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异方差ARFIMA模型的分数单整自助得分检验及商品价格应用AI 解读

Empirical evidence from time series methods which assume the usual I(0)/I(1) paradigm suggests that the efficient market hypothesis, stating that spot and futures prices of a commodity should co-integrate with a unit slope on futures prices, does not hold. However, these statistical methods are known to be unreliable if the data are fractionally integrated. Moreover, spot and futures price data tend to display clear patterns of time-varying volatility which also has the…

好与坏的不确定性：宏观经济和金融市场含义AI 解读

Does macroeconomic uncertainty increase or decrease aggregate growth and asset prices? To address this question, we decompose aggregate uncertainty into ‘good’ and ‘bad’ volatility components, associated with positive and negative innovations to macroeconomic growth. We document that in line with our theoretical framework, these two uncertainties have opposite impact on aggregate growth and asset prices. Good uncertainty predicts an increase in future economic activity, such…

含厚尾 G-GARCH 噪声的自回归模型渐近推断AI 解读

It is well known that the least squares estimator (LSE) of an AR( p ) model with i.i.d. (independent and identically distributed) noises is n 1/ α L ( n )-consistent when the tail index α of the noise is within (0,2) and is n 1/2 -consistent when α ≥ 2, where L ( n ) is a slowly varying function. When the noises are not i.i.d., however, the case is far from clear. This paper studies the LSE of AR( p ) models with heavy-tailed G-GARCH(1,1) noises. When the tail index α of…

时变非参数回归模型的结构变化检验AI 解读

In this paper, we consider a nonparametric model with a time-varying regression function and locally stationary regressors. We are interested in the question whether the regression function has the same shape over a given time span. To tackle this testing problem, we propose a kernel-based L 2 -test statistic. We derive the asymptotic distribution of the statistic both under the null and under fixed and local alternatives. To improve the small sample behavior of the test, we…

含单整解释变量门限模型的稳健估计与推断AI 解读

This paper studies the robust estimation and inference of threshold models with integrated regressors. We derive the asymptotic distribution of the profiled least squares (LS) estimator under the diminishing threshold effect assumption that the size of the threshold effect converges to zero. Depending on how rapidly this sequence converges, the model may be identified or only weakly identified and asymptotic theorems are developed for both cases. As the convergence rate is…

时间序列计量模型的简便综合过度识别设定检验AI 解读

Despite their theoretical advantages, Integrated Conditional Moment (ICM) specification tests are not commonly employed in the econometrics practice. An important reason is that the employed test statistics are nonpivotal, and so critical values are not readily available. This article proposes an omnibus test in the spirit of the ICM tests of Bierens and Ploberger (1997, Econometrica 65, 1129–1151) where the test statistic is based on the minimized value of a quadratic…

利用惩罚样条估计含非平稳解释变量的变系数模型AI 解读

This paper considers estimation and inference for varying-coefficient models with nonstationary regressors. We propose a nonparametric estimation method using penalized splines, which achieves the same optimal convergence rate as kernel-based methods, but enjoys computation advantages. Utilizing the mixed model representation of penalized splines, we develop a likelihood ratio test statistic for checking the stability of the regression coefficients. We derive both the exact…

非平稳与尖峰厚尾金融时间序列的建模AI 解读

Financial time series is often assumed to be stationary and has a normal distribution in the literature. Both assumptions are however unrealistic. This paper proposes a new methodology with a focus on volatility estimation that is able to account for nonstationarity and heavy tails simultaneously. In particular, a local exponential smoothing (LES) approach is developed, in which weak estimates with different memory parameters are aggregated in a locally adaptive way. The…

外商直接投资与时间对追赶的影响：条件非参数前沿分析的新见解AI 解读

Summary We use an appropriate nonparametric two‐step approach on conditional efficiencies to investigate how foreign direct investment (FDI) and time affect the process of catching up. By using a dataset of 44 countries over 1970–2007, we explore the channels under which FDI fosters productivity by disentangling the impact of this factor on the production process and its components: impact on the attainable production set (input–output space) and the impact on the…

利用鞍点近似进行 INAR(p) 模型的似然估计AI 解读

Xanthi Pedeli, Anthony C. Davison & Konstantinos FokianosXanthi Pedeli, Department of Statistics, Athens University of Economics & Business, 10434 Athens, Greece (E-mail: ). Anthony C. Davison, École Polytechnique Fédérale de Lausanne, EPFL-FSB-MATHAA-STAT, Station 8, 1015 Lausanne, Switzerland (E-mail: ). Konstantinos Fokianos, Department of Mathematics & Statistics, University of Cyprus, 1678 Nicosia, Cyprus (E-mail: ). X. Pedeli and K. Fokianos are supported by the…

混频非平稳存量与流量时间序列的估计、预测及信号提取AI 解读

An important practical problem for statistical agencies and central banks that publish economic data is the seasonal adjustment of mixed frequency stock and flow time series. This may arise in practice due to changes in funding of a particular survey. Mathematically, the problem can be reduced to the need to compute imputations, forecasts, and backcasts from a given model of the highest available frequency data. The nonstationarity of the economic time series coupled with…

多元时间序列变化检测及其脑电数据应用AI 解读

The primary contributions of this article are rigorously developed novel statistical methods for detecting change points in multivariate time series. We extend the class of score type change point statistics considered in 2007 by Hušková, Prášková, and Steinebach to the vector autoregressive (VAR) case and the epidemic change alternative. Our proposed procedures do not require the observed time series to actually follow the VAR model. Instead, following the strategy…

含结构突变的多区制门限自回归模型估计AI 解读

The threshold autoregressive (TAR) model is a class of nonlinear time series models that have been widely used in many areas. Due to its nonlinear nature, one major difficulty in fitting a TAR model is the estimation of the thresholds. As a first contribution, this article develops an automatic procedure to estimate the number and values of the thresholds, as well as the corresponding AR order and parameter values in each regime. These parameter estimates are defined as the…

含移动平均残差的非线性自回归模型的 Whittle 似然估计AI 解读

The Whittle likelihood estimation (WLE) has played a fundamental role in the development of both theory and computation of time series analysis. However, WLE is only applicable to models whose theoretical spectral density function (SDF) is known up to the parameters in the models. In this article, we propose a residual-based WLE, called extended WLE (XWLE), which can estimate models with their SDFs only partially available, including many popular time series models with…

弱依赖与异方差误差下时间序列回归模型的推断AI 解读

Motivated by the need to assess the significance of the trend in some macroeconomic series, this article considers inference of a parameter in parametric trend functions when the errors exhibit certain degrees of nonstationarity with changing unconditional variances. We adopt the recently developed self-normalized approach to avoid the difficulty involved in the estimation of the asymptotic variance of the ordinary least-square estimator. The limiting distribution of the…

重新审视面板单位根检验的单变量方法：用协变量解决附带趋势问题AI 解读

In an influential article, Hansen showed that covariate augmentation can lead to substantial power gains when compared to univariate tests. In this article, we ask if this result extends also to the panel data context? The answer turns out to be yes, which is maybe not that surprising. What is surprising, however, is the extent of the power gain, which is shown to more than outweigh the well-known power loss in the presence of incidental trends. That is, the covariates have…

可能不可逆的移动平均模型的最小距离估计AI 解读

This article considers estimation of moving average (MA) models with non-Gaussian errors. Information in higher order cumulants allows identification of the parameters without imposing invertibility. By allowing for an unbounded parameter space, the generalized method of moments estimator of the MA(1) model is classical root-T consistent and asymptotically normal when the MA root is inside, outside, and on the unit circle. For more general models where the dependence of the…

使用混频 VAR 进行实时预测AI 解读

This article develops a vector autoregression (VAR) for time series which are observed at mixed frequencies—quarterly and monthly. The model is cast in state-space form and estimated with Bayesian methods under a Minnesota-style prior. We show how to evaluate the marginal data density to implement a data-driven hyperparameter selection. Using a real-time dataset, we evaluate forecasts from the mixed-frequency VAR and compare them to standard quarterly frequency VAR and to…

小型 DSGE 模型的频率学派评估AI 解读

This article proposes a new evaluation approach for the class of small-scale “hybrid” new Keynesian dynamic stochastic general equilibrium (NK-DSGE) models typically used in monetary policy and business cycle analysis. The empirical assessment of the NK-DSGE model is based on a conditional sequence of likelihood-based tests conducted in a vector autoregressive (VAR) system, in which both the low- and high-frequency implications of the model are addressed in a coherent…

一种灵活的半参数时间序列预测模型AI 解读

In this paper, we propose a semiparametric procedure called the “Model Averaging MArginal Regression” (MAMAR) that is flexible for forecasting of time series. This procedure considers approximating a multivariate regression function by an affine combination of one-dimensional marginal regression functions. The weight parameters involved in the approximation are estimated by least squares on the basis of the first-stage nonparametric kernel estimates of the marginal…

利用回归变量幂变换检验线性关系AI 解读

We develop a method of testing linearity using power transforms of regressors, allowing for stationary processes and time trends. The linear model is a simplifying hypothesis that derives from the power transform model in three different ways, each producing its own identification problem. We call this modeling difficulty the trifold identification problem and show that it may be overcome using a test based on the quasi-likelihood ratio (QLR) statistic. More specifically,…

预测回归中基于工具变量与变量增补的推断AI 解读

Valid inference in predictive regressions depends in a crucial manner on the degree of persistence of the predictor variables. The paper studies test procedures that are robust in the sense that their asymptotic null distributions are invariant to the persistence of the predictor, that is, the limiting distribution is the same irrespective of whether the regressors are stationary or (nearly) integrated. Existing procedures are often conservative (e.g. tests based on…

时变参数回归模型的半参数建模AI 解读

This paper considers the problem of semiparametric model building for linear regression models with potentially time-varying coefficients. By allowing the response variable and explanatory variables be jointly a nonstationary process, the proposed methods are widely applicable to nonstationary and dependent observations. We propose a local linear shrinkage method that can simultaneously achieve parameter estimation and variable selection. Its selection consistency and the…

整数单整原假设对分数单整备择的检验AI 解读

This paper proposes a test of the null of integer integration against the alternative of fractional integration. The null of integer integration is satisfied if the series is either I(0) or I(1). We reject the null if the KPSS test rejects I(0) and a unit root test rejects I(1). We suggest a new unit root test (a lower-tail KPSS test applied to the differenced data) to use in this procedure. We provide critical values under standard asymptotics and fixed-b asymptotics. We…