High-frequency credit spread information and macroeconomic forecast revision

We examine whether professional forecasters incorporate high-frequency information about credit conditions when revising their economic forecasts. Using a mixed data sampling regression approach, we find that daily credit spreads have significant predictive ability for monthly forecast revisions of output growth, at both the aggregate and individual forecast levels. The relationships are shown to be notably strong during ‘bad’ economic conditions, which suggests that forecasters anticipate more pronounced effects of credit tightening during economic downturns, indicating an amplification effect of financial developments on macroeconomic aggregates. The forecasts do not incorporate all financial information received in equal measures, implying the presence of information rigidities in the incorporation of credit spread information.     

Probabilistic wind forecasting up to three months ahead using ensemble predictions for geopotential height

We develop a method for forecasting the distribution of the daily surface wind speed at timescales from 15-days to 3-months in France. On such long-term timescales, ensemble predictions of the surface wind speed have poor performance, however, the wind speed distribution may be related to the large-scale circulation of the atmosphere, for which the ensemble forecasts have better skill. The information from the large-scale circulation, represented by the 500 hPa geopotential height, is summarized into a single index by first running a PCA and then a polynomial regression. We estimate, over 20 years of daily data, the conditional probability density of the wind speed at a specific location given the index. We then use the ECMWF seasonal forecast ensemble to predict the index for horizons from 15-days to 3-months. These predictions are plugged into the conditional density to obtain a distributional forecast of surface wind. These probabilistic forecasts remain sharper than the climatology up to 1-month forecast horizon. Using a statistical postprocessing method to recalibrate the ensemble leads to further improvement of our probabilistic forecast, which then remains calibrated and sharper than the climatology up to 3-months horizon, particularly in the north of France in winter and fall.     

The effects of slack resource of R&D professionals on firm performance: evidence from traditional manufacturing firms in an emerging economy

Abstract

As an important component of organizational human resource slack (HR slack), the slack of research-and-development (R&D) professionals has been studied by several authors. However, it remains unclear whether and how this small component of general HR slack, i.e. the slack of research-and-development professionals (RHR slack), may affect overall firm performance in an emerging economy without much R&D tradition or pro-R&D institutions. Based on two organizational theories, i.e. institutional theory and the resource-based view of the firm (RBV), we propose competing hypotheses on the relationship between RHR slack and firms’ accounting performance. We also examine whether the relationship between RHR slack and firm performance should be linear or curvilinear. Finally, we also test the relationship between RHR slack and other dimensions of firm performance. Several interesting findings have been obtained. For instance, neither the perspective based on institutional theory nor that based on RBV can fully predict all types of RHR slack-performance relationships, be these relationships linear or curvilinear.     

Can environmentally oriented CEOs and environmentally friendly suppliers boost the growth of small firms?

The core question addressed in the natural resource‐based view (NRBV) of the firm is how to develop and exploit resources beneficial for both the natural environment and firm performance. Due to the resource constraints and increased competition facing small manufacturing firms, achieving this is a challenge for such companies. Building on the NRBV and resource orchestration literatures, we examine the relationship between green purchasing capabilities (GPCs), CEO's environmental orientation (EO), and firm growth. Results from 304 Swedish small manufacturing firms indicate a significant relationship between GPC and growth, and this relationship is positively moderated by the EO of the CEO.     

医疗卫生资源、新型冠状病毒肺炎死亡率与资源优化配置

新冠肺炎疫情发生后，湖北省一直是疫情的重灾区与抗疫的焦点地区，患者死亡率远远高于全国平均水平。本文构建纳入医疗资源条件的新冠肺炎传播的SIER模型进行机制分析和模拟研究，发现改善卫生资源条件会降低疫情的死亡率。针对湖北省疫情数据，使用最小二乘方法进行实证研究后发现,无论是增加医院或者卫生系统内的床位数，还是增加医护人员数，均可显著地降低疫情死亡率。进一步通过时变效应和断点回归模型考察重大突发公共卫生事件一级响应政策效应和外援医疗团队效应，实证结果也佐证了上述推断。结合研究结论和湖北省防疫经验，本文提出先整合医院内部医疗资源，打破医院内部各科室之间分割，再整合地区内医疗卫生系统的资源，同时实施医疗系统外部资源三管齐下的医疗资源配置建议措施，以期为国内外疫情防控贡献中国智慧。     

技术购买与资源协奏式创新 ——基于技术吸收与整合互补性的联合中介视角

基于资源协奏理论，本文将外部技术购买、技术吸收和技术整合纳入同一框架，运用2005—2014年中关村国家高技术企业的面板回归和Tobit回归分析，研究技术购买影响创新的资源协奏机制。研究发现：技术吸收与技术整合在技术购买的创新实现中具有互补性，且二者基于互补性发挥联合中介作用，实现技术购买企业的资源协奏式创新。本文基于资源协奏框架探讨外部技术投入战略的创新效果实现机制，为技术购买实现创新机制的研究引入新视角，深化开放式创新理论和资源协奏理论。     

金融科技能影响金融分权吗? ——来自金融科技信贷的证据

金融科技正在变革全球金融体系、鼎新世界金融格局。那么，金融科技在改变中国金融业格局的同时，是否会影响中国中央和地方之间的金融分权呢？本文在理论分析的基础上，使用2010—2018年中国31个省级区域的面板数据进行实证检验，结果表明金融科技降低了地方政府的金融分权水平。进一步讨论发现：金融科技对金融分权的抑制效应受到财政分权和城镇化率影响，财政分权越大的地区，金融科技对金融分权的抑制效应越明显；城镇化率越高的地区，金融科技对金融分权的抑制效应越小；在中国区域经济发展不平衡的现实背景下，金融科技对金融分权的抑制作用在金融发展欠发达地区比在较发达地区更强。     

黑龙江省农业旅游资源分布及其价值分析

[目的]对黑龙江省农业旅游资源分布及其价值进行分析和评价,以期为黑龙江省农业旅游的可持续发展提供参考和借鉴。[方法]文章对黑龙江省农业旅游资源进行分类型论述,采用层次分析法(AHP)建立黑龙江省农业旅游资源价值评价体系,根据农业旅游经营者和管理者对指标的打分值与指标权重值加权计算各类型农业资源价值指数并分析资源价值。[结果](1)根据农业资源分布、地理环境、气候天象、人文特色,将黑龙江省农业旅游资源划分为地文农业旅游区、水文农业旅游区、气候天象农业旅游区、生物生态农业旅游区、人文农业旅游区5个区域,各区域各有特色,差异性明显。(2)根据各区域资源价值指数分析看出,气候天象农业旅游区的资源价值最大,其次是地文农业旅游区,然后是水文农业旅游区和生物生态农业旅游区,人文农业旅游区的资源价值最小。[结论]黑龙江省农业旅游资源非常丰富,能够形成一个相对完整的农业旅游资源体系,具有较强的可持续发展潜力。在黑龙江省农业旅游的五大发展区域中,气候天象农业旅游区和地文农业旅游区的旅游资源价值较大。黑龙江省可以持续开发建设这一类农业旅游项目,并根据季节性与地理环境特征着力打造冰雪农业旅游。     

Payday loans and consumer financial health

The annualized interest rate for a payday loan often exceeds 10 times that of a typical credit card, yet this market grew immensely in the 1990s and 2000s, elevating concerns about the risk payday loans pose to consumers and whether payday lenders target minority neighborhoods. This paper employs individual credit record data, and Census data on payday lender store locations, to assess these concerns. Taking advantage of several state law changes since 2006 and, following previous work, within-state-year differences in access arising from proximity to states that allow payday loans, I find little to no effect of payday loans on credit scores, new delinquencies, or the likelihood of overdrawing credit lines. The analysis also indicates that neighborhood racial composition has little influence on payday lender store locations conditional on income, wealth and demographic characteristics.     

The ties that bind: Bank relationships and small business lending

The importance of bank relationships for small firms’ ability to raise external finance is well-documented, yet the mechanism through which relationships improve access to capital markets has received little empirical attention. This paper uses hand-collected, proprietary data from a mid-sized bank in the United States to identify the channels that strengthen the relationship between a small business and its bank. In contrast to earlier work that focuses on the role of relationships in alleviating information and incentive problems in lending, I find that the source of value in relationship banking is not limited to enhanced monitoring. Exploiting a unique feature of this dataset, I examine two channels of relationship strength that directly measure the stream of non-lending profits generated from (1) the non-credit services cross-sold to the borrower, and (2) the additional bank clients referred by the borrower. I document that non-lending profitability empirically determines the risk-adjusted terms of lending. In models of loan price that already include both the bank’s proprietary risk rating and traditional risk proxies, non-lending profits significantly improve explanatory power and account for up to half of the total explained variation. Conditional on risk profile, a one-standard deviation increase in aggregate non-lending profits lowers the loan interest rate by 32 basis points and increases access to credit by 26%.