An empirical note about estimation and forecasting Latin American Forex returns volatility: the role of long memory and random level shifts components

Portuguese Economic Journal - A set of RLS-type models with ARMA and ARFIMA dynamics is estimated and compared in a forecasting exercise with ARFIMA, GARCH and FIGARCH models. It is an extension of...     

The education pillar of the Europe 2020 strategy: a convergence analysis

Empirica - In March 2010, the European Commission launched the Europe 2020 strategy ‘for smart, sustainable and inclusive growth’ in the EU. Education is a major pillar of the Europe...     

Mapping global sustainability report scoring: a detailed analysis of Europe and Asia

This study maps the General Reporting Initiative (GRI) relations for a set of global enterprises. Enterprise interrelationships are built using the Mutual Information (MI) of the data reported by enterprises. From the MI topology, we describe interrelationships among the enterprises using chord diagrams to represent the inter- and intra-connectivity between geographical regions and economic sectors globally, by continent and country. Detailed maps are presented for European and Asian regions/sectors, including the relationship between Europe and Asia’s top reporting countries. Our findings reinforce previous research regarding the role of Europe as a driver of sustainability and its influence worldwide. We also determined that Spain is a major player in Europe and that Northern Europe does not have the assumed leading role mentioned in related studies. Eastern Asia is, by far, the leader of the region, and the GRI maps demonstrate the preponderant role of China in the region and the minimal role of India. MI topology maps outline the behavior of the economic sectors, for all the studied regions. Furthermore, a measure that relates the inter- to intra-connections is presented to describe the internal an external relationships among regions/sectors.     

Inequality and entrepreneurial thresholds

We explore the relationship between inequality and entrepreneurial activity. Drawing on cross-sectional data from a largescale survey of the economic conditions of individuals across India, we develop a number of dimensions of inequality to explore empirically how inequality interacts with entrepreneurship, operationalized as self-employment or as employing other people. We find compelling evidence that there are thresholds to becoming self-employed, and even more so to assembling the combinations of resources and personal attributes required to become an employer. Greater inequality leaves more people unable to make the transition to self-employment, leaving casual laboring as the occupation of necessity. At the same time, inequality increases the number of employers in a society, by concentrating resources - particularly land and finance - enough for significant numbers of people to be able to cross this higher threshold. Lastly, greater differentiation into social or religious groups curtails the ability to cross either entrepreneurial threshold, presumably by limiting the extent and benefits of social networks of value for entrepreneurship.     

When age does not harm innovative behavior and perceptions of competence: Testing interdepartmental collaboration as a social buffer

Can older managers overcome stereotypes relating age to low competence? We integrate the literature on age and cognitive ability with research on innovation to explore whether—and if so, when—employees' age harms performance and promotability appraisals made by their supervisors. Multisource, time‐lag data from 305 project managers indicate that the negative stereotypes can be explained through decreased innovative behavior. However, older employees are not always seen as poorer performers with less potential to be promoted due to their reduced innovative behavior. Rather, interdepartmental collaboration moderates these effects. Specifically, older employees with low interdepartmental collaboration are less innovative and receive worse performance and promotability appraisals than younger employees, but the “age handicap” vanishes when older employees collaborate with members of other departments. Organizations should foster formal or informal collaboration among units to prevent negative consequences of an aging workforce.     

Productivity Growth: Technological Progress and Technical Efficiency

Atlantic Economic Journal -     

供应链金融智慧化创新的内在机理研究——基于扎根理论的探索性分析

文章基于10个智慧供应链金融案例,对供应链金融中信息通信技术的赋能机制、作用机理及所实现的智慧效应进行了梳理,报告了供应链金融进行智慧化创新的内在逻辑.通过采用扎根理论方法,展开实践案例资料调查,反映了供应链金融业务迫切需要新的技术支撑以解决资金供需双方的信息不对称问题,进而构建出"需求—手段—中介—效应"这一供应链金融创新机理模型,揭示了供应链金融智慧化创新的路径方法.     

Who do you care about? Scientists’ personality traits and perceived impact on beneficiaries

We investigate the roots of scientists' perceptions of the impact of their work by examining stable psychological characteristics such as personality traits. An analysis of personality traits highlights the effects of policies related to gender equality, allocation of research time and skills acquisition. It improves our understanding of the conflicts related to scientists’ perceptions of the impact of their research on beneficiaries. For example, conscientiousness increases the perceived impact on clinical beneficiaries, but reduces the perceived impact on industrial beneficiaries. Organizational scientific freedom increases the effects of personality traits on perceived impact on beneficiaries such that scientists affiliated to a university are less likely than colleagues working in other research settings to perceive the simultaneous impact of their work on both industrial and clinical beneficiaries.     

Coordination in a skeptical two-group population

Journal of Economic Interaction and Coordination - This paper explores a situation in which a population split into two groups attempts to achieve the socially efficient outcome of a coordination...     

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.