  The Council on Environmental Quality's Climate and Economic Justice Screening
Tool defines "disadvantaged communities" (DAC) in the USA, highlighting census
tracts where benefits of climate and energy investments are not accruing. We
use a principal component generalized linear model, which addresses the
intertwined nature of economic factors, income and employment and model their
relationship to DAC status. Our study 1) identifies the most significant income
groups and employment industries that impact DAC status, 2) provides the
probability of DAC status across census tracts and compares the predictive
accuracy with widely used machine learning approaches, 3) obtains historical
predictions of the probability of DAC status, 4) obtains spatial downscaling of
DAC status across block groups. Our study provides valuable insights for
policymakers and stakeholders to develop strategies that promote sustainable
development and address inequities in climate and energy investments in the
USA.
