Energy Affordability
The Energy Affordability dimension contains data elements about the income level of customers in a given area. This data is primarily sourced from the US Census and other reputable US government sources. In comparison to the data in the Demographic dimension, the Energy Affordability shared data comes with the benefit of offering nearly comprehensive coverage for each attribute for all of the customers in your service territory. The US Census asks a number of questions and then offers a number which is an average for an area, such as a census tract. There could be as few as 1,500 people in a census tract, but there are typically ~5,000 people in an average census tract, so each person in that area would be assigned the same value.
| Data Element | Description |
|---|---|
| Ability to Pay |
The Ability to Pay of a household is defined as income minus housing costs, by Census Tract. The Ability to Pay serves as a proxy for a consumer’s available household budget. (Housing costs are the sum of payments for mortgages, rent, and real estate taxes; fire, hazard, and flood insurance on the property; utilities; and fuels). This index was calculated using an Analytical Hierarchical Process (AHP) weighting method to reconcile the relative importance of income versus housing costs, where income is a first order factor and housing cost is second order. The AHP method resulted in an index that ranged from 0-1000 where 1000 represented the highest need, or lowest available income, by households that had the least income and the highest housing costs. By contrast, those households with the highest income and the lowest housing costs would have the lowest index, closest to 0. The index is normalized for a number of households. Income bins used are derived from the Area Median Household (AMI) delineation.
Allowed Values: double Source: 2016 US Department of Energy. Calculated from the American Community Survey. For more information, see Affordability and Access in Focus: Metrics and Tools of Relative Energy Vulnerability (Lin et al. 2018). Notes: The ability to pay provides a more accurate interpretation of affordability for communities that have high housing costs, such as New York City, San Francisco, and other high-cost metro areas. Type: Attribute |
| Approximate Income Level |
Median household income in the past 12 months (in 2018 Inflation-Adjusted Dollars). This data is available in $10,000 increments. Allowed Values: integer Source: 2018 US Census, American Community Survey (ACS) Type: Attribute |
| Dominant Fuel Price |
The price of the dominant fuel type. Source: American Community Survey (ACS) Type: Attribute |
| Dominant Fuel Type |
Dominant heating fuel type. This data is available at the county level. Allowed Values: Fuel price units are $/mmbtu. Source: Fuel type estimates are from the 2014 US Census American Community Survey housing units by fuel type estimates. Fuel costs are from the 2017 Energy Information Administration (EIA) Residential Energy Consumption Survey (RECS). Costs are joined to counties by the dominant fuel type and census division. Type: Attribute |
| Energy Burden |
Energy burden is defined as the total household energy costs divided by the household's income. (Transportation is out of scope.) This value is a percentage which ranges from 0-100%. An energy burden above 6% is considered a high energy burden. Note: This attribute is different from the HH Level Energy Burden attribute in the Customer Energy Burden dimension. Allowed Values: integer Source: 2016 US Department of Energy. Low Income Energy Affordability Data (LEAD) Tool. Type: Attribute |
| Housing Vintage |
Percentage of houses by vintage for a census tract. Sources: 2016 US Census, American Community Survey. Data downloaded using IPUMS NHGIS, University of Minnesota, NHGIS. Type: Attribute |
| Locale |
The locale of the customer using the National Center for Education Statistics (NCES) framework. The NCES locale framework is composed of four basic types: City, Suburban, Town, and Rural. Each of these basic types contains three subtypes. It relies on standard urban and rural definitions developed by the U.S. Census Bureau. Each type of locale is either urban or rural in its entirety. A city is considered urban, and a town is considered a subset of the "Rural" category. Allowed Values:
Source: 2016 National Center for Education Statistics (NCES), Education Demographic and Geographic Estimates Program (EDGE). Type: Attribute |
| Percent Children and Elderly |
Tract-level estimates for percent children (<18 years) and elderly (>65 years) populations. Sources: 2016 US Census, American Community Survey. Data downloaded using IPUMS NHGIS, University of Minnesota, NHGIS. Type: Attribute |
| Sub Locale |
The sub locale of the population. Type: Attribute |