Estimating yield curves of the U.S. Treasury securities: An interpolation approach

Following the approach of interpolation, this paper proposes the multiple exponential decay model to fit yield curves for both the U.S. TIPS market and the conventional Treasury security market. Several estimation methods, including the unconstrained/constrained nonlinear minimization, quadratic programming, and the iterative linear least squares, are applied to estimate the unknown parameters according to different curve‐fitting purposes. Comparisons between the proposed model and the alternatives show that the multiple exponential decay successfully (1) adapts to a variety of shapes associated with yield curves, (2) (partially) keeps in line with the economic interpretations of Nelson–Siegel summarized by Diebold and Li ( 2006 ), and (3) dominates the competing models in curve‐fitting performance measured by mean fitted‐price errors over the sample period. In addition, the exact specification of a nonparametric interpolation model is pinned down by applying three statistical tools, which enable us to jointly take into account validity, optimality, and parsimoniousness of the proposed model.     

Economic Impacts of the Possible China–US Trade War

This article uses a multi-country global general equilibrium (GE) model to numerically simulate the effects of possible China–US trade wars. We introduce an endogenous trade imbalance structure with trade cost into the model which helps to explore both tariff and non-tariff trade war effects. Our simulation results show that China will be significantly hurt by the China–US trade war, but negative impacts are affordable. The US can gain under unilateral sanction measures to China, but will lose if China takes retaliation measures. Comparing the effects under mutual trade war, China will lose more than the US. Introducing non-tariff barrier trade wars will intensify the negative effects, and comparatively negative effects to China are larger than to the US. Mexico’s involvement in trade war with the US will strengthen the negative effects and comparatively hurt the US more. Under non-cooperative and cooperative Nash bargaining equilibrium, the US can gain more than China in trade war negotiation, which means the US has stronger bargaining power than China. Additionally, trade wars between China and the US will hurt most countries and the world especially in GDP and manufacturing employment, but benefit their welfare and trade.     

Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific

In this paper, we focus on the question to what extent machine learning (ML) tools can be used to support systematic literature reviews. We apply a ML approach for topic detection to analyze emerging topics in the literature—our context is accounting and finance research in the Asia–Pacific region. To evaluate the robustness of the approach, we compare findings from the automated ML approach with the results from a manual analysis of the literature. The automated approach uses a keyword algorithm detection mechanism whereby the manual analysis uses common techniques for qualitative data analysis, that is, triangulation between researchers (expert judgement). From our paper, we conclude that both methods have strengths and weaknesses. The automated analysis works well for large corpora of text and provides a very standardized and non-biased way of analyzing the literature. However, the human researcher is potentially better equipped to evaluate current issues and future trends in the literature. Overall, the best results might be achieved when a variety of tools are used together.     

延迟退休年龄下隔代抚育与劳动参与的抉择*——基于工资收入随机性假定的研究

隔代抚育会对延迟退休年龄政策在促进劳动力供给上产生挤出效应。为了对此进行验证，本文在工资收入随机性的假定及延迟退休5年的情景下，模拟了面临孙辈照护需求的女性临近退休者提前退休所产生的福利变化。进一步，本文采用CHIP和CHARLS的微观调查数据，对不同群组的收入增长率和收入风险进行了估计，继而分析了当面临孙辈照护需求时这些收入特征对退休决策者制度退休和退休后劳动参与抉择产生的影响。总体上，在延迟退休年龄政策下，隔代抚育将对女性劳动力供给产生挤出效应。当面临孙辈照护需求时，女性临近退休者的制度退休抉择主要受自身收入增长率和收入风险的影响，收入增长率越低，或收入风险越高，她们提前退休的意愿就越强烈；制度退休后的劳动参与则更多地受子女收入增长率的影响，子女收入增长率越高，劳动参与的概率越低。     

Interventions in Markets with Adverse Selection: Implications for Discount Window Stigma

I study the implications for central bank discount window stigma of a workhorse model of adverse selection in financial markets. In the model, firms (banks) need to borrow to finance a productive project. There is limited liability and firms have private information about their ability to repay their debts, which gives rise to the possibility of adverse selection. The central bank can ameliorate the impact of adverse selection by lending to firms. Discount window borrowing is observable and it may be taken as a signal of firms' credit worthiness. Under some conditions, firms borrowing from the discount window may pay higher interest rates to borrow in the market, a phenomenon often associated with the presence of stigma. I discuss these and other outcomes in detail and what they suggest about the relevance of stigma as an empirical phenomenon.     

高科技社会我国风险沟通重塑

高科技社会衍生“人为风险”，西方发达高科技国家倡导新型风险沟通，而后发场域由于系统落差，呈现出迟滞型风险沟通。通过构建全球化高科技风险社会、全球本地化风险沟通的新分析框架，发现高科技社会我国风险沟通面临着风险的社会放大、气泡结构、路径互动阙如、手段叠加、目标战略缺失、过程碎片化等迟滞困境。通过创新理念、吸纳型风险沟通、复合式路径、平衡化手段、连续统、政府学习和政府职能的“七位一体”再造，可有效重塑高科技社会我国风险沟通，推进国家风险治理体系和治理能力现代化。     

Larger,counter-intuitive and lasting – The PSM role in responding to the COVID-19 pandemic,exploring opportunities for theoretical and actionable advances

PSM has played an important role in the initial mitigation of risks caused by the COVID-19 pandemic. We explore the nature and scope of this role and develop a roadmap for PSM contributions towards greater supply chain resilience. We find that the role of PSM is (1) multidimensional; responding to supply risks but also to demand and logistics risks, (2) counter to game theory; collaboration increased instead of decrease, (3) multi-stage; beyond the initial response the hardest change efforts are still ahead. The pandemic is accelerating the journey towards future-proof PSM but not necessarily revolutionizing the future of PSM.     

Do ongoing networks block out new friends? Reconciling the embeddedness constraint dilemma on new alliance partner addition

Research Summary: This study addresses a theoretical dilemma regarding how alliance network constraint (reflected by network cohesion) affects a firm’s alliance formation with new partners. Using a network pluralism approach, we separate a firm’s ego alliance network into two activity‐based networks—an exploratory network and an exploitative network—based on the primary value chain activity involved in each alliance. We argue that the cohesion of exploratory or exploitative networks has an inverted U‐shaped effect on the addition of new partners in the same activity‐based network, and a positive effect on the addition of new partners in the other network. Results based on data from the biotechnology industry largely support our predictions with one exception. Our study contributes to both scholarly understanding of network embeddedness and alliance practice. Managerial Summary: The structure of firms’ ongoing alliance networks may have paradoxical implications for their efforts to search for and form alliance with new partners. That is, when a firm’s alliance partners are tightly connected with each other, the cohesive network tends to both encourage and impede the focal firm to add new partners. We resolve this dilemma by showing that when a firm is deeply entrenched in a cohesive alliance network conducting a certain type of activities (e.g., R&D activities), it may not easily add new R&D alliance partners. However, it may still be able to escape from the cohesive R&D alliance network by seeking new partners conducting other activities (e.g., manufacturing activities).     

Financial development,economic growth and convergence clubs

To study the role of financial development in economic growth, we apply an array of convergence tests designed to capture nonlinear transitional dynamics to real outputs per capita. Strong evidence of multiple convergence clubs is observed, implying that the clubs are formed based on the initial level of real output per capita and average growth rate. Our empirical results show that the stage of economic growth of each country plays an important role for the composition of the convergence clubs. Furthermore, financial development emerges to be a significant determinant, albeit plays differently in the economic growth of each convergence club.     

颠覆性技术识别与预测方法研究进展

为了把握颠覆性技术识别与预测方法研究进展，首先对颠覆性的内涵、特征和运行机制进行论述；然后，通过对已有文献进行系统梳理，将识别与预测方法分为5类，分别展开详述；最后，对各类方法进行比较分析。研究发现，已有颠覆性技术识别与预测方法仍处于发展的初期阶段，所有识别研究方法均围绕颠覆性技术的外部影响或内在特征中的某一方面展开，并未将二者有机结合起来。未来，应综合把握颠覆性技术内外部特征，构建全面、系统的识别与预测框架。