The Real Estate market, specifically the residential sector, can often be perceived as being somewhat speculative as an outsider or “consumer”. There happens to be a significant amount of analysis on both macro and micro markets, and in recent years an influx of data aggregation, analytics, and market analysis services (Zillow, Curbed, etc.).
In this project I explore the “Starbucks Effect”, where proximity to a Starbucks can be used as a predictor of residential price. This is inspired by the Stan Humphries and Spencer Rascoff book “Zillow Talk: The New Rules of Real Estate” where it is shown to have a positive correlation. I additionally compared the correlation results for Starbucks against Dunkin’ Donuts. Link: The Starbucks Effect
Micro markets that performed contra to macro trends, for example San Fransisco and New York City, following the real estate market crash and correction in the mid-to-late 00’s are interesting from a feature and predictor perspective. In this project I took the perspective of a developer trying to determine if a local market is approaching another high by comparing to macro indicators (e.g. Case-Shiller index), peak analysis, and examining locally available features such as building permit issuances. Link: Local Market Developer Analysis
Vanished Gradient 