Investment Scenarios Research Articles

Economic and environmental impacts of public investment in clean energy RD&D

Learning curve theory has been adopted for investigating the relationship between technological learning and technology cost developments. The aim of this paper is to explore the impacts of public investment in clean energy research, development, and demonstration (RD&D) on future technology cost developments by using a two-factor learning curve approach. Learning-by-deploying and learning-by-researching were chosen as the main sources of learning. The focus is on onshore wind and solar photovoltaics in the United States of America. By using publicly available data, we estimated learning-by-deploying rates of 31.4% and 27.6%; and learning-by-researching rates of 2.3% and 4.7% for onshore wind and solar PV, respectively. By adopting a logistic curve approach, an additional $1322 and $819 mil. were forecast to be spent by 2050 in RD&D for onshore wind and solar PV, respectively. We explored the plausible long-term effects of diverse RD&D investment scenarios on electricity generation and greenhouse gas (GHG) emissions using a system dynamics model. The findings reveal that public investment in RD&D for clean energy technologies may play a key role in the pace of capital cost reductions and technology diffusion. However, relatively little long-term effects of RD&D efforts alone were found on market dynamics and GHG emissions.

Analisis Return, Risk dan VaR Portofolio Saham JII dengan Metode SIM, MAD dan DD

Before pandemic, Islamic stocks performance (ISSI, JII70, JII) contracted. During pandemic, outperformed JCI and LQ45. JII prospect is good this year, increase 5.81% early 2021, exceeded JCI (4.66%) and LQ45 (4.75%) ytd. This study uses 4 investment scenarios aimed at analyzing and exploring the Return and Risk of the selected JII Portfolio using SIM, MAD, and DD Methods; perform calculations and analyze VaR of the selected JII Portfolio; calculate and analyze the relationship between Return and Risk of the selected JII Portfolio using SIM, MAD, and DD Methods; calculate and analyze the differences in Return and Risk of the selected JII Portfolio using the SIM, MAD, and DD Methods. The research methods are SIM, MAD, DD, VaR, Correlation-Test and Difference-Test. The results of the study of the highest return of each method resulted in scenario 2, the highest risk of each method resulted in a scenario of 33.3% investment proportion, the highest VaR resulted in scenario 2. Test-correlation method in calculating returns: there is no significant relationship between the SIM-MAD and DD-MAD methods, there is a significant positive relationship between the SIM-DD method.

Investment strategy for blockchain technology in a shipping supply chain

In the post-COVID-19 pandemic era, how to promote blockchain technology to improve the efficiency of port customs clearance and logistics transparency has become a hot research question in the shipping industry. In this paper, we investigate the value of blockchain-based vertical cooperation led by a port or a shipping company in a one-to-two shipping service competition model. A status quo scenario and two different investment scenarios led by different stakeholders are constructed, and equilibrium solutions of the Stackelberg game in three scenarios are proposed. Meanwhile, consumer surplus and social welfare under different cooperation frameworks are discussed. We find that i) investment in blockchain technology can significantly increase the profits of shipping supply chain participants. ii) From the point of view of profit, when the investment efficiency of the port and the shipping company satisfies a certain relationship, there is a balanced strategy for both parties to invest in blockchain technology. iii) The more intense the competition for the services of shipping companies, the lower the level of blockchain technology to improve the logistics capabilities of the shipping supply chain participants. iv) The port's investment in blockchain technology brings more consumer surplus and social welfare. The abovementioned findings can provide managerial insights for ports and shipping companies and present decision support for the government to formulate blockchain technology promotion policies.

A taxonomic evaluation of Indian mutual funds’ performance and its determinants – Post-pandemic

The COVID-19 pandemic has caused significant disruption in financial markets worldwide and impacted the performance of investment avenues like mutual funds. It has been a challenging scenario for all mutual funds to sustain the pre-pandemic performance. To understand the mutual fund investment scenario further, this study focused on examining the post-pandemic performance in the year 2021 of various categories of mutual funds, the significance of scheme characteristics in determining the performance, risk-adjusted performance, and outperformance of various categories of funds. Out of 4,305 mutual fund schemes, tax planning funds (58%), sectoral funds (57%), and equity diversified funds (55%) achieved better returns. Further, using the ordinary least squares (OLS) regression, the study estimated the effect of fund characteristics like scheme category, scheme type, scheme access type along with the fund’s tracking error and corpus size on funds’ return. The results show that tax planning, sectoral, and equity diversified funds significantly outperform. Tracking error significantly reduces the fund return by 4.52%. Scheme type, scheme access type, and corpus size were not significant. Equity, index, pension, and balanced category funds exhibit risk-adjusted performance, and only bond funds were able to outperform the respective benchmarks. The study adds to the existing literature by investigating the post-pandemic performance determinants of mutual funds.

Assessing the Socio‐Economic Effects of Carbon Capture, Utility and Storage Investment From the Perspective of Carbon Neutrality in China

AbstractCarbon Capture, Utility and Storage (CCUS) is essential for achieving carbon neutrality and has great development potential in China. CCUS, as a long‐term new investment, can address global warming and has significant social and economic impacts. This paper assessed the socio‐economic effects of CCUS investment based on carbon neutrality in China by combining the dynamic GTAP model and the Input‐output method. The result indicates that: CCUS investment may accumulate US$ 67.09 billion and US$ 776.61 billion from 2026 to 2030 and 2056 to 2060, respectively, based on International Energy Agency (IEA) investment scenario. Moreover, the corresponding value may increase to 8.26 billion and 743.21 billion US dollars from 2026 to 2030 and 2056 to 2060, respectively, based on Asian Development Bank (ADB) investment scenario; CCUS investment may stimulate gross value‐added of US$ 1.2 billion and US$ 10.4 billion based on ADB and IEA investment scenarios, respectively. CCUS investment may mainly promote the machinery industry, metal manufacturing industry, other service industries, power equipment manufacturing industry, and light processing manufacturing industry; Furthermore, ADB and IEA investment scenarios showed that CCUS industrial investment may indirectly create about 12,796 and 103,886 jobs, respectively, and US$ 85 million and US$ 692 million of labor employment income, respectively, in 2030. The corresponding values may increase to 0.82 million and 0.85 million jobs, respectively, and US$ 5,168 and US$ 5,396 million employment income, respectively, in 2060.

Social housing as infrastructure and the role of mission driven financing

Australia, like many other housing systems in Western Europe and the US, increasingly relies on private financing arrangements for social housing. It is spending more than ever before on demand side assistance, yet both the production of dedicated social housing and housing affordability are declining. From the perspective of needs-based social infrastructure, this paper presents the outcomes of research into the development of a more productive investment pathway. Multi-criteria evaluation and financial modelling compares and assesses the cost to government of five investment scenarios involving a range of debt, efficient financing and capital investment strategies. This research finds that, while current governments tend to favour private financing and facility lease arrangements, paying down private financing during operations is the least cost effective means for governments to subsidise social housing. Capital grant funding and land valuation policies are more cost effective in the medium and long term but require more active government involvement in needs based planning, strategic investment and regulation.

Low-Carbon Strategic Planning of Integrated Energy Systems

With the rapid promotion of renewable energy technologies and the trend to a low-carbon society, the positive impacts of an integrated energy system that realizes various forms of energy-utilizing improvement and carbon reduction have fully emerged. Hydrogen with a decarbonized characteristic being integrated into the integrated energy system has become a viable option to offset the intermittency of renewables and decline the fossil fuel usage. An optimal planning model of a wind–photovoltaic–hydrogen storage-integrated energy system with the objective of total economic and environmental cost minimization by considering various energy technology investments is proposed. Case studies are developed to compare the economic and environmental benefits of different energy investment scenarios, especially hydrogen applications. The cost–benefit analysis was carried out to prove that hydrogen investment is not a cost-competitive option but can alleviate the burden of carbon emissions somehow. Finally, sensitivity analysis of key parameters of sale capacity, carbon tax, and renewable penetration level was performed to indicate the rational investment for a wind–photovoltaic–hydrogen storage-integrated energy system.

Spotlight Personnel: How Hiring and Turnover Drive Service Performance Versus Demand

In many sectors of the entertainment industry, a few employees attract the public spotlight when performing the core service. For example, in professional team sports, a team of players competes in games, and in TV shows, a cast of artists acts in different episodes. These employees, coined “spotlight personnel,” are an essential but expensive element of ongoing service delivery. Despite their importance and cost, very little is known about how changes in spotlight personnel affect service performance and demand. To address this gap, this article uses unique data on professional German soccer teams, tracking the quantity (number of players) and quality (average transfer price) of spotlight personnel hiring (incoming transfers) and turnover (outgoing transfers), objective service performance (winning percentage), and demand (ticket sales) across four decades, using both traditional and novel time series methods. The results show that service performance and demand are primarily affected by spotlight personnel hiring rather than by turnover. Hiring quantity decreases service performance yet increases demand, whereas hiring quality benefits both service performance and demand. The analysis further uncovers that these effects are subject to dynamic interactions and nonlinearities. Investment scenarios showcase how understanding these effects can substantially improve managerial decision making.

Scenarios of the Foreign Investments in the Sectors and Areas Promoting Development of the Tourism Sector

The role of direct investments is important for the development of the fields promoting the tourism sector. The aim of the article is to assess, based on the examples of other countries, what field of the tourism sector needs development and what methods could be applied in Georgia for its promotion. How can tax liberalism promote such a hotel direction as “apart -hotel” status which is growing despite the COVID situation. By investing in apart-hotel, a person receives not only a highly profitable investment asset, but also a flexible financial instrument. The analyses of various investment scenarios will reveal the model of efficient use of the country’s investment and resource potential which will be aimed at the development of the sector via investment in the field development promoting the tourist sector development.

Stumpage Price Distributions and Correlations and Their Impact On Timberland Investment Modeling: An Analysis Using Maine Stumpage Prices (1961–2017)

Abstract This paper analyzes more than 55 years of Maine stumpage prices and finds that the normal distribution does not best characterize many of the primary species and products located in the state. Nontrivial correlations are also identified among many of the species and product stumpage prices. The implications of these findings are discussed for the value of species and age diversification and the use of financial simulations to assess projected return distributions from timberland investments. Specifically, we look at two hypothetical timberland investment scenarios with varying amounts of species and age diversification and demonstrate the differences in the projected return distributions timber analysts would obtain with simple (normal distribution and independence) versus data-based (best-fit distributions and correlations) assumptions.

How to de-bias investment judgements–unpacking bias and possible remedies in a capital investment context

PurposeResearch on biases in investment decision-making is indubitably important; however, studies in this context are relatively scarce. Unpacking bias has received attention in the psychological literature yet very little attention from management accounting research. This bias suggests that the perceived probability that an event will occur generally increases when the event's description is unpacked into a disjunction of subevents. The authors hypothesize that for a capital investment decision context, managers' judgement of the probability of a future event depends on whether the event is described as one packed event or is unpacked into several disjoint subevents. Additionally, the authors propose that altering the format of the description of an event's occurrence from percentage values to relative frequencies reduces unpacking bias.Design/methodology/approachTo test the study’s hypotheses, the authors conducted two experiments based on a 3 × 2 mixed experimental design in which manager participants were asked to estimate the failure probabilities of technical systems in the context of an investment decision.FindingsThe authors provide evidence that unpacking bias occurs in an investment scenario, which can be characterized as a high-stakes decision context. Changing the format in which probabilities are presented from percentage values to relative frequencies significantly reduces the bias.Research limitations/implicationsAdditional instructions did not further reduce unpacking bias.Practical implicationsFor investment decisions under uncertainty, performance indicators in management templates should be presented in relative frequencies to improve managerial decision-making. The fact that the authors could not show an additional effect of instructions in management accounting reports indicates that it is challenging for management accountants to reduce the biased decision-making of managers by “teaching” them through the provision of instructions.Originality/valueThe authors contribute to accounting research by illustrating unpacking bias and by deriving a debiasing mechanism in a capital investment decision context.

A two-stage joint operation and planning model for sizing and siting of electrical energy storage devices considering demand response programs

This study describes a computationally efficient model for the optimal sizing and siting of Electrical Energy Storage Devices (EESDs) in Smart Grids (SG), accounting for the presence of time-varying electricity tariffs due to Demand Response Program (DRP) participation. The joint planning and operation problem for optimal siting and sizing of the EESD is proposed in a two-stage optimization problem. In this regard, the long-term decision variables deal were the size and location of the EESDs and have been considered at the master level while the operating point of the generation units and EESDs is determined by the slave stage of the model utilizing a standard mixed-integer linear programming model. To examine the effectiveness of the model in the slave sub-problem, the operation model is solved for different working days of different seasons. Binary Particle Swarm Optimization (BPSO) and Binary Genetic Algorithm (BGA) have been used at the master level to propose different scenarios for investment in the planning stage. The slave problem optimizes the model in terms of the short-term horizon (day-ahead). Additionally, the slave problem determines the optimal schedule for an SG considering the presence of EESD (with sizes and locations provided by the upper level). The electricity price fluctuates throughout the day, according to a Time-of-Use (ToU) DRP pricing scheme. Moreover, the impacts of DRPs have been addressed in the slave stage. The proposed model is examined on a modified IEEE 24-Bus test system.

Correcting market failure? Stalled regeneration and the state subsidy gap

This paper develops the neologism state subsidy gap to underscore the necessity of state intervention in the formation and potential closure of rent gaps. The state subsidy gap is the economic gap that must be bridged by the state to make a currently unviable urban investment scenario potentially profitable for private developers. The pertinence of this conception is particularly apparent in old industrial, relatively impoverished cities where global capital is less likely to dump its surpluses with secure expectation of profitable returns. The issue is exacerbated in economically risky neighbourhoods encompassing fragmented land ownership, poor infrastructure and large-scale areas of urban devalorisation. Such conditions necessitate substantial derisking public intervention if ‘market failure’ is to be addressed—yet success is never guaranteed and is far from universal. It is argued that much closer attention to the stalling, interruption or failure of urban regeneration projects is imperative given the extent of public expenditure and the limited social outcomes arising from attempts to correct market failure. Here, the concept of the state subsidy gap shows its value, shedding light on unjust social outcomes, exposing capitalism’s inherent vulnerabilities, and illustrating the dependence of private capital on public interventions for its reproduction.

Strategic digital shipbuilding project portfolio configuration and optimisation

Program portfolio managers in digital transformation projects need knowledge that can guide allocation decisions associated with the configuration of project assets within the sustainable and strategic objectives of the firm. This research aims to propose a framework capable of optimising the cost-benefit adjustments from assessing investment risks of digital transformation projects such as cybersecurity projects. The context considers the innovative sector of military shipbuilding and repair. Our approach uses an artificial neural network (ANN) and Monte Carlo simulation modelling to capture risk effects and quantify investment priorities. This method enables the application of portfolio management theory principles to measure and optimise the performance of the digitalisation project portfolio. The framework's utility is discussed using a hypothetical case study presenting several digital transformation project investment scenarios.

Points of Consideration on Climate Adaptation of Solar Power Plants in Thailand: How Climate Change Affects Site Selection, Construction and Operation

Solar energy is planned to undergo large-scale deployment along with Thailand’s transformation to a carbon neutral society in 2050. In the course of energy transformation planning, the issue of energy infrastructure adaptation to climate change has often been left out. This study aims to identify climate-related risks and countermeasures taken in solar power plants in Thailand using thematic analysis with self-administered observations and structured interviews in order to propose points of consideration during long-term energy planning to ensure climate adaptation capacity. The analysis pointed out that floods and storms were perceived as major climate events affecting solar power plants in Thailand, followed by lightning and fires. Several countermeasures were taken, including hard countermeasures that require extensive investment. Following policy recommendations were derived from the climate-proofing investment scenario study. Policy support in terms of enabling regulations or financial incentives is needed for implementation of climate-proofing countermeasures. Public and private sectors need to secure sufficient budget for fast recovery after severe climate incidents. Measures must be taken to facilitate selection of climate-resilient sites by improving conditions of power purchase agreement or assisting winning bidders in enhancing climate adaptability of their sites. These issues should be considered during Thailand’s long-term energy planning.

Концепції державної політики розвитку “зеленої” економіки: еволюція, сутність, цілі та принципи

Досліджено сутнісні теорії розвитку “зеленої” економіки, які обумовлені неможливістю задоволення нескінченно зростаючих потреб людства в умовах обмеженості ресурсів. Запропоновано визначення терміна “зелена економіка” та виконано порівняльну характеристику концепції “зеленої” економіки, визначено її цілі та принципи. Акцентовано увагу, що модель “зеленої” економіки нормалізує взаємодію людської діяльності і природи. Узагальнюючи існуючі підходи до формування концепції “зеленої” економіки, виокремлено її головні напрямки: екологічний, економічний і соціальний.

The Gerber Statistic: A Robust Co-Movement Measure for Portfolio Optimization

The purpose of this article is to introduce the Gerber statistic, a robust co-movement measure for covariance matrix estimation for the purpose of portfolio construction. The Gerber statistic extends Kendall’s Tau by counting the proportion of simultaneous co-movements in series when their amplitudes exceed data-dependent thresholds. Because the statistic is not affected by extremely large or extremely small movements, it is especially well suited for financial time series, which often exhibit extreme movements and a great amount of noise. Operating within the mean–variance portfolio optimization framework of Markowitz, we consider the performance of the Gerber statistic against two other commonly used methods for estimating the covariance matrix of stock returns: the sample covariance matrix (also called the <i>historical covariance matrix</i>) and shrinkage of the sample covariance matrix given by Ledoit and Wolf. Using a well-diversified portfolio of nine assets over a 30-year period (January 1990–December 2020), we find, empirically, that for almost all investment scenarios considered, the Gerber statistic’s returns dominate those achieved by both historical covariance and by the shrinkage method of Ledoit and Wolf.

Future-Generation Perception: Equal or Not Equal? Long-Term Individual Discount Rates for Poland

Energy-related investments gain increasing attention nowadays, particularly in Poland due to clean-energy investment needed to limit greenhouse gas emissions (GHG) and counteract climate change. However, economic appraisal is problematic: the longevity of impacts inextricably involves intergenerational ethical considerations. A crucial parameter is the choice of a discount rate. The predominant approach to estimate the discount rate in EU countries is the Ramsey rule, based on macroeconomic data, but not referring directly to society’s preferences. Those are considered by studies using surveys to elicit individual discount rates (IDR), but rarely concentrating on intergenerational time frame. The paper aims at delivering an insight into the intergenerational intertemporal preferences for Poland (households, n = 471) focusing on whether respondents are willing to declare zero discount rate intergenerationally and whether their choices differ between the short- and long-term perspectives and between human lives and money. To elicit IDR, two hypothetical investment scenarios were designed: lifesaving programs and lottery gains with delays from 10 to 150 years accompanied by attitude and socioeconomic questions. The results indicate that IDR follows hyperbolic time-decline, and a considerable share of respondents (around 20%) are willing to treat future generations as equally important in the case of human lives, while this proportion for monetary gains is two times lower. The IDR drivers differ between lives and money in respect of socioeconomic profile and attitude characteristics as well as between intragenerational and intergenerational time frames. The findings support (a) the rationale for distinct treatment of intergenerational allocations, (b) the divergence of preferences between public and private impacts, and (c) the switch from single to declining discount rate regime in Poland.

Impact of COVID-19 on FDI flows: developing investment scenarios for Brazil

Impact of COVID-19 on FDI flows: developing investment scenarios for Brazil

Residential Construction with a Focus on Evaluation of the Life Cycle of Buildings

The article focuses on highlighting the role of life cycle costing (LCC) in the preparatory and implementation phase of residential projects. It involves the evaluation of several investment scenarios in the pre-investment phase, the choice between variants of the design of the entire building or its parts, and the choice of variants of structures and equipment with acceptable parameters. An innovative method of evaluating the life cycle of buildings is described in the article. This method was tested in selected residential projects realized by Skanska in the Czech Republic. Experience from construction practice shows that the choice of variants, constructions, or equipment of buildings only on the basis of the lowest acquisition costs (lowest bid prices) is wrong. The LCC calculation tool has been designed to model life cycle costs of individual variants of construction designs with different input parameters. It is possible to analyze the components or equipment that have the greatest impact on total life cycle costs. The article presents a tool that evaluates the long-term economic efficiency of the proposed residential buildings in terms of analysis of life cycle costs. The article will also expand the knowledge of the professional and general public about the importance of examining investment and operating costs already in the phase of construction preparation.