Overview of Census Projections
mySidewalk provides a rich collection of U.S. Census data spanning over 40 years. By leveraging historical data, we have developed projections for many key indicators. These projections are available for all mySidewalk geographies and can be apportioned to custom boundaries.
Published Census Data Sources
The projections are based on data from the following sources:
Decennial Census 1990
Decennial Census 2000
Decennial Census 2010
Decennial Census 2020
American Community Survey (ACS) 2007–2011 (used to supplement data not covered by the short-form Decennial Census 2010)
Decennial Census 2020
Current ACS 5-year Estimates
How We Prepare the Data
Creating projections requires rigorous data preparation, which includes:
Geographic Harmonization
Data from Decennial Census 1990 and 2000 is adjusted to align with 2010 block group boundaries.
All historical data is harmonized to the current 2020 boundaries, ensuring consistency.
Apportionment
Data is apportioned from block groups to mySidewalk boundaries using weighted block-to-block group apportionment.
Values for states and the nation are directly sourced from Decennial Census data for accuracy.
Missing Data Imputation
Missing values in the block group dataset are estimated using geographically proximate data within the same census tract.
Example: If a block group from the 1990 Census is missing total household data, the missing value is estimated based on surrounding block groups in the same tract.
Missing values are not imputed for mean or median indicators if there is insufficient data in the census tract.
Projection Methodology
Projections are calculated for 5 years into the future, spaced 2 years apart, using a modified linear regression model. Here’s how:
Regression Slope: Standardized to avoid overfitting.
Baseline Value: The midpoint of the most recent ACS 5-year estimates is used as the starting point for projections.
Key Terms Explained
Geographic Harmonization: Aligning historical data to match current geographic boundaries.
Apportionment: Distributing data from one geographic level to another (e.g., block groups to custom boundaries).
Where to Learn More
For details on geographic harmonization and custom boundaries, visit our guide:Getting Data into Modern and Custom Geographic Boundaries.