论民营银行成长的逻辑——一个基于国家效用函数的分析框架

中国金融制度变迁具有政府强制性与渐进式等特征,因此从国家金融方面的效用函数结构变动的视角来探究中国民营银行的成长逻辑,无疑是关键和有益的。运用规则经济学中的国家理论与制度变迁原理,在已有研究的基础上构建一个国家效用函数,并从此效用函数的动态变化,论证中国民营银行成长的内在动机与逻辑。     

创新环境约束下高技术产业区域创新效率及收敛性研究

以各地区高技术产业为样本,应用超越对数随机前沿模型实证测算了创新环境约束下各地高技术产业基础研发和成果转化创新效率,并基于σ收敛、β收敛以及俱乐部收敛3种判别方法,考察了高技术产业基础研发效率和成果转化效率的收敛性特征。研究发现,2000-2014年我国创新环境对区域高技术产业的影响不可小觑,在其约束下高技术产业基础研发效率不断提升,呈现出东西较高、中北较低的分布态势且出现收敛特征;在应用效率方面,各地区成果转化效率大致划分为2000-2007年的缓慢增长期与2008-2014年的缓慢衰退期两个阶段,具有东高西低、南高北低的分布态势且趋于发散。     

内外部知识源化、非研发对创新绩效影响的空间计量研究

封闭式创新向开放式创新转型过程中,正确选择技术创新路径对创新转型至关重要。在考察高技术产业开展内、外部知识源化和非研发创新路径发展特征的基础上,运用空间计量经济学方法,探讨2008-2014年高技术产业内外部知识源化、非研发和创新绩效的空间相关性及分布结构,并将地理空间因素纳入多种创新路径驱动创新绩效机理框架下进行比较分析,实证考察其对创新绩效的影响机理。结果表明,高技术产业外部知识源化与非研发投入所占比重远远小于内部知识源化,技术创新路径非均衡性发展特点显著;高技术产业内外部知识源化、非研发与创新绩效存在较为显著的空间自相关性,内外部知识源化、非研发与创新绩效一定程度上呈现为相似值在空间上趋于集聚的分化态势,相邻地区空间溢出效应显著;高技术产业外部知识源化对创新绩效起到显著正向促进作用,而现阶段内部知识源化和非研发规模对创新绩效分别呈现微弱的正向和负向影响,没有充分发挥促进效应。     

中国高技术产业转移趋势时空分析

基于脱钩理论研究方法,借鉴其他学者构建的产业动态脱钩指数和区域产业集聚与扩散判定条件,对1995-2015年中国高技术产业在东部、中部、西部和东北四大区域的转移趋势进行实证研究。结果表明,1995-2015年中国高技术产业在四大区域间存在明显的产业集聚和产业扩散现象。其中,1995-2004年向东部地区集聚趋势明显;2005-2015年则由东部地区向外扩散,不断向中部和西部地区集聚趋势明显。可见,2004年是中国高技术产业集聚与扩散的分水岭。自2013年始,我国东北地区高技术产业进入衰退期,部分行业出现向外绝对扩散趋势。     

国家高新区创新能力对城市全要生产率的影响及中介效应

利用2007-2019年国家高新区及中国城市数据，实证考察了“成熟型”和“成长型”高新区创新能力对城市全要素生产率的影响。研究发现：总体上，高新区创新能力的提高有助于城市TFP增长，“成熟型”高新区创新能力对城市TFP存在抑制作用，“成长型”高新区创新能力对城市TFP有显著促进作用。中介效应检验表明：“成熟型”国家高新区创新能力通过促进城市产业结构升级对城市TFP的影响产生了遮掩效应；“成长型”高新区创新能力通过增强城市劳动力素质促进城市TFP增长。异质性检验显示：东部地区“成熟型”高新区创新能力对城市TFP有显著负面影响，而中西部地区“成熟型”创新能力能显著促进城市TFP提升。不同政府规模城市的高新区创新能力对城市TFP亦有不同影响。     

Harmonizing regulatory regimes for the governance of patient-generated health data

Patient-generated health data (PGHD), created and captured from patients via wearable devices and mobile apps, are proliferating outside of clinical settings. Examples include sleep trackers, fitness trackers, continuous glucose monitors, and RFID-enabled implants, with many additional biometric or health surveillance applications in development or envisioned. These data are included in growing stockpiles of personal health data (PHI) being mined for insight by health economists, policy analysts, researchers, and health system organizations. Dominant narratives position these highly personal data as valuable resources to transform healthcare, stimulate innovation in medical research, and engage individuals in their health and healthcare. Large tech companies are also increasingly implicated in these areas, through mobile health application sales and data acquisitions. Given the many possible uses and users for PGHD, ensuring privacy, security, and equity of benefits from PGHD will be challenging. This is due in part to disparate regulatory policies and practices across technology firms, health system organizations, and health researchers. Rapid developments with PGHD technologies and the lack of harmonization between regulatory regimes may render existing safeguards to preserve patient privacy and control over their PGHD ineffective, while also failing to guide PGHD-related innovation in socially desirable directions. Using a policy regime lens to explore these challenges, we examine three existing data protection regimes relevant to PGHD in the United States that are currently in tension with one another: federal and state health-sector laws, regulations on data use and reuse for research and innovation, and industry self-regulation of consumer privacy by large tech companies. We argue that harmonization of these regimes is necessary to meet the challenges of PGHD data governance. We next examine emerging governing instruments, identifying three types of structures (organizational, regulatory, technological/algorithmic), which synergistically could help enact needed regulatory oversight while limiting the friction and economic costs of regulation that may hinder innovation. This policy analysis provides a starting point for further discussions and negotiations among stakeholders and regulators to do so.