Abstract
In the residential housing sector, energy conservation issues may arise in the relationship between landlords and renters (a.k.a. tenants) due to principal-agent and information problems. An example is the split incentive, where one party makes the energy efficiency decisions while the other pays the energy bill. Herein, we investigate whether the landlord and renter split incentive problem may be more likely and more challenging for college student renters than those who are not college students. This may occur from landlords perceiving that college renters lack sufficient demand for energy efficient improvements.
There is a lack of studies regarding the possibility that college renters may face greater exposure to the split incentive problem. We surveyed landlords to better understand their prior energy efficiency investment decisions and used a contingent valuation question to further investigate their choices for a hypothetical return on investment scenario. The landlords had various mixes of college students and non-students in their properties. Landlords renting one single-family property exclusively to college students had, on average, completed fewer major upgrades to their rental properties and were less likely to invest in a hypothetical insulation upgrade.
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Data availability
The de-identified data are available from the authors upon reasonable request.
Notes
Climate zones according to Beck et al. 2018.
In the same climate zone as Duluth there are two U.S. metropolitan statistical areas in the top ten for population, two more are in the top 20, and six more in the top 100 (U.S. Census Bureau 2019a).
The U.S. ENERGY STAR program’s performance criteria maps show the program’s suggestions for energy efficient investments for windows in its Northern region and for insulation in its zones 5 through 7; both of these areas are similar to the climate region that includes Duluth (U.S. Environmental Protection Agency (USEPA) 2019).
Two surveys were designed and executed, one for landlords and one for renters. For brevity, at the suggestion of an anonymous referee, we focus on the landlord survey in this manuscript. The survey was approved by the University of Minnesota Institutional Review Board to comply with research regulations regarding the use of human subjects.
The landlord survey is available at: https://umn.qualtrics.com/jfe/form/SV_7PosBhlkuJS58LH.
We acknowledge that our design does not explicitly incorporate inflation and time rate of preference calculations. While these factors are important in decision-making, we think adding ways to capture these factors would make the design overly complex and create respondent fatigue; we allowed respondents to implicitly consider these factors by picking a shorter investment recovery horizon.
Greene (2012) emphasizes that the mean and variance are per unit of time. Experience of individual landlords in their capacity is not equal. Although we do not have the count of experience in years for each individual landlord, we do have categorical ranges. Those were converted to a binary independent variable set to control for length of time as a landlord.
Variables that were considered for the regression but were ultimately insignificant or did not improve model performance included: respondent type (property manager, landlord, or both), if a majority of their income came from being a landlord, willingness to perform an energy audit, percentage of student renters, percentage of student renters multiplied by counts of property types, gender, race, and education.
It is also statistically significant for other values; however, the sample sizes are so small it seems best to focus on the outcome for one or two properties.
Protest bidders were removed from the statistical analysis based on answers to a follow-up question after the initial upgrade choice. Those choosing “No” to the upgrade decision where asked why and presented with a variety of options, being allowed to select all that applied. Those that only selected either “I don’t know how this survey will be used” or “I don’t trust that UMD [University of Minnesota Duluth] will use the information properly” were removed from the statistical sample (four observations). Those that selected one of these options in addition to one of the market-based decision choices (“The listed cost of the upgrade is too expensive for that product.” “My budgeting does not allow for more expensive upgrades.” “Reducing utility bills in my rental units is not a priority.”) were not removed. An open-ended “Other” option with a text box was provided as an option. After reviewing the text entries, no additional observations were removed as protest bidders.
As part of the insulation treatment, the language “A recent home energy audit recommended that the insulation be upgraded.” was used to help provide legitimacy to the insulation recommendation. However, the survey included the contingency that some landlords may not trust energy audits. Yet, only one respondent selected the “I don’t trust home energy audits.” option, but they also selected other market-based reasons.
Variables that were considered for the regression but were ultimately insignificant or did not improve model performance included: respondent type (property manager, landlord, or both), if a majority of their income came from being a landlord, willingness to perform an energy audit, percentage of student renters, percentage of student renters multiplied by counts of property types, gender, race, and education.
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Haynes, M., McIntosh, C.R. & Olafson, T. Is the split incentive problem worse for college student renters: an analysis of landlord self-reported and hypothetical choices?. Environ Econ Policy Stud (2024). https://doi.org/10.1007/s10018-024-00399-z
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DOI: https://doi.org/10.1007/s10018-024-00399-z