War and economy. Rediscovering the eighteenth-century military entrepreneur

Abstract

The detrimental effects traditionally assigned to warfare in the development of pre-industrial economies have obscured the prominent role that military entrepreneurs played in economic development in this period. Historiography minimises the extent to which war and the concomitant strengthening of the central state provided a whole new range of opportunities for capital investment, a tendency that has been strengthened by the paradigm of Redlich’s ‘decline of the soldier-entrepreneur’ and the technological determinism of the debate on the Military Revolution among others. The aim of this introduction is to look into the background of this relative lack of interest and to reaffirm the mutual dependence of eighteenth-century state-formation and the business of war.     

A cost-effectiveness analysis of revaccination and catch-up strategies with the 23-valent pneumococcal polysaccharide vaccine (PPV23) in older adults in Japan

Objective: In Japan, the National Immunization Program (NIP) includes PPV23 as the primary vaccination for adults and catch-up cohorts. The Japanese Association for Infectious Diseases recommends revaccination for older adults who received primary vaccination ≥5 years earlier. The cost-effectiveness of adding revaccination and/or continuing catch-up vaccination in the NIP was evaluated from the public payer perspective in Japan.

Methods: The Markov model included five health states: no pneumococcal disease, invasive pneumococcal diseases (IPD), non-bacteremic pneumococcal pneumonia (NBPP), post-meningitis sequelae, and death. Cohorts of adults aged 65–95 were followed until age 100 or death: 2014 cohort (aged 65–95, vaccinated: 2014); 2019 cohort (aged 65: 2019); and 2019 catch-up cohort (aged 70–100: 2019, unvaccinated: 2014). Strategies included: (1) vaccinate 2014 and 2019 cohorts; (2) vaccinate 2014 and 2019 cohorts and revaccinate both; (3) strategy 1 and vaccinate 2019 catch-up cohort; (4) strategy 2 and vaccinate 2019 catch-up cohort; and (5) strategy 4 and revaccinate 2019 catch-up cohort. Parameters were retrieved from global and Japanese sources, costs and QALYs discounted at 2%, and incremental cost-effectiveness ratios (ICERs) estimated.

Results: Strategy 1 had the highest number of IPD and NBPP cases, and strategy 5 the lowest. Strategies 3–5 dominated strategy 1 and strategy 2 was cost-effective compared to strategy 1 (ICER: ¥1,622,153 per QALY gained). At a willingness-to-pay threshold of ¥5 million per QALY gained, strategy 2 was cost-effective and strategies 3–5 were cost-saving compared to strategy 1.

Conclusions: Strategies including revaccination, catch-up, or both were cost-effective or cost-saving in comparison to no revaccination and no catch-up. Results can inform future vaccine policies and programs in Japan.     

中国高端装备制造业自主技术创新效率稳定性及影响因素研究

在全面实施创新驱动发展战略的时代背景下，揭示中国高端装备制造业自主技术创新效率稳定性，测度相关因素的影响强度与方向，对揭示中国高端装备制造业自主技术创新规律，制定其发展策略具有重要指导意义。聚焦中国高端装备制造业自主技术创新效率稳定性及影响因素，采用DEA-Malmquist指数方法和Tobit回归模型进行实证研究，结果表明，中国高端装备制造业自主技术创新效率存在一定波动性，且各细分行业技术创新效率内部稳定性较差，产业自主技术创新效率整体稳定性不高；自主技术创新投入因素和环境影响因素对产业自主技术创新效率的影响具有较高的异质性，其中创新资金投入和人力资源投入对自主技术创新综合效率、纯技术效率及规模效率具有正向影响，而新产品开发投入和企业规模对自主技术创新综合效率、纯技术效率和规模效率的影响具有异质性，政策因素与市场因素分别具有显著和非显著负向影响，外源性创新因素具有显著正向影响，且影响强度较大。在此基础上，提出调整政府对高端装备制造业创新支持模式、加强外源性创新与智力引进等策略建议。     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

珠三角工业设计与工业互动比较研究：双重需求拉动与设计驱动增长的区域验证

动态比较珠三角工业发展阶段和设计水平不同的典型区域内，工业用户和最终消费者用户双重需求拉动设计创新以及设计驱动工业增长作用机制的异同，提出克服互动系统短板并因地制宜实施设计驱动转型升级的对策建议。基于SVAR建模的脉冲响应和方差分解分析发现：珠三角工业确实可以通过工业设计创新驱动实现内生性可持续增长，而设计水平的地区差异对设计驱动绩效有调节作用；工业发展质量和结构欠佳，无法有效拉动区域工业设计创新，是珠三角多数地区工业设计有效需求不足的根本原因。区域工业设计与工业互动系统的短板是缺乏内行和挑剔的最终消费者有效需求。最后基于模型稳健性检验，提出因地制宜科学实施设计驱动发展战略的对策建议。     

Foreign inflows and economic growth: An emiprical study of the SAARC region

The study examines and highlights the impact of selected foreign inflows (aid, trade, FDI, debt and remittances) on the economic growth of the South Asian Association for Regional Cooperation (SAARC) countries. The existent literature lacks a comprehensive analysis of the SAARC countries as countries like Afghanistan, Bhutan and the Maldives have largely been ignored due to the shorter time periods of available data. The study is empirical in nature and utilizes panel data techniques on macroeconomic data for the period 2008–2015. Foreign aid and foreign direct investment are found to impact economic growth positively. Foreign debt and trade flows are found to adversely affect economic growth. No relationship is established between the flow of remittances and the economic growth of these countries. The obtained results are robust to different proxy variables and the addition of macroeconomic variables. For the first time, the study provides policy implications based on the data of all SAARC countries. The study recommends focusing on increasing the inflows of resources in the form of aid and foreign direct investment (FDI) from the developed world to achieve higher economic growth.     

Effects of individual resources and team-member exchange on service quality

While workplace resources are generally viewed as positively affecting performance, some studies indicate that not all resources increase performance. This study addresses the controversial disparate effects of workplace resources on performance by exploring functionally classified workplace resources in self-managing service teams and their relative impacts on team service quality. Considering membership dynamics and consequences between members, a field experiment was conducted in a cafeteria, with data collected through a working diary for workplace resources and a customer survey to evaluate service quality. Results suggest that efficacy-resources in self-managing teams should be controlled with caution as they may adversely affect team service quality. Supporting the person–situation interactionism perspective, workplace resources interact dynamically with individual employees and with situations. Esteem-resources were found to increase team service quality, while team-member exchange not only improved team service quality but also moderated the impact of esteem-resources on team service quality.     

Non-linear Gaussian sovereign CDS pricing models

Prior literature indicates that quadratic models and the Black–Karasinski model are very promising for CDS pricing. This paper extends these models and the Black [J. Finance 1995, 50, 1371–1376] model for pricing sovereign CDS’s. For all 10 sovereigns in the sample quadratic models best fit CDS spreads in-sample, and a four factor quadratic model can account for the joint effects on CDS spreads of default risk, default loss risk and liquidity risk with no restriction to factors correlation. Liquidity risk appears to affect sovereign CDS spreads. However, quadratic models tend to over-fit some CDS maturities at the expense of other maturities, while the BK model is particularly immune from this tendency. The Black model seems preferable because its out-of-sample performance in the time series dimension is the best.     

The impact of influencers' multi-SNS use on followers’ behavioral intentions: An integration of cue consistency theory and social identity theory

The considerable marketing potential brought by the rapid growth of social media has been extensively examined in the literature, particularly in terms of the impact of influencers' recommendations on their followers' decisions. However, little attention has been given to how the individual influencers' use of multiple social networking sites affects their followers' behavioral intentions. Hence, this academic gap warrants further exploration. Drawing on cue consistency theory, social identity theory, and stimulus-organism-response framework, this research proposes three research questions and constructs an integrated research model to explore how the influencers' cue consistency affects the social identification of their followers, subsequently influencing their behavioral intentions. A structural equation modeling technique is performed to analyze the data of 510 valid respondents. The findings show that influencers' consistent cues (i.e., information and image consistency) across social media have positive impacts on followers' cognitive and affective identification toward the influencers. Furthermore, the determinants for followers' purchase intention and electronic word-of-mouth intention are affirmed to serve as both cognitive and affective identification. Especially, the results indicate that the relationships between followers’ social identifications and behavioral intentions are moderated by the type of influencer (i.e., lifestyle vs. review). Accordingly, the results indicate how the use of multiple social networking sites by influencers impacts the behavioral intentions of their followers. The findings offer new insights into influencer marketing and provide important lessons for marketers.     

INTERNATIONAL RESERVE MANAGEMENT: A DRIFT‐SWITCHING REFLECTED JUMP‐DIFFUSION MODEL

We study the cost of shocks, that is, jump risk, with respect to reserve management when the reserve process is formulated as a drift‐switching jump diffusion with a reflecting barrier at 0. Inspired by the Brownian drift switching model, our model results in a more realistic dynamic behavior of international reserves than the buffer stock model. The new model can capture both the jump behavior in reserve dynamics and the leptokurtic feature of the increment distribution which has a higher peak and two asymmetric heavier tails than the normal distribution. Through the selection of an initial distribution that reflects certain steady state behaviors, the reserve process becomes a regenerative process. This selection enables us to derive a closed‐form expression for the total expected discounted cost of managing reserves, thus helping us to numerically find management strategies that minimize costs. The numerical results show that shocks at the reserve level have a significant effect on reserve management strategies and that model misspecification can result in nonnegligible additional costs.