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SAMPLE MEANS, SAMPLE AUTOCOVARIANCES, AND LINEAR REGRESSION OF STATIONARY MULTIVARIATE LONG MEMORY PROCESSES

平稳多元长记忆过程的样本均值、自协方差与线性回归

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…

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MIXING AND MOMENT PROPERTIES OF VARIOUS GARCH AND STOCHASTIC VOLATILITY MODELS

多类 GARCH 与随机波动率模型的混合性和矩性质

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…

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High Order Data Sharpening for Density Estimation

密度估计中的高阶数据锐化

Summary It is shown that data sharpening can be used to produce density estimators that enjoy arbitrarily high orders of bias reduction. Practical advantages of this approach, relative to competing methods, are demonstrated. They include the sheer simplicity of the estimators, which makes code for computing them particularly easy to write, very good mean-squared error performance, reduced ‘wiggliness' of estimates and greater robustness against undersmoothing.

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Robust Estimation in Generalized Linear Mixed Models

广义线性混合模型中的稳健估计

Summary Generalized linear mixed models (GLMMs) are widely used to analyse non-normal response data with extra-variation, but non-robust estimators are still routinely used. We propose robust methods for maximum quasi-likelihood and residual maximum quasi-likelihood estimation to limit the influence of outlying observations in GLMMs. The estimation procedure parallels the development of robust estimation methods in linear mixed models, but with adjustments in the dependent…

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Consistency of Bernstein Polynomial Posteriors

伯恩斯坦多项式后验的一致性

Summary A Bernstein prior is a probability measure on the space of all the distribution functions on [0, 1]. Under very general assumptions, it selects absolutely continuous distribution functions, whose densities are mixtures of known beta densities. The Bernstein prior is of interest in Bayesian nonparametric inference with continuous data. We study the consistency of the posterior from a Bernstein prior. We first show that, under mild assumptions, the posterior is weakly…

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Cox Regression in Cohort Studies with Validation Sampling

含验证抽样的队列研究中的 Cox 回归

Summary An estimation procedure is proposed for the Cox model in cohort studies with validation sampling, where crude covariate information is observed for the full cohort and true covariate information is collected on a validation set sampled randomly from the full cohort. The method proposed makes use of the partial information from data that are available on the entire cohort by fitting a working Cox model relating crude covariates to the failure time. The resulting…

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Bootstrapping Survival Times in Stochastic Systems by Using Saddlepoint Approximations

利用鞍点近似对随机系统生存时间进行自助推断

Summary The single bootstrap is implemented by using a saddlepoint approximation to determine estimates for the survival and hazard functions of first-passage times in complicated semi-Markov processes. The double bootstrap is also implemented by resampling saddlepoint inversions and provides BCa confidence bands for these functions. Confidence intervals for the mean and variance of first-passage times are easily computed. A new characterization of the asymptotic hazard rate…

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Censored Regression with the Multistate Accelerated Sojourn Times Model

多状态加速停留时间模型的删失回归

Summary Many disease processes are characterized by two or more successive health states, and it is often of interest and importance to assess state-specific covariate effects. However, with incomplete follow-up data such inference has not been satisfactorily addressed in the literature. We model the logarithm-transformed sojourn time in each state as linearly related to the covariates; however, neither the distributional form of the error term nor the dependence structure…

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Exact tests for contemporaneous correlation of disturbances in seemingly unrelated regressions

似不相关回归中扰动同期相关性的精确检验

This paper proposes finite-sample procedures for testing the SURE specification in multi-equation regression models, i.e. whether the disturbances in different equations are contemporaneously uncorrelated or not. We apply the technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] to obtain exact tests based on standard LR and LM zero correlation tests. We also suggest a MC quasi-LR (QLR) test based on feasible generalized least squares (FGLS). We show that the…

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Nonparametric frontier estimation: a robust approach

非参数前沿估计:一种稳健方法

A large amount of literature has been developed on how to specify and to estimate production frontiers or cost functions. Two different approaches have been mainly developed: the deterministic frontier model which relies on the assumption that all the observations are on a unique side of the frontier, and the stochastic frontier models where observational errors or random noise allows some observations to be outside of the frontier. In a deterministic frontier framework,…

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Regressions, Short and Long

短回归与长回归

We study the problem of identi cation of the long regression E(y j x � z) when the short conditional distributions P (y j x) and P (z j x) are known but the long conditional distribution P (y j x � z) is not known. This problem often arises when a researcher utilizes data from two separate data sets. (A leading example is the ecological inference problem of political science, where voting behavior across electoral districts is observed from administrative records, the…

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Maximum Likelihood Estimation of Discretely Sampled Diffusions: A Closed-form Approximation Approach

离散采样扩散过程的最大似然估计:闭式近似方法

When a continuous-time diffusion is observed only at discrete dates, in most cases the transition distribution and hence the likelihood function of the observations is not explicitly computable. Using Hermite polynomials, I construct an explicit sequence of closed-form functions and show that it converges to the true (but unknown) likelihood function. I document that the approximation is very accurate and prove that maximizing the sequence results in an estimator that…

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A New Specification Test for the Validity of Instrumental Variables

工具变量有效性的一种新规格检验

We develop a new specification test for IV estimators adopting a particular second order approximation of Bekker. The new specification test compares the difference of the forward (conventional) 2SLS estimator of the coefficient of the right-hand side endogenous variable with the reverse 2SLS estimator of the same unknown parameter when the normalization is changed. Under the null hypothesis that conventional first order asymptotics provide a reliable guide to inference, the…

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Higher-Order Improvements of a Computationally Attractive k-Step Bootstrap for Extremum Estimators

极值估计量的计算便捷型 k 步 Bootstrap 的高阶改进

The copyright to this Article is held by the Econometric Society. It may be downloaded, printed and reproduced only for educational or research purposes, including use in course packs. No downloading or copying may be done for any commercial purpose without the explicit permission of the Econometric Society. For such commercial purposes contact the Office of the Econometric Society (contact information may be found at the website

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The Message in Daily Exchange Rates

日度汇率传递的信息

Formal testing procedures confirm the presence of a unit root in the autoregressive ploynomial of the univariate time series representation of daily exchange-rate data. the first differences of the logarithms of daily spot rates are approximately uncorrelated through time, and a generalized autoregressive conditional heteroscedasticity model with daily dummy variables and conditionally t-distributed errors is found to provide a good representation to the leptokurtosis and…

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Tests for Parameter Instability in Regressions With I(1) Processes

含 I(1) 过程的回归中的参数不稳定检验

This article derives the large-sample distributions of Lagrange multiplier (LM) tests for parameter instability against several alternatives of interest in the context of cointegrated regression models. The fully modified estimator of Phillips and Hansen is extended to cover general models with stochastic and deterministic trends. The test statistics considered include the SupF test of Quandt, as well as the LM tests of Nyblom and of Nabeya and Tanaka. It is found that the…

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Determining the Order of Differencing in Autoregressive Processes

自回归过程差分阶数的确定

One way of handling nonstationarity in time series is to compute first differences and fit a model to the differenced series unless the differenced series also looks nonstationary. In that case, second- or higher-order differencing is done. To decide if the current degree of differencing is sufficient, one can look at the autocorrelation function for slow decay. A formal statistical test for the need to difference further is available if one is willing to assume that at most…

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Comparing Predictive Accuracy

预测准确性的比较

We propose and evaluate explicit tests of the null hypothesis of no difference in the accuracy of two competing forecasts. In contrast to previously developed tests, a wide variety of accuracy measures can be used (in particular, the loss of function need not be quadratic and need not even be symmetric), and forecast errors can be non-Gaussian, nonzero mean, serially correlated, and contemporaneously correlated. Asymptotic and exact finite-sample tests are proposed,…

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Vector Autoregressions and Reality

向量自回归与现实

This article questions the statistical significance of variance decompositions and impulse response functions for unrestricted vector auto regressions. It suggests that previous authors have failed to provide confidence intervals for variance decompositions and impulse response functions. Two methods of computing such confidence intervals are developed: first, using a normal approximation; second, using bootstrapped resampling. An example from Sims's work is used to…

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Estimation and Inference in Two-Step Econometric Models

两步计量模型中的估计与推断

A commonly used procedure in a wide class of empirical applications is to impute unobserved regressors, such as expectations, from an auxiliary econometric model. This two-step (T-S) procedure fails to account for the fact that imputed regressors are measured with sampling error, so hypothesis tests based on the estimated covariance matrix of the second-step estimator are biased, even in large samples. We present a simple yet general method of calculating asymptotically…

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Bayesian Analysis of Stochastic Volatility Models

随机波动率模型的贝叶斯分析

New techniques for the analysis of stochastic volatility models in which the logarithm of conditional variance follows an autoregressive model are developed. A cyclic Metropolis algorithm is used to construct a Markov-chain simulation tool. Simulations from this Markov chain coverage in distribution to draws from the posterior distribution enabling exact finite-sample inference. The exact solution to the filtering/smoothing problem of inferring about the unobserved variance…

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Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis

大崩盘、石油价格冲击与单位根假说的进一步证据

Perron (1989) has carried out tests of the unit root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil price shock. Here a variation of Perron's test is considered in which the break point is estimated rather than fixed. The asymptotic distribution of the "estimated break point" test statistic is determined and the data considered by Perron are reanalyzed. The authors find…

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Tests for Unit Roots

单位根检验

Recent work by Said and Dickey (1984, 1985), Phillips (1987), and Phillips and Perron (1988) examines tests for unit roots in the autoregressive part of mixed autoregressive integrated moving average models (tests for stationarity). Monte Carlo experiments show that these unit-root tests have different finite-sample distributions from the unit-root tests developed by Fuller (1976) and Dickey and Fuller (1979, 1981) for autoregressive processes. In particular, the tests…

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