Economic viability of building energy efficiency measures: a review on the discount rate

How does the issue of the discount rate intersect the research on building energy efficiency and the topics into which it has branched? This contribution tries to answer the previous question through a comprehensive review of related studies. Those studies usually rely on two alternative assumptions. The first refers, explicitly or implicitly, to the notion of cost of capital and, hence, to the position of private stakeholders involved in the decision processes focusing on the adoption of energy-efficient measures in buildings. The second assumption relates to the notion of the social discount rate, which is meant to pursue intergenerational equity and environmental sustainability. As far as the results are concerned, the literature agrees that the discount rate is among the key parameters\u2014possibly the most prominent\u2014affecting the evaluation. However, despite the crucial role it plays, its calculation seldom relies on acknowledged methods and models. Furthermore, data sources sometimes lack consistency and accuracy. Some guidance and suggestions are provided as to the improvement of the discount rate estimation

Business as Usual with Article Processing Charges in the Transition towards OA Publishing : A Case Study Based on Elsevier

This paper addresses the topic of the article processing charges (APCs) that are paid when publishing articles using the open access (OA) option. Building on the Elsevier OA price list, company balance sheet figures, and ScienceDirect data, tentative answers to three questions are outlined using a Monte Carlo approach to deal with the uncertainty inherent in the inputs. The first question refers to the level of APCs from the market perspective, under the hypothesis that all the articles published in Elsevier journals exploit the OA model so that the subscription to ScienceDirect becomes worthless. The second question is how much Elsevier should charge for publishing all the articles under the OA model, assuming the profit margin reduces and adheres to the market benchmark. The third issue is how many articles would have to be accepted, in an OA-only publishing landscape, so that the publisher benefits from the same revenue and profit margin as in the recent past. The results point to high APCs, nearly twice the current level, being required to preserve the publisher\u2019s profit margin. Otherwise, by relaxing that constraint, a downward shift of APCs can be expected so they would tend to get close to current values. Accordingly, the article acceptance rate could be likely to grow from 26\u201327% to about 35\u201355%

Economic parameters in the evaluation studies focusing on building energy efficiency : a review of the underlying rationale, data sources, and assumptions

A growing literature has highlighted the variables and parameters that most affect the technical feasibility and the economic viability of the measures meant to improve building energy efficiency. This paper discusses the results of a literature review, which focuses on the studies that deal with three economic parameters: the price to be paid for the energy supply, the energy inflation rate, and the discount rate used to convert future cash flows to a present value, namely, an upfront lump-sum equivalent. A specific co-occurrence analysis of terms is performed on the titles and abstracts of the examined documents. The representation of the results allows recognizing several significant clusters and network relationships. Moreover, that literature review enables to identify two well-established research strands. The first involves the relationship between energy prices and the profitability of efficiency-related investments. The second research branch points at the pivotal role played by the discount rate when evaluating the investments in energy-efficient measures

A Discounted Cash Flow variant to detect the optimal amount of additional burdens in Public-Private Partnership transactions

The Discounted Cash Flow method is a long since well-known tool to assess the feasibility of investment projects, as the background which shapes a broad range of techniques, from the Cost-Benefit Analysis up to the Life-Cycle Cost Analysis. Its rationale lies in the comparison of deferred values, only once they have been discounted back to the present. The DCF variant proposed here fits into a specific application field. It is well-suited to the evaluations required in order to structure equitable transactions under the umbrella of Public-Private Partnership. •The discount rate relies upon the concept of expected return on equity, instead than on those of weighted average cost of capital, although the latter is the most common reference within the scope of real estate investment valuation.•Given a feasible project, whose Net Present Value is more than satisfactory, we aim to identify the amount of the additional burdens that could be charged to the project, under the condition of keeping the same economically viable.•The DCF variant essentially deals with an optimization problem, which can be solved by means of simple one-shot equations, derived from financial mathematics, or through iterative calculations if additional constraints must be considered

Robust space-time modeling of solar photovoltaic deployment

Solar photovoltaic (PV) has established itself as a fairly promising, fast-growing renewable energy source. The main determinants of solar PV deployment are thought to be physical and climatic factors - such as latitude and solar irradiance, not to mention terrain and built environment features - as well as socio-economic drivers - such as population density, household size, and education level. Besides, peer effects and neighborhood effects are found to affect the willingness to adopt solar photovoltaic systems strongly. This study aims to set up robust space-time models, which enable us to investigate the drivers of solar PV deployment using fine-grained spatial and temporal data. We use space-time auto-regressive models (STAR) with several exogenous covariates that are expected to explain the installed solar PV capacity. STAR models require the specification of spatial weight matrices (W). As in regular lattice data, we select causal (lower triangular) W matrices so that the consistency of least-squares (LS) estimators is warranted. We show that they can be extended to robust LS estimators, which are necessary because of strong outlier contamination. Models are tested on the Italian municipal data of residential and industrial PV plants installed under the support schemes in force between 2006 and 2011. Empirical results confirm the important role played by the space-time dynamic components. Significant exogenous predictors are found in the domains of the physical features (elevation and land area), demography (population), built environment (residential buildings), and socio-economic aspects (income, employment rate, commuter workers). (C) 2021 Published by Elsevier Ltd

solar photovoltaic energy and its spatial dependence

Abstract In the last decade, solar photovoltaic has started to play a significant role in the energy mix consumption. Although this growth has involved almost all the western countries, marked differences in the regional distribution of photovoltaic generation capacity have been observed. These differences appear to be weakly related to climate conditions in general, and to solar radiation specifically. The literature has started to investigate the other underlying determinants, suggesting to consider the occurrence of spatial proximity effects. Accordingly, this study aims to analyze whether and to what extent the photovoltaic energy production depends on local factors, such as climate, demand, income, innovative and responsible behavior, and so forth. Through a spatial autoregressive model, we find that the regional distribution of photovoltaic production capacity is affected by strong spatial dependence. We show that the availability of photovoltaic energy may be explained by peer effects, such as diffusion of habits and emulation of neighbors

Real estate market and building energy performance: Data for a mass appraisal approach

Mass appraisal is widely considered an advanced frontier in the real estate valuation field. Performing mass appraisal entails the need to get access to base information conveyed by a large amount of transactions, such as prices and property features. Due to the lack of transparency of many Italian real estate market segments, our survey has been addressed to gather data from residential property advertisements. The dataset specifically focuses on property offer prices and dwelling energy efficiency. The latter refers to the label expressed and exhibited by the energy performance certificate. Moreover, data are georeferenced with the highest possible accuracy: at the neighborhood level for a 76.8% of cases, at street or building number level for the remaining 232%. Data are related to the analysis performed in Bonifaci and Copiello [1] about the relationship between house prices and building energy performance, that is to say, the willingness to pay in order to benefit from more efficient dwellings

The Price Premium in Green Buildings: A Spatial Autoregressive Model and a Multi-Criteria Optimization Approach

The energy issue has given rise to a prolific research field, which branches into several strands. One of these strands focuses on the role played by building energy features in shaping property prices. Indeed, market players are expected to show a higher willingness to pay for building units characterized by higher energy performance. The study of the so-called price premium for building energy efficiency has flourished in the last decade or so; plenty of evidence is now available concerning its occurrence, although its magnitude is still debated. The literature relies on the methodological frameworks of statistical modeling and multiple regression, primarily employing hedonic price models. Lately, spatial autoregressive models have also been adopted. Here, we propose to deal with estimation of the price premium by adopting an innovative perspective. In particular, we use a methodological framework in which regression models are complemented with a multi-criteria optimization approach. Using a spatial autoregressive model first, and with D as the reference energy rating band, we find the following price premiums: 55% for A4, 42% for A3 to A, 20% for B or C, -14% for F, and -29% for G. The multi-criteria optimization approach proves efficient in estimating the price premium. The estimates above are essentially confirmed: the results converge for all the energy rating bands except for G

Economic development and climate change. Which is the cause and which the effect?

Energy efficiency has established as a trending topic in scholarly research in the last four decades. Lately, the purpose of that research strand has broadened so to tackle the increase of greenhouse gas emissions and the issues related to climate change. Human beings and their mass production and consumption activities are thought to be a primary source of climate-altering emissions. However, that assumption has been seldom tested. Here we aim to provide a methodological and empirical framework to check for the causal nexus that allegedly ties together demographic growth, economic development, and climate change. The analysis is based on the historically reconstructed series of several variables that span over the last centuries. Besides, it is based on the class of ARIMAX-ARCH models. The results show evidence for bidirectional causation between human growth and climate change. In particular, we find that solar irradiance and gross domestic product are significant predictors of temperature anomalies. Furthermore, temperature anomalies and solar irradiance are found to exert a positive feedback effect on the growth rate of gross domestic product. As regards the causality measures, despite the strength of the univariate component, the contribution of the exogenous factors is strongly significant in all the estimated models. The analysis we carry out suggests framing climate change within a set of long-run trends

Spatial Dependence of Solar Photovoltaic Systems: Data Gathering Process, Related Issues and Preliminary Results

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