A Blended Data Approach to Measuring Monthly Housing Starts: Satellite Imagery, Survey Data and More!

Nicole Czaplicki, Colin J. Shevlin, Hector R. Ferronato, Aidan D. Smith, Dwarakh V. Nayam, Lei Peng, Scott W. Springer and Doren Walker

No 35113, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: As part of the comprehensive Construction Re-engineering Initiative at the U.S. Census Bureau, alternative data sources are being considered to supplement or replace current data collection methods. For the Survey of Construction (SOC), which measures new residential construction, this includes observing housing starts from satellite imagery in place of the current interviews for housing starts conducted by field representatives. Satellite images are obtained monthly for a subset of places in the SOC sample. Convolutional neural network models are then applied to images to predict likely new residential construction projects, with the current focus being single-family housing starts. Several post prediction processing steps are applied including exclusions based on intersections with known buildings or roads, treatments for missing data due to cloud cover, and adjustments for the length of time between consecutive images, to ultimately produce place level estimates of housing starts. These place level estimates are then combined with the existing building permit level survey data to produce estimates of West South Central division level housing starts, an experimental data product from the Census Bureau.

JEL-codes: C45 C8 C80 (search for similar items in EconPapers)
Date: 2026-04
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