<p>This dissertation examines the impact of the expansion of renewable technology at both national and local level, through distinct essays. At the national level, the first paper analyzes the effects of economic and distributional impacts of climate mitigation policy, in the context of a developing country, to understand the interactions between the energy system and the macroeconomic environment. In the case of the local level, the second paper uses synthetic control method, to estimate the effect at the county level of utility scale wind in the development indicators for two counties in the U.S. </p> <p>The first paper assesses the economic and distributional impacts of Nicaragua’s commitments to limit future greenhouse gas emissions in the context of the Paris Agreement, known as the Nationally Determined Contributions (NDCs). The analysis relies on two distinct models. The first is a top-down approach based on a single-country computable general equilibrium (CGE) model, known as the Mitigation, Adaptation and New Technologies Applied General Equilibrium (MANAGE) Model. The second is a bottom-up approach based on the Open-Source energy Modeling System (OSeMOSYS), which is technology rich energy model. The combined model is calibrated to an updated social accounting matrix for Nicaragua, which disaggregates households into 20 representative types: 10 rural and 10 urban households. For the household disaggregation we have used information from the 2014 Living Standards Measurement Study (LSMS) for Nicaragua. Our analysis focuses on the distributional impacts of meeting the NDCs as well as additional scenarios—in a dynamic framework as the MANAGE model is a (recursive) dynamic model. The results show that a carbon tax has greatest potential for reduction in emissions, with modest impact in macro variables. An expansion of the renewable sources in the electricity matrix also leads to significant reduction in emissions. Only a carbon tax achieves a reduction in emissions consistent with keeping global warming below 2°C. Nicaragua’s NDC alone would not achieve the target and mitigation instruments are needed. An expansion of generation from renewable sources, does not lead to a scenario consistent with a 2°C pathway. </p> <p>The second paper measures the impact of wind generation on county level outcomes through the use of the Synthetic Control Method (SCM). SCM avoids the pitfalls of other methods such as input-output models and project level case studies that do not provide county level estimates. We find that the local per capita income effect of utility wind scale is 6 percent (translate into an increase of $1,511 in per capita income for 2019) for Benton County and 8 percent for White county in Indiana (an increase of $2,100 in per capita income for 2019). The per capita income effect measures the average impact, which includes the gains in rents from capital, land, and labor from wind power in these counties. Moreover, we find that most of the rents from wind power accrue to the owners of capital and labor. Even assuming the lowest projections of electricity prices and the highest reasonable cost we still find a 10 percent minimum rate of return to capital for both Benton and White counties’ wind power generators. Furthermore, we find that there are excess rents that could be taxed and redistributed at the county, state, or federal level without disincentivizing investment in wind power.</p>

Ein geringer Treibstoffverbrauch ist aufgrund von ökologischen und ökonomischen Zielen für die zivile Luftfahrt von großer Bedeutung. Daher werden seit Jahrzehnten konventionell hydraulisch oder pneumatisch betriebene Flugzeugsysteme durch elektrisch betriebene Systeme ersetzt. Dieser Trend wird auch als „More Electric Aircraft (MEA)“ bezeichnet. In bisherigen Studien waren MEA-Architekturen zwar effizienter, jedoch deutlich schwerer als die konventionellen Architekturen. Basierend auf ökonomischen Modellen wird in der vorliegenden Arbeit die modellbasierte Entwicklung eines intelligenten Energiemanagements für Flugzeug-Energiesysteme demonstriert. Das Energiemanagement ermöglicht eine deutliche Reduktion der Systemmasse, verbessert die Energieeffizienz und kann damit den Treibstoffverbrauch eines MEA beträchtlich reduzieren. Insbesondere durch die integrierte und frühzeitige Entwicklung des Energiemanagements mit dem elektrischen System in der Modellbeschreibungssprache Modelica lassen sich die Systemkomponenten mit realistischen Lastprofilen dimensionieren und dadurch die Systemmasse reduzieren. Anhand eines elektrischen Referenzsystems wird das Optimierungspotenzial des Energiemanagements bezüglich Massenreduktion und Energieeffizienzsteigerung quantifiziert und am Systemmodell validiert. Es ergibt sich für das Systemmodell eine Reduktion der Systemmasse um 32 % sowie eine leichte Verbesserung der Energieeffizienz. Durch die multiphysikalische Implementierung des Energiemanagements lässt sich dieses auch für das thermische Management im Flugzeug verwenden. Hierbei kann eine deutliche Verbesserung der Energieeffizienz für die Bereitstellung von Kühlleistung erzielt werden. Aufgrund der erreichten Vorteile sollte ein Energiemanagement bei der Entwicklung zukünftiger Flugzeugenergiesysteme in Betracht gezogen werden. Insbesondere beim MEA existiert ein großes Optimierungspotenzial durch das Energiemanagement. Die Ausführungen in der vorliegenden Arbeit sollen als Motivation für die Flugzeugindustrie dienen, mit realistischen Lastprofilen zu dimensionieren und die modellbasierte und integrierte Entwicklung eines Energiemanagements mit den Energiesystemen bereits in frühen Entwicklungsphasen durchzuführen. / Low fuel consumption is a major concern in civil aerospace due to environmental and economic objectives. Hence, conventional hydraulically or pneumatically driven aircraft systems have been replaced by electrically driven systems for decades. This trend is also known as More Electric Aircraft (MEA). In former studies, MEA architectures were more efficient, but much heavier than their conventional counterparts. The present work demonstrates the model-based development of intelligent energy management algorithms for aircraft energy systems based on economic models. This energy management facilitates a significant reduction of system mass, improves energy efficiency and can hence reduce fuel consumption of MEA considerably. In particular, the integrated development of an energy management along with the electrical system in the Modelica modelling language enables sizing of system components with realistic load profiles. Hence, this reduces the system mass. The optimization potential of the energy management is quantified and validated by means of an electrical reference system model. Applying the energy management, the mass of this system model can be reduced by 32 % and the energy efficiency can be improved slightly. Due to the multi-physical modelling of the energy management, it can also be applied to thermal management of aircraft systems. Thus, the energy efficiency of the cooling system can be improved significantly. As a result of the demonstrated benefits, an energy management should be considered for future development of aircraft energy systems. Especially for MEA, there is tremendous optimization potential for the energy management. Hence, the present work shall motivate aircraft industry to size aircraft systems with realistic load profiles and perform a model-based and integrated development of the energy management along with the electrical system in early phases of the system design process.

Game balance has been a challenge for game developers since the time games have become more complex. There have been a handful of proposals for game balancing processes outside the manual labor-intensive play testing methods, which most game developers often are forced to use simply due to the lack of better methods. Simple solutions, like restrictive game play, are limited because of their inability to provide insight on interdependencies among the mechanisms in the game. Complex techniques framed around the potential of AI algorithms are limited by computational budgets or cognition inability to assess human actions. In order to find a middle ground we investigate Game Theory and Mechanism Design concepts. Both have proven to be effective tools to analyse strategic situations among interacting participants, or in this case `players'. We test the feasibility of using these techniques in an Real Time Strategy (RTS) game domain to understand game balance. MicroRTS, a small and simple execution of an RTS game is employed as our model. The results provide promising insight on the effectiveness of the method in detecting imbalances and further inspection to find the cause. An additional benefit out of this technique, besides detecting for game imbalances, the approach can be leveraged to create imbalances. This is useful when the designer or player desires to do so.

<p dir="ltr">In this thesis, we delve into the exploration of several nonparametric and semiparametric econometric models within the Bayesian framework, highlighting their applicability across a broad spectrum of microeconomic and macroeconomic issues. Positioned in the big data era, where data collection and storage expand at an unprecedented rate, the complexity of economic questions we aim to address is similarly escalating. This dual challenge ne- cessitates leveraging increasingly large datasets, thereby underscoring the critical need for designing flexible Bayesian priors and developing scalable, efficient algorithms tailored for high-dimensional datasets.</p><p dir="ltr">The initial two chapters, Chapter 2 and 3, are dedicated to crafting Bayesian priors suited for environments laden with a vast array of variables. These priors, alongside their corresponding algorithms, are optimized for computational efficiency, scalability to extensive datasets, and, ideally, distributability. We aim for these priors to accommodate varying levels of dataset sparsity. Chapter 2 assesses nonparametric additive models, employing a smoothing prior alongside a band matrix for each additive component. Utilizing the Bayesian backfitting algorithm significantly alleviates the computational load. In Chapter 3, we address multiple linear regression settings by adopting a flexible scale mixture of normal priors for coefficient parameters, thus allowing data-driven determination of the necessary amount of shrinkage. The use of a conjugate prior enables a closed-form solution for the posterior, markedly enhancing computational speed.</p><p dir="ltr">The subsequent chapters, Chapter 4 and 5, pivot towards time series dataset model- ing and Bayesian algorithms. A semiparametric modeling approach dissects the stochastic volatility in macro time series into persistent and transitory components, the latter addi- tional component addressing outliers. Utilizing a Dirichlet process mixture prior for the transitory part and a collapsed Gibbs sampling algorithm, we devise a method capable of efficiently processing over 10,000 observations and 200 variables. Chapter 4 introduces a simple univariate model, while Chapter 5 presents comprehensive Bayesian VARs. Our al- gorithms, more efficient and effective in managing outliers than existing ones, are adept at handling extensive macro datasets with hundreds of variables.</p>

The principal aim of this thesis is to examine the validity of the claim that low productivity led to a decline in Thailand’s competitiveness, and hence, to the 1997 economic crisis. For a decade from 1985 to 1995, Thailand was one of the world’s fastest-growing economies with an average real annual GDP growth of 8.4 percent. However, such growth was criticized as being simply the result of large inward investment and rapid accumulation of capital, leading to very little productivity growth, and therefore, being unsustainable in the long run. Worse still, the later surges of capital inflows came in mainly as speculative stashes, instead of as foreign direct investments in production and businesses. Hence, as predicted, the boom finally came to a sudden end in 1997. The economic growth statistics recorded severe contraction, financial market collapsed, the currency was battered, domestic demand slumped, severe excess capacity was experienced, employment deteriorated, personal and corporate income diminished, inflation and the cost of living mounted, and finally, poverty surged. This thesis utilizes a stochastic production frontier approach to verify the claim that low productivity lessened Thailand’s competitiveness. This approach, unlike the standard econometric approach, allows the existence of technical inefficiency in the production process. It also, unlike other non-parametric approaches, recognizes that such inefficiency can sometimes occur as a result of external factors that are out of the firms’ direct control, such as statistical errors and random shocks. The period covered in this thesis is from 1990 to 2002. This is divided into 2 sub-periods, i.e. the pre-crisis period (1990 – 1996) and the post-crisis period (1997 – 2002). The estimation results indicate a structural shift in the Thai manufacturing sector, from being labour intensive in the pre-crisis period to being capital intensive in the post-crisis period. The productivity level also improved post-crisis, as compared to the pre-crisis level, and is shown to follow an increasing trend. The low productive investment level in the pre-crisis period is identified as having led to the decline in the manufacturing sector’s efficiency. The thesis concludes that this low productivity level did indeed lead to the decline in Thailand’s competitiveness, and hence, to the decline of export growth, which was at that time the main source of Thailand’s economic growth; in turn, playing an important role in precipitating the 1997 economic crisis.

Efficient waste management enables the protection of human health, reducing environmental pollution, saving of natural resources, and achieving sustainable and profitable management of energy. In many countries, the general guidelines for waste management are set by national or local waste management plans. Various models provide local authorities with decision-making tools in planning long-term waste management scenarios.This study aims at providing a special model framework for the evaluation of ecological–economic efficiency (ECO-EE) of waste management. This will serve as an information support tool for decision making by actors of a solid waste management (SWM) scheme, primarily at the municipal and regional levels. The objective of this study is to apply the waste management’s efficient decision (WAMED) model along with the company statistical business tool for environmental recovery indicator (COSTBUSTER) model to SWM and municipal solid waste (MSW) schemes in general in order to evaluate and improve their ECO-EE. COSTBUSTER is a mathematical indicator for the size and extent of implementation costs of a certain SWM scheme, compared with the total size of the average financial budget of a SWM actor of a certain kind. In particular, WAMED is proposed for evaluating the suitability to invest in baling technology. Baling of solid waste is an emerging technology which is extensively used worldwide to temporarily store waste for either incineration or recovery of raw materials. The model for efficient use of resources for optimal production economy (the EUROPE model) is for the first time applied to emissions from baling facilities. It has been analysed how cost-benefit analysis (CBA) and full cost accounting (FCA) can facilitate environmental optimisation of SWM schemes. The effort in this work represents a continuation of such ambitions as an enlargement of the research area of CBA based modelling within SWM. In the thesis, certain theoretical and economic aspects of SWM were analysed as case studies. A shift of viewpoints within the field of waste management is presented. This shift is in accordance with the prevailing concept of sustainable development, as commonly understood. It is concluded that in the practical SWM context, the findings of the study point at the possibilities to modify the common CBA- and FCA-based methods by WAMED, COSTBUSTER, and EUROPE. Therefore, it can be said that estimations in a SWM scheme can be carried out by using certain economic model, if properly modified in a logical and plausible way. New principles for cost allocation to SWM residual products are presented in the current work. They imply strong industrial cost saving incentives through promoting the introduction of new and improved processing technologies for rest-waste. Such incentives then strongly promote investments that are likely to improve both the environment and the corporate profitability. Thereby, the occurrence of non-commercialised, and hence not utilized, wastes is reduced. This improves the short term corporate economy through saving raw materials such as solid waste fuel, spending less time for administrating waste flows, and less wear and tear of the plant machinery. Additional environmental advantages which affect the balance sheets in a favourable way are related to the long-term business economy and extended environmental goodwill. This is due to the recently introduced way of considering solid waste as regular goods in financial terms - the equality principle. If waste is seen as goods, and not wasted in landfills, the environment will improve. This, in turn, leads to an improved quality of life. Based on the current study, it is recommended to apply WAMED to SWM schemes in order to evaluate their ECO–EE to justify decision making and investments. Also, it is recommended to apply COSTBUSTER, based on the current WAMED outcome, to SWM schemes to determine their relative size and extent. It is recommended to apply EUROPE to the emissions in case of accidental burning, treatment of leachate, andabatement with odours at any SWM scheme, based on the induced economic incentives, in order to reduce unwanted substances and phenomena.

No description available.

Из-за сформировавшихся внешне и внутренне политических условий, снижение зависимости экономики РФ от внешних факторов становится все более приоритетным направлением развития. Более того, имеется ряд проблем, связанных с недостаточно эффективным развитием нецентральных районов. В их числе проблемы миграции, низкого уровня рождаемости и другие. Более того, изменяется роль институтов государства и местного самоуправления по отношению к гражданскому обществу. Тем самым возникает потребность в разработке и внедрении современных механизмов функционирования местных сообществ для достижения долгосрочных целей социально-экономического развития муниципальных образований. Указанные обстоятельства актуализируют изучение цифровой финансовой экосистемы местных сообществ. Учитывая вышесказанное, целью работы является разработка методики идентификации отдельного экономического агента на предмет его потенциальной принадлежности к локальному экономическому сообществу. Для этого были проанализированы данные о банковских транзакциях. Замкнутые цепи обмена были найдены. Также были рассчитаны 4 типа коэффициентов для определения полезности потенциального включения в сеть экономического агента. И были рассмотрены 4 возможных стратегии развития местного сообщества. Рассчитан экономический эффект. / Due to the formed external and internal political conditions, reducing the dependence of the Russian economy on external factors is becoming an increasingly priority area of development. Moreover, there are a number of problems associated with the insufficiently effective development of non-central regions. Among them are the problems of migration, low birth rate and others. Moreover, the role of state and local government institutions in relation to civil society is changing. Thus, there is a need for the development and implementation of modern mechanisms for the functioning of local communities to achieve long-term goals of socio-economic development of municipalities. These circumstances actualize the study of the digital financial ecosystem of local communities. Considering the above, the aim of the work is to develop a methodology for identifying an individual economic agent for its potential belonging to the local economic community. For this, data on banking transactions were analyzed. Closed circuits of exchange have been found. Also, 4 types of coefficients were calculated to determine the usefulness of a potential inclusion in the network of an economic agent. And 4 possible strategies for the development of the local community were considered. The economic effect is calculated.

No / OBJECTIVE: To assess clinical outcomes and cost-effectiveness of using a two-layer cohesive compression bandage (TLCCB; Coban 2) compared with a two-layer compression system (TLCS; Ktwo) and a four-layer compression system (FLCS; Profore) in treating venous leg ulcers (VLUs) in clinical practice in the UK, from the perspective of the National Health Service (NHS). METHOD: This was a retrospective analysis of the case records of VLU patients, randomly extracted from The Health Improvement Network (THIN) database (a nationally representative database of clinical practice among patients registered with general practitioners in the UK), who were treated with either TLCCB (n=250), TLCS (n=250) or FLCS (n=175). Clinical outcomes and health-care resource use (and costs) over six months after starting treatment with each compression system were estimated. Differences in outcomes and resource use between treatments were adjusted for differences in baseline covariates. RESULTS: Patients' mean age was 75 years old and 57% were female. The mean time with a VLU was 6-7 months and the mean initial wound size was 77-85 cm2. The overall VLU healing rate, irrespective of bandage type, was 44% over the six months' study period. In the TLCCB group, 51% of wounds had healed by six months compared with 40% (p=0.03) and 28% (p=0.001) in the TLCS and FLCS groups, respectively. The mean time to healing was 2.5 months. Patients in the TLCCB group experienced better health-related quality of life (HRQoL) over six months (0.374 quality-adjusted life years (QALYs) per patient), compared with the TLCS (0.368 QALYs per patient) and FLCS (0.353 QALYs per patient). The mean six-monthly NHS management cost was pound2,413, pound2,707 and pound2,648 per patient in the TLCCB, TLCS and FLCS groups, respectively. CONCLUSION: Despite the systems studied reporting similar compression levels when tested in controlled studies, real-world evidence demonstrates that initiating treatment with TLCCB, compared with the other two compression systems, affords a more cost-effective use of NHS-funded resources in clinical practice, since it resulted in an increased healing rate, better HRQoL and a reduction in NHS management cost. The evidence also highlighted the lack of continuity between clinicians managing a wound, the inconsistent nature of the administered treatments and the lack of specialist involvement, all of which may impact on healing. DECLARATION OF INTEREST: This study was supported by an unrestricted research grant from 3M Health Care, UK. 3M Health Care had no influence on the study design, the collection, analysis, and interpretation of data, or on the writing of, and decision to submit for publication, the manuscript.

因應電子化交易興起而進行的一系列人機互動研究顯示, 縱使人類會透過學習而改善其表現, 電腦化的交易程式獲利能力還是遠勝於真人交易者之表現。本研究遂以遺傳規劃演算法作為學習型交易者之代表, 與一系列電腦化交易策略相競爭, 以探討學習的功效及其限制。 本研究採用離散型雙方喊價機制, 摒除了計算能力所造成之決策時間差異所會帶來的影響, 亦排除掉人類情緒、預期、相關知識不足等可能因子, 在計算能力對等的情況下, 單純地來評估學習與理性設計策略的結果。並且首次嘗試將影響學習至鉅的智商因子帶入模型之中, 實驗結果顯示學習具有相當的能力, 即使是在對環境缺乏認識的情況下, 隨著時間的經過其表現最終可凌駕理性設計的策略之上, 然而學習所需的時間是學習型交易者的一大弱點。同時, 本研究也顯示對於以遺傳規劃建構的學習型交易者而言, 其虛擬智商的參數愈高, 學習的效果也愈佳。此研究因此可作為未來在代理人基經濟學模型中, 更深入地探討智商水準不同所造成之行為差異的基礎。 / The study of a series of human-agent interactions as well as computerized trading tournaments in double auction markets has exhibited a general superiority of computerized trading strategies over learning agents. The ineffectiveness of learning motivates the study of learning versus designed trading agents in this research. We therefore initiates a series of experiments to test the capability of learning GP agents and rationally-designed trading strategies. The results shows that with the cost of time, eventually learning agents can beat all other trading strategies. At the same time, the notion of intelligence is introduced into the model to investigate the influence of individual intelligence on learning ability. We utilize the population size of the GP trader as the proxy variable of IQ which is a measure of general intelligence. The results show that individuals with higher intelligence can perform better than those with lower intelligence, which manifests its importance discovered in Psychological research.