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动态异质面板的混合均值组估计AI 解读

It is now quite common to have panels in which both T, the number of time series observations, and N, the number of groups, are quite large and of the same order of magnitude. The usual practice is either to estimate N separate regressions and calculate the coefficient means, which we call the mean group (MG) estimator, or to pool the data and assume that the slope coefficients and error variances are identical. In this article we propose an intermediate procedure, the…

通过模拟进行滤波：辅助粒子滤波器AI 解读

This article analyses the recently suggested particle approach to filtering time series. We suggest that the algorithm is not robust to outliers for two reasons: The design of the simulators and the use of the discrete support to represent the sequentially updating prior distribution. Here we tackle the first of these problems.

脑电轨迹的评估与比较：非平稳时间序列中的潜在结构AI 解读

We explore and illustrate the use of time series decomposition methods for evaluating and comparing latent structure in nonstationary electroencephalographic (EEG) traces obtained from depressed patients during brain seizures induced as part of electroconvulsive therapy (ECT). Analysis of the patterns of change over time in the frequency structure of such EEG data provides insight into the neurophysiological mechanisms of action of this effective but poorly understood…

重尾实用指南：统计技术与应用AI 解读

Part 1 Applications: heavy tailed probability distributions in the World Wide Web, M.E. Crovella et al self-similarity and heavy tails - structural modelling of network traffic, W. Willinger et al heavy tails in high-frequency financial data, U.A. Muller et al stable paretian modelling in finance - some empirical and theoretical aspects, S. Mittnik et al risk management and quantile estimation, F. Bassi et al. Part 2 Time series: analyzing stable time series, R.J. Adler et…

动态非线性计量经济模型：渐近理论AI 解读

1 Introduction.- 2 Models, Data Generating Processes, and Estimators.- 3 Basic Structure of the Classical Consistency Proof.- 4 Further Comments on Consistency Proofs.- 5 Uniform Laws of Large Numbers.- 6 Approximation Concepts and Limit Theorems.- 7 Consistency: Catalogues of Assumptions.- 8 Basic Structure of the Asymptotic Normality Proof.- 9 Asymptotic Normality under Nonstandard Conditions.- 10 Central Limit Theorems.- 11 Asymptotic Normality: Catalogues of…

脑电轨迹的评估与比较：非平稳时间序列中的潜在结构AI 解读

We explore and illustrate the use of time series decomposition methods for evaluating and comparing latent structure in nonstationary electroencephalographic (EEG) traces obtained from depressed patients during brain seizures induced as part of electroconvulsive therapy (ECT). Analysis of the patterns of change over time in the frequency structure of such EEG data provides insight into the neurophysiological mechanisms of action of this effective but poorly understood…

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水平序列记忆参数估计中的长短记忆条件异方差AI 解读

Semiparametric estimates of long memory seem useful in the analysis of long financial time series because they are consistent under much broader conditions than parametric estimates. However, recent large sample theory for semiparametric estimates forbids conditional heteroskedasticity. We show that a leading semiparametric estimate, the Gaussian or local Whittle one, can be consistent and have the same limiting distribution under conditional heteroskedasticity as under the…

单整时间序列非线性变换的渐近理论AI 解读

An asymptotic theory for stochastic processes generated from nonlinear transformations of nonstationary integrated time series is developed. Various nonlinear functions of integrated series such as ARIMA time series are studied, and the asymptotic distributions of sample moments of such functions are obtained and analyzed. The transformations considered in the paper include a variety of functions that are used in practical nonlinear statistical analysis. It is shown that…

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面板数据中的伪回归与残差型协整检验AI 解读

In the first half of the paper I study spurious regressions in panel data. Asymptotic properties of the least-squares dummy variable (LSDV) estimator and other conventional statistics are examined. The asymptotics of LSDV estimator are different from those of the spurious regression in the pure time-series. This has an important consequence for residual-based cointegration tests in panel data, because the null distribution of residual-based cointegration tests depends on the…

通胀预测中的信息差异化解读AI 解读

We test the hypothesis associated with a standard assumption in the theoretical literature on learning: that economic agents interpret information identically. We use a data set based on a survey of Israeli business executives forecasting future inflation. One of the main advantages of using this data is that a major change in the inflation regime in 1985 can be treated as a natural experiment in new beliefs formation. We develop a methodology for testing this hypothesis and…

资产收益波动率的单位根检验AI 解读

It is now well established that the volatility of asset returns is time varying and highly persistent. One leading model that is used to represent these features of the data is the stochastic volatility model. The researcher may test for non‐stationarity of the volatility process by testing for a unit root in the log‐squared time series. This strategy for inference has many advantages, but is not followed in practice because these unit root tests are known to have very poor…

实际汇率随机游走假说的检验AI 解读

This paper tests the random walk hypothesis for the log‐differenced monthly US real exchange rates versus some major currencies. The tests we use are variance ratio test, Durlauf's (1991) spectral domain tests and Andrews and Ploberger's ( 1996) optimal tests. The variance ratio test is calculated by using Andrews' (1991) optimal data‐dependent methods. Finite sample properties of these tests are also reported. Because the results of applying these tests to the real exchange…

季节性非平稳时间序列中的共同周期AI 解读

This paper extends the notion of common cycles to quarterly time series having unit roots both at the zero and seasonal frequencies. It is shown that common cycles are present in the Hylleberg–Engle–Granger–Yoo decomposition of these series when there exists a linear combination of their seasonal differences which follows an MA process of order, at most, three. The pitfalls of seasonal adjustment for common cycles analysis are also documented. Inference on common cycles in…

季节性非平稳时间序列中的共同周期AI 解读

This paper extends the notion of common cycles to quarterly time series having unit roots both at the zero and seasonal frequencies. It is shown that common cycles are present in the Hylleberg-Engle-Granger-Yoo decomposition of these series when there exists a linear combination of their seasonal differences which follows an MA process of order, at most, three. The pitfalls of seasonal adjustment for common cycles analysis are also documented. Inference on common cycles in…

状态空间模型中最大似然估计量的渐近正态性AI 解读

State space models is a very general class of time series models capable of modelling dependent observations in a natural and interpretable way. Inference in such models has been studied by Bickel, Ritov and Rydén, who consider hidden Markov models, which are special kinds of state space models, and prove that the maximum likelihood estimator is asymptotically normal under mild regularity conditions. In this paper we generalize the results of Bickel, Ritov and Rydén to state…

可变长度马尔可夫链AI 解读

We study estimation in the class of stationary variable length Markov chains (VLMC) on a finite space. The processes in this class are still Markovian of high order, but with memory of variable length yielding a much bigger and structurally richer class of models than ordinary high-order Markov chains. From an algorithmic view, the VLMC model class has attracted interest in information theory and machine learning, but statistical properties have not yet been explored.…

误差修正机制的非对称生成器及其在银行抵押贷款利率动态中的应用AI 解读

Empirical evidence supports asymmetries in the adjustment of prices, interest rates, and other economic variables. The asymmetry hypothesis, however, is often procedurally difficult to set up and test. This article shows that a wide variety of such mechanisms can be nested within an asymmetry generator, which represents the interactions between the disequilibrium term of an error-correction mechanism and an ancillary driver process. The asymmetry hypothesis can then be…

滞后回归残差与序列相关检验AI 解读

A new family of statistics is proposed to test for the presence of serial correlation in linear regression models. The tests are based on partial sums of lagged cross-products of regression residuals that define a class of interesting Gaussian processes. These processes are characterized in terms of regressor functions, the serial-correlation structure, the distribution of the noise process, and the order of the lag of the cross-products of residuals. It is shown that these…

向量自回归过程中协整向量有效归一化的检验AI 解读

This article develops test procedures for checking the validity of general normalizing restrictions imposed on cointegrating vectors in vector autoregressive processes. Such test procedures are of importance because normalizing restrictions, possibly combined with overidentifying restrictions, are often necessary for a proper interpretation of cointegrating vectors. The null hypothesis of the authors' tests assumes that the employed normalization is valid or, alternatively,…

误差修正机制的非对称性生成器及银行按揭利率动态应用AI 解读

Empirical evidence supports asymmetries in the adjustment of prices, interest rates, and other economic variables. The asymmetry hypothesis, however, is often procedurally difficult to set up and test. This article shows that a wide variety of such mechanisms can be nested within an asymmetry generator, which represents the interactions between the disequilibrium term of an error-correction mechanism and an ancillary driver process. The asymmetry hypothesis can then be…