9,297 research outputs found
Essays on financial markets in Africa
Doutoramento em EconomiaEconomic growth in a modern economy hinges on an efficient financial sector that pools
domestic savings and mobilizes foreign capital for productive investments. Absent an
effective set of financial institutions, productive projects will remain unexploited.
Inefficient financial institutions will have the effect of taxing productive investment and
thus reducing scope for increasing the stock equipment needed to compete globally. The
effect is to substantially cut growth from what would have been possible given
appropriate policies and market structures.
In this context, this thesis focuses on three essays analyzing the impact of financial
markets in development and income inequality. First, we assessed the impact of stock
market development on growth in Africa. The study uses annual data from a panel of nine
countries in Africa over the period 1992–2017. Panel Vector Autoregressive
econometrics technique is used in data analysis. Our main findings are that stock market
development has a positive effect on economic growth. The paper also finds that when
using the impulse response function, economic growth reacts to the stock market for a
period of eight years and then returns to the initial level.
The second essay presents evidence about the relationship between private credit, stock
market indicators, income inequality and poverty, using the annual data that ranges from
1992 to 2018 on nine African economies. We applied the estimation method of
Autoregressive Distributed Lag (ARDL) to model the long-run effect. In Addition, we
used Dumitrescu and Hurlin Panel causality to check the direction of causality. The
results of long‐run estimates show that the stock market indicators have a significant
positive impact on income inequalities, but have a negative and significant impact on
poverty. Further, our findings show that private credit adversely reduces income inequalities. The results also establish significant short‐run causalities among stock
market indicators, private credit, income inequalities, and poverty.
Lastly, we examine the relationship between financial development and economic
growth in Angola for the period of Q12002 to Q42018. The results show that there is
evidence of a long-run relationship between financial development and real GDP per
capita, when using the Bound test approach for cointegration. Furthermore, the results of
the Error Correction Model (ECM) indicate that financial development has a negative
impact on GDP growth when considering credit to private and broad money as proxies
for financial development. On the other hand, the degree of intermediation has a positive
impact on GDP growth. The Toda–Yamamoto causality test was carried out, which
indicates a unidirectional causality relationship, running from real GDP per capita to a
purely financial development proxy, which shows demand-following responses.
Consequently, policymakers should adopt policies that sustain the benefits of financial
developments for economic growth.O crescimento económico numa economia moderna depende de um sector financeiro
eficiente que reúna a poupança doméstica e mobilize capital estrangeiro para
investimentos produtivos. Sem um conjunto efetivo de instituições financeiras, os
projetos produtivos permanecerão inexplorados. Instituições financeiras ineficientes
terão o efeito de tributar o investimento produtivo e, assim, reduzir a margem para
aumentar o estoque de equipamentos necessários para competir globalmente. O efeito é
reduzir substancialmente o crescimento do que seria possível com políticas e estruturas
de mercado apropriadas.
Nesse contexto, esta tese se concentra em três artigos que analisam o impacto dos
mercados financeiros no desenvolvimento e na desigualdade de renda em África. Em
primeiro lugar, avaliámos o impacto do desenvolvimento do mercado bolsista no
crescimento económico em África. O estudo usa dados anuais de um painel de nove
países da África durante o período de 1992 a 2017. Para a análise dos dados foi usada a
técnica de econometria autorregressiva de vetor de painel. Nossas principais conclusões
são que o desenvolvimento do mercado de ações tem um efeito positivo sobre o
crescimento económico. O artigo também constata que, ao usar a função de impulso
resposta, o crescimento económico reage ao mercado de ações por um período de oito
anos e depois retorna ao nível inicial.
O segundo artigo apresenta evidências sobre a relação entre crédito privado, indicadores
do mercado de ações, desigualdade de renda e pobreza, usando os dados anuais que
variam de 1992 a 2018 em nove economias africanas. Aplicamos o método de estimação
de Autoregressive Distributed Lag (ARDL) para modelar o efeito de longo prazo. Além
disso, usamos a causalidade do Painel de Dumitrescu e Hurlin para verificar a direção da causalidade. Os resultados das estimativas de longo prazo mostram que os indicadores do
mercado de ações têm um impacto positivo e significativo nas desigualdades de renda,
mas têm um impacto negativo e significativo na pobreza. Além disso, nossos resultados
mostram que o crédito privado reduz negativamente as desigualdades de renda. Os
resultados também estabelecem causalidades significativas de curto prazo entre
indicadores do mercado de ações, crédito privado, desigualdades de renda e pobreza.
Por último, examinamos a relação entre o desenvolvimento financeiro e o crescimento
económico em Angola para o período de T12002 a T42018. Os resultados mostram que
há evidências de uma relação de longo prazo entre o desenvolvimento financeiro e o PIB
real per capita, quando se utiliza a abordagem do teste Bound para cointegração. Além
disso, os resultados do Error Correction Model (ECM) indicam que o desenvolvimento
financeiro tem um impacto negativo no crescimento do PIB quando se considera o crédito
ao privado e a moeda ampla como proxies do desenvolvimento financeiro. Por outro lado,
o grau de intermediação tem um impacto positivo no crescimento do PIB. Foi realizado
o teste de causalidade Toda–Yamamoto, que indica uma relação de causalidade
unidirecional, indo do PIB real per capita a uma proxy de desenvolvimento puramente
financeiro, que mostra respostas de acompanhamento da procura. Consequentemente, os
formuladores de políticas devem adotar políticas que sustentem os benefícios dos
desenvolvimentos financeiros para o crescimento econômico.info:eu-repo/semantics/publishedVersio
Optimising water quality outcomes for complex water resource systems and water grids
As the world progresses, water resources are likely to be subjected to much greater pressures than in the past. Even though the principal water problem revolves around inadequate and uncertain water supplies, water quality management plays an equally important role. Availability of good quality water is paramount to sustainability of human population as well as the environment. Achieving water quality and quantity objectives can be conflicting and becomes more complicated with challenges like, climate change, growing populations and changed land uses. Managing adequate water quality in a reservoir gets complicated by multiple inflows with different water quality levels often resulting in poor water quality. Hence, it is fundamental to approach this issue in a more systematic, comprehensive, and coordinated fashion. Most previous studies related to water resources management focused on water quantity and considered water quality separately. However, this research study focused on considering water quantity and quality objectives simultaneously in a single model to explore and understand the relationship between them in a reservoir system. A case study area was identified in Western Victoria, Australia with water quantity and quality challenges. Taylors Lake of Grampians System in Victoria, Australia receives water from multiple sources of differing quality and quantity and has the abovesaid problems. A combined simulation and optimisation approach was adopted to carry out the analysis. A multi-objective optimisation approach was applied to achieve optimal water availability and quality in the storage. The multi-objective optimisation model included three objective functions which were: water volume and two water quality parameters: salinity and turbidity. Results showed competing nature of water quantity and quality objectives and established the trade-offs. It further showed that it was possible to generate a range of optimal solutions to effectively manage those trade-offs. The trade-off analysis explored and informed that selective harvesting of inflows is effective to improve water quality in storage. However, with strict water quality restriction there is a considerable loss in water volume. The robustness of the optimisation approach used in this study was confirmed through sensitivity and uncertainty analysis. The research work also incorporated various spatio-temporal scenario analyses to systematically articulate long-term and short-term operational planning strategies. Operational decisions around possible harvesting regimes while achieving optimal water quantity and quality and meeting all water demands were established. The climate change analysis revealed that optimal management of water quantity and quality in storage became extremely challenging under future climate projections. The high reduction in storage volume in the future will lead to several challenges such as water supply shortfall and inability to undertake selective harvesting due to reduced water quality levels. In this context, selective harvesting of inflows based on water quality will no longer be an option to manage water quantity and quality optimally in storage. Some significant conclusions of this research work included the establishment of trade-offs between water quality and quantity objectives particular to this configuration of water supply system. The work demonstrated that selective harvesting of inflows will improve the stored water quality, and this finding along with the approach used is a significant contribution to decision makers working within the water sector. The simulation-optimisation approach is very effective in providing a range of optimal solutions, which can be used to make more informed decisions around achieving optimal water quality and quantity in storage. It was further demonstrated that there are range of planning periods, both long-term (>10 years) and short-term (<1 year), all of which offer distinct advantages and provides useful insights, making this an additional key contribution of the work. Importantly, climate change was also considered where it was found that diminishing water resources, particularly to this geographic location, makes it increasingly difficult to optimise both quality and quantity in storage providing further useful insights from this work.Doctor of Philosoph
Cavity effect in the quasinormal mode spectrum of topological stars
We study scalar perturbations of topological solitons, smooth horizonless
solutions in five-dimensional Einstein-Maxwell theory that correspond to
coherent states of gravity via the dynamics of extra compact dimensions. First,
we compute scalar quasinormal modes for topological stars that have a single
unstable photon sphere, and we show that the spectrum is very similar to that
of a black hole with the same photon sphere. Next, we study topological stars
that have both a stable inner photon sphere and an unstable one. The first few
quasinormal modes are localized around the inner photon sphere. The spectrum
also contains ''black-hole like modes'' localized at the unstable outer photon
sphere. The frequencies of these modes are similar to those of a black hole,
but their imaginary part is smaller due to a cavity effect associated with the
inner photon sphere. The longer damping produced by this trapping effect may
have implications for black hole spectroscopy.Comment: 17 pages + Appendix, 11 figure
Assessing Atmospheric Pollution and Its Impacts on the Human Health
This reprint contains articles published in the Special Issue entitled "Assessing Atmospheric Pollution and Its Impacts on the Human Health" in the journal Atmosphere. The research focuses on the evaluation of atmospheric pollution by statistical methods on the one hand, and on the other hand, on the evaluation of the relationship between the level of pollution and the extent of its effect on the population's health, especially on pulmonary diseases
Modeling and Simulation in Engineering
The Special Issue Modeling and Simulation in Engineering, belonging to the section Engineering Mathematics of the Journal Mathematics, publishes original research papers dealing with advanced simulation and modeling techniques. The present book, “Modeling and Simulation in Engineering I, 2022”, contains 14 papers accepted after peer review by recognized specialists in the field. The papers address different topics occurring in engineering, such as ferrofluid transport in magnetic fields, non-fractal signal analysis, fractional derivatives, applications of swarm algorithms and evolutionary algorithms (genetic algorithms), inverse methods for inverse problems, numerical analysis of heat and mass transfer, numerical solutions for fractional differential equations, Kriging modelling, theory of the modelling methodology, and artificial neural networks for fault diagnosis in electric circuits. It is hoped that the papers selected for this issue will attract a significant audience in the scientific community and will further stimulate research involving modelling and simulation in mathematical physics and in engineering
Meso-scale FDM material layout design strategies under manufacturability constraints and fracture conditions
In the manufacturability-driven design (MDD) perspective, manufacturability of the product or system is the most important of the design requirements. In addition to being able to ensure that complex designs (e.g., topology optimization) are manufacturable with a given process or process family, MDD also helps mechanical designers to take advantage of unique process-material effects generated during manufacturing. One of the most recognizable examples of this comes from the scanning-type family of additive manufacturing (AM) processes; the most notable and familiar member of this family is the fused deposition modeling (FDM) or fused filament fabrication (FFF) process. This process works by selectively depositing uniform, approximately isotropic beads or elements of molten thermoplastic material (typically structural engineering plastics) in a series of pre-specified traces to build each layer of the part. There are many interesting 2-D and 3-D mechanical design problems that can be explored by designing the layout of these elements. The resulting structured, hierarchical material (which is both manufacturable and customized layer-by-layer within the limits of the process and material) can be defined as a manufacturing process-driven structured material (MPDSM). This dissertation explores several practical methods for designing these element layouts for 2-D and 3-D meso-scale mechanical problems, focusing ultimately on design-for-fracture. Three different fracture conditions are explored: (1) cases where a crack must be prevented or stopped, (2) cases where the crack must be encouraged or accelerated, and (3) cases where cracks must grow in a simple pre-determined pattern. Several new design tools, including a mapping method for the FDM manufacturability constraints, three major literature reviews, the collection, organization, and analysis of several large (qualitative and quantitative) multi-scale datasets on the fracture behavior of FDM-processed materials, some new experimental equipment, and the refinement of a fast and simple g-code generator based on commercially-available software, were developed and refined to support the design of MPDSMs under fracture conditions. The refined design method and rules were experimentally validated using a series of case studies (involving both design and physical testing of the designs) at the end of the dissertation. Finally, a simple design guide for practicing engineers who are not experts in advanced solid mechanics nor process-tailored materials was developed from the results of this project.U of I OnlyAuthor's request
New directions in electric arc furnace modeling
This paper presents new directions in the modeling of electric arc furnaces. This work is devoted to an overview of new approaches based on random differential equations, artificial neural networks, chaos theory, and fractional calculus. The foundation of proposed solutions consists of an instantaneous power balance equation related to the electric arc phenomenon. The emphasis is mostly placed on the conclusions that come from a novel interpretation of the equation coefficients
Panel-based Assessment of Ecosystem Condition of Norwegian Barents Sea Shelf Ecosystems
The System for Assessment of Ecological Condition, coordinated by the Norwegian Environment Agency, is intended to form the foundation for evidence-based assessments of the ecological condition of Norwegian terrestrial and marine ecosystems not covered by the EU Water Framework Directive. The reference condition is defined as “intact ecosystems”, i.e., a condition that is largely unimpacted by modern industrial anthropogenic activities. An ecosystem in good ecological condition is defined as a system that does not deviate substantially from this reference condition in structure, functions or productivity. This means that, in practice, what is assessed here is the extent to which an ecosystem is impacted by anthropogenic drivers. This report describes the first operational assessment of the ecological condition of Norwegian Arctic and Sub-Arctic marine shelf ecosystems in the Barents Sea. The assessment method employed is the Panel-based Assessment of Ecosystem Condition (PAEC1), and the current assessment has considered to what extent the Barents Sea shelf ecosystems deviate from the reference condition2 by evaluating change trajectories.Panel-based Assessment of Ecosystem Condition of Norwegian Barents Sea Shelf EcosystemspublishedVersio
Energy Management of Grid-Connected Microgrids, Incorporating Battery Energy Storage and CHP Systems Using Mixed Integer Linear Programming
In this thesis, an energy management system (EMS) is proposed for use with battery energy storage systems (BESS) in solar photovoltaic-based (PV-BESS) grid-connected microgrids and combined heat and power (CHP) applications. As a result, the battery's charge/discharge power is optimised so that the overall cost of energy consumed is minimised, considering the variation in grid tariff, renewable power generation and load demand. The system is modelled as an economic load dispatch optimisation problem over a 24-hour time horizon and solved using mixed integer linear programming (MILP) for the grid-connected Microgrid and the CHP application. However, this formulation requires information about the predicted renewable energy power generation and load demand over the next 24 hours. Therefore, a long short-term memory (LSTM) neural network is proposed to achieve this. The receding horizon (RH) strategy is suggested to reduce the impact of prediction error and enable real-time implementation of the energy management system (EMS) that benefits from using actual generation and demand data in real-time.
At each time-step, the LSTM predicts the generation and load data for the next 24 h. The dispatch problem is then solved, and the real-time battery charging or discharging command for only the first hour is applied. Real data are then used to update the LSTM input, and the process is repeated. Simulation results using the Ushant Island as a case study show that the proposed online optimisation strategy outperforms the offline optimisation strategy (with no RH), reducing the operating cost by 6.12%.
The analyses of the impact of different times of use (TOU) and standard tariff in the energy management of grid-connected microgrids as it relates to the charge/discharge cycle of the BESS and the optimal operating cost of the Microgrid using the LSTM-MILP-RH approach is evaluated. Four tariffs UK tariff schemes are considered: (1) Residential TOU tariff (RTOU), (2) Economy seven tariff (E7T), (3) Economy ten tariff (E10T), and (4) Standard tariff (STD). It was found that the RTOU tariff scheme gives the lowest operating cost, followed by the E10T tariff scheme with savings of 63.5% and 55.5%, respectively, compared to the grid-only operation. However, the RTOU and E10 tariff scheme is mainly used for residential applications with the duck curve load demand structure. For community grid-connected microgrid applications except for residential-only communities, the E7T and STD, with 54.2% and 39.9%, respectively, are the most likely options offered by energy suppliers.
The use of combined heat and power (CHP) systems has recently increased due to their high combined efficiency and low emissions. Using CHP systems in behind-the-meter applications, however, can introduce some challenges. Firstly, the CHP system must operate in load-following mode to prevent power export to the grid. Secondly, if the load drops below a predefined threshold, the engine
will operate at a lower temperature and hence lower efficiency, as the fuel is only half-burnt, creating significant emissions. The aforementioned issues may be solved by combining CHP with a battery energy storage system. However, the dispatch of CHP and BESS must be optimised. Offline optimisation methods based on load prediction will not prevent power export to the grid due to prediction errors. Therefore, a real-time EMS using a combination of LSTM neural networks, MILP, and RH control strategy is proposed. Simulation results show that the proposed method can prevent power export to the grid and reduce the operational cost by 8.75% compared to the offline method.
The finding shows that the BESS is a valuable asset for sustainable energy transition. However, they must be operated safely to guarantee operational cost reduction and longer life for the BESS
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