Natural and incentive-induced conservation in voluntary energy management programs.

• Author: Waldman, Donald M.

1. Introduction

   Energy conservation is a topic of worldwide importance. In addition to the prospect of depleted nonrenewable supplies, increased concern over environmental issues, such as air pollution and global warming, have contributed to the interest in energy conservation. The U.S., as the largest per capita user of energy, has taken the lead in promoting conservation and pollution abatement, through incentive and regulation. This climate has led to an important development in the utility industry in the last few years: the growth of "demand-side management" (DSM) programs. These voluntary programs are designed to induce the adoption of energy efficient technology (new capital) by consumers (both residential and commercial/industrial).

   DSM is advocated by utility regulators, who cite factors such as the divergence of the private and social short run costs of energy (due to, e.g., the existence of environmental externalities), and the fact that the price of energy is not equal to its long run marginal cost. This means that the cost of implementing these programs may be below the cost of increasing capacity. In addition, some DSM programs are designed to flatten the load curve (power demand over time), since the cost of producing power at peak load is considerably greater than at times of normal system demands. For the consumer, it is argued that there are market imperfections which prevent adoption of energy efficient measures. These imperfections are usually attributed to the consumer's lack of knowledge concerning energy efficient technology.

   Total revenue lost by the utility from a DSM program is the sum of the direct incentive cost, returned to the consumer, and the value of any lost sales. These costs may be offset by any efficiency gains in production, especially during periods of peak demand. In order to preserve the stockholders' rate of return in these regulated companies, this revenue loss is usually recovered by an increase in utility rates. To warrant this, utilities must present evidence of lost revenue due to energy savings to their regulatory commissions. These programs are becoming so large and wide-spread that by the turn of the century, it is expected that they will cost utilities over two billion dollars annually [6].

   Lewis and Sappington [7] have examined the role of information for optimal regulatory policy with respect to firms offering DSM programs. They assume that firms have better information about the effect of the programs than the regulators. If the firms have good information, regulators can motivate firms to use their superior knowledge to achieve socially optimal outcomes.

   Of obvious importance, then, is the estimation of the reduction in energy use resulting from these programs. This is a formidable task, as there are a number of economic and econometric problems that arise. First, the programs are voluntary - in most states by law no controlled experiments can be performed. This means that those who participate are a nonrandom sample of the population, and unless a complete model of program participation and energy savings is formulated, estimates of program savings will suffer from sample selection bias [4; 5]. Second, variable measurement is difficult, as desired conservation behavior does not necessarily equal observed conservation behavior. This means that data sets will be characterized by endogenous variables that are truncated and polytomous. Third, energy efficient capital is lumpy by nature. This means that only some households or firms faced with a reduction in the price of capital due to the DSM program will purchase new equipment. These corner solutions or lack of response smoothness make estimation difficult.

   But perhaps the most important problem is that, during any observation period, a certain amount of natural conservation takes place. This conservation, concurrent with but unrelated to the DSM program confounds attempts to measure the true effect of the program. The purpose of this paper is to analyze a method of decomposing measured conservation into a natural component and an incentive-induced component. This will be done in a complete model of energy conservation and energy use that eliminates the sample selection bias due to the voluntary nature of the programs, while at the same time properly treating the truncated and polytomous variables that arise. Moreover, we propose a common statistical framework for estimating savings for the three most widely adopted (residential) DSM programs. The important observation that allows this decomposition is the fact that, in any random sample of consumers both program participants and others, unaware of the available incentives, have undertaken conservation action. Therefore, despite the fact that a controlled experiment is not possible, this form of natural experiment allows the decomposition of energy savings.

   Our model and methodology is widely applicable. As another environmental example, to conserve rapidly depleting clean groundwater sources, water utilities have started to offer incentives to reduce its use (such as free low-flow shower heads). In any location where water is metered and households are billed, natural conservation may take place. The effectiveness of the program then depends upon incentive-induced savings. But the model is even more general. Consider a firm that offers workers incentives to take training. Some workers may have decided to add to their human capital without firm incentive, but these "free riders" will be counted in an evaluation of the training program.

   We utilize an enriched sample of program participants and nonparticipants from a large midwestern utility. The data are of high quality as actual billing records from the utility provide information on energy use. The dependent variable in the analysis, therefore, is not subject to either measurement or reporting error, as would be the case with survey data.

   The next section outlines a behavioral model for taking conservation action and for energy use. Section III describes the data and presents empirical estimates. In section IV the estimated parameters of the model are used to simulate program-induced conservation in different incentive scenarios. The last section concludes.

2. An Econometric Model of Conservation Behavior and Energy Use

   Consider a two-equation model of energy conservation behavior and energy use.(1) The first equation determines whether or not any energy conservation action (purchase of new capital equipment) is taken as well as the amount of conservation action. The observed amount of energy conservation action will not necessarily equal the desired amount, for several reasons. First, some conservation action, such as ordering a home energy audit or purchasing energy efficient appliances, is lumpy by nature. Second, it is conceivable that some households would prefer to dissave energy, that is, if it were possible they would make their homes less energy efficient and claim the capital cost difference in other goods. This is not usually possible, which means that when desired action is negative observed conservation action is zero. Therefore, depending upon the program being analyzed, observed conservation action could be dichotomous (home energy audit program), polytomous and ordered (appliance rebate program), or bounded nonnegative (subsidized loan program). That is, in the audit program, households are observed to have their homes inspected for possible conservation measures, or not to order such an audit. In the rebate program, they may do nothing, or purchase any of a discrete menu of appliances in increasing degree of efficiency (and cost). In a subsidized low-interest loan program, households may borrow money to install new equipment (but they cannot sell any existing equipment to reduce their energy efficiency).

   Let [Mathematical Expression Omitted] be the per-period, desired amount of conservation action. This is the result of a utility maximization calculation over the price of energy, other goods, and the utilities associated with the consumption of the services of energy and other goods. Let [x.sub.1] be a column vector of individual, household, and housing characteristics that affect the benefits and costs of undertaking energy conservation. Let z be a column vector of program characteristics, such as the amount of a subsidy for a home energy audit or the interest rate buy-down in a loan program. Desired conservation is assumed to be a linear function of [x.sub.1] and z:

   [Mathematical Expression Omitted],

   where [[Beta].sub.1] and [Lambda] are unknown row vectors of parameters to be estimated and [[Epsilon].sub.1] is a random disturbance symmetrically distributed about zero, assumed to be uncorrelated with [x.sub.1] and z. Equation (1) forms the basis for the analysis of natural conservation. Some households, unaware of a utility-sponsored incentive, undertake conservation.(2) This natural conservation is undertaken, for many reasons: as new, energy efficient products become available; due to changes in relative prices; and due to changes in tastes for the services of energy. In the absence of, or unaware of utility-sponsored incentives, households have desired, expected conservation action equal to [[Beta].sub.1][x.sub.1]. The program is responsible for the marginal desired conservation action, [Lambda]z. Put another way, households are assumed to be in long run equilibrium with respect to their expenditures on the capital equipment that produces the services of energy (such as heating/cooling equipment), and in short run equilibrium with respect to their budget shares for energy and other goods. Additional (marginal) conservation is then undertaken as a result of the reasons suggested above, and the introduction of incentives (z) that change the budget set faced by households. When utility companies introduce a savings program, households may no longer be in long run...