Estimating the long-run impact of guaranteed prices on wind and solar power in Germany

ABSTRACT

The purpose of this study is to analyze the dynamics between the guaranteed prices introduced by pieces of legislation and the investment in new electricity-generation facilities in Germany that can be of great assistance to policymakers in planning development strategies for green electricity sources in other countries. This article uses the guaranteed price in the source markets as a proxy for market price and estimates the effects of price changes on the investment in generation facilities for renewable energy. To avoid the possible existence of spurious relationships that may arise in time series analysis, the bounds-testing approach to co-integration was applied. The long-run elasticities for the explanatory variables were obtained from the error correction model (ECM). The results indicate that guaranteed prices have a positive effect on the installed power capacity of the two renewable electricity sources: wind and solar power. Moreover, the findings are useful to governments in order to promote renewable energy and prevent negative attitudes toward renewable energies caused by increasing energy prices.

KEYWORDS:

• ARDL approach
• cost-effectiveness
• Germany
• solar power
• times series
• wind power

Notes

¹ Gesetzt über die Einspeisung von Strom aus erneuerbaren Energien in das öffentliche Netzt (StrEinpG) from 7 Dezember 1990.

² The last Act (Erneuerbare-Energien-Gesetz vom 21. Juli 2014) can be found in the Federal Law Gazette (BGBl. I S. 1066) and in the web page http://www.gesetze-im-internet.de/eeg_2014/.

³ Even the European Commission has opened a state aid investigation into the German Renewable Energy Source Act (EEG). In its preliminary assessment, the Commission has come to the conclusion that the EEG may have given unlawful advantages to energy-intensive companies in Germany (Spiegel Online, 2013).

⁴ Previous research has yielded other explanatory variables as statistically significant (de Freitas and Kaneko, 2012; Apergis and Payne, 2015. Consequently, we have considered the following explanatory variables: R&D spending in renewable energies, GDP, electricity production in Germany. None of these variables was statistically significant; they were not included in the final model. The results are not reported here for the sake of brevity.

⁵ Following Pesaran and Pesaran (1997), we examine the stability of the long-run coefficients using the cumulative sum of the recursive residuals (CUSUM) and the cumulative sum of squares (CUSUMQ) tests. For the sake of brevity, the plots of CUSUM and CUSUMSQ are not reported here, but they can be sent upon request.