风险税务筹划决策方法探讨

随着税务筹划理论与实务的研究与发展,风险已经成为人们在税务筹划决策中关注的重要因素之一.对涉及风险的税务筹划,筹划者需要重点解决两大问题:第一,税务筹划风险的度量问题;第二,恰当地选择风险税务筹划决策方法.关于第一个问题,我们曾在《风险税务筹划方案的衡量与选择》(经济与管理研究,2005.9)一文中进行过探讨.本文将集中探讨风险税务筹划决策方法问题,即运用风险型决策方法解决风险税务筹划决策问题.     

公允价值会计顺周期性及其改进——基于金融危机的视角

近两年的金融市场动荡显示了会计信息的不确定性,公允价值会计（FVA）方法被引入到银行的资产负债表中,是金融机构首选的核算框架。FVA方法的缺陷可能会带来波动性和顺周期性,因此需要一些改进。资本缓冲、前瞻性的拨备和更完善的信息披露有助于减轻FVA方法的顺周期性。会计估值方法、审慎监管措施和风险管理之间需要相互协调,并根据各方要求作出调整。     

"十一五"经济增长速度规划的科学内涵

本文建立了一个经济增长方程并利用1987—2004年中国经济增长数据对“十一五”时期的经济增长速度作出了预测,将预算速度与十一五规划纲要规划的经济增长速度进行了比较,从中解读出“十一五”规划的经济增长速度的科学内涵。     

我国高技术服务业研发机构科技创新效率评价

构建了高技术服务业研发机构科技创新效率评价指标体系。利用2010—2011年我国高技术服务业7个细分行业研发机构的科技创新活动数据,运用数据包络分析法,测度了2010—2011年我国高技术服务业7个细分行业研发机构的科技创新效率,比较了各细分行业研发机构的科技创新效率差异,并分析其原因。进而利用理想点模型,对2010—2011年我国高技术服务业研发机构的科技创新效率进行了排名。研究结果显示:我国高技术服务业研发机构的科技创新效率总体良好,但行业差异较大。最后,提出促进我国高技术服务业发展的对策建议。     

风险分类对保险市场效率的影响分析

本文将社会福利作为衡量保险市场效率的标准,分析保险人的风险分类行为是否有助于信息不对称保险市场效率的提高.本文首先证明了信息不对称保险市场存在市场失灵,然后比较了实施风险分类前后社会福利的差异.结论表明:当保险市场处于R-S均衡时,准确性较高的分类能使社会福利得到改进,准确性不高的分类不能使社会福利得到改进;当保险市场...     

技术创新视角下的政府积极干预

技术创新与政府干预是紧密联系在一起的：一方面，技术创新的过程离不开政府的干预；另一方面，技术创新目标的实现需要政府的干预来协调。政府实施正确的干预方式和政策对技术创新具有积极的促进作用。     

经济领先指数构建及对资产配置的影响

通过选取多个对宏观经济具有领先性的初始指标构造合成的经济领先指数(CLI),并研究了CLI对宏观经济的预警能力以及对资产及股票风格配置的影响。结果发现:CLI指标领先工业增加值5个月以上,且对宏观经济指标均有持续稳定的影响;HP滤波相对EMD和Hamilton方法能够更好地提取CLI的趋势项,用马尔科夫区制转换模型对CLI趋势项进行状态划分,发现CLI对股债配置以及股票风格配置可以起到非常有益的指导作用,股债轮动、规模轮动以及价值轮动策略在样本区间分别可以获得12.93%、15.6%及14%的收益率,远高于单独对两项资产的买入持有配置以及等权配置。综合来看,构造的CLI指标不仅能够对宏观经济进行提前预判,而且对资产配置实践具有较强的指导意义。     

2005年中国纺织品贸易回顾

为了遏制中国纺织服装产品出口,早在中国入世谈判期间,美国与欧盟就主张将<中国加入世贸组织工作组报告书>第242条款强加于中国.该条款规定,其他世贸组织成员在2008年12月31日前可对中国纺织服装产品实施特别保障措施.去年,美欧对中国纺织品发起的特保争端就是以第242条款为依据.同时,<中国加入世贸组织议定书>第十五条、第十六条也为进口国借助反倾销和保障措施阻挠中国产品出口提供了便利.除此之外,各类技术性贸易壁垒也会不断对中国出口纺织服装产品提出新的要求.而一些发展中国家担心在纺织品后配额时代,失去原有的欧美纺织出口市场,绞尽脑汁阻止中国纺织品出口.因此,中国的纺织品出口在短期内尚面临诸多挑战.     

Portfolio Returns,Market Volatility,and Seasonality

This paper examines three important issues related to the relationship between stock returns and volatility. First, are Duffee's (1995) findings of the relationship between individual stock returns and volatility valid at the portfolio level? Second, is there a seasonality of the market return volatility? Lastly, do size portfolio returns react symmetrically to the market volatility during business cycles? We find that the market volatility exhibits strong autocorrelation and small size portfolio returns exhibit seasonality. However, this phenomenon is not present in large size portfolios. For the entire sample period of 1962–1995, the highest average monthly volatility occurred in October, followed by November, and then January. Examining the two sub-sample periods, we find that the average market volatility increases by 15.4% in the second sample period of 1980–1995 compared to the first sample period of 1962–1979. During the contraction period, the average market volatility is 60.9% higher than that during the expansion period. Using a binary regression model, we find that size portfolio returns react asymmetrically with the market volatility during business cycles. This paper documents a strongly negative contemporaneous relationship between the size portfolio returns and the market volatility that is consistent with the previous findings at the aggregate level, but is inconsistent with the findings at the individual firm level. In contrast with the previous findings, however, we find an ambiguous relationship between the percentage change in the market volatility and the contemporaneous stock portfolio returns. This ambiguity is attributed to strongly negative contemporaneous and one-month ahead relationships between the market volatility and portfolio returns.

     

Knowledge spillovers from FDI in China: The role of educated labor in multinational enterprises

This paper employs a firm-level panel data set for a high-tech cluster in China to examine knowledge spillovers from multinational enterprises (MNEs) to domestic firms, focusing on the role of MNEs’ employment of educated workers. We find that knowledge of MNEs spills over to domestic firms in the same industry through MNEs’ employment of workers with graduate-level or overseas education. We also find that Japanese MNEs contribute less to knowledge spillovers than US MNEs. This is likely due to the fact that Japanese MNEs in China do not employ much educated labor.