Predicting California Deman Response
How do customers react to hourly prices?
As California embarks on a Statewide Pricing Pilot (SPP) for residential and small commercial (200 kW) customers, policymakers and participants in the proceedings are asking several questions:
- What elasticity estimates should we expect the pilot to produce?
- Will a voluntary SPP program produce less load reduction than a mandatory program?
- What is the likely response of the participants, and will that response differ as a function of usage level, appliance holdings, or other non-price factors?
The answers to those questions can be anticipated somewhat by reviewing the existing literature on price responsiveness of the residential and small commercial customer segment. 1 The data, summarized in this article, is based on experiments and studies run by the Department of Energy, academic researchers, and utility companies around the world during the past three decades.
Standard economic theory holds that customers react to changes in prices by adjusting their demand for the goods in question. As prices rise, customers reduce the quantity demanded. As prices drop, customers increase the quantity demanded. The responsiveness of customers to price changes is called their .
One measurement of elasticity is the customer's change in consumption in the same time period in which the price change occurs. Another measurement is the customer's shift in consumption across time periods-such as peak to off-peak-in response to price changes that alter the price relationship between the two time periods (for example, changing the price ratio from 1:1 to 2:1). These two measurements are called the and , respectively .
What elasticity estimates could we expect the California pilot to produce?
In 1984, Jan Acton and Rolla Park reviewed 34 published studies of residential electricity use drawn from North America. Acton and Park estimated overall "short-run" and "long-run" elasticities with respect to electricity. Short-run is a period in which consumers make no changes in appliance holdings to respond to price changes, while long-run is long enough to make changes in appliance holdings. Acton and Park summarized their findings as shown in Table 1, with "low" and "high" bracketing the 80 percent confidence band.
To update these results, we reviewed the results of 56 papers published since 1980 (see Figure 1 and Table 2). These studies expanded on earlier studies by utilizing additional methodologies for analyzing price response and by examining the effects of additional rate structures, such as critical peak prices. Four studies included automated thermostat controls.
Several researchers, including Caves, Christensen, and Herriges (1983), have looked at the transferability of elasticity estimates from one geographical area to another. Caves . use a modeling approach in the spirit of a hybrid demand system. The key price effects are estimated as an elasticity of substitution between peak and off-peak periods. Table 3 shows the consistency of elasticity results calculated form the data collected in five residential time-of-use experiments.
Other researchers have looked at how price response for a time-of-use or critical peak pricing program varies when weather becomes more extreme. Aigner and Lillard (1984) found that time-of-use customers behave in a similar fashion on system