Optimal model averaging forecasting in high-dimensional survival analysis

This article considers ultrahigh-dimensional forecasting problems with survival response variables. We propose a two-step model averaging procedure for improving the forecasting accuracy of the true conditional mean of a survival response variable. The first step is to construct a class of candidate models, each with low-dimensional covariates. For this, a feature screening procedure is developed to separate the active and inactive predictors through a marginal Buckley–James index, and to group covariates with a similar index size together to form regression models with survival response variables. The proposed screening method can select active predictors under covariate-dependent censoring, and enjoys sure screening consistency under mild regularity conditions. The second step is to find the optimal model weights for averaging by adapting a delete-one cross-validation criterion, without the standard constraint that the weights sum to one. The theoretical results show that the delete-one cross-validation criterion achieves the lowest possible forecasting loss asymptotically. Numerical studies demonstrate the superior performance of the proposed variable screening and model averaging procedures over existing methods.     

母公司控股、融资约束与企业创新投入

利用2012－2017年我国A股上市公司数据，检验母公司控股对企业创新投入的作用。结果发现：子公司创新投入意愿明显不足。进一步分析发现，融资约束弱化了母公司控股与企业创新投入意愿之间的关系。运用变换模型估计和变量处理方法检验后，结论仍然十分稳健。结论为法学和经济学的有限责任理论、管理学的前景理论与威胁刚性模型提供了经验证据，从而丰富了上述领域文献。同时，对我国集团型公司治理中的创新管理具有一定借鉴意义。     

金融资源配置、技术进步与经济高质量发展

随着我国发展阶段及内外部条件的变化,科技创新已成为新时代引领我国经济高质量发展的核心驱动力。本文以金融驱动技术进步的视角,构建内生增长DSGE模型,分析金融资源配置、技术进步和经济增长之间的关系。研究佐证了我国技术创新的逆周期性,并发现金融资源在企业生产性投资与创新投资之间的分配,可以通过改变生产要素投入规模和技术进步率两种途径影响经济增长,且这两种影响之间存在“跷跷板”关系,但后者更具主导性。在此基础上,诠释了金融、技术与经济的动态传导机制:经济扩张期,企业生产规模扩张,金融资源对生产性投资的支持增加,对创新的投入相对减少,技术进步率放缓;经济收缩期,企业缩减生产规模,金融资源对生产性投资的支持减少,对创新的投入相对增加,技术进步率提升。本研究的政策启示为,面对当前发展新矛盾、新挑战,应把握发展新格局、新机遇,进一步深化金融改革,优化金融资源配置机制,鼓励创新投资,充分发挥股权市场对企业研发创新的支持作用,并辅以稳健适度的宏观调控政策,为企业创新提供良性的宏观环境,激活企业创新需求,促进技术进步,推动经济高质量发展。     

Feeling hungry? let's order through mobile! examining the fast food mobile commerce in China

This study proposes a unique framework that aids to enrich online shopping experience (psychological and monetary gains) and accelerates fast food mobile commerce (m-commerce). The extended technology acceptance model (TAM) is applied while the stimulus–organism–response (S–O–R) paradigm served as the predominant framework combined with the acquisition-transaction utility theory. This study investigates the mobile website quality, website brand equity (stimulus) influence on (PEOU) and (PU) (organism) to predict Chinese consumer intention to use fast food mobile commerce (response). A total of 936 respondents were participated while data were collected using a convenience sampling technique in China. Results reveal that all dimensions of mobile WQ (i.e., service quality, system quality, and information quality) and Website BE (i.e., brand image, perceived quality, brand association, and brand loyalty) (stimulus) significantly substantially influence PEOU and PU (organism) toward the acceptance of online fast food shopping (response). Digital Coupon Proneness (an accelerator) substantially moderates the relationship between PEOU, PU, and intention to use fast food m-commerce. Based on the assumptions of acquisition-transaction utility theory, category-specific (fast food) digital coupon proneness increase m-commerce for online fast food buying– a novel contribution of the study. Furthermore, research provides unique managerial insights for the industry to utilize the maximum potential of m-commerce in the fast-food industry.     

创业企业何以提高创新绩效——基于创业学习与商业模式创新协同联动视角的QCA方法

以150个创业企业为样本，基于创业学习和商业模式创新理论，运用模糊集定性比较分析方法（fsQCA），探究经验学习、认知学习、新颖型商业模式创新和效率型商业模式创新对创新绩效的影响路径及机制。研究发现，存在新颖型商业模式创新等4条创新绩效产出关键路径；相较于效率型商业模式创新，新颖型商业模式创新在关键路径中更容易提高创新绩效；利用QCA方法证实了影响创业企业创新绩效的组态内部各要素之间的替代性。结论丰富了创新绩效产出内部机制，可为创业企业提高创新绩效提供指导和借鉴。     

基于CE模型的河南省耕地生态补偿额度研究

[目的]基于生态补偿利益主体的需求和支付意愿,充分考虑区域经济发展状态,测算具有弹性的生态补偿标准,确保生态补偿机制顺利运行。[方法]以河南省457份实地调查问卷为基础,采用选择实验法,建立由4个属性水平、7个选择集组成的生态价值属性集,测算受访对象生态补偿的支付意愿。[结果]城乡居民对于耕地资源景观与生态环境关注度最高,其次是耕地质量和耕地面积;农民和市民对于耕地生态价值属性满足的支付意愿存在显著差异性,农民支付意愿为2 060.55元/hm~2,市民支付意愿为3 396.15元/hm~2,两者相差近1 335.60元/hm~2,收入水平、环保意识是影响受访对象生态补偿支付意愿的最直接因素,但两者均认为耕地面积不变、耕地质量改善和耕地景观生态环境改善为最优选择。[结论]补偿额度应充分考虑相关利益主体的支付能力和意愿,将农民的支付意愿作为生态补偿下限,市民的支付意愿作为生态补偿上限,可建立具有一定弹性的生态补偿机制。     

分析师跟踪、内控有效性与科技型中小企业创新

基于2009-2017年创业板317家科技型中小企业数据，从发明专利产出视角，探究分析师跟踪、内部控制有效性与企业技术创新的关系。结果显示，分析师跟踪人数显著提升了企业发明专利产出，内部控制有效性在分析师跟踪人数与企业发明专利产出关系中起部分中介作用，且在融资约束程度较高的企业中更为显著。即企业内外部治理机制有效配合对科技型中小企业技术创新发挥促进效应，且该效应在企业融资约束程度较高时更为显著。     

An information-theoretic approach for forecasting interval-valued SP500 daily returns

We develop an iterative and efficient information-theoretic estimator for forecasting interval-valued data, and use our estimator to forecast the SP500 returns up to five days ahead using moving windows. Our forecasts are based on 13 years of data. We show that our estimator is superior to its competitors under all of the common criteria that are used to evaluate forecasts of interval data. Our approach differs from other methods that are used to forecast interval data in two major ways. First, rather than applying the more traditional methods that use only certain moments of the intervals in the estimation process, our estimator uses the complete sample information. Second, our method simultaneously selects the model (or models) and infers the model’s parameters. It is an iterative approach that imposes minimal structure and statistical assumptions.     

Forecasting value at risk and expected shortfall with mixed data sampling

I propose applying the Mixed Data Sampling (MIDAS) framework to forecast Value at Risk (VaR) and Expected shortfall (ES). The new methods exploit the serial dependence on short-horizon returns to directly forecast the tail dynamics of the desired horizon. I perform a comprehensive comparison of out-of-sample VaR and ES forecasts with established models for a wide range of financial assets and backtests. The MIDAS-based models significantly outperform traditional GARCH-based forecasts and alternative conditional quantile specifications, especially in terms of multi-day forecast horizons. My analysis advocates models that feature asymmetric conditional quantiles and the use of the Asymmetric Laplace density to jointly estimate VaR and ES.     

THE ECONOMIC AND BEHAVIORAL CONSEQUENCES OF ONLINE USER REVIEWS

Online user reviews have become an increasingly relevant informational tool during product search and adoption. Recent surveys have shown that consumers trust and rely on online reviews more than they do on website recommendations and experts opinions. As a new way of driving consumer purchasing intentions, online user reviews have therefore come under scrutiny by researchers. The objective of this paper is to offer an overview of the literature regarding the impact of online user reviews on economic indicators (e.g., sales, marketing strategies) and on consumer behavior. Furthermore, following the growing interest of academics and professionals alike on the topic, the present work provides an exploratory analysis of the consequences of online reviews on individual rating behavior – empirical regularities showed that online rating distributions tend to be concentrated on extreme values, possibly because of rating biases. As consumers and firms incorporate the heuristic cues from such distributions into their decision-making processes, biased ratings might lead to suboptimal choices. This overview presents established results (e.g., the impact of volume on product sales) and insights as issues for future research.