突发公共事件对电影行业影响的量化研究

人工收集和整理2012—2018年在中国市场上映的首轮院线电影信息数据，构建电影需求的嵌套logit回归模型，以新冠肺炎疫情为准自然实验，来量化突发公共事件对电影行业复产复工的影响。结果显示：第一，关于上映时间选择，在恢复营业后，如果所有因为疫情尚未上映的电影选择顺延上映能有效避免过度竞争的局面。第二，关于上映节奏控制，控制好未定档电影的上映节奏，保持适当的竞争能促进经济效益提升。其中，从11月份开始以每周两部的频率上映未定档电影的经济效益最佳。第三，关于上映方式选择，与线下播放相比，疫情期间选择线上播放能及时收回成本并有利于经济收益最大化的实现。研究结论为电影行业制定复产复工策略提供依据，为未来应对突发公共卫生事件提供参考。     

二代涉入、制度情境与中国家族企业创新投入——基于社会情感财富理论的研究

基于社会情感财富理论,本文以2012-2016年中国A股上市家族企业为样本,采用倾向得分匹配法,对一定制度情境下二代涉入对家族企业创新投入的影响进行实证研究。研究结果表明:二代涉入会抑制家族企业的创新投入,发生二代涉入的家族企业会更重视约束型社会情感财富,而该类社会情感财富会导致家族企业对创新投入持保守态度;制度环境对二代涉入与家族企业创新投入之间的关系具有正向调节效应,从而会缓和二代涉入对家族企业创新投入的抑制作用;政治关联对二代涉入与家族企业创新投入之间的关系具有负向调节效应,从而会加剧二代涉入对家族企业创新投入的抑制作用。据此,本文建议:发生二代涉入的家族企业不能为了加强对企业的控制而排斥引入外部优良人才或外部投资者,创始人应该注重二代成员对家族企业归属感等的培养,提升二代成员对延伸型社会情感财富的保护意愿;政府和家族企业必须共同努力推进市场化改革,藉此完善家族企业赖以生存的制度环境;家族企业应当尽量避免政治寻租等行为对创新的抑制作用。     

Household Determinants of the Adoption of Improved Cassava Varieties using DNA Fingerprinting to Identify Varieties in Farmer Fields: A Case Study in Colombia

We examine factors affecting the adoption of improved cassava varieties of 217 households in the Cauca Department in southwest Colombia. Using DNA fingerprinting through Single Nucleotide Polymorphisms (SNPs), we identified different cultivars in farmers fields. We also used this information to remove possible bias in the adoption model that could have resulted from a misclassification of improved varieties (IVs). As a result, we found that farmers substantially overestimate their use of IVs and there are important differences in the determinants of adoption between farmer self‐identification and DNA fingerprinting. This finding implies that the incorporation of DNA fingerprinting in IV adoption studies is important to ensure the accuracy of future agricultural economic research and the relevance of subsequent policy recommendations.     

Building relationship innovation in global collaborative partnerships: big data analytics and traditional organizational powers

This study examines how relationship innovation can be developed in global collaborative partnerships (alliances, joint ventures, mergers, and acquisitions). The recently emerging theory of big data analytics linked with traditional organizational powers has attracted a growing interest, but surprisingly little research has been devoted to this important and complex topic. Therefore, after developing the theoretical foundations, our study empirically quantifies the links between the theoretical constructs based on the data collected from chief executive officers, managing directors, and heads of departments who work in contemporary global data‐and‐information driven collaborative partnerships. The results from structural equation modeling indicate that the relationship innovation depends on the power of big data analytics and non‐mediated powers (NMP, expert and referent). The power of big data analytics also mediates the correlation between NMP and relationship innovation. However, mediated powers (coercive and manipulative) negatively affect the power of big data analytics and relationship innovation. The interaction effects further depict that analytically powered partnerships have better relationship innovation compared with those which focus less on the analytical power. Consequently, the contributions of this study provide a deeper understanding of mechanisms of how modern collaborative partnerships can use big data analytics and traditional organizational powers to co‐create relationship innovation.     

Target‐Setting,Pay for Performance,and Quality Improvement: A Case Study of Ontario Hospitals’ Quality‐Improvement Plans

This study examines whether difficult targets and quality indicators in executives' pay‐for‐performance (P4P) plans affect performance. The impact of target‐setting and P4P plans on quality improvement in the public sector is unclear. The Ontario government initiated the Quality Improvement Plan (QIP), which requires hospitals to set targets for quality indicators annually and link executive pay to target achievement since 2011. Analyzing Health Quality Ontario's database and hospitals' 2012–2013 QIPs, this study shows greater quality improvement in hospitals with difficult targets than hospitals with easy targets or without assigned targets; however, the positive impact disappears for high‐performance hospitals relative to their peers. We find no significant effect of the use of quality indicators in executives' P4P plans on quality improvement. Copyright © 2018 ASAC. Published by John Wiley & Sons, Ltd.     

Time series copulas for heteroskedastic data

We propose parametric copulas that capture serial dependence in stationary heteroskedastic time series. We suggest copulas for first‐order Markov series, and then extend them to higher orders and multivariate series. We derive the copula of a volatility proxy, based on which we propose new measures of volatility dependence, including co‐movement and spillover in multivariate series. In general, these depend upon the marginal distributions of the series. Using exchange rate returns, we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models, and produce more accurate value‐at‐risk forecasts.     

基于经济新常态的长春市水资源开发利用潜力评价

以长春市为研究对象,基于未来经济处于新常态的发展态势,构建包含水资源、社会、经济、生态环境4个子系统的评价指标体系,并确定各指标的评价等级标准;基于模糊数学理论以及层次分析法构建包括目标层、准则层、指标层的3层模糊综合评价模型,以2015年为现状水平年,应用模型对长春市水资源开发利用潜力进行综合评价。结果表明:长春市水资源开发利用程度处于中等偏上水平,各辖区水资源开发利用规模不平衡,可通过产业结构调整提高全市用水效率,为经济持续增长提供保障。     

The equivalence of supporting software delegation and sales delegation

This paper considers a duopoly market with horizontally differentiated system goods to examine system owners' behaviors under supporting software delegation, in which owners of system firms use varieties of supporting software, coupled with profit, to evaluate their managers' performance. Supporting software delegation seems to induce managers to act more aggressively in price competition than sales delegation does; however, we prove that if two systems are compatible and the varieties of supporting software are determined by hardware owners' overall expenditure amount on software, then supporting software delegation is equivalent to sales delegation. Owners of system firms induce their managers to act less aggressively in hardware price competition by offering contracts with a negative weight on varieties of supporting software under supporting software delegation. We find that stronger network externalities do not reverse system owners' contracting behaviors under supporting software delegation. Finally, it is worth mentioning that hardware technologies are static in this paper. In other words, dynamic changes such as hardware evolution are not considered in our analysis.     

EMPIRICAL PERFORMANCE OF GARCH MODELS WITH HEAVY‐TAILED INNOVATIONS

We introduce a new type of heavy‐tailed distribution, the normal reciprocal inverse Gaussian distribution (NRIG), to the GARCH and Glosten‐Jagannathan‐Runkle (1993) GARCH models, and compare its empirical performance with two other popular types of heavy‐tailed distribution, the Student's t distribution and the normal inverse Gaussian distribution (NIG), using a variety of asset return series. Our results illustrate that there is no overwhelmingly dominant distribution in fitting the data under the GARCH framework, although the NRIG distribution performs slightly better than the other two types of distribution. For market indexes series, it is important to introduce both GJR‐terms and the NRIG distribution to improve the models’ performance, but it is ambiguous for individual stock prices series. Our results also show the GJR‐GARCH NRIG model has practical advantages in quantitative risk management. Finally, the convergence of numerical solutions in maximum‐likelihood estimation of GARCH and GJR‐GARCH models with the three types of heavy‐tailed distribution is investigated.