University of California Energy Institute

This paper provides the first systematic analysis of the choice by organizations to occupy green office space. We develop a framework of ecological responsiveness, and we formulate five propositions to explain why specific firms and industries may be more likely to lease green space. We test these propositions by analyzing the decisions of more than 11,000 tenants to choose office space in green buildings or in otherwise comparable non-green buildings located nearby. We find that corporations in the oil and banking industries, as well as government-related and non-profit organizations, are among the most prominent green tenants. After appropriately controlling for building quality and for location within one quarter mile, our empirical analysis shows that firms in mining and construction and organizations in public administration are relatively more likely to lease green rather than conventional office space. Furthermore, organizations employing higher levels of human capital (as measured by skills and compensation) are more likely to lease green office space.

This paper examines the factors responsible for changes in crude oil prices. The paper reviews the statistical behavior of oil prices, relates these to the predictions of theory, and looks in detail at key features of petroleum demand and supply. Topics discussed include the role of commodity speculation, OPEC, and resource depletion. The paper concludes that although scarcity rent made a negligible contribution to the price of oil in 1997, it may be an important feature of the most recent data.

In response to Assembly Bill 32, the State of California is considering three types of carbon emissions trading programs for the electric power sector: load-based, source-based, and first-seller. They differ in terms of their point-of-regulation, and in whether in-state-to-out-of-state and out-of-state-to-in-state electricity sales are regulated. In this paper, we formulate a market equilibrium model for each of the three approaches, considering power markets, transmission limitations, and emissions trading, and making the simplifying assumption of pure bilateral markets. We analyze the properties of their solutions and show the equivalence of load-based, first-seller and source-based approaches, when power sales in both directions are regulated under the cap. A numeric example illustrates the emissions and economic implications of the models. In the simulated cases, "leakage" eliminates most of the emissions reductions that the regulations attempt to impose. Further, "contract reshuffling" occurs to such an extent that all the apparent emissions reductions resulting from changes in sources of imported power are illusory.

The global petroleum system is undergoing an “oil transition,” shifting from conventionally produced petroleum to a suite of substitutes for conventional petroleum (SCPs). This paper describes the Regional Optimization Model for Emissions from Oil Substitutes, or ROMEO, which models this oil transition. ROMEO models the dynamics of the transition to substitutes for oil and the environmental impacts (greenhouse gas (GHG) intensity) of such a transition. It models the global liquid fuel market in an optimization framework. The ROMEO market mechanism operates differently than “perfect foresight” models: it solves each year sequentially, with each year optimized under uncertainty about future prevailing prices or resource quantities.

ROMEO includes more fuel types than models designed for integrated assessments of climate change. ROMEO also includes the differing carbon intensities and costs of production of these fuel types. We use ROMEO to calculate the uncertainty of future costs, emissions, and total fuel production under a number scenarios. We first explore the effects of altering three key input parameters. We then use this flexibility to more formally explore two uncertainties simultaneously: the endowment of conventional petroleum, and future carbon taxes. Results indicate that emissions penalties from production of oil substitutes are on the order of 5-20 GtC over the next 50 years, and that these results are highly sensitive to the endowment of conventional oil and less sensitive to the values of a carbon tax.

Personal computers (PCs) are one of the most ubiquitous and indispensable electronic devices in use within California’s homes and businesses. More PCs are estimated to be in use in California than in any other U.S. state. According to the latest published estimates from U.S. Department of Energy (DOE), 11.5 million PCs were installed in California’s homes (as of 2001) and 6.5 million PCs were installed in California’s commercial buildings (as of 2003) (U.S. DOE 2003, 2006a). Based on these DOE data and recent PC sales data, it was estimated in this research project that as of 2005 nearly 19 million PCs were installed in California homes and businesses and that this number is expected to grow significantly through 2012.

This research project focused on evaluating a set of realistic measures aimed at reducing the life-cycle energy use and GHG emissions associated with operating and maintaining California’s residential and commercial PC stock (hereafter referred to simply as “California’s PC stock”). The term “maintain” is used here to describe the ongoing process of replacing, upgrading, and discarding obsolete PCs within California’s PC stock as necessary. The project employed a life-cycle assessment (LCA) approach to characterize both direct and indirect energy use and GHG emissions. Direct energy use and GHG emissions were defined as the energy use and GHG emissions attributable to the operational electricity consumption of California’s PC stock. Indirect energy use and GHG emissions were defined as the energy use and GHG emissions attributable to activities that support ongoing PC stock maintenance, namely, the manufacture of new PCs and PC components as needed and the end-of-life treatment (i.e., waste disposal and recycling) of obsolete PCs and PC components.

In this research project, the potential reductions in life-cycle energy use and GHG emissions associated with the measures considered were projected through the year 2012. The purpose of this work was to characterize the effectiveness of these measures to inform PC-related policies for near-term energy efficiency improvements and GHG emission reductions in the State of California. Baseline projections were first established for the life-cycle energy use and GHG emissions associated with operating and maintaining California’s PC stock from 2005 to 2012. These baseline projections were made using best-available data from public sources for all key modeling parameters. Whenever possible, ranges for key modeling parameters were established to account for published data variations. Two future scenarios were considered: a low energy use and GHG emissions scenario (“low scenario”) and a high energy use and GHG emissions scenario (“high scenario”). The purpose of the two-scenario approach was to establish preliminary upper and lower bounds on the results based on the feasible data ranges identified from the literature for key modeling parameters. The potential reductions in life-cycle energy use and GHG emissions associated with the measures considered were then projected for each scenario over the same time period.

Commercial PC estimate was derived by: (1) assuming that 8.6 million PCs were installed in commercial buildings in the Pacific Census Region in 2003, based on the U.S. DOE 2003 Commercial Building Energy Use Survey (CBECS) (U.S. DOE 2006), and (2) assuming that 75% of Pacific Census Region commercial sector employment (as defined by the 2003 CBECS) and hence PC usage occurs in California based on employment data from the U.S. Census Bureau (U.S. Census Bureau 2006).

Electricity mergers pose distinctive challenges for competition policy - in market definition and for modelling price impacts in markets with no storage, inelastic short-run demand and transmission constraints. FERC’s pivotal supply test for screening mergers is an improvement on market shares, but still potentially misleading. We counter-propose competitive residual demand analysis. The EU is poorly placed to deal with domestic mergers that impact external energy flows. The paper argues that vertical (convergent) mergers between electricity and gas raise additional concerns, given current EU gas market power, exemplified by the E.On-Ruhrgas merger. The form of the Emissions Trading System amplifies these concerns.

A model of two-settlement electricity markets is introduced, which accounts for flow congestion, demand uncertainty, system contingencies and market power. We formulate the subgame perfect Nash equilibrium for this model as an equilibrium problem with equilibrium constraints (EPEC), in which each firm solves a mathematical program with equilibrium constraints (MPEC). The model assumes linear demand functions, quadratic generation cost functions and a lossless DC network, resulting in equilibrium constraints as a parametric linear complementarity problem (LCP). We introduce an iterative procedure for solving this EPEC through repeated application of an MPEC algorithm. This MPEC algorithm is based on solving quadratic programming sub-problems and on parametric LCP pivoting. Numerical examples demonstrate the effectiveness of the MPEC and EPEC algorithms and the tractability of the model for realistic size power systems.

We present an empirical analysis of a supply function equilibrium model in the Texas spot electricity market. We derive condititions for optimal bidding behavior in a spot market with ex ante bilaterally contracted sales. By using generation cost information, we are able to derive a set of ex post- and ex ante-optimal supply functions and use a nonparametric model of firm behavior to compare our theoretically-optimal supply functions to actual offers made in years 2002 and 2003. Our results show that with markups and markdowns far in excess of what a model of profit-maximizing behavior suggests. For small generators, municipalities, and cogenerators we find evidence suggesting these firms may be acting to exclude themselves from the market by economically witholding their generation.By using partial-linear behavior model we demonstrate some learning effects to have taken place during the first quarter of 2002.

Observers of restructured electricity markets emphasize: (1) Spot prices are extremely variable, because electricity is not storable; (2) long-dated forward markets rarely exist – those in California were a single day ahead. Actually, the first observation implies the second. With the aid of a simulation model, which replicates the seasonality, heteroskedasticity, and serial correlation in load, the precise constellations of forward prices can be deduced in a setting of perfect competition, risk neutrality, and best possible forecasting. Even at extreme conditions in the idealized spot market, the constellations of these forward prices converge to long-run seasonal means at the horizon of just a few days. Another reason long-dated forward markets for electricity are redundant is the futures market for natural gas on NYMEX, functioning at a horizon beyond two years, as demonstrated by analyses of forecasting power using the simulation data as well as the data from NYMEX and California over 1998-2000.

We estimate the rebound effect for motor vehicles, by which improved fuel efficiency causes additional travel, using a panel of US states for 1966-2001. Our model accounts for endogenous changes in fuel efficiency, distinguishes between autocorrelation and lagged effects, includes a measure of the stringency of fuel-economy standards, and interacts the rebound effect with income. At sample averages of variables, our 3SLS estimates of the short- and long-run rebound effect are 4.7% and 22.0%. But they decline substantially with income: with variables at 1997-2001 levels they become 2.6% and 12.1%, considerably smaller than typically assumed for policy analysis.