The Importance of Revenue Sharing for the Local Economic Impacts of a Renewable Energy Project: A Social Accounting Matrix Approach

As demand for electricity from renewable energy sources grows, there is increasing interest, and public and financial support, for local communities to become involved in the development of renewable energy projects. In the UK, “Community Benefit” payments are the most common financial link between renewable energy projects and local communities. These are “goodwill” payments from the project developer for the community to spend as it wishes. However, if an ownership stake in the renewable energy project were possible, receipts to the local community would potentially be considerably higher. The local economic impacts of these receipts are difficult to quantify using traditional Input-Output techniques, but can be more appropriately handled within a Social Accounting Matrix (SAM) framework where income flows between agents can be traced in detail. We use a SAM for the Shetland Islands to evaluate the potential local economic and employment impact of a large onshore wind energy project proposed for the Islands. Sensitivity analysis is used to show how the local impact varies with: the level of Community Benefit payments; the portion of intermediate inputs being sourced from within the local economy; and the level of any local community ownership of the project. By a substantial margin, local ownership confers the greatest economic impacts for the local community.

The Rebound Effect with Energy Production: A Partial Equilibrium Analysis

Rebound is the extent to which improvements in energy efficiency fail to translate fully into reductions in energy use because of the implicit fall in the price of energy, when measured in efficiency units. This paper discusses aspects of the rebound effect that are introduced once energy is considered as a domestically produced commodity. A partial equilibrium approach is adopted in order to incorporate both energy use and production in a conceptually tractable way. The paper explores analytically two interesting results revealed in previous numerical simulations. The first is the possibility that energy use could fall by more than the implied improvement in efficiency. This corresponds to negative rebound. The second is the finding that the short-run rebound value can be greater than the corresponding long-run value.

The regional electricity generation mix in Scotland: A portfolio selection approach

Standalone levelised cost assessments of electricity supply options miss an important contribution that renewable and non-fossil fuel technologies can make to the electricity portfolio: that of reducing the variability of electricity costs, and their potentially damaging impact upon economic activity. Portfolio theory applications to the electricity generation mix have shown that renewable technologies, their costs being largely uncorrelated with non-renewable technologies, can offer such benefits. We look at the existing Scottish generation mix and examine drivers of changes out to 2020. We assess recent scenarios for the Scottish generation mix in 2020 against mean-variance efficient portfolios of electricity-generating technologies. Each of the scenarios studied implies a portfolio cost of electricity that is between 22% and 38% higher than the portfolio cost of electricity in 2007. These scenarios prove to be “inefficient” in the sense that, for example, lower variance portfolios can be obtained without increasing portfolio costs, typically by expanding the share of renewables. As part of extensive sensitivity analysis, we find that Wave and Tidal technologies can contribute to lower risk electricity portfolios, while not increasing portfolio cost.

The regional employment impacts of renewable energy expenditures: The case for modelling

One aspect of the case for policy support for renewable energy developments is the wider economic benefits that are expected to be generated. Within Scotland, as with other regions of the UK, there is a focus on encouraging domestically‐based renewable technologies. In this paper, we use a regional computable general equilibrium framework to model the impact on the Scottish economy of expenditures relating to marine energy installations. The results illustrate the potential for (considerable) ‘legacy’ effects after expenditures cease. In identifying the specific sectoral expenditures with the largest impact on (lifetime) regional employment, this approach offers important policy guidance.

The regional employment impacts of renewable energy expenditures: The case for modelling

One aspect of the case for policy support for renewable energy developments is the wider economic benefits that are expected to be generated. Within Scotland, as with other regions of the UK, there is a focus on encouraging domestically‐based renewable technologies. In this paper, we use a regional computable general equilibrium framework to model the impact on the Scottish economy of expenditures relating to marine energy installations. The results illustrate the potential for (considerable) ‘legacy’ effects after expenditures cease. In identifying the specific sectoral expenditures with the largest impact on (lifetime) regional employment, this approach offers important policy guidance.

The regional economic impacts of biofuels: A review of multisectoral modelling techniques and evaluation of applications

The regional economic impact of biofuel production depends upon a number of interrelated factors: the specific biofuels feedstock and production technology employed; the sector’s embeddedness to the rest of the economy, through its demand for local resources; the extent to which new activity is created. These issues can be analysed using multisectoral economic models. Some studies have used (fixed price) Input-Output (IO) and Social Accounting Matrix (SAM) modelling frameworks, whilst a nascent Computable General Equilibrium (CGE) literature has also begun to examine the regional (and national) impact of biofuel development. This paper reviews, compares and evaluates these approaches for modelling the regional economic impacts of biofuels.

The regional economic impacts of biofuels: A review of multisectoral modelling techniques and evaluation of applications

The regional economic impact of biofuel production depends upon a number of interrelated factors: the specific biofuels feedstock and production technology employed; the sector’s embeddedness to the rest of the economy, through its demand for local resources; the extent to which new activity is created. These issues can be analysed using multisectoral economic models. Some studies have used (fixed price) Input-Output (IO) and Social Accounting Matrix (SAM) modelling frameworks, whilst a nascent Computable General Equilibrium (CGE) literature has also begun to examine the regional (and national) impact of biofuel development. This paper reviews, compares and evaluates these approaches for modelling the regional economic impacts of biofuels.

Evaluating the usefulness of forecasts of relative growth

Forecasts of differences in growth between countries serve an important role in the justification of governments’ fiscal policy stances, but are not tested for their accuracy as part of the current range of forecast evaluation methods. This paper examines forecasted and outturn growth differentials between countries to identify if there is usefulness in forecasts of “relative” growth. Using OECD forecasts and outturn values for GDP growth for (combinations of) the G7 countries between 1984 and 2010, the paper finds that the OECD’s success in predicting the relative growth of G7 countries during this period is good. For each two-country combination results indicate that relative growth forecasts are less useful for countries which have smaller outturn growth differentials.

The Impacts of Temporary and Anticipated Tourism Spending.

Part of the local economic impact of a major sporting event comes from the associated temporary tourism expenditures. Typically demand-driven Input-Output (IO) methods are used to quantify the impacts of such expenditures. However, IO modelling has specific weaknesses when measuring temporary tourism impacts; particular problems lie in its treatment of factor supplies and its lack of dynamics. Recent work argues that Computable General Equilibrium (CGE) analysis is more appropriate and this has been widely applied. Neglected in this literature however is an understanding of the role that behavioural characteristics and factor supply assumptions play in determining the economic impact of tourist expenditures, particularly where expenditures are temporary (i.e. of limited duration) and anticipated (i.e. known in advance). This paper uses a CGE model for Scotland in which agents can have myopic- or forward-looking behaviours and shows how these alternative specifications affect the timing and scale of the economic impacts from anticipated and temporary tourism expenditure. The tourism shock analysed is of a scale expected for the Commonwealth Games to be held in Glasgow in 2014. The model shows how “pre-shock” and “legacy” effects – impacts before and after the shock – arise and their quantitative importance. Using the forward-looking model the paper calculates the optimal degree of pre-announcement.

Nowcasting Scottish GDP Growth

The delays in the release of macroeconomic variables such as GDP mean that policymakers do not know their current values. Thus, nowcasts, which are estimates of current values of macroeconomic variables, are becoming increasingly popular. This paper takes up the challenge of nowcasting Scottish GDP growth. Nowcasting in Scotland, currently a government office region within the United Kingdom, is complicated due to data limitations. For instance, key nowcast predictors such as industrial production are unavailable. Accordingly, we use data on some non-traditional variables and investigate whether UK aggregates can help nowcast Scottish GDP growth. Such data limitations are shared by many other sub-national regions, so we hope this paper can provide lessons for other regions interested in developing nowcasting models.