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混合频率与混合样本数据的协整向量频域估计AI 解读

This paper proposes a simple method for exploiting the information contained in mixed frequency and mixed sample data in the estimation of cointegrating vectors. The asymptotic properties of easy-to-compute spectral regression estimators of the cointegrating vectors are derived and these estimators are shown to belong to the class of optimal cointegration estimators. Furthermore, Wald statistics based on these estimators have asymptotic chi-square distributions which enable…

混频数据下连续时间模型的估计AI 解读

This paper derives exact representations for discrete time mixed frequency data generated by an underlying multivariate continuous time model. Allowance is made for different combinations of stock and flow variables as well as deterministic trends, and the variables themselves may be stationary or nonstationary (and possibly cointegrated). The resulting discrete time representations allow for the information contained in high frequency data to be utilised alongside the low…

基于频域回归的季节单位根检验AI 解读

This paper develops univariate seasonal unit root tests based on spectral regression estimators. An advantage of the frequency domain approach is that it enables serial correlation to be treated non-parametrically. We demonstrate that our proposed statistics have pivotal limiting distributions under both the null and near seasonally integrated alternatives when we allow for weak dependence in the driving shocks. This is in contrast to the popular seasonal unit root tests of,…

平稳自回归模型的刀切估计AI 解读

This paper explores the properties of jackknife methods of estimation in stationary autoregressive models. Some general results concerning the correct weights for bias reduction under various sampling schemes are provided and the asymptotic properties of a jackknife estimator based on non-overlapping sub-samples are derived for the case of a stationary autoregression of order p when the number of sub-samples is either fixed or increases with the sample size at an appropriate…

连续时间ARMA过程的离散时间表示AI 解读

This paper derives exact discrete time representations for data generated by a continuous time autoregressive moving average (ARMA) system with mixed stock and flow data. The representations for systems comprised entirely of stocks or of flows are also given. In each case the discrete time representations are shown to be of ARMA form, the orders depending on those of the continuous time system. Three examples and applications are also provided, two of which concern the…

混合存量与流量数据下协整连续时间模型的离散时间表示AI 解读

This paper derives an exact discrete time representation corresponding to a triangular cointegrated continuous time system with mixed stock and flow variables and observable stochastic trends. The discrete time model inherits the triangular structure of the underlying continuous time system and does not suffer from the apparent excess differencing that has been found in some related work. It can therefore serve as a basis for the study of the asymptotic sampling properties…

摘要暂缺

经济过程的采样与格兰杰因果关系AI 解读

This paper provides a discussion of the developments in econometric modelling that are designed to deal with the problem of spurious Granger causality relationships that can arise from temporal aggregation. We outline the distortional effects of using discrete time models that explicitly depend on the unit of time and outline a remedy of constructing timeinvariant discrete time models via a structural continuous time model. In an application to testing for money-income…

含未知滞后参数的微分差分方程组估计AI 解读

This paper considers the estimation of the parameters of general systems of stochastic differential-difference equations in which the lag parameters themselves are treated as unknown and are not restricted to be integers and therefore form part of the parameter vector to be estimated. The asymptotic properties of an infeasible frequency domain maximum likelihood estimator are established in addition to those of a feasible version based on truncating an infinite series that…

摘要暂缺

时间聚合下协整估计量的渐近效率AI 解读

This paper examines the effects of temporal aggregation on the asymptotic variances of estimators in cointegrated systems. Two important findings are obtained. First, estimators based on flow data alone are more efficient than when the data are all stocks or a mixture of stocks and flows. Second, estimators based on flow data are as efficient as when the data are recorded continuously. A method of improving efficiency with stock variables is also proposed, and an empirical…

在不可观测成分框架中用微分差分方程刻画周期行为AI 解读

This paper considers a continuous time unobserved components model in which the cyclical component follows a differential-difference equation whereas the trend and seasonal components follow more standard differential equations. Estimation of the parameters of the model with either a stock or a flow variable is analyzed using a frequency domain Gaussian estimator whose asymptotic properties are derived paying particular attention to the role of a truncation parameter that…

时间聚合与协整系统中谱回归估计量的有限样本表现AI 解读

The finite sample performance of spectral regression estimators in temporally aggregated cointegrated systems is investigated via the use of simulation experiments. The simulations address issues such as “optimal” choice of bandwidth parameter and effects of smoothing kernel in constructing estimates of spectral densities that are used by the spectral regression estimators; the effects of stock and flow variables and mixtures of the two, including the relative finite sample…

连续时间长记忆时间序列模型的估计AI 解读

A class of univariate fractional ARIMA models with a continuous time parameter is developed for the purpose of modeling long-memory time series. The spectral density of discretely observed data is derived for both point observations (stock variables) and integral observations (flow variables). A frequency domain maximum likelihood method is proposed for estimating the longmemory parameter and is shown to be consistent and asymptotically normally distributed, and some issues…

用于估计一般线性连续时间系统的离散模型AI 解读

This paper derives discrete models for estimating systems of both first- and second-order linear differential equations in which derivatives of the exogenous variables appear in addition to their levels.