1. AirBnB in
New York City

2. What is AirBnB? Online broker for short-term lodging and rentals
Operates in >65,000 cities in 191 countries across the world
Statistics are kept for rentals in different cities including:
Nightly rental price
Average review + # reviews
# Bedrooms and max # accommodated
Location by city, borough, neighborhoods, and coordinates
Type of property (apartment, townhouse, house…)
Christian Survey of 4 months in 2017

3. City of Interest: New York (New York)
Subset the data to approx. 29,000 apartments in Brooklyn and Manhattan
The two boroughs are very distinct, culturally and geographically
Is there a difference in the rental markets as well?
Christian
Since Manhattan and Brooklyn contained the most observations ,and with apartments being the most abundant as well as comparable, lead us to subset
Expecting Manhattan to be more expensive, (has midtown, central park,financial district) Brooklyn to be less

4. What do we want to model? Average rating: How good is a property?
Issue: Discretization of values in half-stars
Rental Price/night: How expensive is a property?
Multiple Linear Regression
Location: What borough is the property located?
Multiple Logistic Regression
Kyle

5. Predicting Price
Price by # Accommodated, Overall Satisfaction, and their interaction
Accommodates: + $14 / person for one more person accommodated
Overall satisfaction: + $15.66/person for each 1-star increase
Positive interaction: These rates will increase with larger and higher-rated properties
Kyle

6. Predicting Boroughs Logistic Regression using # Accommodated and Price
Predicts probability that property is in Manhattan
66.1% Classification rate
Predicted Manhattan properties well (80.3%), Brooklyn properties not as well (45.7%)
Actual
Brooklyn
Manhattan
4177
2579
4966
10539
Predicted
Christian
Expect more accommodation in Brooklyn, higher price in Manhattan

7. Price for Max # Accommodated
Light blue: Manhattan properties
Purple = Brooklyn properties
Christian

8. Discussion
What other factors could go into the listing price of a property?
Amenities
Length of Stay
Cleanliness
Would different housing types in NYC look different?
Whole houses
Lofts
Townhouses
Condos
Kyle
# Bathrooms, laundry, proximity to places of interest

9. Conclusion Pursuing different model types
Tree based model
Smaller scale: Looking at neighborhoods inside the boroughs
Larger scale: Applications to other cities
Comparison with other large American Cities
Comparison to World Class Cities
Christian
Subsetting further into each boroughs neighborhood for comparisons
Developing models for other cities, applying model to other cities, generalizable?

10. Additional Resources
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