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As arid cities’ water scarcity concerns grow, so does the importance of residential water conservation. Understanding the drivers of participation in water conservation programs can aid policymakers in designing programs that achieve conservation and enrollment targets while achieving cost-effectiveness and distributional goals. In this study I identify and analyze the characteristics that drive participation in the Southern Nevada Water Authority’s Water Smart Landscaping rebate program – a program that pays homeowners to replace their grass lawns with xeric landscaping – and how those characteristics change over time as rebate values and water prices vary.
In order to determine what characteristics influence participation in this program I gathered data from multiple sources. I use a panel dataset of household water consumption that spans 12 years of approximately 300,000 homes. I merged this dataset with home structural characteristics, geographical, and demographic context. I then use these characteristics in a linear probability model, with school enrollment zone fixed effects to determine their influence on a household’s probability of participation. School zones are used to control for unobserved characteristics, such as demographics, which are not at a household level. I then utilize these school zone fixed effects in a 2nd stage regression to decompose these elements and analyze their effect on participation.
I find that a household’s water costs, as reflected in the marginal price faced in the summer and the differential between summer and winter water bills, as well as yard size are primary factors that influence participation. I also show that changes in rebate value and water rates can affect different types of households. There is also evidence to support that neighborhood characteristics affect a household’s likelihood of participating.
In order to determine what characteristics influence participation in this program I gathered data from multiple sources. I use a panel dataset of household water consumption that spans 12 years of approximately 300,000 homes. I merged this dataset with home structural characteristics, geographical, and demographic context. I then use these characteristics in a linear probability model, with school enrollment zone fixed effects to determine their influence on a household’s probability of participation. School zones are used to control for unobserved characteristics, such as demographics, which are not at a household level. I then utilize these school zone fixed effects in a 2nd stage regression to decompose these elements and analyze their effect on participation.
I find that a household’s water costs, as reflected in the marginal price faced in the summer and the differential between summer and winter water bills, as well as yard size are primary factors that influence participation. I also show that changes in rebate value and water rates can affect different types of households. There is also evidence to support that neighborhood characteristics affect a household’s likelihood of participating.
ContributorsRusso, Jonathan (Author) / Abbott, Joshua (Contributor) / Brelsford, Christa (Contributor) / Larson, Kelli (Contributor)
Created2018-04-21