农户和农业主体对土地承包经营权抵押贷款政策的态度

一项政策的实施效果与主体看待该政策的态度密切相关。研究1基于1 002份有效问卷,引入态度的三维度模型,将农业主体对土地承包经营权抵押贷款的态度分成认知态度、情感态度与行为态度。结果显示：主体对土地产权的认知存在一定的偏差,对贷款政策的认知程度不高;对政策具有较高的满意度,认为能在一定程度上缓解资金难问题,增加农业收入;但利用政策贷款意愿度并不高。研究2基于857份农户和145份农业新型经营主体有效问卷,选用态度强度以及态度中心性,对农户与新型经营主体态度进行差异性分析。结果显示：农户与农业新型经营主体在态度强度与中心性上均存在不同程度的差异性。态度强度上,行为强度差异显著,认知强度部分显著,情感强度不显著。中心态度上,农户的中心态度是认知态度,而新型经营主体是情感态度。此外,对农户与新型经营主体贷款意愿进行关联性分析,发现影响贷款意愿的态度具有差异性。可见,农户与新型经营主体态度差异是影响贷款受益群体不均衡的原因之一。     

人民币加入ＳＤＲ 预期对其国际化的影响

一国货币的国际化程度主要体现在其国际影响力及对国际主要国家货币汇率波动的反应程度。人民币纳入ＳＤＲ 货币篮子将会改变人民币在国际货币金融体系中的地位与作用,从而影响人民币国际化程度。基于２０１５ 年８ 月１１ 日至２０１６ 年３ 月１６ 日的样本区间数据,通过构建ＶＡＲ模型实证检验人民币加入ＳＤＲ 预期因素对人民币国际化程度的影响。结果发现：第一,人民币加入ＳＤＲ 预期能够提升人民币在国际货币金融体系中的影响力,尤其是人民币对美元的影响力将大大增加,但是其对世界其他主要货币的影响力仍显不足;第二,样本区间内,人民币自由化程度并没有提升,因为人民币汇率并没有随着世界主要货币汇率的波动而有所变化。     

Inference in Semi‐Parametric Dynamic Models for Repeated Count Data

This paper deals with a longitudinal semi‐parametric regression model in a generalised linear model setup for repeated count data collected from a large number of independent individuals. To accommodate the longitudinal correlations, we consider a dynamic model for repeated counts which has decaying auto‐correlations as the time lag increases between the repeated responses. The semi‐parametric regression function involved in the model contains a specified regression function in some suitable time‐dependent covariates and a non‐parametric function in some other time‐dependent covariates. As far as the inference is concerned, because the non‐parametric function is of secondary interest, we estimate this function consistently using the independence assumption‐based well‐known quasi‐likelihood approach. Next, the proposed longitudinal correlation structure and the estimate of the non‐parametric function are used to develop a semi‐parametric generalised quasi‐likelihood approach for consistent and efficient estimation of the regression effects in the parametric regression function. The finite sample performance of the proposed estimation approach is examined through an intensive simulation study based on both large and small samples. Both balanced and unbalanced cluster sizes are incorporated in the simulation study. The asymptotic performances of the estimators are given. The estimation methodology is illustrated by reanalysing the well‐known health care utilisation data consisting of counts of yearly visits to a physician by 180 individuals for four years and several important primary and secondary covariates.     

A comparison study on modeling of clustered and overdispersed count data for multiple comparisons

Data collected in various scientific fields are count data. One way to analyze such data is to compare the individual levels of the factor treatment using multiple comparisons. However, the measured individuals are often clustered – e.g. according to litter or rearing. This must be considered when estimating the parameters by a repeated measurement model. In addition, ignoring the overdispersion to which count data is prone leads to an increase of the type one error rate. We carry out simulation studies using several different data settings and compare different multiple contrast tests with parameter estimates from generalized estimation equations and generalized linear mixed models in order to observe coverage and rejection probabilities. We generate overdispersed, clustered count data in small samples as can be observed in many biological settings. We have found that the generalized estimation equations outperform generalized linear mixed models if the variance-sandwich estimator is correctly specified. Furthermore, generalized linear mixed models show problems with the convergence rate under certain data settings, but there are model implementations with lower implications exists. Finally, we use an example of genetic data to demonstrate the application of the multiple contrast test and the problems of ignoring strong overdispersion.     

On comparing,classifying and clustering several dependent regression models

Classifying several regression models fitted on a dataset is one of the most problems in data analysis. In other words, scientists are interested in comparing several regression models that can be used for a dataset. In this paper, an approach will be used to compare and classify several dependent regression models. Then the performance of the proposed method is investigated using simulation study and real example.     

借鉴美国成功经验发展我国住房抵押贷款保险市场

针对目前我国个人住房抵押贷款市场的现状,提出发展住房抵押贷款保险来规避风险。美国发达的住房抵押贷款市场很大程度上得益于抵押贷款保险市场的发展,其运行模式值得我们借鉴。通过分析国内现行的抵押贷款保险体系中存在的问题,提出了发展住房按揭保险的一些建议、想法,以促进个人住房抵押贷款的良性发展,推动住房商品化的顺利进行。     

浅析房地产抵押关系的成立及抵押权的实现

本文从主体、客体、内容及形式四个方面,详细地分析了作为民事法律关系之一的房地产抵押担保关系成立的要件,并从当今有关法律规定入手,阐明了房地产抵押权实现的方式是拍卖.对部分有争议的相关问题谈了自己粗浅的认识.     

不动产抵押法律问题研究

不动产抵押是商品经济发展的一种重要担保方式 ,素有担保之王的美称。依据物权法和债法原理 ,探讨涉及的几个主要法律问题 :不动产抵押与不动产的紧密关系、不动产抵押的滞后立法检讨、不动产抵押的特征、不动产抵押标的物范围、不动产抵押人资格、不动产抵押权的设立、不动产抵押权的清偿顺序。     

金融危机对我国劳动力就业的影响

现阶段,由美国次贷危机引发的金融危机席卷全球,在全球经济一体化背景下,我国自然无法置身事外。金融危机对我国的影响表现在方方面面,其中对劳动力就业的冲击是最重要的问题之一。在现阶段的就业问题中,大学生就业和农民工返乡成为最为重要的两个方面。要应对金融危机对我国劳动力就业的影响,缓解就业压力,需要中央、地方政府、企业和个人的密切配合,从多方面入手寻求解决问题的根本途径。     

对我国住房抵押贷款证券化若干问题的思考

该文介绍了住房抵押贷款证券化的概念及其在我国的发展情况 ,论述了住房抵押贷款证券化是我国住房金融发展的必然趋势 ,同时分析了我国实行住房抵押贷款证券化存在的几个问题并提出了一些新的观点。