A Note on the Predictors of Differenced Sequences

In this note we consider the problems of optimal linear prediction (o.l.p.) and the minimum mean squared error prediction (m.m.s.e.p.) of a sequence X_t, which fits to a stationary and invertible ARMA model through the filter (1 - B^s)^d X_t= Y_t. It is shown that these two predictors are not identical in general from the theoretical point of view. Permitting the degree of differencing d to take any real value, a set of conditions for these commonly applied prediction formulas to be identical is given.     

On the characteristic function of multivariate Student t-distribution

The characteristic function of the multivariate Student t-distribution is obtained, and it is shown that this characteristic function has the pedogogical virtue of reducing the multivariate problem to the analogous univariate problem. Applications of the characteristic function are discussed.     

An empirical study on the threshold cointegration of Chinese A and H cross-listed shares

We investigate the dynamic relationship between the prices of Chinese A and H market cross-listed shares using the Enders–Siklos threshold cointegration approach. Our data are the daily closing prices of the Hang Seng China AH (A) index and the Hang Seng China AH (H) index from 4 January 2006 to 1 November 2013. We find a threshold cointegration between these two indices, instead of the linear cointegration well established in the literature. The short-term adjustment to the equilibrium shows an asymmetric effect according to the price deviation from the equilibrium. Moreover, using a Granger causality test, we find a bi-directional causality between these two markets, indicating a close relationship between them. A pairs trading rule, based on the estimated threshold cointegration model, demonstrates the usefulness of our results as it generates a significantly higher return than a naive buy-and-hold trading rule.     

所有制结构与企业能源效率——基于制糖业的实证研究

文章基于微观企业数据对比分析不同所有制结构下制糖企业全要素能源效率(total-factor energy efficiency,TFEE)的静态与动态差异,并运用面板分数响应模型检验所有制结构对TFEE的影响。研究发现:样本期间,外资企业的TFEE最高,其次为国有、多元混合投资和民营企业;四种所有制形式企业的能源效率均存在追赶效应,但制糖业仍存在能源效率差异现象。进一步的估计表明,外资、民营所有制形式对提高TFEE影响显著,比国有企业更有竞争力。因此,建议制糖业不断推进所有制改革,鼓励国有企业进行产权改制,吸收外资企业和民营企业的先进管理理念和技术,从而提高企业的能源效率。     

Innovative methods for modeling of scale invariant processes

This paper presents some innovative methods for modeling discrete scale invariant (DSI) processes and evaluation of corresponding parameters. For the case where the absolute values of the increments of DSI processes are in general increasing, we consider some moving sample variance of the increments and present some heuristic algorithm to characterize successive scale intervals. This enables us to estimate scale parameter of such DSI processes. To present some superior structure for the modeling of DSI processes, we consider the possibility that the variations inside the prescribed scale intervals show some further self-similar behavior. Such consideration enables us to provide more efficient estimators for Hurst parameters. We also present two competitive estimation methods for the Hurst parameters of self-similar processes with stationary increments and prove their efficiency. Using simulated samples of some simple fractional Brownian motion, we show that our estimators of Hurst parameter are more efficient as compared with the celebrated methods of convex rearrangement and quadratic variation. Finally we apply the proposed methods to evaluate DSI behavior of the S&P500 indices in some period.     

Likelihood-based panel cointegration test in the presence of a linear time trend and cross-sectional dependence

This article proposes a new likelihood-based panel cointegration rank test which extends the test of Örsal and Droge (2014 Örsal, D. D. K., Droge, B. (2014). Panel cointegration testing in the presence of a time trend. Computational Statistics and Data Analysis 76:377–390.[Crossref], [Web of Science ®] , [Google Scholar]) (henceforth panel SL test) to dependent panels. The dependence is modelled by unobserved common factors which affect the variables in each cross-section through heterogeneous loadings. The data are defactored following the panel analysis of nonstationarity in idiosyncratic and common components (PANIC) approach of Bai and Ng (2004 Bai, J., Ng, S. (2004). A PANIC attack on unit roots and cointegration. Econometrica 72(4):1127–1177.[Crossref], [Web of Science ®] , [Google Scholar]) and the cointegrating rank of the defactored data is then tested by the panel SL test. A Monte Carlo study demonstrates that the proposed testing procedure has reasonable size and power properties in finite samples.     

向量金融时间序列协整与协同持续关系——基于理论的思考

本文在协整和协同持续基本理论的基础上,继续考虑金融时间序列协整与协同持续的关系,在揭示时间序列内部稳定关系的研究上作一些新的尝试.提出具有波动持续性的向量金融时间序列,若各分量均为一阶单整且各分量间存在线性协整关系,则其一定存在线性协同持续关系,并且协同持续向量即为协整向量.从而揭示了协整与协同持续之间的数量经济关系,加深了我们对许多金融时间序列非平稳性和波动随时间变化这两个基本性质的理解.同时这一研究也展示了金融时间序列一阶矩和二阶矩之间的内在联系,有利于深刻理解向量金融时间序列在各阶矩意义上的内在均衡关系.     

中国区域经济差距收敛性的协整检验

本文根据1957-2006年人均实际GDP数据,运用协整检验方法对中国东中西三大地带内和地带间经济增长的收敛性进行了检验,从一个新视角研究了我国的区域经济差距问题。结果发现,我国东部地区内部各省经济差距存在收敛趋势,而中部和西部地区内部的经济差距却不存在收敛趋势,但它们的经济增长在长期都受到三个共同冲击的影响;我国三大经济带之间以及经济带两两之间的经济差距不存在收敛趋势,但三大经济带的经济增长在长期受到两个共同冲击的影响。     

贫困减少与经济增长和收入不平等的关系研究——基于时序数据

基于时间序列分析方法,以1981年～2004年贫困发生率、基尼系数和农村人均纯收入等相关指标,从时序雏度考察贫困人口的变动与经济增长和收入不平等的长期均衡关系和相互作用机制.Johansen协整检验结果表明,3个变量之间存在着一定的长期协整性:格兰杰因果检验发现,农村人均纯收入和基尼系数能够预测贫困发生率的变化,反之不能成立;误差修正模型显示,贫困发生率对农村人均纯收入的弹性系数为正,对基尼系数的弹性系数为负.且前者大于后者.由此认为,农村人均纯收入的提高是促进贫困减少的影响因素,收入不平等在一定程度上阻碍了贫困减少,经济增长对贫困减少的积极效应大于收入不平等对贫困减少的消极效应.因此,在目前中国经济增长时期,确保农民收入大幅度增加、努力缓解收入差距是贫困减少的有效途径.     

General purpose multiply robust data integration procedures for handling nonprobability samples

In recent years, there has been an increased interest in combining probability and nonprobability samples. Nonprobability sample are cheaper and quicker to conduct but the resulting estimators are vulnerable to bias as the participation probabilities are unknown. To adjust for the potential bias, estimation procedures based on parametric or nonparametric models have been discussed in the literature. However, the validity of the resulting estimators relies heavily on the validity of the underlying models. Also, nonparametric approaches may suffer from the curse of dimensionality and poor efficiency. We propose a data integration approach by combining multiple outcome regression models and propensity score models. The proposed approach can be used for estimating general parameters including totals, means, distribution functions, and percentiles. The resulting estimators are multiply robust in the sense that they remain consistent if all but one model are misspecified. The asymptotic properties of point and variance estimators are established. The results from a simulation study show the benefits of the proposed method in terms of bias and efficiency. Finally, we apply the proposed method using data from the Korea National Health and Nutrition Examination Survey and data from the National Health Insurance Sharing Services.