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.     

岩土工程中边坡加固工程施工技术探究

在社会经济稳定发展的推动下,建筑行业的发展较为迅速,而且高层建筑的数量越来越多,提高人们的生活质量.但由于建筑工程建设过程中受负载地质条件影响,导致岩土工程边坡施工面临多种困难,尤其是边坡的稳定性问题,一旦无法保障其质量,将会影响整体工程的建设,甚至会为工程埋下隐患.因此,为了能够有效解决这一问题,本文就岩土工程中边坡加固工程施工技术进行详细探究.     

基于Python平台通过单因子指标法进行地下水质量评价

水质评价关系到水质质量,常见的评价方法有层次分析法、综合评价法等,这些方法评价过程非常复杂,单因子评价方法相比具有操作容易.实际中单因子进行评价时存在概念理解难、计算容易出错等问题.为解决单因子计算问题,本文提出采用Python编程语言进行单因子评价.本文详细分析了Python进行单因子评价流程,从数据采集、数据清洗、数据处理、系统实现进行分析.应用结果表明基于Python编程的单因子评价方法具有评价效率高、准确度高优点.     

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.