Economic Impacts of Renewable Energy Increase in Germany

Abstract

The positive impacts of an increasing share of renewable energy (RE) on the mitigation of climate change as well as on the decrease of the dependence of energy imports are indisputable. Currently, more than 350,000 people work in the respective industries in Germany. The contribution explains the calculation of gross employment comprising direct and indirect jobs in the facility production, operation, and maintenance and fuel production. The number of jobs in the field has more than doubled from 2004, when the first calculation has been done. However, also increasing are the additional costs of heat and electricity generation from most renewable energy sources (RES). For a stable economic development, the overall balance of positive and negative effects under different possible future development pathways of fossil fuel prices, global climate policies and global trade is of interest. To account for all effects in a consistent framework, a macroeconometric model is employed. Economic development is measured via the comparison of economic indicators such as GDP and employment from different simulation runs. Overall net positive effects can be seen for instance as higher employment in one simulation run compared with the other.

Our analysis shows possible positive impacts of the expansion of renewable energy in Germany—and the conditions and policy implication for a positive development. The German example shows how a large domestic market leads to the development of a successful industry. However, these successes are vulnerable to abrupt policy changes, as experiences with the US industry or the Spanish market and lately the German PV industry show.

Annex

The economy-energy-environment model PANTA RHEI is at the core of our methodological approach. PANTA RHEI [8, 9] is an environmentally extended version of the econometric simulation and forecasting model INFORGE [10, 11]. Among others it has been used for economic evaluation of different energy scenarios that have been the basis for the German energy concept in 2010 [12, 13]. A similar model for Austria [14] has recently been applied to the case of sustainable energy development in Austria until 2020. The following description is taken from [4].

The behavioral equations reflect bounded rationality rather than optimizing behavior of agents. All parameters are estimated econometrically from time series data (1991–2008). Producer prices are the result of mark-up calculations of firms. Output decisions follow observable historic developments, including observed inefficiencies rather than optimal choices.

Structural equations are usually modeled on the 59 sector level (two digit NACE classification) of the input–output accounting framework of the official system of national accounts (SNA) and the corresponding macro variables are then endogenously calculated by explicit aggregation. In that sense the model has a bottom-up structure. The input–output part is consistently integrated into the SNA accounts, which fully reflect the circular flow of generation, distribution, redistribution, and use of income.

The core of PANTA RHEI is the economic module, which calculates final demand (consumption, investment, exports) and intermediate demand (domestic and imported) for goods, capital stocks, employment, wages, unit costs and producer as well as consumer prices in deep disaggregation of 59 industries. The disaggregated system also calculates taxes on goods and taxes on production. The corresponding equations are integrated into the balance equations of the input–output system.

Value added of the different branches is aggregated and gives the base for the SNA system that calculates distribution and redistribution of income, use of disposable income, capital account and financial account for financial enterprises, non financial enterprises, private households, the government and the rest of the world. Macro variables like disposable income of private households and disposable income of the government as well as demographic variables represent important determinants of sectoral final demand for goods. Another important outcome of the macro SNA system are net savings and governmental debt as its stock. Both are important indicators for the evaluation of policies. The demand side of the labor market is modeled in deep sectoral disaggregation. Wages per head are explained using Philips curve specifications. The aggregate labor supply is driven by demographic developments.

The model is empirically evaluated: The parameters of the structural equations are econometrically estimated. On the time consuming model-specification stage various sets of competing theoretical hypotheses are empirically tested. As the resulting structure is characterized by highly nonlinear and interdependent dynamics the economic core of the model has furthermore been tested in dynamic ex-post simulations. At this, the model is solved by an iterative Gauss-Seidel algorithm year by year.

The energy module captures the dependence between economic development, energy input and CO₂ emissions. It contains the full energy balance with primary energy input, transformation and final energy consumption for 20 energy consumption sectors, 27 fossil energy carriers and the satellite balance for renewable energy [15]. The energy module is fully integrated into the economic part of the model.

To fully assess the impacts from the production and operation and maintenance of renewable energy systems, input–output structures for the renewable energy sectors have been developed and integrated in the modeling framework [9]. Input–output tables provide detailed insights in the flows of goods and services between all sectors of the economy and the interdependence of the economy of a country and with the rest of the world. They are closed accounting schemes where the identity of the sum of inputs and the sum of outputs has to hold in each sector. This consistency check of course also holds true for the newly created sector “Production of systems for the use of RES”. The new sector is defined in economic terms by its input and output structure, being represented by a new column and a new row in an existing table. The input or cost structure describes the amounts of goods and services required as intermediate inputs from all other domestic sectors, the amount of imported intermediate inputs and the value added in the sector itself. The output or sales structure describes the amounts of goods and services delivered to other sectors as intermediate goods or as final goods to final demand: Wind energy offshore and onshore, PV, hydro, solar thermal heat generation, biomass electricity generation, biomass heat generation, geothermal electricity generation, heat pumps, and biogas generation.

To account for the variety of technologies involved in RES use the newly created sector is build up in a bottom up process based on ten subsectors each of which represents a defined RES technology. Compared to a previous study [9] the larger number of technologies distinguished improves the homogeneity of subsectors which is beneficial for empirical quality of representing technologies in an input–output framework. Figure 2 shows examples of the cost structures in percent of gross production volume (GPV) derived for the production of systems for the use of wind energy and photovoltaic systems in comparison to systems for the use of fossil fuels. The difference in structures shows the importance of creating a new sector in the system, since the intermediate inputs used for the respective production processes come from very different sectors of the economy so that the overall and sectoral impacts are depending on a reliable empirical representation of the new RES technologies in the applied analytical tool.

Fig. 2

Cost structure for the production of systems for the use of different energy types, in percent of Gross Production Value (GPV)

To examine the economic effects of increasing shares of renewable energy in Germany our analysis applies PANTA RHEI to a set of scenarios and compares the resulting economic outcomes.