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Policy makers are interested in estimates of the potential economic impacts of oil price shocks, particularly during periods of rapid and large increases that accompany severe supply shocks. Literature estimates of the economic impacts of oil price shocks, summarized by the oil price elasticity of GDP, span a very wide range due to both fundamental economic and methodological factors. This paper presents a quantitative meta-analysis of the oil price elasticity of GDP for net oil importing countries, with a focus on the United States (US). The full range of estimates of the oil price elasticity of GDP for the US in the data is − 0.124 to + 0.017, accounting for different methodologies, data and other factors. We employ a meta-regression model that controls for key determinant factors to estimate the mean and variance of the GDP elasticity across studies. We use a robust estimation technique to deal with heterogeneity of the data and well-known econometric issues that confront meta-analysis. The resulting regression model is used to simulate the oil price elasticity of GDP for the US, with a mean of − 0.020% and 68% confidence interval of − 0.035 to − 0.006, four quarters after a shock.

The issuance of a Federal Energy Regulatory Commission (FERC) license is an important milestone in the development process of new U.S. hydropower projects. The complexity and uncertain timeline of the licensing process have been often cited as a key deterrent to new hydropower installations in the United States. However, very little attention has been paid to post-licensing timelines and attrition rates. This article explores the challenges faced by developers in bringing their FERC-licensed hydropower projects to the construction stage. Post-licensing activities to be completed before starting construction include obtaining additional permitting from other federal or state agencies, completing the technical design, securing financing, and in most cases, negotiating a power purchase agreement. For the set of projects that obtained a FERC license between 2007 and 2018, we assembled a dataset—combining information from FERC dockets and responses from a questionnaire to developers—to calculate attrition rates and development timelines and to examine the reasons for delays and cancellations.