GEL statistics under weak identification

The central concern of this paper is the provision in a time series moment condition framework of practical recommendations of confidence regions for parameters whose coverage probabilities are robust to the strength or weakness of identification. To this end we develop Pearson-type test statistics based on GEL implied probabilities formed from general kernel smoothed versions of the moment indicators. We also modify the statistics suggested in Guggenberger and Smith (2008) for a general kernel smoothing function. Importantly for our conclusions, we provide GEL time series counterparts to GMM and GEL conditional likelihood ratio statistics given in Kleibergen (2005) and Smith (2007). Our analysis not only demonstrates that these statistics are asymptotically (conditionally) pivotal under both classical asymptotic theory and weak instrument asymptotics of Stock and Wright (2000) but also provides asymptotic power results in the weakly identified time series context. Consequently, the empirical null rejection probabilities of the associated tests and, thereby, the coverage probabilities of the corresponding confidence regions, should not be affected greatly by the strength or otherwise of identification. A comprehensive Monte Carlo study indicates that a number of the tests proposed here represent very competitive choices in comparison with those suggested elsewhere in the literature.     

Can Technology-Specific Deployment Policies Be Cost-Effective? The Case of Renewable Energy Support Schemes

While there is relatively limited disagreement on the general need for supporting the deployment of renewable energy sources for electricity generation (RES-E), there are diverging views on whether the granted support levels should be technology-neutral or technology-specific. In this review paper we question the frequently stressed argument that technology-neutral schemes will promote RES-E deployment cost-effectively. We use a simple partial equilibrium model of the electricity sector with one representative investor as a vehicle to synthesize the existing literature, and review potential rationales for technology-specific RES-E support. The analysis addresses market failures associated with technological development, long-term risk taking, path dependencies as well as various external costs, all of which drive a wedge between the private and the social costs of RES-E deployment. Based on analytical insight and a review of empirical literature, we conclude that the relevance of these market failures is typically heterogeneous across different RES-E technologies. The paper also discusses a number of possible caveats to implementing cost-effective technology-specific support schemes in practice, including the role of various informational and politico-economic constraints. While these considerations involve important challenges, neither of them suggests an unambiguous plea for technology-neutral RES-E support policies either. We close by highlighting principles for careful RES-E policy design, and by outlining four important avenues for future research.