Empirical Uncertain Bayes Methods in Area‐level Models

Random effects model can account for the lack of fitting a regression model and increase precision of estimating area‐level means. However, in case that the synthetic mean provides accurate estimates, the prior distribution may inflate an estimation error. Thus, it is desirable to consider the uncertain prior distribution, which is expressed as the mixture of a one‐point distribution and a proper prior distribution. In this paper, we develop an empirical Bayes approach for estimating area‐level means, using the uncertain prior distribution in the context of a natural exponential family, which we call the empirical uncertain Bayes (EUB) method. The regression model considered in this paper includes the Poisson‐gamma and the binomial‐beta, and the normal‐normal (Fay–Herriot) model, which are typically used in small area estimation. We obtain the estimators of hyperparameters based on the marginal likelihood by using a well‐known expectation‐maximization algorithm and propose the EUB estimators of area means. For risk evaluation of the EUB estimator, we derive a second‐order unbiased estimator of a conditional mean squared error by using some techniques of numerical calculation. Through simulation studies and real data applications, we evaluate a performance of the EUB estimator and compare it with the usual empirical Bayes estimator.     

Threshold Estimation for Stochastic Processes with Small Noise

Consider a process satisfying a stochastic differential equation with unknown drift parameter, and suppose that discrete observations are given. It is known that a simple least squares estimator (LSE) can be consistent but numerically unstable in the sense of large standard deviations under finite samples when the noise process has jumps. We propose a filter to cut large shocks from data and construct the same LSE from data selected by the filter. The proposed estimator can be asymptotically equivalent to the usual LSE, whose asymptotic distribution strongly depends on the noise process. However, in numerical study, it looked asymptotically normal in an example where filter was chosen suitably, and the noise was a Lévy process. We will try to justify this phenomenon mathematically, under certain restricted assumptions.     

安徽省小城镇改革发展反思

近年来,安徽省将培育小城镇作为促进县域经济社会发展的重要基础,安徽小城镇逐渐摆脱了以传统农业为主的发展模式,各类特色城镇层出不穷。但安徽省小城镇在规模、产业发展、投资资金及发展制度等方面存在一些问题,为此,提出了发展特色产业、找准承接产业转移的切入点、拓宽资金渠道、科学规划小城镇布局等相应对策。     

中小微型企业民间借贷融资的财务风险管理研究

从企业的角度深入探索分析企业民间借贷融资成因,提出以财务风险管理视角应加快立法,整治系统环境,严格执行现代法人制度、强化综合理财手段的运用、强化财务风险管理、推动国家建立风险投资市场的可行性解决方案。     

金融发展影响我国中小企业出口规模的实证研究

基于2001—2013年我国30个省市面板数据,从金融规模、金融结构和金融效率3个角度,详细探究了金融发展与我国中小企业出口规模的关系以及影响效应。结果表明：金融规模对中小企业出口规模扩张存在显著的负向影响,金融结构对中小企业出口规模扩张产生促进作用,而金融效率指标对中小企业出口的影响不显著;政府财政支出和外商直接投资显著促进中小企业出口活动,基础设施水平一定程度上抑制了中小企业出口活动。     

中小企业自主创新资金瓶颈的解决措施

自主创新是支撑一个国家崛起的筋骨,把增强自主创新能力作为国家战略是必然的,但我国中小企业进行自主创新存在融资难的问题,因此本文分析了中小企业自主创新融资难的主要原因,并提出了解决中小企业自主创新资金瓶颈的几点措施。     

小城镇基础设施建设融资现状实证分析

通过对云南省小城镇基础设施关于建设需求、资金来源、融资模式应用以及影响因素的调查问卷分析,以实证数据进一步证明小城镇基础设施建设融资中存在的不足,用图形、表格等方式更加直观地呈现出目前小城镇基础设施建设融资存在投资需求矛盾突出、融资渠道单一、新型融资模式与途径难以推广等问题。在此基础上,分析总结出问题存在的根源为小城镇经济基础薄弱、产业集聚小,政府缺乏多渠道融资意识以及规模小、利益驱动规律阻碍融资。     

小型微型企业商业模式创新及其集群成长机制

小型微型企业成长近年来逐渐引起政府、学术界和企业界的重视。我国小型微型企业面临着行业内大型中型企业在渠道和终端上的垄断,仅依靠国家和政府在金融、财税上的支持无法扫清成长道路上所面临的障碍。地方政府在推动小型微型企业集群发展,创新商业模式过程中应充分发挥好引导者与服务者的角色。小型微型企业要突破行业垄断获得持续的发展,关键与核心在于企业需要突破惯性思维,寻求自我改变,勇于创新商业模式。