Browsing by Author "Almeida, Dora"
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- Are Mobility and COVID-19 Related? A Dynamic Analysis for Portuguese DistrictsPublication . Casa Nova, António; Ferreira, Paulo; Almeida, Dora; Dionísio, Andreia; Quintino, Derick
- Company Management in the Insurance Sector: Valuing Employees and their Work CommitmentPublication . Serrasqueiro, João; Felix, Marta; Veiga, Pedro Mota; Ferreira, Paulo Jorge Silveira; Almeida, DoraThis study focuses mainly on the role of employees in insurance companies in Portugal, analysing the importance of valuing them and their commitment to their work. Considering the above, this research aims to examine which aspects lead to greater commitment on the part of employees and what makes them feel valued within the organisations where they work. A quantitative methodology was used to fulfil this objective, and a questionnaire was applied to various employees in the insurance companies operating in the Portuguese market. The study’s results of the study highlight a positive relationship between leadership, the inclusion of employees, and their commitment to work. They also highlight that participation in decision-making positively influences their satisfaction, appreciation, and loyalty to their company. It can, therefore, be concluded that investing in employees and increasing their satisfaction and commitment is crucial for sustainable growth and organisational success.
- From wars to waves: geopolitical risks and environmental investment behaviourPublication . Gabriel, Vítor; Dionísio, Andreia; Almeida, Dora; Ferreira, PauloThis study investigates the impact of geopolitical risk (GPR) on sustainable investments, focusing on five global environmental indices and two global GPR indices. Using Corrected Dynamic Conditional Correlation Generalised Autoregressive Conditional Heteroskedasticity (cDCC-GARCH) model and Diebold and Yilmaz’s spillover analysis, we use daily data from January 2009 to October 2022, covering various market phases, including the European sovereign debt crisis, the COVID-19 pandemic, and the war in Ukraine. Results from the cDCC-GARCH model reveal high dynamic conditional correlations. During periods of high volatility, environmental indices displayed simultaneous and more intense responses, limiting investment diversification alternatives when considering only the environmental side. Diebold and Yilmaz’s static analysis demonstrates that environmental segments are more influenced by systemic shocks than specific causes, with GPR’s influence proving relatively weak. In the dynamic analysis, the spillover effects of GPR in environmental segments intensified during the pandemic crisis and the invasion of Ukraine, affecting market conditions.
- A Giant Falls: The Impact of Evergrande on Asian Stock IndexesPublication . Almeida, Dora; Dionísio, Andreia; Enamul Haque, Muhammad; Ferreira, PauloThe economic growth of China has been driven by the development of its real estate market, especially after the 2008 crisis. This growth is mostly related to the huge housing bubble and growing amounts of sovereign debt that have been redirected to corporations in the sector. Evergrande is one of those corporations; it is a Chinese company in the construction and real estate sector, a global giant with investments in many parts of the world. Its bond default in September 2021 sounded alerts in financial markets. Several news outlets spoke of the “next Lehman Brothers”, and apprehension was very high, especially in Asian markets. This research work aims to evaluate the impact of Evergrande’s bond default on six Asian stock markets, using an event study approach. The results show a strong reaction from the markets towards the event in study, even anticipating it. Furthermore, it is worth mentioning a quick reversion to “normal” behavior, indicating the rapid absorption of information by the markets.
- Global Dynamics of Environmental Kuznets Curve: A Cross-Correlation Analysis of Income and CO2 EmissionsPublication . Almeida, Dora; Carvalho, Luísa; Ferreira, Paulo; Dionísio, Andreia; Haq, Inzamam UlThe environmental Kuznets curve (EKC) hypothesis posits an inverted U-shaped relationship between economic growth and environmental degradation. However, there is no consensus regarding the EKC hypothesis among countries and regions of different income groups. This study revisits the EKC hypothesis by employing cross-correlation analysis to explore the income–CO2 emissions relationship across 158 countries and 44 regions from 1990 to 2020. The empirical method utilizes a dynamic cross-correlation coefficient (CCC) approach, allowing for the assessment of lead-lag dynamics between income and CO2 emissions over time. By categorizing nations into the World Bank’s income classifications, we found a heterogeneous EKC pattern highlighting distinct environmental–economic dynamics across different income groups. The findings indicate that highincome countries show a decoupling of economic growth from CO2 emissions; whereas, low-income countries still exhibit a positive correlation between both variables. This underscores the necessity for tailored policy interventions that promote carbon neutrality, while considering each country’s unique development stage. Our research contributes to the ongoing issue of sustainable economic development by providing empirical evidence of the different pathways nations follow in balancing growth with environmental preservation.
- Impact of the COVID-19 Pandemic on Cryptocurrency Markets: A DCCA AnalysisPublication . Almeida, Dora; Dionísio, Andreia; Ferreira, Paulo Jorge Silveira; Isabel VieiraExtraordinary events, regardless of their financial or non-financial nature, are a great challenge for financial stability. This study examines the impact of one such occurrence—the COVID19 pandemic—on cryptocurrency markets. A detrended cross-correlation analysis was performed to evaluate how the links between 16 cryptocurrencies were changed by this event. Cross-correlation coefficients that were calculated before and after the onset of the pandemic were compared, and the statistical significance of their variation was assessed. The analysis results show that the markets of the assessed cryptocurrencies became more integrated. There is also evidence to suggest that the pandemic crisis promoted contagion, mainly across short timescales (with a few exceptions of non-contagion across long timescales). We conclude that, in spite of the distinct characteristics of cryptocurrencies, those in our sample offered no protection against the financial turbulence provoked by the COVID-19 pandemic, and thus, our study provided yet another example of ‘correlations breakdown’ in times of crisis.
- A new vision about the influence of major stock markets in CEEC indices: a bidirectional dynamic analysis using transfer entropyPublication . Ferreira, Paulo; Dionísio, Andreia; Almeida, Dora; Quintino, Derick; Aslam, FaheemThis research work aims to understand the dynamics of influence among CEEC stock market indices and between these and the US, German, UK and Chinese indices. Through a nonlinear approach, based on transfer entropy, we find strongly influential relationships between some CEEC indices and the influencing nature of the US index stands out. In addition to the complexity of causality relationships, which has a limited compatibility with purely linear analyses, we also perceive an intensification in the leadership of the big 4 from the first quarter of 2020, which suggests that the pandemic crisis may be a factor for the intensification of influence from Chinese and US indices.
- A new vision about the influence of major stock markets in CEEC indices: a bidirectional dynamic analysis using transfer entropyPublication . Ferreira, Paulo; Dionísio, Andreia; Almeida, Dora; Quintino, Derick; Aslam, FaheemThis research work aims to understand the dynamics of influence among CEEC stock market indices and between these and the US, German, UK and Chinese indices. Through a nonlinear approach, based on transfer entropy, we find strongly influential relationships between some CEEC indices and the influencing nature of the US index stands out. In addition to the complexity of causality relationships, which has a limited compatibility with purely linear analyses, we also perceive an intensification in the leadership of the big 4 from the first quarter of 2020, which suggests that the pandemic crisis may be a factor for the intensification of influence from Chinese and US indices.
- Nonlinear nexus between cryptocurrency returns and COVID-19 news sentimentPublication . Banerjee, Ameet Kumar; Akhtaruzzaman, Md; Dionisio, Andreia; Almeida, Dora; Sensoy, AhmetThe paper examines how various COVID-19 news sentiments differentially impact the behaviour of cryptocurrency returns. We used a nonlinear technique of transfer entropy to investigate the relationship between the top 30 cryptocurrencies by market capitalisation and COVID-19 news sentiment. Results show that COVID-19 news sentiment influences cryptocurrency returns. The nexus is unidirectional from news sentiment to cryptocurrency returns, in contrast to past findings. These results have practical implications for policymakers and market participants in understanding cryptocurrency market dynamics under extremely stressful market conditions.
- Quality Education for All: A Fuzzy Set Analysis of Sustainable Development Goal CompliancePublication . Carvalho, Luisa; Almeida, Dora; Loures, Ana; Ferreira, Paulo; Rebola, FernandoThe relationship between education and societal development is unquestionable. Education contributes to achieving both societies’ and individuals’ social and economic goals. Quality education is recognized as one of the Sustainable Development Goals (SDGs), which, jointly with other behaviors and attitudes, could impact the development of societies in other fields like health and well-being, cultural preservation, environmental sustainability, and even peace and stability—all of them also listed as SDGs. However, the capacity, or not, to reach higher levels of compliance with quality in education (SDG 4) varies from country to country, according to the 2023 Sustainable Development Report results. Thus, the present study aims to identify the sufficient conditions for achieving higher levels of quality education (SDG 4) globally and to analyze how these conditions vary across different world regions. Applying a fuzzy set qualitative comparative analysis and using data from the 2023 Sustainable Development Report, we focus our analysis on four SDG 4 indicators—early education, primary education, lower secondary education, and literacy rate—across 117 countries, in order to assess the conditions for attaining higher levels of quality education. The results reveal there are specific and identifiable conditions that are sufficient for achieving higher levels of quality education on a global scale, with significant regional variations. These insights contribute to understanding the complex dynamics of educational quality and could be used as guidance for policymakers and educators aiming to improve educational outcomes worldwide.