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具有截面依赖的随机前沿面板中的技术效率建模AI 解读

Summary This paper proposes a unified framework for accommodating both time and cross‐sectional dependence in modelling technical efficiency in stochastic frontier models by combining the exogenously driven factor‐based approach and an endogenous threshold efficiency regime selection mechanism. This approach is able to deal with both weak and strong cross‐sectional dependence in a flexible manner. Using a dataset of 26 OECD countries over 1970–2010, we provide satisfactory…

非标准计量问题中置信集的可信性AI 解读

Confidence intervals are commonly used to describe parameter uncertainty. In nonstandard problems, however, their frequentist coverage property does not guarantee that they do so in a reasonable fashion. For instance, confidence intervals may be empty or extremely short with positive probability, even if they are based on inverting powerful tests. We apply a betting framework to formalize the “reasonableness ” of confidence intervals as descriptions of parameter uncertainty,…

非平稳次线性过程的预测器聚合与时变自回归过程的在线自适应预测AI 解读

In this work, we study the problem of aggregating a finite number of predictors for nonstationary sub-linear processes. We provide oracle inequalities relying essentially on three ingredients: (1) a uniform bound of the $\ell^{1}$ norm of the time varying sub-linear coefficients, (2) a Lipschitz assumption on the predictors and (3) moment conditions on the noise appearing in the linear representation. Two kinds of aggregations are considered giving rise to different moment…

半参数模型中光滑泛函的 Bernstein–von Mises 定理AI 解读

A Bernstein–von Mises theorem is derived for general semiparametric functionals. The result is applied to a variety of semiparametric problems in i.i.d. and non-i.i.d. situations. In particular, new tools are developed to handle semiparametric bias, in particular for nonlinear functionals and in cases where regularity is possibly low. Examples include the squared $L^{2}$-norm in Gaussian white noise, nonlinear functionals in density estimation, as well as functionals in…

高维情形下的同时变点检验AI 解读

Consider $d$ dependent change point tests, each based on a CUSUM-statistic. We provide an asymptotic theory that allows us to deal with the maximum over all test statistics as both the sample size $n$ and $d$ tend to infinity. We achieve this either by a consistent bootstrap or an appropriate limit distribution. This allows for the construction of simultaneous confidence bands for dependent change point tests, and explicitly allows us to determine the location of the change…

非线性时间序列模型中条件分位数的统计推断AI 解读

This paper studies the statistical properties of a two-step conditional quantile estimator in nonlinear time series models with unspecified error distribution. The asymptotic distribution of the quasi-maximum likelihood estimators and the filtered empirical percentiles is derived. Three applications of the asymptotic result are considered. First, we construct an interval estimator of the conditional quantile without any distributional assumptions. Second, we develop a…

具有鞅差误差的广义 ARMA 模型AI 解读

The analysis of non-Gaussian time series has been studied extensively and has many applications. Many successful models can be viewed as special cases or variations of the generalized autoregressive moving average (GARMA) models of Benjamin et al. (2003), where a link function similar to that used in generalized linear models is introduced and the conditional mean, under the link function, assumes an ARMA structure. Under such a model, the ‘transformed’ time series, under…

多门槛双重自回归模型的渐近推断AI 解读

This paper investigates a class of multiple-threshold models, called Multiple Threshold Double AR (MTDAR) models. A sufficient condition is obtained for the existence and uniqueness of a strictly stationary and ergodic solution to the first-order MTDAR model. We study the Quasi-Maximum Likelihood Estimator (QMLE) of the MTDAR model. The estimated thresholds are shown to be n-consistent, asymptotically independent, and to converge weakly to the smallest minimizer of a…

门限扩散过程的拟似然估计AI 解读

The threshold diffusion process, first introduced by Tong (1990), is a continuous-time process satisfying a stochastic differential equation with a piecewise linear drift term and a piecewise smooth diffusion term, e.g., a piecewise constant function or a piecewise power function. We consider the problem of estimating the (drift) parameters indexing the drift term of a threshold diffusion process with continuous-time observations. Maximum likelihood estimation of the drift…

函数型时间序列之间的独立性检验AI 解读

Frequently econometricians are interested in verifying a relationship between two or more time series. Such analysis is typically carried out by causality and/or independence tests which have been well studied when the data is univariate or multivariate. Modern data though is increasingly of a high dimensional or functional nature for which finite dimensional methods are not suitable. In the present paper we develop methodology to check the assumption that data obtained from…

非负时间序列乘法误差模型的设定错误检验AI 解读

In recent years, analysis of financial time series focuses largely on data related to market trading activity. Apart from modeling of the conditional variance of returns within the generalized autoregressive conditional heteroskedasticity (GARCH) family of models, presently attention is also devoted to that of other market variables, for instance volumes, number of trades or financial durations. To this end, a large group of researchers focus their studies on a class of…

时间序列分析中的门限模型：若干回顾与思考AI 解读

In this paper, I reflect on the developments of the threshold model in time series analysis since its birth in 1978, with particular reference to econometrics.

门限自回归模型的 LASSO 估计AI 解读

This paper develops a novel approach for estimating a threshold autoregressive (TAR) model with multiple-regimes and establishes its large sample properties. By reframing the problem in a regression variable selection context, a least absolute shrinkage and selection operator (LASSO) procedure is proposed to estimate a TAR model with an unknown number of thresholds, where the computation can be performed efficiently. It is further shown that the number and the location of…

时间序列与金融计量经济学前沿：概览AI 解读

Two of the fastest growing frontiers in econometrics and quantitative finance are time series and financial econometrics. Significant theoretical contributions to financial econometrics have been made by experts in statistics, econometrics, mathematics, and time series analysis. The purpose of this special issue of the journal on “Frontiers in Time Series and Financial Econometrics” is to highlight several areas of research by leading academics in which novel methods have…

含潜在因子、内生性与非线性的高维随机回归AI 解读

We consider a multivariate time series model which represents a high dimensional vector process as a sum of three terms: a linear regression of some observed regressors, a linear combination of some latent and serially correlated factors, and a vector white noise. We investigate the inference without imposing stationary conditions on the target multivariate time series, the regressors and the underlying factors. Furthermore we deal with the endogeneity that there exist…

具有时间序列误差的回归模型最优模型平均AI 解读

Consider a regression model with infinitely many parameters and time series errors. We are interested in choosing weights for averaging across generalized least squares (GLS) estimators obtained from a set of approximating models. However, GLS estimators, depending on the unknown inverse covariance matrix of the errors, are usually infeasible. We therefore construct feasible generalized least squares (FGLS) estimators using a consistent estimator of the unknown inverse…

Lévy 驱动连续时间 ARMA 过程的预测AI 解读

The conditional expectations, E(Y(h)|Y(u),−∞<u≤0) and E(Y(h)|Y(u),−M≤u≤0) with h>0 and 0<M<∞ are determined for a continuous-time ARMA (CARMA) process (Y(t))t∈R driven by a Lévy process L with E|L(1)|<∞. If E(L(1)2)<∞ these are the minimum mean-squared error predictors of Y(h) given (Y(t))t≤0 and (Y(t))−M≤t≤0 respectively. Conditions are also established under which the sample-path of L can be recovered from that of Y, both when Y is causal and strictly stationary and…

具有变量选择的函数型指数系数模型AI 解读

We consider model (variable) selection in a semi-parametric time series model with functional coefficients. Variable selection in the semi-parametric model must account for the fact that the parametric part of the model is estimated at a faster convergence rate than the nonparametric component. Our variable selection procedures employ a smoothly clipped absolute deviation penalty function and consist of two steps. The first is to select covariates with functional…

长记忆随机波动模型中的信号提取AI 解读

Long memory in stochastic volatility (LMSV) models are flexible tools for the modeling of persistent dynamic volatility, which is a typical characteristic of financial time series. However, their empirical applicability is limited because of the complications inherent in the estimation of the model and in the extraction of the volatility component. This paper proposes a new technique for volatility extraction, based on a semiparametric version of the optimal…

预测回归模型中的差分变换与推断AI 解读

The limit distribution of conventional test statistics for predictability may depend on the degree of persistence of the predictors. Therefore, diverging results and conclusions may arise because of the different asymptotic theories adopted. Using differencing transformations, we introduce a new class of estimators and test statistics for predictive regression models with Gaussian limit distribution that is instead insensitive to the degree of persistence of the predictors.…

共同断点下因子载荷结构变化的检验AI 解读

This paper proposes a new test for factor loading structural change in dynamic factor models. We first show that the leading test proposed by Breitung and Eickmeier (2011) exhibits nonmonotonic power, essentially because the breaks are considered as spurious factors with stable factor loadings. The proposed test eliminates the effects of the spurious factors by maximizing the test statistic over possible numbers of the original factors. Monte Carlo simulations and an…

从多项经济指标中提取非线性信号AI 解读

We develop a twofold analysis of how the information provided by several economic indicators can be used in Markov switching dynamic factor models to identify the business cycle turning points. First, we compare the performance of a fully nonlinear multivariate specification (one-step approach) with the ‘shortcut’ of using a linear factor model to obtain a coincident indicator, which is then used to compute the Markov switching probabilities (two-step approach). Second, we…

Factor models of disaggregate inflation indices suggest that sectoral shocks generate the bulk of sectoral inflation variance, but no persistence. Aggregate shocks, by contrast, are the root of sectoral inflation persistence, but have negligible relative variance. We show that simple factor models do not cope well with essential features of price data. In particular, sectoral inflation series are subject to features such as measurement error, sales and item substitutions. In…

专业预测者不确定性的测量与特征AI 解读

Several statistical issues that arise in the construction and interpretation of measures of uncertainty from forecast surveys that include probability questions are considered, with application to the Bank of England Survey of External Forecasters. Substantial heterogeneity of individual forecasters' uncertainty is found, together with significant persistence in their relative uncertainty, which is a new finding in professional forecast surveys. It is an individual…