集体土地所有权实现的价值目标、基本原则与制度框架

集体土地所有权实现是长期困扰学术界的研究命题。我们既无法直接沿用传统物权法知识进行分析,也不能纯粹依据现实做出判定。《物权法》在文本结构上已经确认,集体土地所有权是成员集体享有的“所有权”。在现代法治中国,集体土地所有权实现应当以经济效益、实质公平、经济安全为基本诉求。在法律规制与乡村自治协调、法律保障与政策指导互动、个体利益与集体利益均衡等基本原则的指引下,建构科学合理的集体土地所有权实现相关制度框架。     

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。     

集体林权纠纷解决的制度现状与对策研究--基于江西省某县个案的分析

化解集体林权纠纷是新一轮集体林权制度改革的重要工作,但林权纠纷解决难度大,影响了改革工作的深入开展。研究首先梳理了集体林权纠纷解决的制度安排;其次以江西省某县A、B两个村民小组因737号山场发生的林权纠纷案件作为研究对象,介绍了林权纠纷解决过程的特殊性;再次,探析了现行纠纷解决制度存在的低效问题及其成因。最后提出完善制度的顶层设计、重视非正式制度作用、加强调解机构能力建设、创新纠纷解决方法等对策建议。     

外空探索国际合作知识产权保护探析

中国外空探索国际合作的形式由双边合作发展到多边合作,合作的程度日益深化,技术出口与共同研发成为合作的常态。对于合作中已有技术的知识产权的保护要通过协议规定保密条款,并明确在此基础上改进专利的实施条件及违约责任。对于合作研发技术应综合考虑合作各方贡献,通过合作协议明确知识产权利益分享机制。空间技术具有国防敏感性,应在国家利益与单位利益、保密性与公开性之间寻求合理的平衡。为此应建立合作项目知识产权评估机制和国家介入权听证制度。为增强中国在空间技术知识产权竞争力,应加强对外合作和单位内部的合同管理,以减少合作中知识产权利益分配的不确定性,并针对合作项目风险性的差异,建立知识产权分类评价机制。     

关于“非遗”保护三个基本问题的话语分析

话语研究不仅关心人们如何言说,而且更为重视分析决定言说方式的深层动因。“非遗”保护既是一个社会各阶层权力角逐的场域,又是一个可通过不断协商达成共识的平台。人们对于“非遗”保护的认识人言言殊的根本原因在于参与“非遗”保护的社会各阶层各自的利益诉求并不完全一致。“非遗”保护工作正是在争论中逐渐确立了自身的工作目标、指导原则、实施方案,体现了极强的话语建构性。“非遗”作为一种传统生活方式的隐形载体,活态传承性是其精髓与灵魂;“非遗”保护必须以人为本,只有让“非遗”与现实的人民群众的日常生活发生联系和耦合,“非遗”保护才可能取得实效。     

房产免税立法与税收公平的归位

房产税法律制度的改革折射的是社会演进与经济发展的必然趋势。经济发展加剧了社会成员间资源占有的不公平,但是房产税法律制度的发展却并没有弥合资源分配的不公平,反而在多元利益的指导下出现了三种维度的不公平：政府与市场之间的不公平、中央与地方之间的不公平以及居住者和投机者之间的不公平。刚性的税法常常为社会、经济所不融,免税的设计恰好可以弥补税法柔性的不足,在确保财政收入的情况下兼顾社会公平的维护,这也是深化财税体制改革背景下税法变革的秩序要求。房产税法律制度的变革应以量能课征为依据,以税收中性为准绳,区分房产的普遍性与特殊性,达成税收公平的改革效果。     

A Necessary Condition for the Strong Oracle Property

A problem of using a non‐convex penalty for sparse regression is that there are multiple local minima of the penalized sum of squared residuals, and it is not known which one is a good estimator. The aim of this paper is to give a guide to design a non‐convex penalty that has the strong oracle property. Here, the strong oracle property means that the oracle estimator is the unique local minimum of the objective function. We summarize three definitions of the oracle property – the global, weak and strong oracle properties. Then, we give sufficient conditions for the weak oracle property, which means that the oracle estimator becomes a local minimum. We give an example of non‐convex penalties that possess the weak oracle property but not the strong oracle property. Finally, we give a necessary condition for the strong oracle property.     

Lassoing the Determinants of Retirement

This article uses Danish register data to explain the retirement decision of workers in 1990 and 1998. Many variables might be conjectured to influence this decision such as demographic, socioeconomic, financial, and health related variables as well as all the same factors for the spouse in case the individual is married. In total, we have access to 399 individual specific variables that all could potentially impact the retirement decision. We use variants of the least absolute shrinkage and selection operator (Lasso) and the adaptive Lasso applied to logistic regression in order to uncover determinants of the retirement decision. To the best of our knowledge, this is the first application of these estimators in microeconometrics to a problem of this type and scale. Furthermore, we investigate whether the factors influencing the retirement decision are stable over time, gender, and marital status. It is found that this is the case for core variables such as age, income, wealth, and general health. We also point out the most important differences between these groups and explain why these might be present.     

Variable selection in additive quantile regression using nonconcave penalty

This paper considers variable selection in additive quantile regression based on group smoothly clipped absolute deviation (gSCAD) penalty. Although shrinkage variable selection in additive models with least-squares loss has been well studied, quantile regression is sufficiently different from mean regression to deserve a separate treatment. It is shown that the gSCAD estimator can correctly identify the significant components and at the same time maintain the usual convergence rates in estimation. Simulation studies are used to illustrate our method.