David Ritzwoller
@dritzwoller.bsky.social
Ph.D Candidate, Stanford GSB
Econometrics, Causal Inference, Machine Learning
https://davidritzwoller.github.io/
Econometrics, Causal Inference, Machine Learning
https://davidritzwoller.github.io/
This suggests geographic proximity alone inadequately captures spatial dependence. Even adding population as a covariate doesn’t fully resolve the issue. While several covariates predict high correlations, no single factor completely captures the dependence structure.
May 4, 2025 at 2:04 AM
This suggests geographic proximity alone inadequately captures spatial dependence. Even adding population as a covariate doesn’t fully resolve the issue. While several covariates predict high correlations, no single factor completely captures the dependence structure.
Here's a correlogram for counties in CA, NY, and ND, sorted by state and population. Urban counties in CA correlate more strongly with urban counties in NY than with rural counties in CA. Rural CA counties correlate more closely with ND counties than with urban areas within CA.
May 4, 2025 at 2:04 AM
Here's a correlogram for counties in CA, NY, and ND, sorted by state and population. Urban counties in CA correlate more strongly with urban counties in NY than with rural counties in CA. Rural CA counties correlate more closely with ND counties than with urban areas within CA.