Why do the numbers you see in mySidewalk sometimes differ from other sources?
There are two main reasons the numbers you see in mySidewalk may differ from other sources:
Dynamic calculation of data for your custom boundary, AKA apportionment
Harmonization of historical data to modern boundaries
1. Dynamic Calculation of Data for Your Custom Boundary (Apportionment)
You can upload or draw a custom boundary within the mySidewalk platform. The platform automatically calculates data for your custom boundary by using two key elements:
Census Block Ratio Tables: These tables provide the number population, households, and housing units in each block.
Data for Census Block Groups or Tracts: If block group data isn't available, we'll look at census tracts instead.
mySidewalk then looks up all the Census blocks contained within your custom boundary, and finds the population, household, or housing unit ratio from those blocks to apportion values from the Census block group or tract into your custom boundary.
Why use blocks?
People are not evenly distributed across a Census block group or tract. There may be parks, industrial areas, or retail spaces that affect the distribution. Census blocks reflect this uneven distribution, allowing for a more accurate calculation for your custom boundary.
Population, Households, or Housing Units?
Most Decennial Census and ACS data fall into one of these three categories: population, households, or housing units. A household is a group of people living together, whereas housing units describe the physical structures where people reside. mySidewalk maintains a metadata system that tracks the best-fit ratio type for each case.
Pro-Tip:
The accuracy of data calculated for a small number of Census blocks can be affected by errors. That's why mySidewalk shows a warning if your custom geography overlaps fewer than 40 Census blocks or fewer than three different Census block groups or tracts.
2. Harmonization of Historical Data to Modern Boundaries
mySidewalk uses the most up-to-date geographic boundaries. We harmonize historical data into the new boundaries as they update. This involves taking historical data which was produced for a different boundary, and recalculating it to fit the modern boundaries.