农业现代化进程中的企业式家庭农场

在政策与市场的推动下,以改造传统农业为目标的企业式家庭农场应运而生。企业型家庭农场的生产经营方式具有如下特征：高资本技术要素、大规模专业化经营、集约化生产管理及企业化的市场销售和风险规避方式,这完全符合政府对现代农业的期许,因而常常被树为典型。但是,因为在发展中要求较高的环境、面临较大的风险,企业式家庭农场只能是少数精英农户的选择,大多数小农无法走通此路。因此政府不应将农业现代化的目标完全寄托于企业式家庭农场身上,大量存在的小农、中农等多元经营方式作为现代农业基础,仍将发挥重要作用。     

基于VAR模型下的安徽省金融发展和城镇化的关系分析

以1980-2012年安徽省金融发展和城镇化发展的相关数据为基础,运用VAR模型对安徽省金融发展和城镇化发展之间的关系进行研究,发现金融发展水平与城镇化水平存在高度的正相关性,且金融发展规模的贡献率要大于金融发展效率.通过建立多元化的金融机构,完善市政债券市场和加大对中小规模企业的信贷支持力度,来创新融资方式,拓宽融资渠道,从而为推进城镇化建设和促进经济增长提供资金保障.     

城市运行监管与应急响应平战结合机制研究——来自北京市海淀区地方政府经验数据

针对城市大范围多点突发事件应急处置带来的应急力量超常规供给的现实问题,构建反映城市运行监管与应急响应内在联系的平战结合机制.选择北京市海淀区地方政府经验数据作为研究样本,数据资源来自于信息化城市管理记录文件和城市应急值守记录文件.将城市应急响应事件分为"日常处置、快速处置、紧急处置"3种类型,城市运行监管事件分为"交通标志、便道设施、井盖、其他市政设施"4种类型,考虑两类变量关系建立结构方程(SEM)模型展开研究.研究结论:需要快速处置的城市应急响应事件属于敏感事件,与其联系密切的城市运行监管事件为交通标志类和其他市政设施类;需要紧急处置的城市应急响应事件属于关键事件,具有适时敏捷处置的时间压力.地方政府应充分考虑整合城市多灾种应急力量实施分类管理,广泛动员社会力量参与,提高各级别平战转换能力.     

“宅一族”行为自评量表与心理特征量表的编制与信效度检验

我国“宅一族”群体日益壮大,但目前学界缺乏对“宅”的测评工具。宅的行为表现、心理特征和对宅的态度是相互关联但又有所区别的概念,有关宅现象的研究需要根据研究目的的不同选取相应的宅量表。可以将宅的评价量表分为宅行为自评量表（“行为宅”的判定标准）和宅心理特征量表（“心理宅”的判定标准）进行设计与信效度检验。结果表明,这两份量表具有良好的内部一致性及重测信度、内容效度、区分效度和效标效度,可以作为宅现象相关研究的测评工具。今后的研究可以进一步对“主动宅”和“被动宅”进行更为深入细化的探索,揭示心理和行为两个维度上的宅对人的体质、心理和社会适应所产生的影响。     

不同经营规模农户的油菜生产技术效率分析——基于湖北、四川等6省市689户农户的调查数据

利用四川、湖北、河南、陕西、上海、江苏6省市油菜示范县689户农户的微观数据,基于超对数随机前沿分析方法,分析了不同经营规模农户油菜生产的技术效率分布及其影响因素的差异。结果发现:主要生产要素投入对油菜产量增加的效果较明显,其大小顺序为农药投入>化肥投入>种子投入>劳动力投入>土地投入;样本农户油菜种植平均技术效率为83.99%,仍有16.01%的增产空间;不同经营规模农户的油菜生产技术效率分布差别较大,总体呈偏态分布;在影响农户技术效率的主要因素中,受教育程度对不同规模农户的生产技术效率均有正向影响,家庭受农业技术培训人次、家庭成员是否有人担任村或村以上干部、外出务工人数、农户到最近农产品贸易市场的距离等因素,对小规模农户技术效率具有显著的正效应,大规模农户油菜生产技术效率则对家庭规模、家庭成员接受农业技术培训的人次及油菜收入占家庭总收入的比例的反应较为敏感。     

Bayesian analysis of censored linear regression models with scale mixtures of normal distributions

As is the case of many studies, the data collected are limited and an exact value is recorded only if it falls within an interval range. Hence, the responses can be either left, interval or right censored. Linear (and nonlinear) regression models are routinely used to analyze these types of data and are based on normality assumptions for the errors terms. However, those analyzes might not provide robust inference when the normality assumptions are questionable. In this article, we develop a Bayesian framework for censored linear regression models by replacing the Gaussian assumptions for the random errors with scale mixtures of normal (SMN) distributions. The SMN is an attractive class of symmetric heavy-tailed densities that includes the normal, Student-t, Pearson type VII, slash and the contaminated normal distributions, as special cases. Using a Bayesian paradigm, an efficient Markov chain Monte Carlo algorithm is introduced to carry out posterior inference. A new hierarchical prior distribution is suggested for the degrees of freedom parameter in the Student-t distribution. The likelihood function is utilized to compute not only some Bayesian model selection measures but also to develop Bayesian case-deletion influence diagnostics based on the q-divergence measure. The proposed Bayesian methods are implemented in the R package BayesCR. The newly developed procedures are illustrated with applications using real and simulated data.     

Comparisons of asymptotic biases and variances of m-estimators of scale under asymmetric contamination

We study robustness properties of two types of M-estimators of scale when both location and scale parameters are unknown: (i) the scale estimator arising from simultaneous M-estimation of location and scale; and (ii) its symmetrization about the sample median. The robustness criteria considered are maximal asymptotic bias and maximal asymptotic variance when the known symmetric unimodal error distribution is subject to unknown, possibly asymmetric, £-con-tamination. Influence functions and asymptotic variance functionals are derived, and computations of asymptotic biases and variances, under the normal distribution with ε-contamination at oo, are presented for the special subclass arising from Huber's Proposal 2 and its symmetrized version. Symmetrization is seen to reduce both asymptotic bias and variance. Some complementary theoretical results are obtained, and the tradeoff between asymptotic bias and variance is discussed.     

煤矿企业安全氛围量表开发研究

采用标准化的量表开发程序,对煤矿企业安全氛围量表进行研究.通过文献分析、高管访谈与专家反馈确定量表的初始项目池,通过预测试样本的项目分析与探索性因子分析对量表题项进行精炼,通过大样本数据的验证性因子分析与回归分析对量表有效性进行确认.研究表明,煤矿企业安全氛围包括7个维度,即安全意识、管理允诺、监管者行为、安全政策、安全交流、安全培训和风险准备.本研究的开发过程不仅规范、可靠,得到的量表结构亦具有较高的信度和效度,能够为煤矿企业安全氛围管理提供理论指导和测量工具.     

Comparing Fisher information in record values and their concomitants with random observations

In a sequence of bivariate random variables {(X _i , Y _i ), i≥1} from a continuous distribution with a real parameter θ, general comparison results between the amount of Fisher information about θ contained in the sequence of the first n records and their concomitants, and the desired information in an i.i.d. sample of size n from the parent distribution are established. Some relationships between reliability properties and the proposed criteria are obtained in situations in which the univariate counterpart of the underlying bivariate family belongs to location, scale or shape families. It is also shown that in some classes of bivariate families, the concerned information property is equivalent to that of its univariate counterpart. The proposed procedure is illustrated by considering several examples.     

基于面板数据的中国供电行业 规模收益分析

 公共事业企业的规模收益关系到政府监管策略的选择。近年有关中国电力行业运营规模与效率的研究主要集中在电力需求和电价调整方面，本文利用具有面板数据模型形式的成本函数，分析资本和劳动力要素投入对企业规模收益及经营效率的影响程度。主要结论是，电力供应机制的运行受劳动力因素的制约较大，企业规模收益呈递增趋势；劳动力价格对成本的长期影响明显大于短期。