长江经济带旅游业碳排放强度的时空演变及其影响因素

文章通过利用长江经济带11个省市2010—2019年旅游业面板数据测算其旅游业碳排放强度,借助SDM模型,探究旅游业碳排放强度的时空演变及影响因素。结果表明:旅游业碳排放强度整体明显降低,其中以云南省、四川省和贵州省的碳排放强度下降幅度最大;碳排放强度在研究时期向着较高碳排放强度区域集中在中游地区的趋势发展,呈现碳排放强度“中间高,两侧低”的空间格局;产业结构与贸易依赖水平的间接效应和总效应分别表现出显著的抑制、促进效应,表明产业结构优化显著促进本地及相邻地区的旅游业碳排放强度下降,而贸易依赖水平提升效果相反。最后,文章对所得结论提出建议,旨在为旅游业实现低碳科学发展提供决策参考。     

基于双边减排成本信息不对称的排污权二级交易市场拍卖机制研究

本文构建了一个基于双边减排成本信息不对称的排污权二级交易市场拍卖模型,分析了统一价格、歧视价格及混合拍卖机制下卖方收益、排污权价格波动及排污权供给量差异,在此基础上给出了排污权二级交易市场最优拍卖机制,并进一步讨论了相关参数对最优拍卖机制的影响。结果表明：从收益最大化角度来看,最优的拍卖机制为歧视价格拍卖机制,但考虑到价格波动及排污权供给量等其他因素,排污权二级市场交易应选用混合拍卖机制。风险偏好变化对混合拍卖机制下卖方收益及价格波动的影响存在不确定性,当风险偏好超过某一阈值时,随着风险偏好程度增大,需求隐蔽效应占主导,收益及价格波动增大;相反,当风险偏好小于某一阈值时,随着风险偏好程度增大,竞争效应占主导,收益及价格波动减小。价格变动的供给影响系数对卖方收益的影响随买方参与人数的不同而不同。当买方参与人数较小时,需求隐蔽效应占主导,竞争效应不明显,随着价格变动的供给影响系数增大,混合拍卖机制下卖方的收益不断增加;当买方参与人数较大时,卖方收益同时受到需求隐蔽和竞争效应影响,随着价格变动的供给影响系数增大,收益呈先增大后减小趋势。随着价格变动的供给影响系数增大,价格波动呈先增大后减小趋势。     

京津冀节能减排政策措施的差异与协同研究

在对京津冀1981年以来节能减排政策措施进行量化处理的基础上,建立针对节能减排政策措施有效性的计量模型,分析了京津冀节能减排政策措施的演变状况,并探究京津冀节能减排政策措施对其节能减排效果影响的差异性.研究结果表明:京津冀节能减排政策颁布经历了早期各年份相对零散、缺乏连续性到新世纪以来政策颁布数量显著增多、政策总体力度逐渐增大的过程,但三地政策总效力的增加主要是由于节能减排政策颁布数量增多引起的;京津冀三地在政策的制定过程中更多的是趋于实现短期目标,政策整体缺乏系统性和权威性;人事措施、行政措施、引导措施、财税措施、金融措施等不同节能减排政策措施对京津冀节能和减排的有效性具有明显的差异;三地对不同政策措施的使用方式、使用程度方面存在明显的差异,这对京津冀协同推进节能减排的治理工作提出挑战.论文还从京津冀完善单一节能减排政策措施的使用、加强市场手段的应用及京津冀区域协同治理等方面提出了相应政策建议.     

Copula structure analysis

Summary.  We extend the standard approach of correlation structure analysis for dimension reduction of high dimensional statistical data. The classical assumption of a linear model for the distribution of a random vector is replaced by the weaker assumption of a model for the copula. For elliptical copulas a correlation-like structure remains, but different margins and non-existence of moments are possible. After introducing the new concept and deriving some theoretical results we observe in a simulation study the performance of the estimators: the theoretical asymptotic behaviour of the statistics can be observed even for small sample sizes. Finally, we show our method at work for a financial data set and explain differences between our copula-based approach and the classical approach. Our new method yielear models also.     

Shrinkage inverse regression estimation for model-free variable selection

Summary.  The family of inverse regression estimators that was recently proposed by Cook and Ni has proven effective in dimension reduction by transforming the high dimensional predictor vector to its low dimensional projections. We propose a general shrinkage estimation strategy for the entire inverse regression estimation family that is capable of simultaneous dimension reduction and variable selection. We demonstrate that the new estimators achieve consistency in variable selection without requiring any traditional model, meanwhile retaining the root n estimation consistency of the dimension reduction basis. We also show the effectiveness of the new estimators through both simulation and real data analysis.     

Conditional variance estimation in heteroscedastic regression models

First, we propose a new method for estimating the conditional variance in heteroscedasticity regression models. For heavy tailed innovations, this method is in general more efficient than either of the local linear and local likelihood estimators. Secondly, we apply a variance reduction technique to improve the inference for the conditional variance. The proposed methods are investigated through their asymptotic distributions and numerical performances.     

A new estimation method for Weibull-type tails based on the mean excess function

Studying the right tail of a distribution, one can classify the distributions into three classes based on the extreme value index γ$\gamma$. The class γ>0$\gamma >0$ corresponds to Pareto-type or heavy tailed distributions, while γ<0$\gamma <0$ indicates that the underlying distribution has a finite endpoint. The Weibull-type distributions form an important subgroup within the Gumbel class with γ=0$\gamma =0$. The tail behaviour can then be specified using the Weibull tail index. Classical estimators of this index show severe bias. In this paper we present a new estimation approach based on the mean excess function, which exhibits improved bias and mean squared error. The asserted properties are supported by simulation experiments and asymptotic results. Illustrations with real life data sets are provided.     

我国公司治理问题的实质及其政策含义

本文认为我国公司治理问题的实质主要是大股东与少数股东的利益冲突,而且由于政府常常身兼大股东的角色,所以这后一种冲突还表现为政府多重职能引发的冲突。把握这一点对于理解政府在我国公司治理中的作用以及作为我国现阶段公共政策一部分的国有股减持的途径和方式具有重要意义。     

Vine copula constructions of higher-dimensional dependent reliability systems

Copulas have proved to be very successful tools for the flexible modeling of dependence. Bivariate copulas have been deeply researched in recent years, while building higher-dimensional copulas is still recognized to be a difficult task. In this paper, we study the higher-dimensional dependent reliability systems using a type of decomposition called “vine,” by which a multivariate distribution can be decomposed into a cascade of bivariate copulas. Some equations of system reliability for parallel, series, and k-out-of-n systems are obtained and then decomposed based on C-vine and D-vine copulas. Finally, a shutdown system is considered to illustrate the results obtained in the paper.