This report synthesizes consumer behavior research as it pertains to the plug-in electric vehicle (PEV) purchase decision process. The purpose is to clarify what is known about the vital role consumers play in the U.S. PEV market as it matures to become less policy-reliant and more representative of the U.S., both spatially and demographically. A more representative PEV market will: help OEMs recoup more of their R&D investments in PEVs; help American consumers access the economic and performance benefits of PEVs; and help the U.S. become more energy independent while improving air quality-related public health and reducing greenhouse gas emissions.

This report provides and update to and expansion upon our 2008 LBNL report “An Analysis of the Price Elasticity of Demand for Appliances,” in which we estimated an average relative price elasticity of -0.34 for major household appliances (Dale and Fujita 2008). Consumer responsiveness to price change is a key component of energy efficiency policy analysis; these policies influence consumer purchases through price both explicitly and implicitly. However, few studies address appliance demand elasticity in the U.S. market and public data sources are generally insufficient for rigorous estimation. Therefore, analysts have relied on a small set of outdated papers focused on limited appliance types, assuming long-term elasticities estimated for other durables (e.g., vehicles) decades ago are applicable to current and future appliance purchasing behavior. We aim to partially rectify this problem in the context of appliance efficiency standards by revisiting our previous analysis, utilizing data released over the last ten years and identifying additional estimates of durable goods price elasticities in the literature. Reviewing the literature, we find the following ranges of market-level price elasticities: -0.14 to -0.42 for appliances; -0.30 to -1.28 for automobiles; -0.47 to -2.55 for other durable goods. Brand price elasticities are substantially higher for these product groups, with most estimates -2.0 or more elastic. Using market-level shipments, sales value, and efficiency level data for 1989-2009, we run various iterations of a log-log regression model, arriving at a recommended range of short run appliance price elasticity between -0.4 and -0.5, with a default value of -0.45.

Underlying each of the U.S. Department of Energy’s (DOE’s) federal appliance and equipment energy conservation standards are a set of complex analyses of the projected costs and benefits of regulation. Any new or amended standard must be designed to achieve significant additional energy conservation, provided that it is technologically feasible and economically justified (42 U.S.C. 6295(o)(2)(A)). DOE determines economic justification based on whether the benefits exceed the burdens, considering a variety of factors, including the economic impact of the standard on consumers of the product and the savings in lifetime operating cost compared to any increase in price or maintenance expenses (42 U.S.C. 6295(o)(2)(B)). As part of this determination, DOE conducts a life-cycle cost (LCC) analysis, which models the combined impact of appliance first cost and operating cost changes on a representative commercial building sample to identify the fraction of customers achieving LCC savings or incurring net cost at the considered efficiency levels. Thus, the commercial discount rate value(s) used to calculate the present value of energy cost savings within the LCC model implicitly plays a role in estimating the economic impact of potential standard levels. This report provides an in-depth discussion of the commercial discount rate estimation process. It is an update to previous reports on estimating commercial discount rates from firm-level and sector-level financial data (e.g., Fujita, 2021, 2016). Major topics covered in this report include the following: -Discount rate estimation methods and rationale -Data sources used and data limitations -Discount rate distributions for use in standards analysis -Discount rate estimation methods and distributions specific to the small business subgroup analysis A version of this analysis was most recently released in 2022. Going forward, this report will be updated as data allow and analyses necessitate.

Minimum efficiency standards for products such as appliances are economically efficient when they correct a market failure. Negative ramifications of these standards, particularly for credit constrained or low-income consumers, such as increased prices or decreased choice, are contingent on the pricing behavior of suppliers. We use market point of sales data to estimate the change in price and efficiency of clothes washers following the change in United States minimum efficiency standards in 2004 and 2007, differentiated by market segment. With a relatively narrow confidence interval, the average price of the baseline market segment did not change significantly concurrent with either the 2004 or 2007 standard change, while efficiency of these products increased by 30%, resulting in significant financial savings for consumers of the least expensive baseline products. The highest efficiency products experienced a significant drop in price and increase in efficiency as well, particularly following the 2007 standard change. The results suggest that the effect of this increase in minimum efficiency standards for clothes washers was beneficial to all consumers, but particularly those with lower incomes or renters. Low-income consumers were not priced out of the market, but rather benefited particularly. We offer discussion of potential explanations of these findings.

We define and test three main hypotheses each examining a mechanism by which personal commitment statements may influence behavior: future-self continuity, disappointment or regret aversion, and present-biased preferences coupled with sophistication. A set of additional analyses are conducted exploring a personal commitment statement’s role as an enabling device that either increases, or is correlated with, intent to implement the desired behavior. Hypotheses are tested using data from a field experiment regarding public transit ridership. Results indicate that the strongest candidate mechanism for the effectiveness of a commitment statement to induce behavior change is the presence of present-biased preferences coupled with sophistication, or self-awareness of one’s own limitations in following through with effortful behaviors. In addition, results suggest that the preference for one commitment mechanism could indicate a general preference for commitment mechanisms, but the presence of one commitment mechanism may crowd out perceived need for or interest in other enabling steps.

Although it is commonly understood that the average U.S. new vehicle buyer ranks price and safety above environmental attributes, a stated ranking of one shopping criterion above another is not necessarily maintained when consumers make an actual purchase decision. In fact, the distribution of shopping criteria rankings is not well understood, and it is unclear how rankings translate to the attributes of purchased vehicles. This raises several related questions: What is the distribution of shopping criteria rankings across the U.S. and how do they differ among demographic groups and purchasers of different vehicle fuel types or body styles?How do consumers weigh their purchase criteria?How does the environmental impact of a vehicle rank as a purchase criterion for U.S. new vehicle buyers, and its importance differ among gender, age, or income groups?Do purchase criteria differ for consumers who state that they value the environment?Is a consumer's shopping criteria ranking of environmental attributes reflected in the vehicles they consider and ultimately purchase? We explore these issues using data from an extensive survey of new vehicle buyers in 2014, 2015, and 2016 (approximately 250,000 respondents per year). We broadly find the environmental criterion outranked by preference for safety and performance, but different patterns emerge across groups defined by household income, purchased vehicle fuel type, and other measures of respondent attitude toward the environment. Stated preferences for environmental attributes align with higher fuel economy and greater likelihood of electric or hybrid fuel type within considered and purchased vehicles.

Building upon previous work in innovation, technology, and economic fields, we propose a conceptual framework to address the interplay dynamics of public policy and the value chains of clean energy technology innovation systems, by focusing on market structural and strategic conditions in relation to the rate and direction of knowledge diffusion within activity-based value chains. Our framework extends beyond socio-technical transition models by considering such nuances as: 1) the implications of geography, 2) the locus of knowledge types, 3) the dynamics of financial and knowledge flow, and 4) emphasizing the importance of both market structure and institutional conditions. At the firm level, we consider dynamics of interactions between suppliers and customers, innovation activities, the competitive environment, and the firm’s broader strategic relationship to governance activities and structures; we allow for the fact that each of these aspects of a firm’s identity may have a strategically relevant geographic dimension (e.g., service territories, locational concentration of input resources, etc.). We provide a proof-of-concept application of the U.S. utility-scale solar photovoltaic (PV) and onshore wind sectors, including their interactions with the U.S. power market, which we in present in a web-based information platform (Energy I-SPARK, ei-spark.lbl.gov).