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Population Density and Housing Price Dynamics

A Comparative Analysis of the Southeastern and Midwestern United States

Author: Christian McIntire
View Full Repository: github.com/christianmcintire/DACapstone


Introduction

Housing affordability remains a pressing issue across the United States, particularly in regions experiencing rapid urbanization and population growth. The Southeastern U.S. has seen significant population increases, whereas the Midwest has remained more stable or seen decline (Biernacka-Lievestro & Fall, 2023).

This study investigates the relationship between population dynamics and housing prices in these two regions.

Regions Studied

  • Southeastern U.S.: AR, LA, KY, TN, MS, AL, GA, FL, NC, SC, VA, WV
  • Midwestern U.S.: MN, WI, MI, OH, IN, IL, IA, MO

Research Questions

  1. How has population density historically affected housing prices in the Southeastern and Midwestern U.S.?
  2. How can these patterns be measured to predict future changes in the U.S. housing market?

Methodology

This project combines spatial visualization, econometric modeling, and forecasting:

  • Choropleth Maps – County-level visualizations using TIGER/Line shapefiles
  • Hedonic Regression Models – Decomposing housing prices into population, mortgage, and fixed effects
  • Panel Data Estimation – Handling state-level variation
  • ARIMA Forecasting – Projecting home prices through 2030

Key Findings

Regional Housing Trends

  • Southeast shows higher price inflation, especially in metro counties (e.g., FL, NC, TN)
  • Midwest remains more stable and affordable across most counties

ARIMA Forecasting (2024–2030)

  • Southeast expected to see faster growth and greater volatility
  • Midwest projected to grow steadily and with less uncertainty
  • Confidence intervals show higher forecast risk in the Southeast

Hedonic Regression Results

  • Monthly mortgage payment is the most statistically significant predictor of median price (p < 0.001)

  • log(Population) is not statistically significant (p = 0.5)

  • State fixed effects reveal regional price variations even after controlling for population and mortgage:

    • Virginia & Missouri have significantly lower prices than Alabama (reference)
    • Florida, North Carolina, and Tennessee show mixed effects

County-Level Trends

  • Southeastern counties show a wider distribution in both population growth and prices
  • Midwestern counties are clustered within lower price/growth ranges
  • Choropleth and scatter plots confirm these patterns visually

Data Sources

  • National Association of Realtors – Q3 2024 median home prices and mortgage rates
  • Federal Reserve Bank of St. Louis (FRED) – HPI data (1975–2024)
  • U.S. Census Bureau – County population estimates (2020–2023)
  • Zillow Research – ZHVI (Zillow Home Value Index)
  • TIGER/Line ShapefilesDownload Here

Visual Output

  • Visualizations and Tables included
  • Regional Choropleths, ARIMA Forecasts, Scatterplots
  • Cleanly formatted using the MDPI LaTeX journal style

GitHub Repository

View the full LaTeX report, R code, datasets, and figures:
https://github.com/christianmcintire/DACapstone


References


Built using R, ggplot2, and LaTeX

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