<Sarah Aita, saraaita, soa238>

Introduction:
In 2017, more than 7.8% of New York State’s population did not have any bank accounts, compared to a national rate of 6.5%. This rate tends to be even higher for New York city. In 2013, the unbanked households’ rate in New York City was 11.7%, compared to a state rate of 8.5% and a national rate of 7.7% at the time. The highest unbanking rate is found in the Bronx, where it exceeds 20% (FDIC, 2019)
In 2015, the Urban Institute published a report that focused on identifying neighborhoods that have a high ratio of unbanked populations. Furthermore, the report investigates how neighborhood characteristics, such as income, poverty and demographics might relate to the banking status of its residents. This research project builds up on the Urban Institute's report and attempts to identify which socio-economic feature if a neighborhood affects residents' banking status.
Data:
This analysis uses data from the Urban Institute, which contains the ratio of unbanked and foreign born population, unemployment, poverty, and median income for each neighborhood . To calculate the number of banks in each neighborhood, I used the Department of Consumer Affair's (DCA) list of operating businesses. I selected all banks on the list, and joined each bank with their corresponding neighborhood. This allowed me to count the banks in each neighborhood and compare it with the Urban Institute's dataset
One underlying limitation in the available data is the geographic unit used. The only publicly available data about banking status was classified by Public Use Microdata Areas (PUMA). New York City contains 55 PUMAs, each of which contains a number of census tracts. Combining census tracts results in loss of information about the individual socio-economic characteristics of each census tract. More granular information could be insightful for this analysis and would increase the model's accuracy and precision.