GNLGNADec 23, 2019

Quantifying the Effects of the 2008 Recession using the Zillow Dataset

arXiv:1912.11341v11 citations
Originality Synthesis-oriented
AI Analysis

It addresses the problem of quantifying recession effects for urban economists and policymakers, but is incremental in applying existing methods to new housing data.

This report used the Zillow Home Value Index to analyze the impact of the 2008 recession on US cities, identifying top losers and gainers through methods like Area Under Baseline and ARIMA modeling, but found limited correlation with population trends and unemployment rates.

This report explores the use of Zillow's housing metrics dataset to investigate the effects of the 2008 US subprime mortgage crisis on various US locales. We begin by exploring the causes of the recession and the metrics available to us in the dataset. We settle on using the Zillow Home Value Index (ZHVI) because it is seasonally adjusted and able to account for a variety of inventory factors. Then, we explore three methodologies for quantifying recession impact: (a) Principal Components Analysis, (b) Area Under Baseline, and (c) ARIMA modeling and Confidence Intervals. While PCA does not yield useable results, we ended up with six cities from both AUB and ARIMA analysis, the top 3 "losers" and "gainers" of the 2008 recession, as determined by each analysis. This gave us 12 cities in total. Finally, we tested the robustness of our analysis against three "common knowledge" metrics for the recession: geographic clustering, population trends, and unemployment rate. While we did find some overlap between the results of our analysis and geographic clustering, there was no positive regression outcome from comparing our methodologies to population trends and the unemployment rate.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes