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Synopsis This paper reviews the nature of investment problems in energy conservation and presents two broad propositions:

There is no lack of energy sources in Africa ‐ especially fossil fuels ‐ however many countries in Sub‐Saharan Africa continue to be plagued by energy shortages. This can seriously impede productivity particularly in SME’s and add to energy costs through the need for investment in own generating capacity. In addition the transmission systems are often expensive due to ‘down time’ and this also raises production costs. It also raises costs for households that are effectively forced to generate their own power. This chapter examines three dimensions of the energy ‘gap’ in the context of a number of countries. First, will investment in energy capacity lead to sustainable GDP growth? Second, would investment in renewable or ‘green’ energy capacity make a significant difference? And third, is energy output really such an essential prerequisite for sustainable economic growth?

This study aims to explore the impact of energy investment on economic growth. Specifically, the study investigates the impact of energy consumption, foreign investment, infrastructure development, tax revenue, human capital, international tourism revenue and trade volume on economic growth.

To achieve the aim, the authors sample the 24-years (1996–2019) financial statistics of BRICS countries. Given the econometric recommendations supplemented by the Johnsen cointegration test, the current study uses the fully modified ordinary least square model for regression analysis and checks the robustness through robust least square model.

The statistical analysis shows a direct impact of energy investment on economic growth. In addition, the statistical results indicate a positive impact of energy consumption, foreign investment, infrastructure development, tax revenue, human capital and trade volume on economic growth.

The results present practical implications for policymakers regarding the adequate investment in energy production that can further promote the economic growth in BRICS countries. Policy officials should enhance the volume of renewable energy production, foreign investment and tax revenue. Additionally, it is equally suggested to policymakers regarding the development of infrastructure and human capital to ensure economic growth.

This study supplements the novel and robust evidence on investment in energy-leading economic growth.

Improving the energy efficiency of the existing residential building stock has been identified as a key policy aim in many countries. The purpose of this paper is to review the extant literature on investment decisions in domestic energy efficiency and presents a model that is both grounded in microeconomic theory and empirically tractable.

This study develops a modified and extended version of an existing microeconomic model to embed the retrofit investment decision in a residential property market context, taking into account tenants’ willingness to pay and cost-reducing synergies. A simple empirical test of the link between energy efficiency measures and housing market dynamics is then conducted.

The empirical data analysis for England indicates that where house prices are low, energy efficiency measures tend to increase the value of a house more in relative terms compared to higher-priced regions. Second, where housing markets are tight, landlords and sellers will be successful even without investing in energy efficiency measures. Third, where wages and incomes are low, the potential gains from energy savings make up a larger proportion of those incomes compared to more affluent regions. This, in turn, acts as a further incentive for an energy retrofit. Finally, the UK government has been operating a subsidy scheme which allows all households below a certain income threshold to have certain energy efficiency measures carried out for free. In regions, where a larger proportion of households are eligible for these subsidies,the authors also expect a larger uptake.

While the financial metrics of retrofit measures are by now well understood, most of the existing studies tend to view these investments in isolation, not as part of a larger bundle of considerations by landlords and owners of how energy retrofits might influence a property’s rent, price and appreciation rate. In this paper, the authors argue that establishing this link is crucial for a better understanding of the retrofit investment decision.

Recent findings from a monitor containing around 1.5 million homes in the Dutch non-profit rental sector show that the improvement of the energy performance of the respective homes is mostly carried out in small steps: single measures per dwelling dominate and deep energy renovations are rare. From the way in which housing providers conceive and implement their portfolio and asset management strategies, the purpose of this paper is to explain for the dominance of the small interventions and investigate the argument for a more concentrated allocation of budget resources.

In total, 12 housing providers with different energy investment policies were selected and interviewed.

Results show that energy investments, as most other investments, must fit in regular investment schemes and have to follow general decision criteria such as the lifespan of the respective building element and the market position of the respective dwelling. As these schemes are limited in budget and time, the room for a more concentrated allocation of budget resources is small.

The number of organisations interviewed is obviously not statistically representative, but gives a good indication of the investment planning practice in the Dutch non-profit housing sector.

Much has been written about the (slow) progress of the energy performance in the housing sector, but not about the more structural organisational forces behind this progress.

Rapidly increasing the proportion of installed wind power capacity with zero carbon emission characteristics will help adjust the energy structure and support the realization of carbon neutrality targets. The intermittency of wind resources and fluctuations in electricity demand has exacerbated the contradiction between power supply and demand. The time-of-use pricing and supply-side allocation of energy storage power stations will help “peak shaving and valley filling” and reduce the gap between power supply and demand. To this end, this paper constructs a decision-making model for the capacity investment of energy storage power stations under time-of-use pricing, which is intended to provide a reference for scientific decision-making on electricity prices and energy storage power station capacity.

Based on the research framework of time-of-use pricing, this paper constructs a profit-maximizing electricity price and capacity investment decision model of energy storage power station for flat pricing and time-of-use pricing respectively. In the process, this study considers the dual uncertain scenarios of intermittency of wind resources and random fluctuations in power demand.

(1) Investment in energy storage power stations is the optimal decision. Time-of-use pricing will reduce the optimal capacity of the energy storage power station. (2) The optimal capacity of the energy storage power station and optimal electricity price are related to factors such as the intermittency of wind resources, the unit investment cost, the price sensitivities of the demand, the proportion of time-of-use pricing and the thermal power price. (3) The carbon emission level is affected by the intermittency of wind resources, price sensitivities of the demand and the proportion of time-of-use pricing. Incentive policies can always reduce carbon emission levels.

This paper creatively introduced the research framework of time-of-use pricing into the capacity decision-making of energy storage power stations, and considering the influence of wind power intermittentness and power demand fluctuations, constructed the capacity investment decision model of energy storage power stations under different pricing methods, and compared the impact of pricing methods on optimal energy storage power station capacity and carbon emissions.

1. Electricity pricing and capacity of energy storage power stations in an uncertain electricity market.

2. Investment strategy of energy storage power stations on the supply side of wind power generators.

3. Impact of pricing method on the investment decisions of energy storage power stations.

4. Impact of pricing method, energy storage investment and incentive policies on carbon emissions.

5. A two-stage wind power supply chain including energy storage power stations.

Electricity pricing and capacity of energy storage power stations in an uncertain electricity market.

Investment strategy of energy storage power stations on the supply side of wind power generators.

Impact of pricing method on the investment decisions of energy storage power stations.

Impact of pricing method, energy storage investment and incentive policies on carbon emissions.

A two-stage wind power supply chain including energy storage power stations.

The authors analyse the interactive influence of energy use, capital investment and finance on pollution in energy-dependent African countries.

The study analyses data from 5 selected energy-dependent African nations (i.e. Algeria, Egypt, Nigeria, Morocco and South Africa) between 1981 and 2020 using the fully modified ordinary least squares (FMOLS) approach.

The panel result reveals that capital investment and energy interaction and financial development and capital investment moderation reduce pollution in all the countries. However, for country-specific results, the interaction of investment and energy lowers emissions in Algeria, South Africa, Nigeria and Morocco but increases pollution in Egypt. Similarly, except for Egypt, financial development and capital investment interaction offset pollution in Algeria, Nigeria, South Africa and Morocco.

The limitation of the study stems from the inability to extend the scope to cover the entire African region. However, the fact that the authors selected the most prominent African nations in the sample to enable us to set the template for other smaller nations to follow makes the study tenable in its present form.

Energy-dependent African countries should invest in eco-friendly machines, technologies and equipment to lower pollution vis-à-vis production expansion.

The present research is more expansive by combining the finance and capital investment channels in the quest for decarbonising emerging African nations. Moreover, this is a comparative study, unlike past studies that mainly deploy a one-size-fits-all approach.

Most of the European apartment blocks are rental units of which the majority needs major refurbishments in upcoming years to achieve climate goals. On the other hand, it is still difficult for property owners to evaluate the profitability of energetic retrofitting investments. The purpose of this paper is to contribute to the situation by forming a standardized framework and tool to calculate profitability of energy efficiency investments throughout Europe.

From a European perspective, several different areas of interest (technical, legal, institutional and financial) have been screened to develop an extensive compendium. This has been performed by literature research and several national surveys. Based on these findings, an online-based tool for profitability calculation has been developed to support the decision-making process of each individual, regardless his knowledge on energy efficiency.

This paper provides a short overview on main investment barriers in Germany. It is found that both market conditions and information deficits harm energy efficiency investments. Frequently, the decision-making process is found difficult due to inflexible regulations and lack of knowledge. This dramatically reduces market incentives that are already in place. Most often, the investor user dilemma is seen as the main investment obstacle. In this context, transparency and reliability are found to trigger energy-efficient investments.

Findings are used to identify best practice examples and to assess their transferability to other markets and countries. Innovative solutions have been extracted to improve the overall investment climate.

The paper contributes to a sound foundation for energy-related investments and the fulfillment of EU reduction targets.

Recent research on the energy system highlights the need for understanding the bandwidth of drivers and inhibitors of household investor's behaviour in rooftop PV (or photovoltaic power system) and to fit the broader socio-economic context in which they are deployed. However, apart from few exceptions, these newer perspectives have not been duly applied in the research on rooftop PV. This paper aims to fill this gap and to shed new light on rooftop PV investment decisions.

This study has been conducted with the primary data collected using two data sets of 237 households and 387 households of Indian southern state Kerala using survey-based questionnaire. The findings from first data set revealed that households considering the adoption of PV were likely influenced by six distinct factors, three motivators and three inhibitors. Second data set for multi-state analytic approach was proposed whereby the research model was tested using structural equation modelling (SEM). The outcomes of SEM were used as inputs for an artificial neural network (ANN) model for forecasting investor investment decision in in renewables. The ANN model was also used to rank the relative influence of significant predictors obtained from SEM.

In line with the risk–return framework, government subsidies act as primary motivator which helps in overcoming the initial risk of investment in the new technology. Further, low prices and low cost of maintenance are some of the financial motivators which may likely mitigate the long-term apprehension of returns and maintenance cost. Lastly, the strongest motivators of PV investment come from the environmental and financial motivator in the form of PV subsidies, which further solidifies the role of policy interventions in investment decision. The ANN model identified the technical barrier and knowledge and awareness factors play a significant role in forcasting the investor investing decision.

The study results will be useful for policymakers for framing strategies to attract and influence their investment in renewable energy.

Building upon behavioural finance and institutional theory, this paper posits that, in addition to a rational evaluation of the economics of the investment opportunities, various non-financial factors affect the household's decision to invest in renewables.

The purpose of this paper is to describe a tool that supports an investment strategy aimed at improving the energy performance of existing buildings. It is particularly aimed at large building portfolios, such as encountered on university and corporate campuses, where typically a plethora of potential refurbishment interventions are candidates for a greening effort.

The investment optimization strategy is implemented in a web‐based software tool. Under a chosen financial constraint and investment time horizon, the tool empowers campus facility management to make the difficult “greening” decisions as part of their continuous building commissioning. The tool calculates and accepts user data that reflect different types of risks, posed by uncertainties in investment costs, energy performance, and energy cost scenarios. In addition, decision makers (DMs) can set different investment priorities, reflecting their financial risk attitude and commitment to “greenness”.

The tool helps DMs determine the best investment options from a set of available energy efficiency improvement options in the light of expected long range energy costs. It will enable the choice of the optimal mix of technologies and buildings within a given budget limit and predict the long‐term monetary as well as “green” return on investment.

The tool has been tested on a portfolio of campus buildings, but needs further validation with a larger set of buildings in a real life campus management setting. The tool can become a trusted instrument in the hands of portfolio managers faced with the problem to select the optimal mix of technologies, and buildings within the given budget. It should be noted that “investment returns (IRs)” and “commitment to greenness” are just two elements considered in the broader decision making framework of portfolio energy management.

The investment tool can provide an essential instrument for campus managers who are faced with the task to refurbish buildings in their portfolio to increase their energy performance. In the current business culture of campus management, the decision to investment in energy savings needs to be weighed against competing initiatives that target greener campuses. The target of the research was to develop an instrument that can help DMs to verify rapidly what can be achieved if a budget line item of, say $10 million would be added to the campus budget for energy performance improvements.

The research output from this paper is valuable for continued efforts in the development of indicators that measure “IRs” and “commitment to greenness”. Other elements that impact portfolio decision making can be identified in a common decision framework of which the investment tool will become an integral part over time.