syedmfuad / food_store_location_pred

Codes for food store presence, density and popularity predictor. Merges census tract-level demographic data from ACS, neighborhood amenities from heterogenous sources, and Point of Interest (POI) data from anonymized cellphone GPS ‘pings’ to identify food retailer location and foot traffic information.

food_store_location_pred

This paper uses census tract-level data to determine the presence, density, and popularity of U.S. food retailers. We merge census tract-level demographic data from ACS, neighborhood amenities from heterogenous sources, and Point of Interest (POI) data from anonymized cellphone GPS ‘pings’ to identify food retailer location and foot traffic information.

Sequence: ACS -> Merge -> Regressions

acs2010_codes.R

Downloads ACS 2010 5-year average census tract level demographic data + 2010 dicennial census data. Merges census tract-level data on walkability scores, job density, transit availability, road network, local sales tax and county-level crime statistics.

acs2019_codes.R

Same as above but with 2019 data.

merge.R

Merges with Safegraph point-of-interest data (store count) and store visit frequency data.

regressions.R

• Correlation plot
• t-test
• Logit
• Gradient Boosted Logit
• Gradient Boosted Logit w/ balancing
• OLS
• Gradient Boosted OLS

nbreg.do

• Negative binomial regression
• Zero-truncated negative binomial regression

33523-0004-Data.rda

Crime data

Variable list.xlsx

Total list of variables in final data