Purpose The main purpose of this thesis was to evaluate the investment attractiveness of oil and gas stocks (registered on Nasdaq Stockholm) in face of the increasing campaigns for the adoption of clean energy. The findings can help in the formulation of relevant policy implications on the campaign for a cleaner environment Design/Methodology/Approach The authors assume positivism and objectivity as the philosophical aspects for the purpose of this study. Following these initial considerations, the nature of the study was adopted as quantitative. This follows a longitudinal design and a deductive approach, basing the paper on previous literature in the areas of environmental sustainability, market efficiency, financial news items and their effect on stock volatility in order to test own hypothesis.    Theory Following the methodological assumptions and the adoption of a deductive approach, relevant theory was selected to address the focus of previous research on which the research gaps and purpose are based. It also plays a role in introducing the reader to the relevant theories which will aid comprehension of further sections of this paper. Theories surrounding market efficiency, risk and return, the oil and gas industry and sustainability have all been mentioned.  Findings In order to fulfil the purpose of the study, the authors studied whether the volatility of oil and gas stocks are affected by clean energy related news. The empirical results suggest that the volatility of oil and gas stocks decline whenever news of clean energy is introduced, implying clean energy news cause lower volatility. To this end, oil and gas stocks are better off whenever clean energy/sustainability news are introduced into the market.  Analysis The empirical results seem to point to the fact that oil and gas firms may be benefiting from the investment they have made within the last two decades towards the issue of doing business in a more sustainable and socially responsible manner. It is therefore possible that investors get to reward them whenever news relating to sustainability and clean energy are announced. Conclusions  This thesis confirms the attractiveness of oil and gas stocks notwithstanding the increasing campaigns and initiatives aimed at promoting the adoption of clean energy.  Research limitations The research was limited in terms of setting since it only covered Sweden and therefore cannot answer questions regarding the overall attractiveness of oil and gas stocks across the globe.

Innovation intermediaries provide a range of services to assist firms during the process of innovation. How SMEs perceive innovation intermediaries is an area of investigation that would provide important information on how innovation intermediaries’ assist small and medium enterprises (SMEs). This study focuses on the cleantech industry and explores SMEs’ expectations and perceptions of an established community-based intermediary (CBI) moving into their sector. A qualitative research methodology was adopted to collect data from 15 sample SMEs. In regards to SMEs, the findings show that cleantech companies face financing, partnerships, marketing, sales, regulatory and bureaucratic challenges. In regards to innovation intermediaries, the findings showcase how CBI, a regional intermediary, is not effective in supporting cleantech SMEs with their sector specific needs or challenges.

This master thesis is focused on issue transimission system of Czech republic after 2040. Thesis is divided in two parts, teoretical and practical. Teoretical part contains present trends of transmission sytem and the most probably changes in the future decade. Practical part contains simulation of Czech transmission system and various scenarios with idea of open source.

Clean energy and machine learning are subjects that play significant roles in shaping our future. The current climate crisis has forced the world to take action towards more sustainable solutions. Arrangements such as the UN’s Sustainable Development Goals and the Paris Agreement are causing an increased interest in renewable energy solutions. Further, the EU Taxonomy Regulation, applied in 2020, aims to scale up sustainable investments and to direct cash flows toward sustainable projects and activities. These measures create interest in investing in renewable energy alternatives and predicting future movements of stocks related to these businesses. Machine learning models have previously been used to predict time series with promising results. However, predicting time series in the form of stock price indices has, throughout previous attempts, proved to be a difficult task due to the complexity of the variables that play a role in the indices’ movements. This paper uses the machine learning algorithm long short-term memory (LSTM) to predict the S&P Global Clean Energy Index. The research question revolves around how well the LSTM model performs on this specific index and how the result is affected when past returns from correlating variables are added to the model. The researched variables are crude oil price, gold price, and interest. A model for each correlating variable was created, as well as one with all three, and one standard model which used only historical data from the index. The study found that while the model with the variable which had the strongest correlation performed best among the multivariate models, the standard model using only the target variable gave the most accurate result of any of the LSTM models. / Den pågående klimatkrisen har tvingat allt fler länder till att vidta åtgärder, och FN:s globala hållbarhetsmål och Parisavtalet ökar intresset för förnyelsebar energi. Vidare lanserade EU-kommissionen den 21 april 2021 ett omfattande åtgärdspaket, med syftet att öka investeringar i hållbara verksamheter. Detta skapar i sin tur ett ökat intresse för investeringar i förnyelsebar energi och metoder för att förutspå aktiepriser för dessa bolag. Maskininlärningsmodeller har tidigare använts för tidsserieanalyser med goda resultat, men att förutspå aktieindex har visat sig svårt till stor del på grund av uppgiftens komplexitet och antalet variabler som påverkar börsen. Den här uppsatsen använder sig av maskininlärningsmodellen long short-term memory (LSTM) för att förutspå S&P:s Global Clean Energy Index. Syftet är att ta reda på hur träffsäkert en LSTM-modell kan förutspå detta index, och hur resultatet påverkas då modellen används med ytterligare variabler som korrelerar med indexet. De variabler som undersöks är priset på råolja, priset på guld, och ränta. Modeller för var variabel skapades, samt en modell med samtliga variabler och en med endast historisk data från indexet. Resultatet visar att den modell med den variabel som korrelerar starkast med indexet presterade bäst bland flervariabelmodellerna, men den modell som endast användes med historisk data från indexet gav det mest träffsäkra resultatet.

Thesis (MDF)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: In 2007, Bürer and Wüstenhagen (2009) conducted a survey amongst European and United States venture capital and private equity investors (VC/PE) to ascertain their public clean energy policy preference and concluded that VC/PE investors view the feed-in tariff (FIT) scheme to be the most preferred policy option. In this research study, the author re-conducted part of the Bürer and Wüstenhagen (2009) survey with thirty South African VC/PE investors to determine their perceptions on clean energy public policy preference. It is evident from the survey, that opinions are varied and at times even contradictory. This in itself demonstrates an important feature of the South African VC/PE and clean energy industry: it is young, dynamic, changing rapidly and can look very different, depending on the vantage point. The investors surveyed were mainly optimistic about the long-term development of the South African renewable energy industry led by private investors. VC/PE investors in South Africa have mixed views on various investment options, and are concerned about both the regulatory and macro-economic trends. The interviews and survey results show a number of recurring issues. Altogether, the survey results indicate that VC/PE investors consider FITs to be the best public clean energy policy instrument in leveraging private investment and finance for renewable energy in South Africa. This study serves to illustrate and confirm, in line with empirical studies, that VC/PE investors in South Africa believe that clean energy market-pull policies provide an impetus and indeed spur private investor participation in clean energy in developing countries. While it is true that most VC/PE investors would prefer the price certainty associated with a FIT regime, this is almost an irrelevant question in South Africa since constitutionally the state is bound to procure through competitive tendering. This study also serves to highlight the need for more active research and attention in this field.

Wood pellets are offering opportunities for a cleaner-burning biofuel but major concerns are overshadowing their potential. Tony Bi and UBC’s Clean Energy Research Centre are engineering solutions.

This thesis offers a critique of the dominant strategy to prevent catastrophic climate change, which I call the market fix, and starting points for developing an alternative strategy, which I call the common transition. To prevent catastrophic climate change GHG emissions must both peak by around 2015 and be reduced to near zero by 2050. I will argue that it is unlikely that the market fix will be able to reduce GHG emissions sufficiently because there is a powerful and resilient drive for destructive kinds of economic growth embedded in the relationship between states and the global economy. For this reason, the market fix relies on unrealistically rapid technological development to reduce GHG emissions sufficiently without threatening general economic growth or powerful economic interests. I will argue that self organizing networks and commons institutions, the two key elements of the common transition, can be woven together to change the relationship between societies and their economies in order to weaken the drive for destructive kinds of economic growth, directly reduce GHG emissions, and create a new context for climate action in which societies have a greater ability to achieve zero GHG emissions by 2050.

Thesis (MEng)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: See PDF for abstract. / AFRIKAANSE OPSOMMING: Sien die PDF vir die opsomming.

Submitted by Ricardo Barão (ricardorbarao@gmail.com) on 2015-10-22T17:20:08Z No. of bitstreams: 1 Ricardo Barão - Thesis - Br.pdf: 1029409 bytes, checksum: c798d4c5b758b979c5d388783dbf989a (MD5) / Approved for entry into archive by Ana Luiza Holme (ana.holme@fgv.br) on 2015-10-22T17:32:07Z (GMT) No. of bitstreams: 1 Ricardo Barão - Thesis - Br.pdf: 1029409 bytes, checksum: c798d4c5b758b979c5d388783dbf989a (MD5) / Made available in DSpace on 2015-10-23T11:42:00Z (GMT). No. of bitstreams: 1 Ricardo Barão - Thesis - Br.pdf: 1029409 bytes, checksum: c798d4c5b758b979c5d388783dbf989a (MD5) Previous issue date: 2015 / Este trabalho tem como objectivo compreender de que forma os investidores veem as energias renováveis: se as veem como parte do sector tecnológico, à espera de novos desenvolvimentos, ou como uma alternativa aos métodos existentes de produção de energia. Para responder a esta questão, foi desenvolvido um modelo de vectores autoregressivos com quatro variáveis de forma a se poder aplicar um Granger causality test e Impulse Response function. Os resultados sugerem que para o período de 2002-2007 à escala global ambas as hipóteses se confirmam, porém de 2009-2014 os resultados sugerem que os investidores não reconhecem as energias renováveis como um ramo do sector tecnológico, neste período. Para além disso, durante o período de 2009-2014, e quando comparados investidores Americanos com Europeus, os resultados sugerem que apenas o último identifica as energias renováveis como uma fonte viável para a produção energética. / This work aimed to understand the investor perception on clean energy: if it is seen as part of the technology sector, awaiting new developments, or as an alternative to the existing energy production methods. To answer this question, a four variable vector autoregression model was developed so that a Granger causality test and Impulse response function could be applied. The results suggest that while both hypotheses were confirmed worldwide for the period 2002-2007, from 2009 to 2014 results suggest that investors do not recognize the field of clean energy as part of the technology sector. Moreover, during the period that ranges from 2009 to 2014, and when comparing the American investor with the European investor, only the latter identifies renewable energy as a viable source of energy production.

Chapter 1: This paper offers new causal evidence on how the timing of prenatal temperature shocks affects fetal health, sex ratio at birth, and early-age human capital. Analyzing data on nearly 2 million live births from sub-Saharan African countries and exploiting exogenous spatial and temporal variation in monthly temperature, we uncover three findings. First, we find that a cold temperature shock decreases the likelihood of a male birth. This effect is non-linear, being larger in the first and third trimesters of pregnancy. It is also highly heterogeneous, being larger for older women, higher parity births, and rural areas. Second, combining our empirical estimates with a climate model, we find that the number of fetal deaths caused by climate change will rise from 200 to 400 per 100,000 live births by 2050 throughout sub-Saharan Africa. Third, in contrast to their differential effect on fetal mortality, prenatal temperature shocks increase infant mortality more for females than for males, suggesting that only healthier male fetuses survive to adverse in utero conditions. Our analysis implies that the design of policies to avert the negative impacts of climate change on children should account for stages of fetal development. Chapter 2: Despite its enormous individual and social costs; the fundamental and long- run causes of cognitive aging remain understudied. We study the causal effect of in-utero temperature exposure on cognition during old age. Combining unique data on South African adults between 40 and 99 years of age with geospatial information on historical temperatures, our identification strategy exploits exogenous, within-municipality-of-birth, month-to-month variations in temperature, and controls for contemporaneous weather and location at the time of survey administration. We find that temperature in the first trimester of pregnancy negatively affects the cognitive function score later in life, but temperature in the second and third trimesters has a positive effect on adults cognitive function score. These differing effects result in an overall U-shaped relationship between prenatal exposure to temperature and cognition. This non-linear relationship is robust across measures of memory, reasoning, and information processing speed. Our findings are consistent with the fetal programming theory, which holds that the first trimester of pregnancy is the most crucial window of brain formation. In accordance with this theory, brain development occurring in the first trimester of pregnancy would therefore have the highest vulnerability to external shocks. Heterogeneity analysis reveals that the effect of prenatal temperature on cognition is larger for men, individuals over 75 years of age, and individuals with low social capital. Analyzing causal mechanisms, we find that prenatal temperature affects key determinants of individuals' cognitive reserve. We also find that exposure to drought during the first trimester of pregnancy and reduced sleep during adulthood are other potential channels through which the effects of prenatal exposure to temperature operate. Chapter 3: A large literature seeking to understand the labor market impacts associated with the clean energy transitions broadly finds opposite effects. On the one hand, a net positive impact on the workforce i.e. the new green jobs created in renewable energy sectors will compensate for the jobs lost in fossil-fuel sectors, while on the other hand, the so-called regulated dirty energy sector will reduce the fraction of workers hired. However, empirical and simulation models typically ignore transitional impacts associated with environmental regulations on labour. These relate to how workers adjust over time to environmental regulations, not just the steady state impact that is the focus of prior studies. We evaluate an environmental regulation (Ontario coal-fired electricity generating plants phase-out) regarding its transitional and long-term impacts on employee's outcomes including (i) wages; (ii) unemployment insurance; (iii) sector mobility; and (iv) geographic location. Using the Longitudinal Worker File (LWF) and Postal Codes Conversion File (PCCF) maintained by Statistics Canada, we estimate the labor market impacts of clean energy policy by comparing employees from affected coal plants to a comparable group of employees from non-affected plants. We find that, workers exposed to Ontario phase-out coal policy have earned on average 7000 $ CAD yearly less compared to those who weren't exposed. Our findings are consistent across a set of alternative specifications and robustness checks. Moreover, results from the event study approach suggest that the regulation leads to labor costs with the de- cline of wages just in transition. We provide supportive evidence on large labor costs due to environmental regulation policy and shed lights on the importance of reforms and training programs to support workers during the transition.