The objective of this data analysis capstone project is to examine the impact of economic factors on housing rental prices in Nashville. The study investigates several key areas, including the correlation between changes in Nashville's GDP and rental price fluctuations, the relationship between industry growth in various neighborhoods and increased rental prices, the correlation between short-term rental density and surrounding long-term rental prices, and the potential of using the inflation rate as a predictor for rental prices. The purpose is to gain valuable insights into the dynamics of the rental market in Nashville. The motivation behind this data analysis capstone project stems from the recognition of the critical role that economic factors play in shaping the rental market in Nashville. As an aspiring data analyst with a personal investment interest in real estate, the aim was to delve into the factors influencing rental prices and understand their impact on housing affordability in Nashville.
Nashville, being a vibrant and rapidly growing city, has witnessed significant changes in its economic landscape in recent years. The project's focus on exploring the correlation between changes in Nashville's GDP and rental price fluctuations arises from the need to comprehend how the city's economic performance directly influences housing rental costs. Understanding this relationship can provide valuable insights for policymakers, real estate investors, and residents seeking affordable housing options.
● How does the annual change in Nashville's GDP correlate with the annual percentage change in rental prices from 2018 to 2022?
● Is there a significant difference in rental price fluctuations between neighborhoods with different levels of industry growth in Nashville? If so, which industries show the strongest correlation?
● What is the relationship between the density of short-term rentals and the average long-term rental prices in different neighborhoods of Nashville?
● Are there specific industries or sectors that demonstrate a stronger correlation with rental price increases compared to others?
● How do macroeconomic factors (e.g., interest rates, consumer confidence) impact the rental market in Nashville?
● Can these factors be used to predict rental price movements?
https://www.realtor.com/research/data/
https://fred.stlouisfed.org/series/NGMP34980
https://data.nashville.gov/Licenses-Permits/Data-Lens-of-Short-Term-Rental/u795-vryx
https://nycdatascience.com/blog/student-works/scraping-vrbo-com/ (using this tutorial I will attempt to scrape VRBO)
https://data.nashville.gov/Licenses-Permits/Building-Permits-Issued/3h5w-q8b7
https://data.nashville.gov/Business-Development-Housing/Planning-Department-Development-Applications/mjrr-dybz
Explain any anticipated challenges with your project, and your plan for managing them. Be sure to include:
● Forecasting accuracy: Forecasting rental prices based on economic indicators like inflation may be subject to uncertainty and errors.
● Identifying causality vs. correlation: Establishing causality between economic factors and rental prices will be challenging.
● Data availability and quality: Incomplete or inconsistent data could affect the accuracy and reliability of my analysis.
● Data preprocessing may be complex and beyond my skill set.
Review and assess the collected data
Handle missing values, outliers, and inconsistencies
Perform data transformations or aggregations as necessary
Exploratory Data Analysis
● Visualize the distribution of rental prices and economic factors
● Identify trends, patterns, and outliers
● Calculate summary statistics
Correlation Analysis
● Calculate correlation coefficients between economic factors and rental prices
● Conduct statistical tests to assess the significance
● Visualize correlations using scatter plots or correlation matrices
Neighborhood Analysis
● Segment data by neighborhoods or zip codes
● Compare rental price fluctuations based on industry growth
● Analyze the relationship between short-term rental density and long-term rental prices
Macro Economic Factors Analysis
● Investigate the impact of macroeconomic factors on rental prices
● Explore the correlation between factors such as interest rates and consumer confidence
● Assess the predictive power of these factors for rental price movements
Predictive Modeling (attempt)
● Choose an appropriate modeling technique (e.g., regression, time series analysis)
● Build predictive models using economic factors as independent variables
• A time series plot showing the correlation between annual % change in GDP and the annual percentage change in rental prices over a specific time period
• A bar chart showing the rental price fluctuations between neighborhoods with different levels of industry growth in Nashville
• A scatter plot showing the relationship between the density of short-term rentals and the average long-term rental prices in different neighborhoods of Nashville
• A pie chart showing the percentage of rental price increases that can be attributed to different industries or sectors
• A bubble chart showing the relationship between macroeconomic factors (e.g., interest rates, consumer confidence) and rental prices in Nashville
At this stage, the Lord only knows!