环境管制、知识产权保护与区域创新能力——基于我国省际面板数据的实证研究

文章基于政府主导视角,利用2006—2015年我国30个省级面板数据,构建多元回归模型,分析变量之间的关系.其结果显示,环境管制、知识产权保护与区域创新能力之间呈非线性关系,环境管制与知识产权保护同时实施对区域创新能力有显著的促进作用,且具有区域异质性.从企业生存角度出发,提出门槛效应假说,采用Hansen面板门槛回归模型进行检验.结果表明,在环境管制与知识产权保护共同发挥作用时,环境管制必须控制在合理的范围内.最后采用门槛效应回归方法找到了环境管制与知识产权保护对区域创新能力影响的门槛值,并提出相应的政策建议.     

吉林省廉租房政策实施效果、存在问题及对策

立足于吉林省廉租房政策实施效果的全面调查数据,概述了吉林省廉租房政策实施效果,以独特的视角深入分析了廉租房政策推行过程中出现的一些亟需解决的共性问题,提出了针对性的解决对策。     

我国转租制度的困境与出路

转租是有别于租约让与和普通租赁的特殊租赁形式。在转租方面,世界各国立法大致可分为自由主义、限制主义和区别主义三种模式。我国《合同法》第224条关于转租的规定采限制主义,这虽然减轻了司法任务,促成了判决统一,但因不区分转租与租约转让且不分租赁之具体情形一概加以限制未免显得过于笼统,且该规定本身有违公平原则。在当前政治经济背景下,平衡当事人之利益显得尤为重要。借鉴自由主义的立法模式对现有制度予以修正,并对民事和商事租赁进行区别,对动产和不动产租赁采取不同规则具有重要意义。     

Simultaneous confidence intervals for one-way layout based on generalized pivotal quantities

In this paper, we consider simultaneous confidence intervals for all-pairwise comparisons of treatment means in a one-way layout under heteroscedasticity. Two kinds of simultaneous intervals are provided based on the fiducial generalized pivotal quantities of the interest parameters. We prove that they both have asymptotically correct coverage. Simulation results and an example are also reported. It is concluded from calculational evidence that the second kind of simultaneous confidence intervals, which we provide, performs better than existing methods.     

Hard thresholding regression

In this paper, we propose the hard thresholding regression (HTR) for estimating high‐dimensional sparse linear regression models. HTR uses a two‐stage convex algorithm to approximate the ?₀‐penalized regression: The first stage calculates a coarse initial estimator, and the second stage identifies the oracle estimator by borrowing information from the first one. Theoretically, the HTR estimator achieves the strong oracle property over a wide range of regularization parameters. Numerical examples and a real data example lend further support to our proposed methodology.     

Quadratic Approximation via the SCAD Penalty with a Diverging Number of Parameters

The high-dimensional data arises in diverse fields of sciences, engineering and humanities. Variable selection plays an important role in dealing with high dimensional statistical modelling. In this article, we study the variable selection of quadratic approximation via the smoothly clipped absolute deviation (SCAD) penalty with a diverging number of parameters. We provide a unified method to select variables and estimate parameters for various of high dimensional models. Under appropriate conditions and with a proper regularization parameter, we show that the estimator has consistency and sparsity, and the estimators of nonzero coefficients enjoy the asymptotic normality as they would have if the zero coefficients were known in advance. In addition, under some mild conditions, we can obtain the global solution of the penalized objective function with the SCAD penalty. Numerical studies and a real data analysis are carried out to confirm the performance of the proposed method.     

LAN property for an ergodic Ornstein–Uhlenbeck process with Poisson jumps

In this article, we consider an ergodic Ornstein–Uhlenbeck process with jumps driven by a Brownian motion and a compensated Poisson process, whose drift and diffusion coefficients as well as its jump intensity depend on unknown parameters. Considering the process discretely observed at high frequency, we derive the local asymptotic normality property. To obtain this result, Malliavin calculus and Girsanov’s theorem are applied to write the log-likelihood ratio in terms of sums of conditional expectations, for which a central limit theorem for triangular arrays can be applied.     

Robust modal estimation and variable selection for single-index varying-coefficient models

In this article, we present a new efficient iteration estimation approach based on local modal regression for single-index varying-coefficient models. The resulted estimators are shown to be robust with regardless of outliers and error distributions. The asymptotic properties of the estimators are established under some regularity conditions and a practical modified EM algorithm is proposed for the new method. Moreover, to achieve sparse estimator when there exists irrelevant variables in the index parameters, a variable selection procedure based on SCAD penalty is developed to select significant parametric covariates and the well-known oracle properties are also derived. Finally, some numerical examples with various distributed errors and a real data analysis are conducted to illustrate the validity and feasibility of our proposed method.     

危险驾驶罪的立法浅析

《刑法修正案(八)》将醉驾、飙车行为入罪，对严厉醉驾行为确实起到了震慑作用，收到了积极的社会效果。但是，对于刑法的提前介入以及该罪的内涵与外延该如何理解；社会舆论对于醉驾行为的性质还存在行为犯或者危险犯的争论：这些问题对于该罪在司法实践中的适用极其重要，值得我们深入思考。     

Semi-polynomial copulas

In this paper, we characterise a family of bivariate copulas whose sections between the main diagonal and the border of the unit square are polynomial, generalising several families of copulas, including those with quadratic and cubic sections. We also study a measure of association and the tail dependence for this class, illustrating our results with several examples.