Free Riding, Upsizing, and Energy Efficiency Incentives in Maryland Homes.

• Author: Alberini, Anna
• Position: Report - Statistical data

1. INTRODUCTION

   Residential energy efficiency policies in the US and several other countries have traditionally relied on standards for equipment and new home construction, on incentives, and, more recently, on the explicit provision of information about the energy efficiency of devices and buildings. (1) These approaches have received much recent attention due to i) the large contribution of buildings to total energy use (30-40%) and the associated carbon dioxide (C[O.sub.2]) emissions, ii) assessments that improving energy efficiency in buildings would reduce carbon emissions at low or even negative cost (Levine et al. 2007; Choi Granade et al., 2009), and iii) the view that homeowners are reluctant to invest in energy efficiency improvements. (2)

   Incentives usually take the form of tax credits or direct rebates to the consumers who install insulation or energy-saving windows, and/or purchase high-efficiency heating systems, air conditioners, water heaters, and appliances. Between 2005 and 2009, federal expenditure on residential energy efficiency programs was $2.2 billion (2009 $) (Allaire and Brown, 2012), and in fiscal year 2013 federal expenditures on tax preferences targeting energy efficiency improvements in existing and new homes reached almost $4 billion (2013 $) (Dinan, 2013).

   Proper assessment of the effectiveness of incentive programs is inherently problematic because of adverse selection (people are replacing equipment at the end of life; Sandler, 2012) and the likelihood that the programs attract people who are systematically (and unobservably) more motivated or productive at reducing usage. These considerations have led observers to conclude that, unless the presence of "free riders"--persons who pocket the incentive, but would have done the energy-efficiency renovation or upgrade anyway--is adequately accounted for, assessments will generally overstate the cost-effectiveness of the programs, i.e., the cost per unit of energy or carbon emissions saved (Joskow and Marron, 1992; Hartman, 1988; Waldman and Ozog, 1996; Malm, 1996; Grosche and Vance, 2009; Allaire and Brown, 2012).

   Other undesirable behavioral responses are possible. For example, using data from Canada, Young (2008) documents that many households do not dispose of old and inefficient refrigerators, once they replace them with new ones, and keep using them as "beer fridges" (to store cold beverages), for a net increase in electricity consumption. This can be avoided with careful incentive program design, which in turn will increase program complexity and the associated administrative and enforcement costs. Similarly, in programs that seek to replace conventionally-generated electricity with electricity generated from renewables, Jacobsen et al. (2009) find that participating households actually increased electricity usage, despite the fact that the price per kWh is higher than that of conventionally generated power.

   One concern is that high-efficiency equipment lowers the price per unit of energy services, engendering a combination of substitution and income effects known as the rebound effect (Dimitropolous and Sorrell, 2007), with households purchasing more energy services and/or energy than before. Very strong rebound effects diminish the attractiveness of energy efficiency incentive programs, but in the case of residential electricity and heating fuel use, the (direct) rebound effects have generally been thought to be small (Sorrell et al., 2009; Linares and Labandeira, 2010; Gillingham et al., 2013). (3)

   These claims are often based on inferring the extent of the rebound effect from energy price elasticities (Gillingham et al., 2013). Past evaluations often relied on engineering estimates of the energy savings from certain technologies or measures, without observing actual behaviors, and as such, depending on study design and implementation specifics, may have either over- or understated the true energy savings (Jacobsen and Kotchen, 2013; Grosche, Schmidt and Vance, 2012; Greening et al., 2000; Sorrell et al., 2009; Metcalf and Hassett, 1999). There is also disagreement in the literature as to what exactly should be measured--physical energy units (e.g., kWh), energy services (the temperature in a home over a specified period), or other units yet (Turner, 2013).

   Empirical work on incentive programs and their effects on energy use is, however, no easy task. In the handful of US government-conducted surveys about residential energy use and energy-efficiency investments, renovations are not described in sufficient detail and information about energy-efficiency incentives is limited or absent altogether. Some authors use electricity or gas consumption records provided by the utilities to examine responsiveness to shocks (such as price changes or the provision of feedback on consumption, e.g. Allcott, 2011), but these studies usually lack information about the dwelling and energy efficiency upgrades, which are ignored or assumed away.

   To circumvent these limitations in the literature, we designed and implemented our own survey of households and have carefully attempted to address each data weakness (or omission) mentioned above in the construction of the sample. We conducted our survey in four counties in Maryland in the last quarter of 2011. In the five years prior to the survey, Maryland residents had plentiful opportunities to avail themselves of energy-efficiency incentives. In addition to the incentives made available by the Energy Policy Act (2005) and the American Reinvestment and Recovery Act of 2009, Maryland residents received state- and utility-offered incentives in 2010 and 2011.

   The survey questionnaire asked owners of single-family homes whether in the last five years they had 1) replaced the heating system, 2) replaced the air conditioning system, and 3) installed wall or attic insulation, new windows, etc. If so, we further asked them how much they spent on each of these renovations or installations, whether they received a rebate or tax credit on the purchase, how much that rebate or tax credit was for, and whether they would have still done the replacement(s) or installation(s), had the rebate or tax credit been absent altogether.

   We sent letters to 10,000 Maryland households who own the homes they live in. A total of 1153 of them filled out our questionnaire in September-December 2011. We conducted followups of subsamples of participants and non-participants in the summer of 2012.

   A unique aspect of our study is that for all of the 10,000 households that were invited to participate in the survey, we have extensive information about the dwelling and its structural characteristics. Additional information about the characteristics of housing and residents in the neighborhood comes from the Census. We also have these households' monthly electricity usage and billing records (provided by the local utility) from December 2007 to April 2012, and information about participation in utility programs.

   These sources of data allow us to create a unique panel dataset that we use to study equipment replacement, uptake of incentives, and their effect on energy use. We ask three key research questions. First, in a setting where energy efficiency standards are present, does replacing the heating/cooling system with a new and (at least on paper) more energy-efficient system truly reduce energy use? Second, is there heterogeneity in the effect of changing the heating and cooling equipment? If so, what are the main drivers of this heterogeneity? Third, do households who apply for and receive incentives reduce their electricity consumption more, either because they are more "productive" at reducing usage (Joskow and Marron, 1992) or because they are required to purchase more energy-efficient equipment?

   In this paper attention is focused on homes heated and cooled by a single device, a heat pump. Heat pumps are common in our study area, which is not served by the natural gas line network, where they are the principal heating and cooling system for some 50% of the homes. We study heat pump replacements. The 2005 Energy Policy Act required that as of 2006 all new heat pumps meet certain energy efficiency standards, which means that households that replaced their heat pumps in the five years prior to the survey must have adopted more energy-efficient equipment.

   We use a difference-in-difference approach where the treatment group is comprised of those who changed their heat pumps within the last five years, the control group is comprised of those who haven't, and the treatment is defined as the replacement of a heat pump. We further examine if the treatment effect on electricity usage depends on household and house characteristics, is different for households who received an incentive for their purchase, and depends on the incentive amount. We investigate heterogeneity and incentive effects with fixed-effects "within" estimation and fixed-effects quantile regressions.

   Briefly, we find that replacing an existing heat pump with a new one reduces electricity usage, after we control for household-specific fixed effects, weather and time of the year. The average treatment effect on the treated is an 8% reduction. There is a large difference, however, between "natural replacers" (those that replace units without incentives) and incentive recipients-and the difference is the opposite of what we expected. The former reduce their electricity usage by about 16%; for the latter the reduction is virtually nil, despite the fact that the manufacturerspecified energy efficiency ratings and the expenditure on the new heat pump is virtually identical across the two groups of replacers.

   We also find that the larger the rebate, the less the electricity reduction. For all practical purposes, rebates of $1000 or more have no effect on usage. Rebates of $300 and $450 (the typical rebates offered by utility or state programs) result in usage...