In this dissertation, I will conduct a critical analysis of several methods typically used for modeling patent data, and then use insights gleaned from that analysis to explore four instances of public financing of innovation in the form of renewable-energy technology.

Chapter 1 introduces my overall research objectives, frames the research in terms of its policy relevance, and provides a brief preview of the major results. Chapter 2 provides background on innovation, causes and results thereof, with a particular focus on patent data, and thereby a framework for understanding the relevance of chapters 3 and 4.

The first main essay (chapter 3) addresses statistical regression techniques frequently used with patent-count time-series data, namely negative binomial regressions and log-log regressions. It reveals high rates of spurious correlation (false positives, also known as Type I errors) when using these techniques on patent data, investigates possible ways of addressing this problem, and creates a method for detecting it when using those and other regression techniques on similar data types.

Using lessons learned from the first essay, the second essay (chapter 4) examines public research and development (R&D) funding of four renewable-energy technologies – wind turbines, solar photovoltaics, solar thermal electric, and solar water heating. It employs several novel patent analysis techniques that allow patents to more closely represent the date of inventive activity. It finds that, contrary to popular narratives of public R&D funding driving increased invention (patenting), a diverse set of relationships exist in the renewable energy sector. These relationships range from changes in funding being correlated with future changes in invention rates, to changes in invention rates preceding changes in funding, to changes in funding and invention rates having no discernible relationship.

Taken together, these essays demonstrate the interdependent relationship between appropriate analytic techniques and accurate analysis when examining the sometimes subtle effects of complex policies.

Many national and regional governments have been promoted biofuels as a strategy to mitigate the climate change effects of the existing petroleum-based transportation system. New performance-based policies such as the California Low-Carbon Fuel Standard and the US Renewable Fuel Standard use Life Cycle Assessment (LCA) to estimate greenhouse gas (GHG) emissions to determine the life cycle global warming effects of each fuel production pathway. However, the current generation of policies have largely ignored the highly uncertain and often subjective nature of LCA assessments. Considering these uncertainties raises questions about the appropriateness of using an LCA-based estimate as a performance metric in public policy.

The objective of this dissertation is to characterize--qualitatively and quantitatively--the many data, parameter, model, and decision uncertainties inherent to estimates of the life cycle climate effects of transportation fuels, and to critically examine the robustness of these policies to these uncertainties. As demonstrated herein, LCA-based fuel regulations may accomplish much less than expected, and have the potential to cause more climate change than a business-as-usual scenario absent biofuels. Alternative policies that acknowledge uncertainty and respect the limitations of LCA--and thus of our understanding of the benefits of LCA-based policies--can be more robust

in achieving GHG reductions.

This dissertation investigates earthquake mitigation behavior among a group of rental property owners in Berkeley, California. About 320 owners were affected by a novel local ordinance that sought to address the problem of soft, weak, or open first story wood frame buildings. The law placed notice on the property title and required owners to inform tenants, post warning signs on-site, and hire a structural engineer to evaluate their property. Even though owners were not required to do a seismic upgrade, over 20 percent voluntarily took that costly extra step.

To investigate why some people took precautionary action while others did not, I conducted 43 semi-structured in-depth interviews, including a stratified sample of the affected Berkeley apartment owners (N=37) and some owners who did similar soft-story retrofits prior to the law (N=6). Using a mix of open-ended and survey questions, I developed a rich description of these owners and how the law affected their mitigation investment choices.

My principal finding is that post-law retrofitters were highly motivated by the near-term negative consequences created by the law. The desire to remove stigma (and its perceived economic implications), gain freedom from administrative hassles, and eliminate fear of further regulatory impositions compelled many to act, in some cases more than concern about the actual hazard. Retrofitters and non-retrofitters appear to own similar buildings and otherwise have similar demographic traits and earthquake risk perceptions.

To put this individual behavior into context, I also interviewed 22 key stakeholders involved in developing and implementing the policy and assessed the City of Berkeley's mandatory evaluation approach as a policy strategy. Berkeley's approach successfully influenced enough owners to take voluntary action that the remaining owners now believe that they must either do a retrofit or accept that their property is worth less. The greatest implementation challenge was the development, communication, and consistent application of technical standards for the evaluating engineers to use. Overall, this case illustrates the potential power, as well as some limitations and pitfalls, of using labeling, mandated evaluations, and disclosures to shift social perceptions and behavior regarding risk reduction behaviors.

We estimate the physical supply potential of biofuels from domestic municipal solid waste, forestry residues, crops residues and energy crops grown on existing cropland using optimistic assumptions about near-term conversion technologies. It is technically feasible to produce a significant amount of liquid biofuel (equivalent to 30-100% of 2003 gasoline demand) without reducing domestically produced food and fiber crops or reducing the total calories available as domestic animal feed. Most of this supply can be attributed to the potential of energy crops, with the combination of municipal solid waste and forestry residues supplying between 10% and 30% of recent gasoline demand.

Our modeling approach to energy crops is unique in that it explicitly models interactions between the feed and fuel system using an optimization procedure that adjusts cropland allocation among major crops subject to a simple food security constraint. Our modeling indicates that sizable increases in biofuel production need not result in decreased availability of food or animal feed, but will require changes in the composition of livestock diets away from hay and soymeal toward either whole corn or feed coproducts of biofuel processing such as distillers grains. Whole corn yields very high levels of digestible calories per land area, so shifting away from soymeal and hay to corn feed permits the same total level of digestible calories to be produced from a smaller area. Furthermore, the coproduction of animal feeds with biofuels relaxes the need to grow dedicated feed crops at all. Thus, under our food security constraint, energy crops which yield feed coproducts (such as corn ethanol) can be grown on a larger area than other energy crops, potentially yielding higher total levels of biofuel than other crops (such as switchgrass) that yield more biofuel but less animal feed per land area. When the food security constraint is lifted nearly 200% of recent gasoline demand could be met by liquid biofuels, corresponding to a scenario in which all current cropland is converted to high-yielding switchgrass.

The size of our supply estimates indicate that while domestic biofuels can play a large role in transportation, achieving such high levels of ethanol production may not be socially or ecologically desirable, or may be extremely costly with costs expressed through higher food prices, biodiversity loss, water degradation, and soil erosion. Policies designed to protect natural resources and stabilize food prices should be implemented early in order to achieve a reasonable level of biofuel production that avoids pushing these boundaries.

This study describes how some biofuels are produced, emphasizing agricultural production systems, and considers what is needed in order to measure and communicate environmental performance, and gives examples of how this might be done. We describe a set of seven uses of a Green Biofuels Index, from a wholly market-driven implementation through a set of increasingly intrusive regulatory approaches. We then present several case studies of specific biofuel production pathways using a lifecycle analysis of the inputs to feedstock production and processing, but excluding market-mediated effects.

We recommend four steps to create markets for green biofuels: 1. Measure the global warming intensity of biofuels. 2. Measure the overall environmental performance of biomass feedstock production. 3. Develop and implement a combined Green Biofuels Index. 4. Research better practices, assessment tools, and assurance methods.

Introduction

Methods

Results

Conclusion