双循环驱动我国城市产业转移效应研究

基于201个城市的相关数据,利用动态面板模型和空间杜宾模型,实证分析了内循环、外循环和双循环对产业转移的影响。研究结果表明：前期产业转移在一定程度上会影响后期产业转移,前一期当地产业比例较大,其后产业转移受到的促进作用也较大;内循环、外循环和双循环均对产业转移起到显著的正向促进作用,东部城市受到的促进作用略高于中西部城市;要素流动在产业转移中发挥着重要作用,劳动力要素流动、技术要素流动和资本要素流动不仅受到内、外循环和双循环的促进作用,同时对产业转移也起到一定的促进作用;产业转移具有空间相关性,产业在空间上倾向于向产业转入较高的城区转移。为此,我国在政策上应进一步加快推动内循环,促进外循环,关注要素流动在产业转移中的重要作用,合理分配要素资源。     

产业集群的阶段性演进机制分析

在对产业集群相关理论进行综述的基础上,提出“地理因素”和“经济因素”两个维度,以此为基础对产业集群的演化过程进行三阶段划分,并对这一演化过程的内在机制和制约条件进行研究。     

改进的人工神经网络方法在农业现代化综合评价中的应用

该文将因子分析的方法引入人工神经网络,运用于农业现代化多指标综合评价,克服了人工神经网络在多指标情况下预测精度降低的不足,为农业现代化综合评价的研究方法提出了新的思路。     

合作创新中情境因素、合作效果与信任关系的实证

文章构建了情境因素、合作效果和相互信任之间关系的概念模型。通过问卷调查和利用结构方程模型,对概念模型进行了实证分析。研究表明情境因素中的沟通和关系专用性资产促进了企业之间的信任,而力量对比关系显著影响企业之间的承诺,信任导致合作效果的提高。     

政府补贴对企业真实创新绩效的影响——基于中国A股上市公司数据的实证分析

在分析政府补贴政策的特征及其影响企业真实创新绩效的理论机制的基础上,运用A股上市公司数据,检验了政府补贴对企业真实创新绩效的直接和传导效应。研究发现：政府补贴对企业真实创新绩效具有激励效应,且国有企业较非国有企业的创新效应更强;研发资本要素市场扭曲能够强化政府补贴激励企业真实创新绩效的调节作用,并与产权性质联合调节政府创新补贴效果;创新投入与融资约束在政府补贴对企业真实创新绩效的影响中起部分中介效应;政府补贴对企业创新持续性具有负向抑制效应,政府补贴效果受到研发资本要素市场扭曲和产权性质明显的负向调节作用,且创新投入与融资约束在政府补贴对企业持续性创新的影响中起部分中介效应。     

影响创新扩散速度的社会和技术因素之研究

通过对美国、中国内地和香港等不同地区不同创新物在各自特定时空中的扩散轨迹的总结和分析,把影响创新扩散的因素归纳为两大类:社会的和技术的。其中,社会因素又区分为创新产生的年代和创新扩散的地区,而技术因素主要指创新属性,分为计算类、电信类、家庭娱乐类和大众媒介类。研究结果发现,社会因素中的创新出现的时间对于创新扩散的形态具有显著影响;扩散所在地区和创新特性对创新扩散的形态没有显著影响。     

试论李佩甫《城的灯》中的恶魔性因素

恶魔性因素在中西方文学传统中具有普遍意义,栩栩如生的恶魔性人物形象始终具有着无限的艺术生命力。恶魔性因素的内涵是对某种正常秩序的破坏,对正常意义上的社会伦理道德的反叛,其核心要素是反抗,其生命是叛逆,其实质是战斗。原始的生命冲动和颇具创造性的智慧是其性格中共有特点。李佩甫小说《城的灯》中的冯家昌这一人物性格中,就具有较强的恶魔性因素。     

Three Recommendations for Improving the Use of p-Values

ABSTRACT

Researchers commonly use p-values to answer the question: How strongly does the evidence favor the alternative hypothesis relative to the null hypothesis? p-Values themselves do not directly answer this question and are often misinterpreted in ways that lead to overstating the evidence against the null hypothesis. Even in the “post p?<?0.05 era,” however, it is quite possible that p-values will continue to be widely reported and used to assess the strength of evidence (if for no other reason than the widespread availability and use of statistical software that routinely produces p-values and thereby implicitly advocates for their use). If so, the potential for misinterpretation will persist. In this article, we recommend three practices that would help researchers more accurately interpret p-values. Each of the three recommended practices involves interpreting p-values in light of their corresponding “Bayes factor bound,” which is the largest odds in favor of the alternative hypothesis relative to the null hypothesis that is consistent with the observed data. The Bayes factor bound generally indicates that a given p-value provides weaker evidence against the null hypothesis than typically assumed. We therefore believe that our recommendations can guard against some of the most harmful p-value misinterpretations. In research communities that are deeply attached to reliance on “p?<?0.05,” our recommendations will serve as initial steps away from this attachment. We emphasize that our recommendations are intended merely as initial, temporary steps and that many further steps will need to be taken to reach the ultimate destination: a holistic interpretation of statistical evidence that fully conforms to the principles laid out in the ASA statement on statistical significance and p-values.     

Learning from a lot: Empirical Bayes for high‐dimensional model‐based prediction

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, stored in public repositories. We review applications of a variety of empirical Bayes methods to several well‐known model‐based prediction methods, including penalized regression, linear discriminant analysis, and Bayesian models with sparse or dense priors. We discuss “formal” empirical Bayes methods that maximize the marginal likelihood but also more informal approaches based on other data summaries. We contrast empirical Bayes to cross‐validation and full Bayes and discuss hybrid approaches. To study the relation between the quality of an empirical Bayes estimator and p, the number of variables, we consider a simple empirical Bayes estimator in a linear model setting. We argue that empirical Bayes is particularly useful when the prior contains multiple parameters, which model a priori information on variables termed “co‐data”. In particular, we present two novel examples that allow for co‐data: first, a Bayesian spike‐and‐slab setting that facilitates inclusion of multiple co‐data sources and types and, second, a hybrid empirical Bayes–full Bayes ridge regression approach for estimation of the posterior predictive interval.     

Values and happiness among Asian adolescents: a cross-national study

Despite policy efforts to increase adolescent happiness, their impact has been unsatisfactory. Their limited impact may be rooted from a discrepancy between values that adolescents pursued and those that the policies were based on. To provide policy implications, our study aims to identify prevailing values for South Korean, Japanese, and Chinese adolescents and to examine the relationship between the values and self-rated happiness (SRH). A cross-sectional study was conducted using survey data collected on approximately 2000 middle and high school students (7th to 12th school grade) from each country in 2008. Firstly, an explanatory factor analysis was conducted to identify salient adolescent values from each country. Subsequently, a multiple logistic regression analysis was conducted for each population group to examine the relationship between the identified values and adolescent SRH after controlling for sociodemographic characteristics. We found that benevolence and altruism were positively associated with adolescent SRH in all three population groups. Patriarchy was associated with SRH positively in Chinese yet inversely in Japanese. Success pursuit was inversely associated with SRH in Korean. Policy efforts based on values of communities or social harmony may benefit adolescents’ SRH in these three countries.