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...     

A comprehensive conceptual and bibliometric study of person-centered methodologies

Person-centered approaches, such as latent profile analysis (LPA) and qualitative comparative analysis (QCA), have gained in popularity in organizational scholarship because of their ability to provide insight into how interrelations between a group of conditions can lead to a particular outcome. Despite the growing acceptance of person-centered approaches in social science research, traditional variable-centered approaches continue to prevail, although their dominance is increasingly questioned. This paper offers in-depth analysis of the current state of QCA and LPA from both a conceptual and a bibliometric perspective. This study thus aims to contextualize the role of person-centered methodologies in organizational scholarship. This aim is important, given the significance of exploring novel approaches to advance knowledge in organizational research. This paper provides scholars with quantifiable and readily comparable information on the use of these emerging but promising methods in organizational studies. Ultimately, this scientific contribution sheds light on the current and prospective applications of person-centered methods in research. Moreover, it offers scholars who are considering applying these methods objective analysis of the scientific production in this area thus far.

     

The Limitations of International Relations Regarding MNCs and the Digital Economy: Evidence from Brazil

ABSTRACT

Multinationals (MNCs) have been considered a relevant research topic for International Relations since the emergence of the field of International Political Economy in the 1970s. Nowadays, MNCs are undergoing deep changes in their business models and global strategies due to the digital economy. This has considerable implications for the international system. For instance, the rise of information and communication technology (ICT) MNCs to the top of market value lists globally. Nonetheless, IR scholars have been slow in grasping the importance of ICT MNCs and the digital economy. In this paper, I justify this statement by evaluating the inclusion of MNCs and ICT MNCs in Brazilian IR scholarship. The method used is a bibliometric mapping of the scientific production of Brazilian IR scholars, supported by a systematic literature review. The results showcase that, in spite of the impact of digitalization on Brazil's economy and politics, IR scholars have conducted few studies on MNCs and practically no studies on ICT MNCs. This case illustrates the emergence of new dynamics in global value chains triggered by digitalization. It also illustrates the challenges for developing countries such as Brazil to engage in global production networks within the highly competitive ICT sector.     

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.     

Family firm’s management composition: the role played by family members’ age in TMT and supervisor levels

Quality & Quantity - Family firms (FFs) are the backbone of entrepreneurial fabric in many countries. Management of such businesses is complex because of their features: the overlap between...     

Determinants of bank’s interest margin in the aftermath of the crisis: the effect of interest rates and the yield curve slope

Empirical Economics - This paper analyses the determinants of net interest margin, focusing on the impact of interest rates and the slope of the yield curve, using a broad panel of data from 32...     

Local tax interaction and endogenous spatial weights based on quality of life

This paper studied the role of municipal quality of life as a driver of strategic tax interactions among local governments. A number of studies point out the existence of strategic interactions using spatial econometric models in which the spatial weights are mostly based on non-economic criteria or basic economic variables such as per capita gross domestic product (GDP). We propose the more sophisticated well-being indicator of municipal quality of life as the driver for these interactions. To deal with the potential endogeneity, we rely on instrumental variable estimators. The empirical analysis focuses on the main local tax in Spain (property) and on municipalities with more than 50,000 inhabitants, and it confirms the relevance of differentials in quality of life for the understanding of tax choices.     

Claims Reserving with a Stochastic Vector Projection

In the last three decades, a variety of stochastic reserving models have been proposed in the general insurance literature mainly using (or reproducing) the well-known Chain-Ladder claims-reserving estimates. In practice, when the data do not satisfy the Chain-Ladder assumptions, high prediction errors might occur. Thus, in this article, a combined methodology is proposed based on the stochastic vector projection method and uses the regression through the origin approach of Murphy, but with heteroscedastic errors instead, and different from those that used by Mack. Furthermore, the Mack distribution-free model appears to have higher prediction errors when compared with the proposed one, particularly, for data sets with increasing (regular) trends. Finally, three empirical examples with irregular and regular data sets illustrate the theoretical findings, and the concepts of best estimate and risk margin are reported.