团队科学创造力的提升需重视团队成就目标导向——被调节的中介效应

基于创造力成分等多维理论，构建以团队反馈寻求行为为中介变量，团队凝聚力为调节变量的被调节的中介效应模型，以期深入解释创新团队成就目标导向如何影响其团队科学创造力。基于129个理工科大学生科技创新团队数据，研究结果表明，团队学习目标导向和团队表现目标导向分别与团队科学创造力有显著的正向和负向关系；团队反馈寻求行为在团队成就目标导向与团队科学创造力间起部分中介作用；团队凝聚力负向调节团队反馈寻求行为与团队科学创造力间的关系，并弱化了团队成就目标导向通过团队反馈寻求行为对团队科学创造力的间接影响。结论对提高科技创新团队科学创造力有一定指导价值。     

The cross‐cultural study of LMX and individual employee voice: The moderating role of conflict avoidance

This article examines the role of national culture, measured by conflict avoidance, on the relationship between leader–member exchange (LMX) and individual employee voice. Using data collected from automotive industry employees in the United States and Korea, the findings show that conflict avoidance is negatively related to employee voice and also moderates the relationship between LMX and employee voice in the Korean sample. In particular, the relationship between LMX and voice becomes less positive when conflict avoidance is high. On the other hand, conflict avoidance does not have a direct effect on employee voice as well as an interactive effect with LMX on employee voice in the U.S. sample. This study, therefore, highlights the importance of the national culture in the comparative study of employee voice.     

Measuring Inflation Anchoring and Uncertainty: A U.S. and Euro Area Comparison

We use several U.S. and euro‐area surveys of professional forecasters to estimate a dynamic factor model of inflation featuring time‐varying uncertainty. We obtain survey‐consistent distributions of future inflation at any horizon, both in the U.S. and the euro area. Equipped with this model, we propose a novel measure of the anchoring of inflation expectations that accounts for inflation uncertainty. Our results suggest that following the Great Recession, inflation anchoring improved in the United States, while mild de‐anchoring occurred in the euro area. As of our sample end, both areas appear to be almost equally anchored.     

Investor behaviour and reaching for yield: Evidence from the sterling corporate bond market

We provide evidence on how corporate bond investors react to a change in yields, and how this behaviour differs in times of market‐wide stress. We also investigate ‘reaching for yield’ across investor types, as well as providing insights into the structure of the corporate bond market. Using proprietary sterling corporate bond transaction data, we show that insurance companies, hedge funds and asset managers are typically net buyers when corporate bond yields rise. Dealer banks clear the market by being net sellers. However, we find evidence for this behaviour reversing in times of stress for some investors. During the 2013 ‘taper tantrum’, asset managers were net sellers of corporate bonds in response to a sharp rise in yields, potentially amplifying price changes. At the same time, dealer banks were net buyers. Finally, we provide evidence that insurers, hedge funds and asset managers tilt their portfolios towards higher risk bonds, consistent with ‘reaching for yield’ behaviour.     

政府主导模式下地方企业征信体系建设研究

经过多年发展,我国企业征信领域取得了显著成绩,但相较于社会发展,还处于滞后状态,存在企业征信市场整体规模较小,公共征信部门业务简单,企业征信机构面临数据瓶颈,企业征信领域的各种要素受制于资源的条块分割等问题。在企业征信市场的有效性处于缺乏的状态,政府应当有所作为,要打破现有征信框架中制约市场发展的障碍,在政府主导下进行制度设计,搭建企业征信基础数据库,鼓励市场参与数据分享和征信产品开发,建设有中国特色的地方企业征信体系。     

Close relationship with the supervisor may impede employee creativity by suppressing vertical task conflict

Leader‐member exchange as a form of supportive leadership is expected to foster employee creativity. However, empirical evidence suggested this relationship is complex. This study attempts to address this complexity by proposing and testing a curvilinear mechanism, which attenuates the overall positive effect of LMX on creativity by transmitting a curvilinear indirect effect via vertical task conflict. Results drawn from a sample of 276 supervisor–subordinate dyads provided support for the hypothesized curvilinear indirect effect. Specifically, LMX was found to negatively influence employee creativity by suppressing vertical task conflict for subordinates in high‐quality LMX relationships, while the indirect effect was not significant for subordinates in low‐quality LMX relationships.     

State‐Dependent Forward Guidance and the Problem of Inconsistent Announcements

Forward guidance can be provided as an unconditional promise, i.e. commitment to a specific low policy rate. Alternatively, the promise may include an escape clause, i.e. a condition defining the state of the economy under which the central bank would not keep such a low rate and, instead, it would revert to setting policy under discretion. The escape clause can be expressed as a threshold in terms of a specific variable. The present paper shows that, when such a threshold is expressed in terms of an endogenous variable (e.g. output, inflation), there are cases where it becomes impossible for the central bank to act in a way that is consistent with its promise. Consistency imposes limits on the policy rate that can be set since reverting immediately to the optimal discretionary rate can be incompatible with exceeding the threshold.     

Time series copulas for heteroskedastic data

We propose parametric copulas that capture serial dependence in stationary heteroskedastic time series. We suggest copulas for first‐order Markov series, and then extend them to higher orders and multivariate series. We derive the copula of a volatility proxy, based on which we propose new measures of volatility dependence, including co‐movement and spillover in multivariate series. In general, these depend upon the marginal distributions of the series. Using exchange rate returns, we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models, and produce more accurate value‐at‐risk forecasts.     

Building relationship innovation in global collaborative partnerships: big data analytics and traditional organizational powers

This study examines how relationship innovation can be developed in global collaborative partnerships (alliances, joint ventures, mergers, and acquisitions). The recently emerging theory of big data analytics linked with traditional organizational powers has attracted a growing interest, but surprisingly little research has been devoted to this important and complex topic. Therefore, after developing the theoretical foundations, our study empirically quantifies the links between the theoretical constructs based on the data collected from chief executive officers, managing directors, and heads of departments who work in contemporary global data‐and‐information driven collaborative partnerships. The results from structural equation modeling indicate that the relationship innovation depends on the power of big data analytics and non‐mediated powers (NMP, expert and referent). The power of big data analytics also mediates the correlation between NMP and relationship innovation. However, mediated powers (coercive and manipulative) negatively affect the power of big data analytics and relationship innovation. The interaction effects further depict that analytically powered partnerships have better relationship innovation compared with those which focus less on the analytical power. Consequently, the contributions of this study provide a deeper understanding of mechanisms of how modern collaborative partnerships can use big data analytics and traditional organizational powers to co‐create relationship innovation.     

EMPIRICAL PERFORMANCE OF GARCH MODELS WITH HEAVY‐TAILED INNOVATIONS

We introduce a new type of heavy‐tailed distribution, the normal reciprocal inverse Gaussian distribution (NRIG), to the GARCH and Glosten‐Jagannathan‐Runkle (1993) GARCH models, and compare its empirical performance with two other popular types of heavy‐tailed distribution, the Student's t distribution and the normal inverse Gaussian distribution (NIG), using a variety of asset return series. Our results illustrate that there is no overwhelmingly dominant distribution in fitting the data under the GARCH framework, although the NRIG distribution performs slightly better than the other two types of distribution. For market indexes series, it is important to introduce both GJR‐terms and the NRIG distribution to improve the models’ performance, but it is ambiguous for individual stock prices series. Our results also show the GJR‐GARCH NRIG model has practical advantages in quantitative risk management. Finally, the convergence of numerical solutions in maximum‐likelihood estimation of GARCH and GJR‐GARCH models with the three types of heavy‐tailed distribution is investigated.