重大责任事故罪法定刑配置研究

近几年来,各类重大责任事故频发使重大责任事故罪的研究成为关注的焦点.本文是对重大责任事故罪法定刑配置进行的专题研究,着重研究重大责任事故罪的刑量、重大责任事故罪的刑种、重大责任过失危险犯的法定刑配置等三个问题.我国重大责任事故罪的法定刑配置的立法缺陷表现为,在刑量上配刑偏轻,在刑种设置方面过于简单.应调整重大责任事故罪的法定刑幅度,增加罚金刑、资格刑等刑种;增设重大责任事故过失危险犯,其法定刑设置应轻于实害犯的法定刑,更多地适用罚金刑或资格刑.     

均衡汇率的理论发展与人民币均衡汇率测算方法

在开放经济条件下,汇率水平适当与否,对一国经济的和谐发展具有十分重要的作用。而有关均衡汇率的讨论正是关注如何估算和评价一国的合理的汇率水平。近年来,人们对均衡汇率定义进行了全新的解释,并且提出了一些计算均衡汇率的新方法,其中既有优点也有不足。在对人民币均衡汇率的测算方法的比较中,行为均衡汇率(BEER)方法具有明显的优势。在对人民币均衡汇率研究中,建立动态调整模型,适当加入微观变量应成为今后理论与实证分析的发展方向。     

人力资本理论基本假设的检验：对中国大学生的个案分析

应用1998年对中国北京、南京、西安三地14所高校13511名大学生的调查数据,估计了大学生期望的高等教育收益与回报率,以及它们对学生接受高等教育与研究生教育意愿的影响.结果表明,人力资本理论的基本假设,即学生及其家庭根据教育的市场回报选择最优的教育水平和类型,在中国的情景中只获得了部分支持.造成这一结果的原因,可能与学生及其家庭在作出高等教育决定时,常常缺乏高等教育成本与收益方面的信息,或即使了解这方面的信息,他们也可能不一定会以经济理性的方式处理它们有关,也可能与高等教育的供求机制不同于一般的私人物品,或与估计方法没有考虑高等教育的非经济收益等因素有关.     

恐怖主义犯罪与危害国家安全犯罪的比较分析——以3.01昆明暴力恐怖袭击案为视角

恐怖主义犯罪是针对于平民实施的,蓄意造成人员伤亡的,意图借此对现政府或国际社会施压达到目的的犯罪行为,在我国刑法没有明确规定。危害国家安全罪是指故意危害中华人民共和国国家安全的行为,其犯罪构成在我国刑法学界已经达成共识。恐怖主义犯罪与危害国家安全犯罪在犯罪目的、罪过形式、危害行为表现形式、犯罪既遂类型方面存在联系。但是,两类犯罪的犯罪目的、具体行为方式、危害行为表现形式、国际刑事处遇方面也存在区别。     

结果加重犯的共同犯罪问题

共同犯罪的问题一直是刑法理论界研究的重点和难点。结果加重犯是指行为人的一个犯罪行为在已经满足一个基本犯罪的全部构成要件的基础上,又发生了更为严重的结果,因而法律规定加重其刑的犯罪形态。我国刑法关于结果加重犯的共同犯罪问题的理论研究上众说纷纭、莫衷一是。不能成立结果加重犯的共同犯罪并不意味着共犯人对重的结果免责。     

刑事侦查学同一认定理论之定位

基础理论研究是学科的根本,刑事侦查基础理论不仅影响着学科的内容和体系,还决定着侦查学的学科层次和定位。以基础理论为命题,系统的分析侦查学的产生、发展过程,就可以得出这样的结论:同一认定理论是刑事侦查学的特定基础理论。同一认定是一种专门的认识活动,是在侦查过程中具有专门知识或者了解客体特征的人,通过比较先后出现的客体的特征,而对客体是否同一所作出的判断,是发现、控制、证实犯罪的主要方法和手段,是确定侦查方向、范围的依据。这一观点明确了同一认定理论的价值和功能,必将推动侦查学理论研究和学科建设的发展。     

中国利率期限结构平滑样条拟合改进研究

在FNZ模型和Waggoner模型的基础上,结合中国国债市场的发展现状,从拟合对象、粗糙度惩罚项的函数形式、参数估计方法、最优化目标函数形式以及估计样本等五方面进行修正和改进,提出利用可变粗糙度惩罚项三次平滑样条改进模型来拟合中国的利率期限结构,并利用上交所国债市场2002年1月1日至2003年12月31日的国债收盘价格数据对该模型进行实证研究.结果发现,笔者提出的改进模型能够较合理、有效地估计较为完整的中国静态利率期限结构.     

The impact of Multiple Mini Interviews on the attrition and academic outcomes of midwifery students

BackgroundAdmission to the Bachelor of Midwifery (BMid) in Australia has traditionally been based on academic ranking. The BMid is a high demand course offered to a limited number of students and therefore choosing applicants who complete the degree is important. Multiple Mini Interviews (MMIs) are used to assess non-cognitive skills and select students into healthcare degrees. One university in Australia has introduced MMIs as part of the application process for the BMid.AimCompare attrition rates and Grade Point Average (GPA) scores between students admitted into the BMid using both academic ranking and MMIs, to those admitted on academic ranking alone.MethodsA basic convergent mixed methods design, using an explanatory unidirectional framework to integrate data. Attrition rates, GPA, and multiple mini interview scores (2013–2019), were linked and compared for before and after the use of MMI’s. Focus groups with students, interviewers, and hospital-based educators, explored stakeholder experiences. Open-ended questions from an applicant survey were added to the qualitative data set, which was analysed thematically.FindingsStudents who enrolled via the MMI’s had significantly lower attrition rates than those enrolled before MMI’s were introduced. GPA scores were significantly higher for students who enrolled via the MMI’s. Integration of data found MMI’s identified students passionate to undertake midwifery, and that success at the interviews increased students’ confidence to successfully complete their studies.ConclusionMMI’s as part of the entry process into the BMid enabled identification of applicants more likely to remain in the course and succeed in their studies.     

Prior distributions expressing ignorance about convex increasing failure rates

This paper deals with the specification of probability distributions expressing ignorance concerning annual or otherwise discretized failure or mortality rates, when these rates can safely be assumed to be increasing and convex, but are completely unknown otherwise. Such distributions can be used as noninformative priors for Bayesian analysis of failure data. We demonstrate why a uniform distribution used in earlier work is unsatisfactory, especially from the point of view of insensitivity with respect to the time scale that is chosen for the problem at hand. We suggest alternative distributions based on Dirichlet distributed weights for the extreme points of relevant convex sets, and discuss which consequences a requirement for scale neutrality has for the choice of Dirichlet parameters.     

Nonstationary Binary Choice

This paper develops an asymptotic theory for time series binary choice models with nonstationary explanatory variables generated as integrated processes. Both logit and probit models are covered. The maximum likelihood (ML) estimator is consistent but a new phenomenon arises in its limit distribution theory. The estimator consists of a mixture of two components, one of which is parallel to and the other orthogonal to the direction of the true parameter vector, with the latter being the principal component. The ML estimator is shown to converge at a rate of n^3/4 along its principal component but has the slower rate of n^1/4 convergence in all other directions. This is the first instance known to the authors of multiple convergence rates in models where the regressors have the same (full rank) stochastic order and where the parameters appear in linear forms of these regressors. It is a consequence of the fact that the estimating equations involve nonlinear integrable transformations of linear forms of integrated processes as well as polynomials in these processes, and the asymptotic behavior of these elements is quite different. The limit distribution of the ML estimator is derived and is shown to be a mixture of two mixed normal distributions with mixing variates that are dependent upon Brownian local time as well as Brownian motion. It is further shown that the sample proportion of binary choices follows an arc sine law and therefore spends most of its time in the neighborhood of zero or unity. The result has implications for policy decision making that involves binary choices and where the decisions depend on economic fundamentals that involve stochastic trends. Our limit theory shows that, in such conditions, policy is likely to manifest streams of little intervention or intensive intervention.