Are public policies towards renewables successful? Evidence from European countries António Cardoso Marques * , José Alberto Fuinhas NECE, University of Beira Interior, Management and Economics Department, Estrada do Sineiro, 6200-209 Covilhã, Portugal 1 article info Article history: Received 15 December 2011 Accepted 9 January 2012 Available online 31 January 2012 Keywords: Renewable energy Public policies supporting renewables Panel corrected standard errors estimator European countries JEL Classification: C23 N74 Q42 Q58 abstract Qualitative and theoretical literature indicates public policies as a major driver in the development of renewables. This paper empirically tests this claim, within a context of several drivers of renewables, by focusing on a large panel of European countries. Given the presence of heteroskedasticity and contemporaneous correlation resulting from the uniformity of public policies supporting renewables, we use a Panel Corrected Standard Errors estimator. Results are consistent with the usual drivers indicated by the literature and they give empirical support to the notion that public policy measures contribute, as a whole or disaggregated, to wider use of renewables. Specifically, policies of incentives/subsidies (including feed-in tariffs) and policy processes prove to be significant drivers of improved RE use. We show that the usual panel data estimators, random effects and fixed effects, are inefficient and lead to the erroneous exclusion of these policies as renewables’ drivers. Ó 2012 Elsevier Ltd. All rights reserved. 1. Introduction The need to use renewable energy sources would appear to be a purpose of humanity. As a consequence of the use of indigenous resources, Renewable Energy (hereafter RE) is associated with several advantages, such as reducing carbon dioxide emissions or increasing energy independence. These advantages have been claimed to support the implementation of public policy measures to encourage the use of renewable sources. International commit- ments, such as the ratification of the Kyoto Protocol and guidelines set within the European Union (for instance Directives 2001/77/ EC e [1], and 2009/28/EC e [2]) have led to the setting of compulsory targets for the use of RE. Public Policies Supporting Renewables (PPSR) of different natures have been implemented with the aim of meeting these commitments. In the literature, PPSR are also known as market opening policies or market driven poli- cies [3]. While almost all qualitative and theoretical literature suggests that PPSR are one of the main drivers of the development of RE, the scarce empirical literature would not appear to lend its unques- tioning support to this claim. For instance, by using a panel with fixed effects model, Johnstone et al. [4] work on the number of patents per technological area of RE and not on the use of RE in the total energy supply. They observe, for instance for feed-in tariffs levels, a different significant effect, which is negative for wind technology and positive for solar technology. In their turn, Popp et al. [5] recognize the relevance of the presence of contempora- neous correlation in the data by using the generalized least squares estimator. Feed-in tariffs are not always statistically significant, and other policies are not significant, throughout their models. The main objectives of this paper are: (i) to shed some light on the real effect of public policies on renewables; (ii) to evaluate the impact of the policies’ measures either as a whole or disaggregated; (iii) to check the robustness of results, assessing their sensitivity to the estimators used; and (iv) to analyze public policies within a wide context of other drivers that promote renewables, as iden- tified in the literature. Focusing on a set of 23 European countries, the results suggest that the use of the Panel Corrected Standard Errors estimator is appropriate given the presence of Abbreviations: AR(1), First-order autoregressive error; CO 2 , Carbon dioxide emissions; EU, European Union; FEE, Panel Fixed Effects Estimator; FGLS, Gener- alized Least Squares; LM, Lagrange Multiplier; LR, Likelihood Ratio; NECE, Research Unit in Business Science and Economics; PCSE, Panel Corrected Standard Errors; PPSR, Public Policies Supporting Renewables; RE, Renewable Energy; REE, Panel Random Effects Estimator; VIF, Variance Inflation Factor. * Corresponding author. Tel.: þ351 275 319 600; fax: þ351 275 319 601. E-mail addresses: amarques@ubi.pt, acardosomarques@gmail.com (A.C. Marques). 1 Research supported by: NECE, I&D unity funded by the FCT - Portuguese Foundation for the Development of Science and Technology, Ministry of Science, Technology and Higher Education. Contents lists available at SciVerse ScienceDirect Renewable Energy journal homepage: www.elsevier.com/locate/renene 0960-1481/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.renene.2012.01.007 Renewable Energy 44 (2012) 109e118