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长记忆自标准化线性过程的渐近性质AI 解读

In this paper we study the convergence to fractional Brownian motion for long memory time series having independent innovations with infinite second moment. For the sake of applications we derive the self-normalized version of this theorem. The study is motivated by models arising in economic applications where often the linear processes have long memory, and the innovations have heavy tails.

分数型函数中心极限定理的必要矩条件AI 解读

We discuss the moment condition for the fractional functional central limit theorem (FCLT) for partial sums of x t = Δ − d u t , where $d\, \in \,\left({ - {1 \over 2}\,,\,{1 \over 2}} \right)$ is the fractional integration parameter and u t is weakly dependent. The classical condition is existence of q ≥ 2 and $q\, > \,\left( {d\, + \,{1 \over 2}} \right)^{ - 1} $ moments of the innovation sequence. When d is close to $ - {1 \over 2}$ this moment condition is very strong.…

白噪声中的单位根AI 解读

We show that the empirical distribution of the roots of the vector autoregression (VAR) of order p fitted to T observations of a general stationary or nonstationary process converges to the uniform distribution over the unit circle on the complex plane, when both T and p tend to infinity so that (ln T )/ p → 0 and p 3 / T → 0. In particular, even if the process is a white noise, nearly all roots of the estimated VAR will converge by absolute value to unity. For fixed p , we…

利用扩展函数型Delta方法检验未知时点的相关性变化AI 解读

We propose a new test against a change in correlation at an unknown point in time based on cumulated sums of empirical correlations. The test does not require that inputs are independent and identically distributed under the null. We derive its limiting null distribution using a new functional delta method argument, provide a formula for its local power for particular types of structural changes, give some Monte Carlo evidence on its finite-sample behavior, and apply it to…

自回归模型的统一区间估计AI 解读

An empirical likelihood–based confidence interval is proposed for interval estimations of the autoregressive coefficient of a first-order autoregressive model via weighted score equations. Although the proposed weighted estimate is less efficient than the usual least squares estimate, its asymptotic limit is always normal without assuming stationarity of the process. Unlike the bootstrap method or the least squares procedure, the proposed empirical likelihood–based…

金融改革的政治经济学：Huang 的发现有多稳健？AI 解读

SUMMARY Using new data on financial liberalization taken from Abiad et al . (2008, IMF Working Papers, No. 08/266) for 62 countries over the period 1975–2005, we show that some of the main findings of Huang's (2009, Journal of Applied Econometrics 24 : 1207–1213) replication study on the drivers of financial liberalization are not robust. Major changes concern the effect of democracy on financial reform and the supposed relationship between the desired level of financial…

能源价格动态中时变参数的识别稳健检验AI 解读

SUMMARY We test for the presence of time‐varying parameters (TVP) in the long‐run dynamics of energy prices for oil, natural gas and coal, within a standard class of mean‐reverting models. We also propose residual‐based diagnostic tests and examine out‐of‐sample forecasts. In‐sample LR tests support the TVP model for coal and gas but not for oil, though companion diagnostics suggest that the model is too restrictive to conclusively fit the data. Out‐of‐sample analysis…

GVAR 框架下产出增长、通胀与贸易差额的概率预测AI 解读

SUMMARY We apply a global vector autoregressive (GVAR) model to the analysis of inflation, output growth and global imbalances among a group of 33 countries (26 regions). We account for structural instability by use of country‐specific intercept shifts, the timings of which are identified taking into account both statistical evidence and our knowledge of historic economic conditions and events. Using this model, we compute both central forecasts and scenario‐based…

经济增长的决定因素：贝叶斯面板数据方法AI 解读

Model uncertainty hampers consensus on the key determinants of economic growth. Some recent cross-country cross-sectional analyses have employed Bayesian model averaging to tackle the issue of model uncertainty. This paper extends that approach to panel data models with country-specific fixed effects in order to simultaneously address model uncertainty and endogeneity issues. The empirical findings suggest that in a panel setting, the most robust growth determinants are the…

长记忆或中间记忆高斯过程谱密度的贝叶斯非参数估计AI 解读

A stationary Gaussian process is said to be long-range dependent (resp., anti-persistent) if its spectral density $f(\lambda)$ can be written as $f(\lambda)=|\lambda|^{-2d}g(|\lambda|)$, where $0<d<1/2$ (resp., $-1/2<d<0$), and $g$ is continuous and positive. We propose a novel Bayesian nonparametric approach for the estimation of the spectral density of such processes. We prove posterior consistency for both $d$ and $g$, under appropriate conditions on the prior…

非线性非平稳模型的设定检验AI 解读

We provide a limit theory for a general class of kernel smoothed U-statistics that may be used for specification testing in time series regression with nonstationary data. The test framework allows for linear and nonlinear models with endogenous regressors that have autoregressive unit roots or near unit roots. The limit theory for the specification test depends on the self-intersection local time of a Gaussian process. A new weak convergence result is developed for certain…

高维时间序列因子建模：因子个数的推断AI 解读

This paper deals with the factor modeling for high-dimensional time series based on a dimension-reduction viewpoint. Under stationary settings, the inference is simple in the sense that both the number of factors and the factor loadings are estimated in terms of an eigenanalysis for a nonnegative definite matrix, and is therefore applicable when the dimension of time series is on the order of a few thousands. Asymptotic properties of the proposed method are investigated…

部分变系数动态模型的半参数分位数回归估计AI 解读

We study quantile regression estimation for dynamic models with partially varying coefficients so that the values of some coefficients may be functions of informative covariates. Estimation of both parametric and nonparametric functional coefficients are proposed. In particular, we propose a three stage semiparametric procedure. Both consistency and asymptotic normality of the proposed estimators are derived. We demonstrate that the parametric estimators are root-n…

相关面板中基于残差的协整检验AI 解读

In the paper, we propose residual based tests for cointegration in general panels with cross-sectional dependency, endogeneity and various heterogeneities. The residuals are obtained from the usual least squares estimation of the postulated cointegrating relationships from each individual unit, and the nonlinear IV panel unit root testing procedure is applied to the panels of the fitted residuals using as instruments the nonlinear transformations of the adaptively fitted…

受扰动分数过程的局部多项式 Whittle 估计AI 解读

We propose a semiparametric local polynomial Whittle with noise estimator of the memory parameter in long memory time series perturbed by a noise term which may be serially correlated. The estimator approximates the log-spectrum of the short-memory component of the signal as well as that of the perturbation by two separate polynomials. Including these polynomials we obtain a reduction in the order of magnitude of the bias, but also inflate the asymptotic variance of the long…

非平稳非线性回归的部分参数估计AI 解读

This paper proposes an estimation method for a partial parametric model with multiple integrated time series. Our estimation procedure is based on the decomposition of the nonparametric part of the regression function into homogeneous and integrable components. It consists of two steps: In the first step we parameterize and fit the homogeneous component of the nonparametric part by the nonlinear least squares with other parametric terms in the model, and use in the second…

使用柯西估计量的异方差面板单位根检验AI 解读

The Cauchy estimator of an autoregressive root uses the sign of the first lag as instrumental variable. The resulting IV t-type statistic follows a standard normal limiting distribution under a unit root case even under unconditional heteroscedasticity, if the series to be tested has no deterministic trends. The standard normality of the Cauchy test is exploited to obtain a standard normal panel unit root test under cross-sectional dependence and time-varying volatility with…

实际油价的实时预测AI 解读

We construct a monthly real-time dataset consisting of vintages for 1991.1–2010.12 that is suitable for generating forecasts of the real price of oil from a variety of models. We document that revisions of the data typically represent news, and we introduce backcasting and nowcasting techniques to fill gaps in the real-time data. We show that real-time forecasts of the real price of oil can be more accurate than the no-change forecast at horizons up to 1 year. In some cases,…

基于Copula的非参数条件独立检验及其格兰杰因果应用AI 解读

This article proposes a new nonparametric test for conditional independence that can directly be applied to test for Granger causality. Based on the comparison of copula densities, the test is easy to implement because it does not involve a weighting function in the test statistic, and it can be applied in general settings since there is no restriction on the dimension of the time series data. In fact, to apply the test, only a bandwidth is needed for the nonparametric…

数据修订条件下的 VAR 估计与预测AI 解读

We show that Howrey’s method for producing economic forecasts when data are subject to revision is easily generalized to handle the case where data are produced by a sophisticated statistical agency. The proposed approach assumes that government estimates are efficient with a finite lag. It takes no stand on whether earlier revisions are the result of “news” or of reductions in “noise.” We present asymptotic performance results in the scalar case and illustrate the technique…

非平稳波动下单位根检验的自助法联合检验AI 解读

Three important issues surround testing for a unit root in practice: uncertainty as to whether or not a linear deterministic trend is present in the data; uncertainty as to whether the initial condition of the process is (asymptotically) negligible or not, and the possible presence of nonstationary volatility in the data. Assuming homoskedasticity, Harvey, Leybourne, and Taylor (2011, Journal of Econometrics , forthcoming) propose decision rules based on a four-way union of…

短记忆、长记忆及负记忆时间序列学生化均值的固定带宽渐近理论AI 解读

This paper considers the problem of variance estimation for the sample mean in the context of long memory and negative memory time series dynamics, adopting the fixed-bandwidth approach now popular in the econometrics literature. The distribution theory generalizes the short memory results of Kiefer and Vogelsang (2005, Econometric Theory 21, 1130–1164). In particular, our results highlight the dependence on the kernel (we include flat-top kernels), whether or not the kernel…

平稳高斯过程记忆参数极大似然估计的渐近理论AI 解读

Consistency, asymptotic normality, and efficiency of the maximum likelihood estimator for stationary Gaussian time series were shown to hold in the short memory case by Hannan (1973, Journal of Applied Probability 10, 130–145) and in the long memory case by Dahlhaus (1989, Annals of Statistics 34, 1045–1047). In this paper we extend these results to the entire stationarity region, including the case of antipersistence and noninvertibility.

因子模型的有效估计AI 解读

This paper considers the factor model X t = Λ F t + e t . Assuming a normal distribution for the idiosyncratic error e t conditional on the factors { F t }, conditional maximum likelihood estimators of the factor and factor-loading spaces are derived. These estimators are called generalized principal component estimators (GPCEs) without the normality assumption. This paper derives asymptotic distributions of the GPCEs of the factor and factor-loading spaces. It is shown that…