Renewable Energy

Abstract

This study evaluates the economic impact of a shift towards renewable electricity mix in the Netherlands using the neo-Keynesian CGEM ThreeME (Multi-sector Macroeconomic Model for the Evaluation of Environmental and Energy policy). This scenario has been inspired by the Urgenda’s report ‘Energy 100% Sustainable in the Netherlands by 2030’, which have been quantified using the Energy Transition Model (ETM) developed by Using the output of the ETM regarding the change in the electricity generation shares as input in ThreeME, we derive the impact in terms of key economic variables (GDP, employment, investment, value-added, prices, trade, tax revenue, ).

We find that transition to renewable energy may have a positive impact on the Dutch economy, creating almost 50 000 new jobs by 2030 and adding almost 1% of gross domestic product.

Introduction

The Paris Agreement signed in December 2015 during the COP 21 (2015 United Nations Climate Change Conference) has the ambition to limit the global temperature increase to 5°C compared to pre-industrial The Intergovernmental Panel on Climate Change (IPCC) estimated that the world has used more than 65 percent of the carbon dioxide budget allowing to stay within the 2°C limit and that to stay within this limit, global carbon neutrality should be achieved between 2055 and 2070” (UNEP, 2014 XV). Meeting a 1.5 °C target implies a big effort both for developing and advanced countries which have to implement a rapid and major change in the structure of their supply and demand of This is likely to have an important impact on energy sectors but also on the rest of the economy.

The Paris Agreement acknowledges also the historical responsibility of advanced countries regarding the current situation, implying that they will have to support a larger share of the efforts.

In particular, they are expected to demonstrate the feasibility of the energy transition to a low carbon There is also more and more internal pressure to respect existing commitments.

After the plaint of Urgenda and nine hundred co-plaintiffs, the District court of The Hague ordered the Dutch government to reduce its emissions by a minimum of 25% by 2020 compared to 1990 (urgenda.nl/en/climate-case/, 24 June 2015). The Netherlands are currently on a path towards 59 17% in 2020.

It is therefore useful to evaluate the feasibility of ambitious scenarios where the energy system is largely based on renewable This is a difficult task involving both technical and economic issues since one expects the future energy system to provide equivalent performance as the current one while been economically This rises the following questions. Is a high penetration of renewable energy for power generation technically feasible? Does it lead to an increase in the electricity price? What is the impact on the economic activity (sectorial employment, investment, value-added, prices, trade, tax revenue, etc.)?

Energy and economic models may help answering these Here we simulate the economic impact of a shift towards a renewable scenario on the Dutch This scenario has been inspired by the one developed by Urgenda (urgenda.nl) using the open source Energy Transition Model (ETM) developed by Quintel (quintel.nl). This tool can be used to evaluate the technical feasibility of the The Urgenda scenario is detailed in Urgenda (2014). It aims for a large decrease of the carbon intensity of the economy by This is achieved by changes occurring both on the demand and on the supply side of the energy On one hand, wide adoption of more energy efficient technologies in the building and transport sector, as well as by industry, is expected to reduce the final demand for energy by On another hand, electricity and heat is produced only from renewable source, with the increasing role of local sources, such as rooftop PV panels and heat Biomass and green gas are used as back-up technologies for the intermittent solar and wind Liquid fuels are still present in the economy, but they are 100% from biological The production of Dutch natural gas is entirely exported. In this paper, we only analyze the economic impact of the supply side part of the Urgenda Namely, we focus on the adoption of solar and wind technology for electricity generation and biomass for heat production. Demand side measures, as well as biofuels and green gas, are left outside of the analysis for the time being.

In this study, we use the neo-Keynesian CGEM (Computable General Equilibrium Model) ThreeME (Multi-sector Macroeconomic Model for the Evaluation of Environmental and Energy policy). Using the output of the ETM regarding the change in the energy system as input in ThreeME, we derive the impact in terms of key economic variables (GDP, employment, investment, value-added, prices, trade, tax revenue, ). Whereas partial equilibrium bottom-up energy models such as MARKAL (Fishbone & Abilock, 1981), LEAP (Heaps, 2008), TIMES (Loulou, Goldstein, Kanudia, Lehtila, & Remme, 2016), or PRIMES (E3MLab, 2016) generally assume that the demand for energy and the costs of the different technologies are exogenous, CGEMs take into account the interaction and feedbacks between supply and demand by modeling prices and the demand endogenously.

There are mainly two types of CGEMs in the Walrasian CGEMs (e.g. Shoven & Whalley, 1994) assume that the perfect flexibility of prices and quantities (production factors, consumption, etc) ensures the instantaneous equilibrium between supply and The economy is described in real terms (inflation is not modeled) and there is no (involuntary) Examples of these models include GTAP (Center for Global Trade Analysis – GTAP, 2014), GEM-E3 (Capros, Van Regemorter, Paroussos, & Karkatsoulis, 2013) or ENV-Linkages (Chateau, Dellink, & Lanzi, 2014). The assumption of perfect flexibility contrasts with the reality where the adjustments of prices and quantities are generally relatively Walrasian CGEMs are therefore long term models. On the contrary, in neo-Keynesian CGEMs, prices do not clear the markets and market “imperfections” are taken into In coherence with empirical evidences, they assume that prices and quantities are rigid in the short run and that they adjust slowly over time toward their optimal In the short and medium run, there can be situations of disequilibrium between the optimal supply and the actual supply and of underutilization of the production capacity (in particular involuntary unemployment). This framework is better suited for policy purposes because it provides information regarding the transition phase of a particular policy (not only about the long term). Econometric models such as 3EME (Cambridge Econometrics, 2014), NEMESIS (Brécard, Fougeyrollas, Le Mouël, Lemiale, & Zagamé, 2006; ERASME, d.) or GINFORS (Lutz, Meyer, & Wolter, 2010) are examples of neo-Keynesian ThreeME is not an econometric model since the model’s equations are not systematically However we use econometric estimation from the literature to calibrate the parameters of the model: elasticities and adjustment parameters (for more detail, see the online Supplementary material A: Main equations of ThreeME).

We find that more renewable energy in power and heat generation has the potential for creating jobs and growth for the Dutch On the one hand, our modeling exercise projects that around 50 000 new full time jobs can be created by 2030 and the GDP is expected to increase by 85% relatively to the baseline scenario. This positive impact is explained by a relatively higher labor and capital intensity of wind and solar technologies, compared to gas and coal plants, and this creates growth opportunities primarily for domestic, but not imported, products. On the other hand, these positive effects are accompanied by an increase in the future electricity price, mainly due to much higher capital intensity for renewable We also show that the relative increase in electricity price strongly depends on the projected costs of the technologies, giving the uncertainty range of relative price increase between 2 and 18%. And lastly, we have also demonstrated the importance of using a general equilibrium model with price effects when considering impacts on macroeconomic indicators, such as GDP and We show that neglecting of the feedback effects of prices can lead to substantially overestimated impacts. Section 2 gives a short description of the ThreeME Section 3 presents ThreeME for the Section 4 defines the scenario. Section 5 presents the simulation results and Section 6 concludes.

Conclusion

In this paper, we have analyzed the potential short and long-term macroeconomic effects of renewable energy in the Netherlands. We have considered a scenario in which, by 2030, electricity is generated mostly by solar and wind power and heat is derived mainly from This scenario represents a selection of policy measures suggested in the 100% Renewable scenario of Physical and technical feasibility of the scenario has been already assessed by Energy Transition Model (ETM) of We take the electricity mix and future generation costs as defined by ETM and feed them into the neo-Keynesian CGEM ThreeME in order to derive macroeconomic effects.

We find that renewable energy has potential for stimulating growth and jobs for the Dutch economy.

We expect that additional 0.85% of gross domestic product will be created by 2030 as a result of shift towards renewable energy mix, with the largest effect seen in investment In terms of job creation, we project around 50 000 new full time job by This positive impact is explained by a relatively higher labor and capital intensity of wind and solar technologies, compared to gas and coal This creates growth opportunities primarily for domestic, but not imported, At the same time, renewable technologies typically require higher investments per unit of output than fossil fuel technologies, which leads to a higher electricity We also show that the relative increase in electricity price strongly depends on the projected costs of the technologies, giving the uncertainty range for the relative electricity price increase between 2 and 18%. We have not only shown the projected long-term outcome of the change in the electricity mix, but also the time path towards this outcome. 

Furthermore, we have demonstrated how the total effect can be decomposed into a number of multiplier effects using dynamic Input-Output One of the important conclusions here is that positive impacts on the economy can be overestimated when price effects and feedback loops are not taken into General equilibrium models, such as ThreeME, are specifically designed to incorporate price effects and inter-sectoral links. 

This paper has only focused on the macroeconomic effects of change in the electricity and heat generation We have limited the scope of the analysis on purpose, in order to be able to lay out the intuition behind the results and demonstrate the possible role of general equilibrium models in the energy transition But, of course, the question of sustainable and renewable future is much more broad, including many aspects such as energy efficiency, behavior adjustment, biofuels, local energy generation, We therefore believe that the future of energy transition modelling and analysis lays in finding the right combinations of physical and micro models, which give feasibility of a certain energy solution and its effect on the physical system, and of macroeconomic models, which ensure that labor, capital and monetary constrains are also taken into account.