我国电影生命周期模型及实证分析

对我国电影市场的影片生命周期进行了分析,建立了考虑季节性因素和其他影响因素的Gamma需求模型,并结合计量模型中的变截距面板数据模型与普通多元回归模型应用于研究电影观众人数及其衰减情况.估计结果显示:建立的模型能够较准确地反映我国电影市场观众人数.的变化规律.此外,针对我国电影市场,量化研究了影星的票房号召力、续集、投资规模等因素对观众人数的影响情况,为电影决策者制定策略以及预测新上映影片的观众需求做指导与借鉴.实证结果显示:考虑档期因素的必要性,并且发现较多的观众会导致影片观众人数的下降显得更快些,大制作和小制作电影的观众衰减速度相差很小,模拟支持研究结论的合理性.     

地理标志农产品生产质量控制行为分析——基于新疆地理标志水果405户果农的调查

以新疆405户地理标志果农问卷调查数据为依据,运用二元Logistic回归模型对其生产质量控制行为的影响因素进行分析,结果表明：生产者的预期收益、对地理标志水果操作规程的了解程度、是否参加农民专业合作经济组织、是否得到技术指导、是否参加质量培训、政府监管力度与是否得到政府资金支持等影响因素是显著性变量。表14,参12。     

小样本多技术状态性能可靠性的仿真评估方法

针对大型产品性能试验的多技术状态、小样本特点,提出了基于环境因子仿真的性能可靠性评估方法。运用仿真技术获得了环境因子的仿真结果;利用环境因子将多技术状态下的试验数据折算为产品设计状态下的性能试验数据,基于折算后的性能试验数据得到了产品性能可靠性估计。最后,通过一个仿真实例说明了折算模型具有稳健性。     

Best weight pattern evaluation based security constrained power dispatch algorithm

This paper presents a methodology which determines the allocation of power demand among the committed generating units while minimizes number of objectives as well as meets physical and technological system constraints. The procedure considers two decoupled problems based upon the dependency of their goals on either active power or reactive power generation. Both the problems have been solved sequentially to achieve optimal allocation of active and reactive power generation while minimizes operating cost, gaseous pollutants emission objectives and active power transmission loss with consideration of system operating constraints along with generators prohibited operating zones and transmission line flow limits. The active and reactive power line flows are obtained with the help of generalized generation shift distribution factors （GGDF） and generalized Z-bus distribution factors （GZBDF）, respectively. First problem is solved in multi-objective framework in which the best weights assigned to objectives are determined while employing weighting method and in second problem, active power loss of the system is minimized subject to system constraints. The validity of the proposed method is demonstrated on 30-bus IEEE power system.     

同时考虑环境因素和统计噪声的四阶段SFA模型——在我国省际技术效率和政府管理绩效中的应用

为克服三阶段DEA模型忽略了投入-产出之间统计噪声对技术效率的影响这一不足,将环境因素细分为员工工作环境和管理环境两类,提出了一种基于随机前沿分析（stochastic frontier analysis）技术的四阶段模型. 通过对比剔除管理环境因素前后的技术效率,得到动态经营管理效率（management efficiency）. 进一步,利用四阶段SFA模型对2002-2010 年间我国省际技术效率和政府管理绩效进行了测算. 研究发现：（1） 我国整体、三大地区及各省区综合技术效率均呈现“U型”波动趋势,且东部地区最高,中部次之,西部最低;而实际技术效率呈现单调递增的变动趋势,中部最高,东部次之,西部最低. （2） 政策扶持对于地区技术效率的提升具有重大的推动作用,贡献率高达71.4%;政府管理绩效呈现“U型”波动趋势（江西,湖北,海南除外）,且东部地区高出中西部约8.9% 和3.2%. 作为技术效率和经营管理绩效实证研究的技术基础,四阶段SFA 模型为优化资源配置提供了很好参考.     

Incorporating textual and management factors into financial distress prediction: A comparative study of machine learning methods

Financial distress prediction (FDP) has been widely considered as a promising approach to reducing financial losses. While financial information comprises the traditional factors involved in FDP, nonfinancial factors have also been examined in recent studies. In light of this, the purpose of this study is to explore the integrated factors and multiple models that can improve the predictive performance of FDP models. This study proposes an FDP framework to reveal the financial distress features of listed Chinese companies, incorporating financial, management, and textual factors, and evaluating the prediction performance of multiple models in different time spans. To develop this framework, this study employs the wrapper-based feature selection method to extract valuable features, and then constructs multiple single classifiers, ensemble classifiers, and deep learning models in order to predict financial distress. The experiment results indicate that management and textual factors can supplement traditional financial factors in FDP, especially textual ones. This study also discovers that integrated factors collected 4 years prior to the predicted benchmark year enable a more accurate prediction, and the ensemble classifiers and deep learning models developed can achieve satisfactory FDP performance. This study makes a novel contribution as it expands the predictive factors of financial distress and provides new findings that can have important implications for providing early warning signals of financial risk.     

The US Dollar/Euro Exchange Rate: Structural Modeling and Forecasting During the Recent Financial Crises

The paper investigates the determinants of the US dollar/euro within the framework of the asset pricing theory of exchange rate determination, which posits that current exchange rate fluctuations are determined by the entire path of current and future revisions in expectations about fundamentals. In this perspective, we innovate by conditioning on Fama–French and Carhart risk factors, which directly measures changing market expectations about the economic outlook, on new financial condition indexes and macroeconomic variables. The macro‐finance augmented econometric model has a remarkable in‐sample and out‐of‐sample predictive ability, largely outperforming a standard autoregressive specification. We also document a stable relationship between the US dollar/euro Carhart momentum conditional correlation (CCW) and the euro area business cycle. CCW signals a progressive weakening in economic conditions since June 2014, consistent with the scattered recovery from the sovereign debt crisis and the new Greek solvency crisis exploded in late spring/early summer 2015. Copyright © 2016 John Wiley & Sons, Ltd.     

Forecasting key US macroeconomic variables with a factor‐augmented Qual VAR

In this paper, we first extract factors from a monthly dataset of 130 macroeconomic and financial variables. These extracted factors are then used to construct a factor‐augmented qualitative vector autoregressive (FA‐Qual VAR) model to forecast industrial production growth, inflation, the Federal funds rate, and the term spread based on a pseudo out‐of‐sample recursive forecasting exercise over an out‐of‐sample period of 1980:1 to 2014:12, using an in‐sample period of 1960:1 to 1979:12. Short‐, medium‐, and long‐run horizons of 1, 6, 12, and 24 months ahead are considered. The forecast from the FA‐Qual VAR is compared with that of a standard VAR model, a Qual VAR model, and a factor‐augmented VAR (FAVAR). In general, we observe that the FA‐Qual VAR tends to perform significantly better than the VAR, Qual VAR and FAVAR (barring some exceptions relative to the latter). In addition, we find that the Qual VARs are also well equipped in forecasting probability of recessions when compared to probit models.     

海南岛主要的自然因素与社会因素的关系分析

在社会的发展过程中,自然因素与社会因素(社会经济建设和社会问题)的关系是,自然因素提供社会经济建设的物质基础,是经济发展的前提条件,而经济发展带来的社会问题却反过来束约其本身的发展和自然因素的利用方式和途径。为了更好地理顺海南岛的自然因子与社会因子的关系,有助于海南开发建设,本文从发展与演变的角度进行具体的海南岛自然因子与社会因子的质和量的关系分析。文章的主体有一、人口的分布格局与发展规模;二、农业、工业的演变趋势与投资对策;三、自然因素与社会因素的均衡状态探索。     

聚酰胺酸纳米乳液的形成与影响因素

通过在聚酰胺酸(PAA)的DMAc溶液中添加胺和非溶剂,制得PAA纳米乳液.透射电镜和激光粒度仪的分析表明:PAA纳米乳液液滴的形状较为规整,尺寸分布在50～100 nm之间.研究了PAA纳米乳液形成的影响因素,发现聚酰胺酸盐的形成是PAA纳米乳液的形成和稳定的关键.结果表明:以甲醇为分散介质,控制三乙胺与PAA中羧基的比例(R)在0.6～0.7之间,甲醇与DMAc的比值(P/S)在1.5～2.25之间,可以制得稳定的PAA纳米乳液.