General Economics (econ.GN)

Abstract: In the EU-27 countries, the importance of social sustainability of digital transformation (SOSDIT) is heightened by the need to balance economic growth with social cohesion. By prioritizing SOSDIT, the EU can ensure that its citizens are not left behind in the digital transformation process and that technology serves the needs of all Europeans. Therefore, the current study aimed firstly to evaluate the SOSDIT of EU-27 countries and then to model its importance in reaching sustainable development goals (SDGs). The current study, using structural equation modeling, provided quantitative empirical evidence that digital transformation in Finland, the Netherlands, and Denmark are respectively most socially sustainable. It is also found that SOSDIT leads the countries to have a higher performance in reaching SDGs. Finally, the study provided evidence implying the inverse relationship between the Gini coefficient and reaching SDGs. In other words, the higher the Gini coefficient of a country, the lower its performance in reaching SDGs. The findings of this study contribute to the literature of sustainability and digitalization. It also provides empirical evidence regarding the SOSDIT level of EU-27 countries that can be a foundation for the development of policies to improve the sustainability of digital transformation. According to the findings, this study provides practical recommendations for countries to ensure that their digital transformation is sustainable and has a positive impact on society.

Abstract: The purpose of this study was to model the impact of mentoring on women's work-life balance. Indeed, this study considered mentoring as a solution to create a work-life balance of women. For this purpose, semi-structured interviews with both mentors and mentees of Tehran Municipality were conducted and the collected data were analyzed using constructivist grounded theory. Findings provided a model of how mentoring affects women's work-life balance. According to this model, role management is the key criterion for work-life balancing among women. In this model, antecedents of role management and the contextual factors affecting role management, the constraints of mentoring in the organization, as well as the consequences of effective mentoring in the organization are described. The findings of this research contribute to the mentoring literature as well as to the role management literature and provide recommendations for organizations and for future research.

Abstract: We build a new measure of credit and financial market sentiment using Natural Language Processing on Twitter data. We find that the Twitter Financial Sentiment Index (TFSI) correlates highly with corporate bond spreads and other price- and survey-based measures of financial conditions. We document that overnight Twitter financial sentiment helps predict next day stock market returns. Most notably, we show that the index contains information that helps forecast changes in the U.S. monetary policy stance: a deterioration in Twitter financial sentiment the day ahead of an FOMC statement release predicts the size of restrictive monetary policy shocks. Finally, we document that sentiment worsens in response to an unexpected tightening of monetary policy.

Abstract: This work validates a previously established dynamical input-output model to quantify the impact of economic shocks caused by COVID-19 in the UK using data from Belgium. To this end, we used four time series of economically relevant indicators for Belgium. We identified eight model parameters that could potentially impact the results and varied these parameters over broad ranges in a sensitivity analysis. In this way, we could identify the set of parameters that results in the best agreement to the empirical data and we could asses the sensitivity of our outcomes to changes in these parameters. We find that the model, characterized by relaxing the stringent Leontief production function, provides adequate projections of economically relevant variables during the COVID-19 pandemic in Belgium, both at the aggregated and sectoral levels. The obtained results are robust in light of changes in the input parameters and hence, the model could prove to be a valuable tool in predicting the impact of future shocks caused by armed conflicts, natural disasters, or pandemics.