我国钢铁企业技术创新能力分布及演变态势研究

本文依据我国20家大中型上市钢铁企业1998～2013年各项技术创新指标的面板数据,在对企业技术创新能力进行综合评价的基础上,运用非参数Kernel密度估计方法及马尔可夫链分析模型,对我国钢铁企业技术创新能力的分布及发展演变态势进行了研究,研究结果显示：①我国钢铁企业技术创新能力呈现出“单峰→双峰→单峰”的演变规律,钢铁企业技术创新能力水平总体上都得到了一定程度的提高,但不同钢铁企业技术创新能力的发展速度和水平呈现出明显的不平衡性;②不同钢铁企业Kernel密度分布状态与企业所在地区铁矿资源禀赋和工业经济发展水平存在高度关联性;③钢铁企业技术创新能力经过长期发展和积累过程,客观上存在着低水平状态逐渐向高水平状态转移的现实可能性,但由于不同钢铁企业自身的差异性特征,技术创新能力发展将表现出不同步性;④加快企业优化重组和提高生产能力集中度、加强现代高新技术对钢铁产业的改造和升级、加大政府政策引导和科技资金投入是实现钢铁企业技术创新能力快速提升的重要途径。     

静态及动态风险度量模型的实证对比分析

选取上海证券交易所金融、工业指数的收盘价为观察对象,分别对静态及动态模型、上证金融及工业指数的风险程度以及不同置信水平下的度量准确性进行了比较研究,结果表明：动态风险度量模型对VaR、ES的度量比静态模拟更加准确;上证金融指数的风险程度要略高于上证工业指数的风险程度;置信度为99%时度量风险模型要比置信度为95%时更加精确。     

贷款行业集中度对商业银行系统性风险影响的实证研究——基于MES方法

金融危机爆发后,银行业系统性风险得到了广泛的关注。基于2007-2012年中国10家上市银行的相关数据,文章利用MES方法测算系统性风险贡献度,分析贷款行业集中度对商业银行系统性风险的影响。研究结果表明,贷款行业集中度对商业银行系统性风险存在正向影响。因此,商业银行在投放贷款过程中,应该防范贷款行业投向的过度集中,从而减少系统性风险爆发的可能性。该研究结论为我国商业银行合理配置信贷资源提供了有利的依据。     

项目进度绩效指标的改进及其动态性预测

传统的挣值方法中,进度指标的预测多表现单期、静态的特性,存在严重的局限性。为了改进和完善挣值管理方法中进度指标体系,在考虑时间序列的基础上,将统计方法引入挣值管理进度指标体系中,用更加科学的方法对项目进度指标进行描述,并在此基础上基于贝叶斯推断方法,加入专家意见,从统计学的角度提出了进度绩效指数的动态预测模型,因而,可以为项目管理者提供科学的据侧依据。     

Financial density selection

We propose and study simple but flexible methods for density selection of skewed versions of the two most popular density classes in finance, the exponential power distribution and the t distribution. For the first type of method, which simply consists of selecting a density by means of an information criterion, the Schwarz criterion stands out since it performs well across density categories, and in particular when the DGP is normal. For the second type of method, general-to-specific density selection, the simulations suggest that it can improve the recovery rate in predictable ways by changing the significance level. This is useful because it enables us to increase (reduce) the recovery rate of non-normal densities by increasing (reducing) the significance level, if one wishes to do so. The third type of method is a generalisation of the second type, such that it can be applied across an arbitrary number of density classes, nested or non-nested. Finally, the methods are illustrated in an empirical application.     

Closed-form Bayesian inferences for the logit model via polynomial expansions

Articles in Marketing and choice literatures have demonstrated the need for incorporating person-level heterogeneity into behavioral models (e.g., logit models for multiple binary outcomes as studied here). However, the logit likelihood extended with a population distribution of heterogeneity doesn’t yield closed-form inferences, and therefore numerical integration techniques are relied upon (e.g., MCMC methods). We present here an alternative, closed-form Bayesian inferences for the logit model, which we obtain by approximating the logit likelihood via a polynomial expansion, and then positing a distribution of heterogeneity from a flexible family that is now conjugate and integrable. For problems where the response coefficients are independent, choosing the Gamma distribution leads to rapidly convergent closed-form expansions; if there are correlations among the coefficients one can still obtain rapidly convergent closed-form expansions by positing a distribution of heterogeneity from a Multivariate Gamma distribution. The solution then comes from the moment generating function of the Multivariate Gamma distribution or in general from the multivariate heterogeneity distribution assumed. Closed-form Bayesian inferences, derivatives (useful for elasticity calculations), population distribution parameter estimates (useful for summarization) and starting values (useful for complicated algorithms) are hence directly available. Two simulation studies demonstrate the efficacy of our approach. JEL Classification C6 · C8 · M3     

高等教育发展与中国制造业结构升级

探究高等教育发展对制造业结构升级的影响和作用机制,有助于推进中国制造业结构升级的进程。基于2008—2017年中国27个省（市、自治区）的省际面板数据,借助中介效应模型,探究了高等教育发展对制造业结构升级的影响及作用机制。研究表明,高等教育可以通过提高人力资本积累、促进技术创新这两条路径推动中国制造业结构升级。行业异质性检验表明,高等教育发展对劳动密集型制造业影响显著为负,对技术密集型制造业影响显著为正;区域异质性分析表明,中部地区高等教育发展对制造业结构升级有显著正向影响。完善高等教育投资体系,并在区域间合理配置高等教育资源以及优化人才培养的学科专业设置,对中国制造业转型升级至关重要。     

县域经济发展的空间集聚特征与优化思路--以重庆市为例

地区之间人口集聚程度和经济集聚程度的差异是现实世界中普遍存在的特征和事实,这个变化趋势在全球范围内迄今依然是有增无减,而且集聚的大潮将不可阻挡。因此本文以经济密度和集聚程度作为主要指标,对重庆市2010年38个区县的集聚发展状况进行了分析,分析结果表明各区县的集聚发展并不平衡,具体可以划分为4个不同的集聚发展类型。从空间格局上看,主要呈现出如下特征：（1）“两翼”区县集聚发展程度整体偏低,（2）“一圈”内部存在差异,（3）长江南北存在明显差距。最后,结合前述分析结论和不同区县所属主体功能区类型,本文提出了有针对性的差异化集聚发展思路,以便促进全市区域经济更加科学协调发展。     

Nonlinear analysis for forecasting currencies: are they useful to the portfolio manager?

The importance of a time-varying specification for both the return and the risk of financial assets is well known. The purpose of this study is to investigate if some of the most recently developed econometric models, combined with technical indicators often used by practitioners, can significantly predict future returns. While most studies have focused on either univariate series or in-sample analyses of a given econometric specification, this study considers a multivariate framework where a US based investor daily reallocates a portfolio of three currencies (Deutschmark, Swiss Franc and Japanese Yen). Series of three years out-of-sample forecasts are analysed in terms of risk and return and it is shown that some of the tested speciications can indeed signiicantly predict future daily returns and correlations over this three-year period.     

Socially optimal replacement of conventional with electric vehicles for the US household fleet

In this study, a framework is proposed for minimizing the societal cost of replacing gas-powered household passenger cars with battery electric ones (BEVs). The societal cost consists of operational costs of heterogeneous driving patterns' cars, government investments for charging deployment, and monetized environmental externalities. The optimization framework determines the timeframe needed for conventional vehicles to be replaced with BEVs. It also determines the BEVs driving range during the planning timeframe, as well as the density of public chargers deployed on a linear transportation network over time. We leverage data sets that represent US household driving patterns, as well as the automobile and the energy markets, to apply the model. Results indicate that it takes 8 years for 80% of our conventional vehicle sample to be replaced with electric vehicles, under the base case scenario. The socially optimal all-electric driving range is 204 miles, with chargers placed every 172 miles on a linear corridor. All public chargers should be deployed at the beginning of the planning horizon to achieve greater savings over the years. Sensitivity analysis reveals that the timeframe for the socially optimal conversion of 80% of the sample varies from 6 to 12 years. The optimal decision variables are sensitive to battery pack and vehicle body cost, gasoline cost, the discount rate, and conventional vehicles' fuel economy. Faster conventional vehicle replacement is achieved when the gasoline cost increases, electricity cost decreases, and battery packs become cheaper over the years.