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针对分数积分扰动的Durbin–Watson检验有限样本功效AI 解读

We consider the finite-sample power of various tests against serial correlation in the disturbances of a linear regression model when these disturbances follow certain stationary long-memory processes. It emerges that the power depends on the form of the regressor matrix and that, for the Durbin--Watson test and many other tests that can be written as ratios of quadratic forms in the disturbances, the power can drop to zero as the long-memory parameter approaches the…

利用横截面估计协整关系AI 解读

This paper specifies a regression model describing cointegrating relations between variables at the individual level. The models considered allow for homogeneous cointegration and heterogeneous cointegration. In both cases correlation between the regressors and the regression error can occur through aggregate shocks that are common to all cross-section units so the condition about the regressors being independent of the regression error is not imposed. It is shown that the…

存在趋势突变时基于残差的块自助法单位根检验AI 解读

In this paper, we build on the "residual-based block bootstrap unit root testing" (RBB) method, proposed by Paparoditis and Politis (2003). We develop an extension of this method to allow for bootstrap unit root testing in a model defined by an augmented Dickey--Fuller (ADF) equation that contains linear combinations of arbitrary dummies as its deterministic part. The main application of such an extension is that it allows for unit root testing in the presence of arbitrary…

GARCH均值模型中的人工回归检验AI 解读

The issue of finite-sample inference in Generalised Autoregressive Conditional Heteroskedasticity (GARCH)-like models has seldom been explored in the theoretical literature, although its potential relevance for practitioners is obvious. In some cases, asymptotic theory may provide a very poor approximation to the actual distribution of the estimators in finite samples. The aim of this paper is to propose the application of the so-called double length regressions (DLR) to…

This paper derives second‐order expansions for the distributions of the Whittle and profile plug‐in maximum likelihood estimators of the fractional difference parameter in the ‘Autoregressive Fractionally Integrated Moving Average of order (0, d, 0)’ with unknown mean and variance. Both estimators are shown to be second‐order pivotal. This extends earlier findings of Lieberman and Phillips (2004a, Econometric Theory, 20, 464–84), who derived expansions for the Gaussian…

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用于天气雷达反射率即时预报的核时空动态模型AI 解读

A good short-period forecast of heavy rainfall is essential for many meteorological and hydrological applications. Traditional deterministic and stochastic nowcasting methodologies have been inadequate in their characterization of pixelwise rainfall reflectivity propagation, intensity, and uncertainty. The methodology presented herein uses an approach that efficiently parameterizes spatio-temporal dynamic models in terms of integro-difference equations within a hierarchical…

两个时间尺度的故事AI 解读

It is a common practice in finance to estimate volatility from the sum of frequently sampled squared returns. However, market microstructure poses challenges to this estimation approach, as evidenced by recent empirical studies in finance. The present work attempts to lay out theoretical grounds that reconcile continuous-time modeling and discrete-time samples. We propose an estimation approach that takes advantage of the rich sources in tick-by-tick data while preserving…

非随机样本下的预测AI 解读

The 1990s was not the best of decades for electoral polls, with striking errors occurring in, among others, the British, French, and Spanish elections, including election night, when errors are more evident. This article proposes a model for predicting final election outcomes based on the consistency that polling stations show between elections. Using both past and incoming polling station vote proportions, the model produces continuously revised predictions. The method is…

Kim 检验对含结构断点平稳过程的拒绝概率证明AI 解读

In this note we show that, when the true data generating process is a stationary one around a constant term with a break, the stationarity test of Kim (2000, Journal of Econometrics 95, 97–116) against the alternative hypothesis of change of persistence rejects the null of stationarity asymptotically with probability one.I am grateful to an anonymous referee for his useful comments, which have helped to improve the content and presentation of this note. I acknowledge…

异方差与自相关稳健检验的新渐近理论AI 解读

A new first-order asymptotic theory for heteroskedasticity-autocorrelation (HAC) robust tests based on nonparametric covariance matrix estimators is developed. The bandwidth of the covariance matrix estimator is modeled as a fixed proportion of the sample size. This leads to a distribution theory for HAC robust tests that explicitly captures the choice of bandwidth and kernel. This contrasts with the traditional asymptotics (where the bandwidth increases more slowly than the…

时变二阶矩下的平稳性检验AI 解读

In this paper we analyze the effects of a very general class of time-varying variances on well-known “stationarity” tests of the I(0) null hypothesis. Our setup allows, among other things, for both single and multiple breaks in variance, smooth transition variance breaks, and (piecewise-) linear trending variances. We derive representations for the limiting distributions of the test statistics under variance breaks in the errors of I(0), I(1), and near-I(1) data generating…

长程依赖线性过程下采样窗口法的有效性AI 解读

The sampling window method of Hall, Jing, and Lahiri (1998, Statistica Sinica 8, 1189–1204) is known to consistently estimate the distribution of the sample mean for a class of long-range dependent processes, generated by transformations of Gaussian time series. This paper shows that the same nonparametric subsampling method is also valid for an entirely different category of long-range dependent series that are linear with possibly non-Gaussian innovations. For these…

二元 ARCH 模型：QML 估计的有限样本性质及 LM 型检验应用AI 解读

This paper provides two main new results: the first shows theoretically that large biases and variances can arise when the quasi-maximum likelihood (QML) estimation method is employed in a simple bivariate structure under the assumption of conditional heteroskedasticity; and the second demonstrates how these analytical theoretical results can be used to improve the finite-sample performance of a test for multivariate autoregressive conditional heteroskedastic (ARCH) effects,…

动态均衡经济的估计：线性与非线性似然比较AI 解读

Abstract This paper compares two methods for undertaking likelihood‐based inference in dynamic equilibrium economies: a sequential Monte Carlo filter and the Kalman filter. The sequential Monte Carlo filter exploits the nonlinear structure of the economy and evaluates the likelihood function of the model by simulation methods. The Kalman filter estimates a linearization of the economy around the steady state. We report two main results. First, both for simulated and for real…

周期性扩张的贴现债务是否威胁财政政策可持续性？AI 解读

Abstract This paper models the behaviour of discounted US debt using a Markov‐switching time series model. The significance of modelling fiscal policy within this framework derives from the implications it has for long‐term sustainability. The two‐regime framework used in this paper identifies periods where the present value of US Federal debt is expanding versus periods when it is collapsing. Using an updated data series from Hamilton and Flavin ( 1986 ), a test is…

波动模型的预测比较：有模型能胜过 GARCH(1,1) 吗？AI 解读

Abstract We compare 330 ARCH‐type models in terms of their ability to describe the conditional variance. The models are compared out‐of‐sample using DM–$ exchange rate data and IBM return data, where the latter is based on a new data set of realized variance. We find no evidence that a GARCH(1,1) is outperformed by more sophisticated models in our analysis of exchange rates, whereas the GARCH(1,1) is clearly inferior to models that can accommodate a leverage effect in our…

总能实现良好的随机化序贯概率预测AI 解读

Summary Building on the game theoretic framework for probability, we show that it is possible, using randomization, to make sequential probability forecasts that will pass any given battery of statistical tests. This result, an easy consequence of von Neumann's minimax theorem, simplifies and generalizes work by earlier researchers.

Summary We develop a new class of time continuous autoregressive fractionally integrated moving average (CARFIMA) models which are useful for modelling regularly spaced and irregu-larly spaced discrete time long memory data. We derive the autocovariance function of a stationary CARFIMA model and study maximum likelihood estimation of a regression model with CARFIMA errors, based on discrete time data and via the innovations algorithm. It is shown that the maximum likelihood…

规则监测数据的统计方法AI 解读

Summary Meteorological and environmental data that are collected at regular time intervals on a fixed monitoring network can be usefully studied combining ideas from multiple time series and spatial statistics, particularly when there are little or no missing data. This work investigates methods for modelling such data and ways of approximating the associated likelihood functions. Models for processes on the sphere crossed with time are emphasized, especially models that are…

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长记忆回归过程中的结构变化检验AI 解读

The paper considers tests for structural change in time series regression models where both regressors and residuals may exhibit long range dependence. The limiting distribution of the test statistic depends on unknown parameters and is approximated by a bootstrap procedure. The asymptotic validity of bootstrap is shown and performance of the testing procedure is examined in a simple Monte Carlo experiment.

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