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Rebates, Loans, and Customers' Choice of Appliance Efficiency Level: Combining Stated- and Revealed-Preference Data

Kenneth E. Train and Terry Atherton

Year: 1995
Volume: Volume16
Number: Number 1
DOI: 10.5547/ISSN0195-6574-EJ-Vol16-No1-4
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Abstract:
Residential customers' choice of efficiency level for appliances, and their participation in demand-side management (DSM) programs, are examined using data on customers' stated preferences in hypothetical (i.e., conjoint-type) situations and their revealed preferences in real-world choices. The analysis provides information on customers' willingness to pay for energy savings, the importance of rebates in customers' decisions, and customers' response to DSM programs that offer loans for purchases of high-efficiency appliances. An estimated model is used to forecast the decisions of customers under: higher rebates, replacement of rebates with finance programs, offering of loans and rebates as alternative options for customers, and the elimination of DSM programs. We find that attractive loans (e.g., low interest rates, long repayment periods) are necessary to have the same effect as rebates. Programs that offer customers the option of loans or rebates are found to be far more effective than programs that offer only loans or only rebates.



The Impact of Dynamic Pricing on Residential and Small Commercial and Industrial Usage: New Experimental Evidence from Connecticut

Ahmad Faruqui, Sanem Sergici, and Lamine Akaba

Year: 2014
Volume: Volume 35
Number: Number 1
DOI: 10.5547/01956574.35.1.8
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Abstract:
Among U.S. households, a quarter have smart meters but only one percent are on any form of dynamic pricing. Commissions and utilities continue to study the potential benefits of dynamic pricing through experimentation but most of it involves the residential sector. We add to that body of knowledge by presenting the results of a pilot in Connecticut which included small commercial and industrial (C&I) customers in addition to residential customers. The pilot featured a time-of-use rate, two dynamic pricing rates and four enabling technologies. Customers were randomly selected and allocated to these rates, to ensure representativeness of the final results. The experiment included a total of around 2,200 customers and ran during the summer of 2009. Using a constant elasticity of substitution model, we find that customers do respond to dynamic pricing, a finding that matches that from most other experiments. We also find that response to critical-peak pricing rates is higher than response to peak-time rebates, unlike some other experiments where similar results were found. Like many other pilots, we find that there is virtually no response to TOU rates with an eight hour peak period. And like the few pilots that have compared small C&I customer response to residential response, we find that small C&I customers are less price responsive than residential customers. We also find that some enabling technologies boost price responsiveness but that the Energy Orb does not.



An Examination of How Energy Efficiency Incentives Are Distributed Across Income Groups

Grant D. Jacobsen

Year: 2019
Volume: Volume 40
Number: Number 6
DOI: 10.5547/01956574.40.6.gjac
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Abstract:
Many policies lead to the provision of incentives, such as rebates or tax credits, to consumers for the purchase of products that have high energy efficiency. This paper investigates how these incentives are distributed across income groups for three types of subsidies (manufacturer or retailer rebates, utility rebates, and tax credits) and eight types of equipment. While incentives are always concentrated in higher-income households, there is substantial heterogeneity in the magnitude of the concentration depending on how incentives are structured. Tax credits are the type of subsidy that is most concentrated in higher-income households and utility rebates are the least. Incentives for appliances that are not universally-owned, including dishwashers and clotheswashers, are more concentrated than are incentives for other types of equipment. Differences across income groups in the rates of equipment presence and turnover, willingness to purchase Energy Star models, and rates of homeownership contribute to the concentration. After controlling for these factors, utility rebates are no longer concentrated in higher-income households, but manufacturer / retailer rebates and tax credits remain so.



Evaluating the Energy-Saving Effects of a Utility Demand-Side Management Program: A Difference-in-Difference Coarsened Exact Matching Approach

Richard Boampong

Year: 2020
Volume: Volume 41
Number: Number 4
DOI: 10.5547/01956574.41.4.rboa
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Abstract:
This paper seeks to estimate the energy-saving effect of a Demand-Side Management program, specifically Gainesville Regional Utility's (GRU) high-efficiency central Air Conditioner (AC) rebate program in which GRU offers incentives to its customers to replace their old, low-efficiency AC unit with a high-efficiency model. We use a difference-in-difference coarsened exact matching approach to reduce the imbalance of pre-treatment characteristics between treated and control households. We find substantial annual energy savings of the high-efficiency AC program. We disaggregate the energy-saving effects into summer peak effects, winter peak effects, and non-peak effects. The results indicate that the summer peak effects are substantial and statistically significant while there are little or no statistically significant effects of the program on winter peak demand. Also, by following program participants over a three-year period, we find that there is no statistically significant rebound effect of the high-efficiency AC rebate program.





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