Data driven rank test for the change point problem

Data driven test procedure for detection of change is introduced and its properties are studied. The new solution is max-type statistic related to data-driven rank tests for two-sample subproblems. Simulations show that the new test possesses high and stable power. The test is consistent at essentially any alternative. Asymptotic null distribution of the test is derived. The work of the first two authors has been partially supported by the grants GAČR 201/06/0186 and MSM 02160839.     

限价商品住房管理模式思考

近年来,随着我国房地产市场的持续升温,各地的房价涨幅居高不下,已经对城市中低收入居民的基本住房需求造成很大影响.为了缓解供需矛盾,稳定住房价格,中央提出了"双限双竞"的宏观调控措施,各地也纷纷依据精神推出了限价商品住房供应政策.文章主要从限价商品住房管理中存在的主要问题入手,结合国内几个城市的相关政策经验及存在问题,提出对限价商品住房管理模式的几点思考.     

论城市房屋拆迁中物权流转模型的构建及保护对策——兼评《国有土地上房屋征收与拆迁补偿条例》

拆迁问题引发的社会矛盾愈演愈烈,制度设计的缺陷难辞其咎.论文在抽离拆迁行为的基础上,构建公益性房屋拆迁模型与商业性房屋拆迁模型,并以物权的变动为线索,剖析现行拆迁制度,旨在对拆迁立法的完善提出更有针对性的建议,以规范相关物权的归属与保护;并对<国有土地上房屋征收与拆迁补偿条例>(征求意见稿)进行评析.     

主要股票市场指数与我国股票市场指数间的协整分析

本文应用协整分析和误差修正模型(ECM)，对沪、深股市指数和主要股票市场(美国、英国、香港和日本)之间的关系进行了实证分析。通过建立误差修正模型(ECM)，发现指数之间收益率序列具有相异的短期波动，而对沪、深股市指数和主要股票市场指数进行协整分析，我们发现国内市场与国际市场不存在协整关系，即没有长期共同趋势，得出我国股票市场与国际市场相分离的结论。     

Contemporary Extensions of the Rasch Model

This paper will introduce, discuss and illustrate two contemporary extensions of theRasch model: the one parameter logistic model (Verhelst and Glas, 1995) and theMultidimensional Rasch model (Hoijtink et al., 1999). Using data with respect tothe measurement of schizotypy (Vollema and Hoijtink, 2000) the most importantfeatures of both models will be illustrated. For the one parameter logistic modelthese include: a (discrete) discrimination parameter for each item; a test for itembias; and, estimation of the location of a person on the (latent) trait that is beingmeasured. For the multidimensional Rasch model these include: specification ofthe model; and, model selection. All analyses presented in this paper can be executedusing either OPLM (Verhelst et al., 1995), TESTFACT (Wilson et al.,1984) or ConQuest (Wu et al., 1998). At the end of the paper some features ofmodels and software that have not been discussed will be summarized.     

Exploring the development trend of internet finance in China: Perspective from club convergence

We first employ β-conditional convergence and log t regression tests based on nonlinear time-varying factor model and club clustering algorithm to analyze the convergence characteristics of the development level of Internet finance in 335 prefecture-level cities in China. The result of log t regression test illustrates that there is no convergence as a whole in the development level of China's Internet finance. However, seven convergence clubs and a divergent group have been formed, and the development level and growth rate of Internet finance among these convergence clubs have shown obvious differences. Moreover, we also employ the Ordered Probit to explore the formation mechanism of the convergence clubs. The results reveal that the regions with a higher level of economic development, traditional financial development, economic openness and Internet development are more inclined to converge in a club with a higher Internet finance development level. Alternatively, the regions that are interfered with more by the government or that have a lower degree of marketization, tend to converge in a club with a lower level. Finally, according to the conclusions, we propose corresponding policy recommendations for promoting the regional coordinated development of China's Internet finance.     

Optimal model averaging forecasting in high-dimensional survival analysis

This article considers ultrahigh-dimensional forecasting problems with survival response variables. We propose a two-step model averaging procedure for improving the forecasting accuracy of the true conditional mean of a survival response variable. The first step is to construct a class of candidate models, each with low-dimensional covariates. For this, a feature screening procedure is developed to separate the active and inactive predictors through a marginal Buckley–James index, and to group covariates with a similar index size together to form regression models with survival response variables. The proposed screening method can select active predictors under covariate-dependent censoring, and enjoys sure screening consistency under mild regularity conditions. The second step is to find the optimal model weights for averaging by adapting a delete-one cross-validation criterion, without the standard constraint that the weights sum to one. The theoretical results show that the delete-one cross-validation criterion achieves the lowest possible forecasting loss asymptotically. Numerical studies demonstrate the superior performance of the proposed variable screening and model averaging procedures over existing methods.     

Automatic leading indicators versus macroeconometric structural models: A comparison of inflation and GDP growth forecasting

This paper compares the forecast performance of automatic leading indicators (ALIs) and macroeconometric structural models (MESMs) commonly used by non-academic macroeconomists. Inflation and GDP growth form the forecast objects for comparison, using data from China, Indonesia and the Philippines. ALIs are found to outperform MESMs for one-period-ahead forecasts, but this superiority disappears as the forecast horizon increases. It is also found that ALIs involve greater uncertainty in choosing indicators, mixing data frequencies and utilizing unrestricted VARs. Two ways of reducing the uncertainty are explored: (i) give theory priority in choosing indicators, and include theory-based disequilibrium shocks in the indicator sets; and (ii) reduce the VARs by means of the general-to-specific modeling procedure.     

一种新的利用网络爬虫技术的土地价格指数编制方法

研究目标：目前有关中国土地价格指数的研究没有考虑不可观测特征的影响,本文给出一种可以控制不可观测特征的土地价格指数编制方法。[HTH]研究方法：通过结合传统的特征价格模型和重复交易模型,提出固定地理单元并利用组内差分以控制地块不可观测特征,提出了一种新的土地价格指数编制方法。[HTH]研究发现：[HTF][STBZ][WTBZ]以上海为例讨论了分类土地价格指数,研究发现从2008~2015年,上海同质住宅用地价格上升了359.92%,同质工业用地和商服用地价格的涨幅分别为101%和107%。[HTH]研究创新：利用网络爬虫技术收集微观土地交易数据,为指数的编制提供了数据基础。[HTH]研究价值：该方法能够捕捉地块所在的特殊位置对于其价格的影响。     

基于互联网大数据的CPI舆情指数构建与应用

研究目标：基于互联网大数据构建CPI舆情指数辅助预测CPI。研究方法：提出了一种构建CPI低频与高频舆情指数的统计方法,并通过选用2006年6月至2015年12月的数据验证了该方法的有效性。研究发现：相关关键词的搜索热度指标具有领先CPI的预测作用,依此建立的CPI舆情指数有助于改进CPI预测精度。研究创新：揭示了基于相关关键词的搜索热度指标与CPI的非线性关系,提出了一种基于门限回归的CPI低频舆情指数构建方法;使用动态因子模型估计出了CPI高频舆情指数。研究价值：预测CPI时可辅助利用基于大数据构建的CPI低频与高频舆情指数信息。