Terms and Definitions
Area Median Income (AMI) is the income level set by the Department of Housing and Urban Development (HUD) for a specific region. By definition, 50% of households earn above the AMI, while the other 50% earn below it. Typically, AMI is aligned with county boundaries, although some states use subdivisions.
State Median Income (SMI) is similar to AMI but is defined by individual states, which establish thresholds for low, medium, and high-income categories.
The Heating Fuel Type (HFT) category comprises the primary heating fuel sources (e.g., utility gas, bottled gas, electricity, fuel oil) used by housing units within the analyzed geographies.
Energy Burden is calculated as the average annual housing energy cost divided by the average annual household income. This percentage reflects energy expenses as a portion of gross income, excluding other energy costs and transportation expenses.
Monthly housing energy costs are derived from household expenditures on electricity, gas (utility and bottled), and other fuels (including fuel oil and wood).
The Building Age category organizes housing units based on their initial construction year within a given geography.
The Rent/Own category classifies housing units according to occupant tenure (renting or owning) in each geography.
Disadvantaged Communities (DAC) are defined following guidance from the White House for federal agencies. The Climate and Economic Justice Screening Tool (CEJST) assists in identifying these communities by considering factors such as climate change, energy, health, housing, pollution, transportation, water, and workforce development. LEAD incorporates CEJST's DAC data.
Data Calibration
The energy data in LEAD was calibrated to allocate total state energy consumption to specific geographies using state electricity and natural gas sales data reported by the U.S. Energy Information Administration (EIA).
Utility boundaries for electric and gas services were mapped at the census block level utilizing Ventyx utility territories spatial data, allowing the LEAD team to define these boundaries accurately.
- Begin with self-reported monthly energy expenditures by energy type from the ACS Public Use Microdata Samples.
- Scale monthly expenditures to annual energy consumption by multiplying by 12 and adjusting for inflation.
- Calibrate the data against utility-level consumption figures from EIA Forms 861 and 176 to ensure alignment with average revenue values across service territories. The 2024 LEAD release calibrated ACS data from 2018-2022 to 2022 EIA data.
American Community Survey Data
The LEAD 2024 Census data is sourced from the U.S. Census Bureau’s 2022 American Community Survey Public Use Microdata Samples, specifically the 5-Year Average for 2018-2022.
Public Use Microdata Areas (PUMAs) are geographic regions that originally consist of approximately 100,000 people and are adjusted after each Decennial Census.
LEAD opted for PUMA data due to its detailed household-level information at a geographic level, allowing for more flexibility in data aggregation.
PUMAs were assigned to census tracts within the geography. Significant discrepancies between PUMA and ACS data triggered an iterative adjustment process to align values.
The ACS data available to the public is anonymized, which can lead to discrepancies in household counts. LEAD estimates household counts using multiple datasets.
Energy Burden values may appear inflated due to small sample sizes in the ACS, leading to skewed calculations.
- Aggregate households at the census tract level within the county.
- For each census tract, multiply the Energy Burden by the corresponding number of reported households.
- Sum the values from step two.
- Divide the results from step three by the total households to obtain the county-level weighted average Energy Burden.
Weighted average calculations ensure proportional representation of households within geographies, preventing skewing from areas with high Energy Burden but few households.
ACS reports both mean and median income values; LEAD’s income values align more closely with mean incomes. Differences in PUMA data assignment can also contribute to value variances.
Given that ACS data is based on a small sample, decimal points could mislead users. LEAD rounds Energy Burden values to the nearest whole number to enhance transparency.
LEAD utilizes three income models (AMI, Federal Poverty Level, SMI) to aggregate household counts and income without retaining every combination of PUMA data.
Yes, all household sizes are represented within each income model in the LEAD Tool.
The ACS tables corresponding to LEAD data include: B25036, B25127, B25032, B25124, B25117, B25009, B25013, and B01001A-H. Users can access this information via the Census Bureau Tables.
Household energy consumption estimates in LEAD arise from the 2022 ACS 5-Year dataset.
LEAD employs 5-year rolling averages from ACS 2018-2022 data, adjusted for inflation, for household income determinations.
The LEAD Tool uses AMI data based on the 2022 income limits established by HUD.
Demographic variables represent the household population as a percentage based on selected filters within each geography.
Though LEAD utilizes ACS data, which is household-level, it cannot extrapolate energy burden for individuals by race or demographics.
Users can focus on census tracts with high population percentages of specific races to analyze variations in energy burden.
Tool Functionality
Utilize the slider in the Criteria Filters under Energy Burden to adjust the range visualized. Data can also be downloaded as a .csv file from the map and chart areas for further analysis.
The legend updates dynamically to reflect the values of the geographies displayed at different zoom levels.
Heating Fuel Type categorizes primary heating sources, whereas Energy Burden is classified into three main categories: Electricity, Gas, and Other, with "Other" encompassing additional energy costs excluding transportation expenses.
The menu icon in the top right of the LEAD Tool provides access to further data downloads, documentation, case studies, and other helpful resources.
Expand the Chart Settings in the top right corner of the chart window to adjust data on the x-axis and y-axis, and select variables for plotting or add secondary axes.
Use the ‘Share’ link in the top right corner of the LEAD Tool to copy and email the map or save settings for later use.
“RESET LEAD TOOL” resets all comparisons and criteria filters, while “RESET FILTERS” only clears criteria filters that have been applied.
Currently, no login is required to access the LEAD Tool; users can start using it immediately.
Users can activate the DAC layer by checking the "Show DACs" box above the map or by accessing the Map Settings via the gear icon.