adaptations of the classical Wiener–Kolmogorov filters are described that enable them to be applied to short nonstationary sequences. Alternative filtering methods that operate in the time domain and the frequency domain are described. The frequency-domain methods have the advantage of allowing components of the data to be separated along sharp dividing lines in the frequency domain, without incurring any leakage. The paper contains a novel treatment of the start-up problem…