UC Berkeley

Paper 1, Local Solutions to Global Problems: Climate Change Policies and Regulatory Jurisdiction, considers the efficacy of various types of environmental regulations when they are applied locally to pollutants whose damages extend beyond the jurisdiction of the local regulators. Local regulations of a global pollutant may be ineffective if producers and consumers can avoid them by transacting outside the reach of the local regulator. In many cases, this may involve the physical relocation of the economic activity, a problem often referred to as “leakage.” This paper highlights another way in which local policies can be circumvented: through the shuffling of who buys from whom. The paper maintains that the problems of reshuffling are exacerbated when the options for compliance with the regulations are more flexible. Numerical analyses is presented demonstrating that several proposed policies to limit greenhouse gas emissions from the California electricity sector may have very little effect on carbon emissions if they are applied only within that state. Paper 1 concludes that although local subsidies for energy efficiency, renewable electricity, and transportation biofuels constitute attempts to pick technology winners, they may be the only mechanisms that local jurisdictions, acting alone, have at their disposal to address climate change.

Paper 2, Pass-Through of Solar PV Incentives to Consumers: The Early Years of California’s Solar PV Incentives, examines the pass through of incentives to California solar PV system owners. The full post-subsidy price consumers pay for solar power is a key metric of the success of solar PV incentive programs and of overall PV market performance. This study examines the early years of California’s most recent wave of distributed solar PV incentives (2000-2008) to determine the pass-through of incentives. Examination of this period is both intellectually and pragmatically important due to the high level of incentives provided and subsequent high cost to ratepayers; policymakers’ expectations that price declines accrue to consumers; and market structure characteristics that might contribute to incomplete pass-through. This analysis shows that incentive pass-through in the California residential solar PV programs was incomplete. Consumer prices declined 54 cents for every additional dollar of incentive received. A large share of the incentive is captured by the solar PV contractor or other actors in the solar PV supply chain. The finding of incomplete pass-through is persistent across specifications. The analysis also identifies a lower degree of incentive pass-through for consumers in the highest income zip codes. Whether expectations of incentives’ pass-through align with reality is critically important in the beginning years of emerging clean energy technology programs since this can affect the likelihood of future government investments and public support. Given the often-held policy assumption that consumer prices are declining in response to incentives, it is useful for policymakers to understand the circumstances under which such an assumption may not hold.

Paper 3, Testing the Boundaries of the Solar Photovoltaic Learning System, tests how the choice of experience curves’ geographic and technology assumptions affect solar PV experience curve results. Historically, solar PV experience curves have assumed one experience curve represents both module and non-module learning and that this learning happens at a global scale. These assumptions may be inaccurate for solar PV since the learning system, and technology and geographic boundaries, are likely different between PV modules and non-module components. Using 2004 to 2008 PV system price data from 13 states, and a longer time series of PV price data for California, some evidence is found that cumulative capacity at the state level is a better predictor of non-module costs than U.S. or global capacity. This paper explores, but is unable to significantly determine, how knowledge spillovers from neighboring states can influence a state’s non-module costs. Given data limitations, and limitations to the two-factor experience model methodology itself, it is not possible to conclusively determine the correct geographic boundary for the non-module learning system. Throughout the paper ways in which the experience curve model and data can be augmented to achieve a better estimation are discussed.