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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?

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.

This study aims to investigate the effect of oil prices, economic growth and information communication technology (ICT) on investment into renewable energy transition (RET).

Based on six selected African countries (i.e. Algeria, Egypt, Angola, Ethiopia, South Africa and Nigeria), the study uses a nonlinear autoregressive distributed lag model over the period from 1995 to 2020.

The results show that increasing oil prices, by substitution effect, leads to increasing RET investment, while declining oil prices lead to decreasing RET investment in the short and long run. Furthermore, the results reveal that increasing real gross domestic product leads to increased RET investment, while declining real gross domestic product (GDP) leads to decreasing RET investment both in the short and long run. Simultaneously, the study shows that increasing ICT has a significant and positive impact on RET investment, while declining ICT has a significant negative impact on RET investment in the short and long run.

The findings of this study have advanced the understanding of which factors significantly influence RET investment and the need to concentrate efforts on strategically addressing those factors. The findings indicate that these countries are at the progressive stage in terms of renewable energy; though increasing oil prices contribute to rising RET investment, the countries can be more proactive by improving the full potential of ICT as well as facilitating the growth of their economies.

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.

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.

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.

The purpose of this study is to deploy and expand the theory of planned behaviour (TPB) model with application to renewable energy investment by incorporating the component of tax incentives (TIN). This will serve as an additional measure in understanding the conventional energy stakeholders’ investment intention into renewable energy in Nigeria.

Data was collected from 357 individual key conventional energy stakeholders in Nigeria using survey questionnaires. The research model was tested using structural equation modelling.

The results from the study revealed the applicability of the TPB in predicting the conventional energy stakeholders’ investment intention into renewable energy. The result indicates that attitude and subjective norm are significantly associated with investment intentions.

The outcome implies that the integration of tax incentives can improve the predictive power of the model as the introduced variable demonstrates a significant impact on the conventional energy stakeholders’ investment intention into renewable energy.

This study extends on the well-established TPB model by integrating tax incentives in understanding investment intentions and the outcome implies a significant association of tax incentives with investment intention and moderated the influence of attitude and subjective norm over the conventional energy stakeholders’ investment intention.

TPB has been widely deployed and even extended to predict intention in numerous fields of study. Available literature presents the lack of such empirical research that focuses on investment in Nigeria and specifically regarding energy investment. The outcome highlighted the significant influence of tax incentives, thus the need for policymakers to suggest and implement various tax incentives to attract private investment into renewable energy for electricity generation that will consequently assist in achieving SDG-7 and mitigate climate change.

The purpose of this paper is to analyze the effects of investment growth in energy sectors of western areas of China on the local economy and emission of carbon dioxide (CO₂).

The paper is based on a two‐region, ten‐sector recursive dynamic computable general equilibrium model which is based on the input‐output table of Shaanxi Province for 2002.

Three different scenarios are considered in a static analysis where the investment in the energy sector of western areas is increased at the rate of 20, 40 and 60 per cent. The changes of some macro‐economic variables are simulated under these scenarios. The long‐term effects on GDP and emission of CO₂ in different scenarios are also simulated. The results show that the GDP growth is 0‐8.92 per cent, households disposable income growth is 0‐8.94 per cent, and emission of CO₂ growth is 0‐11.10 per cent when the investment grows between 0 and 60 per cent. The oil and gas sector is the most effective sector whose growth rate is 0‐19.47 per cent. The effects of investment growth in base period are relatively big but weaken gradually over time in the long‐run.

The paper is of value in highlighting the importance (for policy makers) of considering the development and application of low‐emission technologies to prevent further environmental degradation.

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.