Not Your Usual Suspects: Mid-Major Cities Showing Weakness

Executive Summary

This report is the third installment of Parcl Labs' US Housing Supply Demand Landscape, leveraging the most real-time data in the real estate industry. In this report, we highlight general residential real estate trends as well as several markets that are beginning to show signs of distress, as defined by inflecting supply and demand trends.

What’s changed since our July research?

The aggregate USA supply/demand imbalance is modestly worse versus July. Supply grew about 30% from the year ago period versus 19% in the July reading. Demand is down ~15% versus 10% in July. On balance, the gap between supply and demand is incrementally worse versus last month as both supply and demand trends moved adversely on aggregate.

Denver is the largest net new negative surprise. While Knoxville has the largest supply demand imbalance in the US (out of the top 100 metros), it screened as #2 in the July edition, implying weakness has been known. Denver, on the other hand is surprising, as it has the second largest supply demand gap in the country while not screening for weakness in July. Denver supply grew ~60% y/y relative to this time last year and demand shrunk about 10%.

Florida remains weak, but showing signs of stabilization on a relative basis. The Florida market continues to screen poorly with respect to supply/demand ratios, which we flagged in June, and since that time has garnered significant media attention. However, of the top 10 markets with the largest gap between supply growth and demand growth, there were only 6 Florida markets versus 8 in the July report. Standouts from this market in terms of weakness include Tampa and Orlando.

Oklahoma is starting to flash red - the states two largest markets are top 10 in terms of demand gap. Oklahoma City (OKC) and Tulsa are both screening in the top 10 with respect to supply demand gap - notably, neither of these metros showed up on our screen a month ago. In OKC, Supply grew 35% in the August period while demand declined 30% in the same period. In Tulsa, supply grew 50% and demand declined 20% through August. We believe this is a new(er) trend and will monitor closely, following up with more specific research if warranted.

Parcl Labs has refined its open-source algorithm to more precisely identify at-risk housing markets. The updated methodology now focuses on the absolute gap between year-over-year supply and demand percentage changes, allowing for more dynamic detection of extreme supply-demand imbalances. Our refreshed algorithm sifted through the top 100 U.S. metros, isolating 17 markets that emerged as focal points of supply-demand divergence and accelerated price cut activity.

Introduction

Since 2020, the U.S. housing market has been on a steady upward climb, with home prices appreciating across the board. However, we're now beginning to see signs of change. Many markets have shifted from limited inventory to an abundance of homes for sale. Recent decreases in mortgage rates—and expectations of further drops—add another layer of complexity to the housing landscape.

To shed light on these dynamics, we developed an algorithm based on the Parcl Labs API to identify high-flying markets at risk of price correction. Our previous two reports generated via this algorithm garnered national attention, cited by ResiClub, Fast Company, Newsweek, Fox Business, and other major outlets.

This month, we've updated our methodology to more precisely pinpoint at-risk housing markets by focusing on areas with the largest supply-demand imbalances and evidence of highly motivated sellers through increased price cut activity (see Appendix for methodology). Our refined algorithm revealed 17 markets out of the top 100 U.S. markets that warrant close attention. This research examines the supply, demand, price cut, and price performance trends across these 17 markets. Let's review what we found.

Supply-Demand Gaps Widen: Knoxville Leads at 86%, Florida Claims 6 of 17 Top High Risk Markets

Our updated algorithm reveals striking supply-demand imbalances across 17 U.S. housing markets, visualized in the charts below. This imbalance is calculated as the gap between the YoY percentage increase in supply and the percentage decrease in demand.

Knoxville, Tennessee leads with an 86.41% gap, driven by a 69.36% supply surge against a 17.05% demand drop. Denver, Colorado follows at 78.68% (66.44% supply increase, 12.24% demand decrease), with Tulsa, Oklahoma close behind at 70.91% (50.21% supply increase, 20.70% demand decrease). While our July research identified Knoxville as imbalanced, Denver and Tulsa are new additions to our watchlist.

These markets stand out due to their exceptional supply expansions - as shown in the scatterplot, they are outliers in the upper section of chart.

Florida continues to feature prominently in our analysis, with 6 of its markets appearing in the top 17:

1. Orlando: 70.23% gap
2. Palm Bay: 69.00% gap
3. Tampa: 67.64% gap
4. Lakeland: 62.91% gap
5. North Port: 61.20% gap
6. Miami: 56.68% gap

Texas presents a different narrative, with major markets showing significant imbalances driven by notable sales declines:

• Houston: 64.50% gap (32.47% supply increase, 32.03% demand decrease)
• Dallas: 57.10% gap (36.32% supply increase, 20.78% demand decrease)

Houston's demand decrease is the most severe among all markets analyzed.

These findings represent markets flagged by our algorithm for significant supply-demand imbalances. When combined with the price cut activity detailed in the following section, these markets emerge as those most at-risk for potential price declines.

Price Cuts Surge: Over 50% of Listings in North Port and Tampa See Reductions

Our price cut data reveals how sellers are responding to market pressures across the 17 identified markets. This metric is a key component of our algorithm, highlighting areas where sellers show increased willingness to reduce prices.

The data indicates a consistent uptick in price cut activity since early 2024 across all highlighted markets. North Port, FL and Tampa, FL stand out with average price cut as percent of inventory of 50.9% and 49.9% respectively. Denver, CO, and Dallas are next with 44.1% and 43.1% respectively.

These markets outpace the national average of 34.6% as of September 9, 2024. The gap between these markets and the U.S. average has widened since January 2024, when the national average was 32.54%.

This trend in price reductions aligns with our earlier findings on supply-demand imbalances. Markets experiencing inventory surges and demand slowdowns are seeing sellers adjust their pricing strategies in response. The data suggests we may begin to see this reflected in downward price pressure.

8 of 17 Markets Within 2% of Peak Price Values as of August 2024

Our analysis of supply-demand imbalances and seller motivation sets the stage for the critical question: Are these market pressures translating into actual price changes? To answer this, we examine the price performance data across our 17 identified markets.

Here's how our identified markets have performed since the start of the pandemic:

These figures underscore the significant appreciation in most markets since the pandemic's start, with many outpacing the national benchmark of 48.4%.

August 2024 data reveals varied price responses across our identified markets:

Resilient Markets: Despite high supply-demand imbalances and increased price cuts, 8 out of 17 markets are within 2% of their peak values. Palm Bay, FL, Orlando, FL, and Oklahoma City, OK maintain peak values (0% change), while Tucson, AZ (-0.41%), Tampa, FL (-0.61%), Miami, FL (-1.21%), and Knoxville, TN (-1.99%) show minimal declines. This resilience is particularly surprising for Tampa and Miami, given their high levels of price cut activity.

Significant Declines: North Port, FL and Colorado Springs, CO exhibit the largest drops from their peaks at -8.64% and -8.07% respectively.

Moderate to Minimal Adjustments: Several markets show moderate degrees of price response to market pressures. Phoenix, AZ (-5.85%), Lakeland, FL (-4.77%), and Denver, CO (-4.05%) show more modest declines, aligning with their high supply-demand imbalances and price cut activity. Denver is particularly intriguing, with a moderate 4.05% decline despite having the second-largest supply-demand gap (78.68%) and high price cut activity (46.21% of inventory). In contrast, Dallas (-2.85%), Houston (-3.04%), and Tulsa (-2.62%) show more incremental drops despite the highest demand declines.

Overall, the data suggests a complex relationship between market pressures and actual price performance. Some markets show immediate alignment between pressures and price declines, while others demonstrate resilience or delayed responses.

Signal From real-time price feeds:

We have real-time price feed coverage for 13 of these markets, enabling us to analyze trends up through September 14, 2024.

Our real-time data for the past two weeks reveals a notable trend: most markets appear to be curling downward. This includes previously resilient areas like Tampa and Miami, as well as markets that had been showing stability or growth.

Conclusion

Our refined algorithm identified 17 at-risk markets out of the top 100 U.S. markets, revealing complex dynamics between supply-demand imbalances, price cut activity, and price performance. Real-time price feeds show a recent downward trend across most markets, suggesting market pressures are translating into price adjustments.

These findings underscore the importance of continuous, granular monitoring. The Parcl Labs API enables real-time tracking of supply, demand, price cuts, and new construction impacts, remaining important for timely, in-depth housing market research as conditions evolve.

Appendix: Methodology

Methodology is completely open source. Review, run it, and build on it here.

Data Source and Market Coverage

• Primary data source: Parcl Labs API
• Property types: All residential properties, including single-family homes, condos, townhouses.
• Geographic scope: 100 largest U.S. metropolitan areas by population
• Temporal range: Data from March 2020 to August 2024, with daily updates for select metrics

Algorithm Structure

1. Supply-Demand Divergence Analysis
   • Calculate monthly year-over-year (YoY) percentage change for:
     • Supply: Total for-sale inventory
     • Demand: Number of completed sales transactions
   • Apply 3-month moving average to smooth short-term fluctuations
   • Compute supply-demand change differential
   • Select markets meeting both criteria:
     • Minimum volume threshold: ≥500 sales AND ≥500 for-sale inventory
     • Supply-demand gap: >50% (supply change exceeding demand change)
2. Price Cut Activity Filtering
   • Calculate monthly percentage of inventory with price cuts for each market
   • Apply 3-month moving average to price cut percentages
   • Compare each market's moving average to the national benchmark
   • Select markets exceeding the national average price cut percentage
3. Market Risk Identification
   • Combine results from steps 1 and 2 to identify at-risk markets
   • Analyze additional metrics for comprehensive assessment:
     • New construction impact: % of new listings from new construction
     • Price change trends: Time series of % inventory with price reductions
     • Home value appreciation: % change in home values since March 2020

Price Performance Analysis

• Monthly analysis: Median price per square foot of sales in each metro (August 2024)
• Real-time analysis: Daily price feed data for markets with available feeds

Methodological Notes

• All percentage changes and moving averages are calculated using consistent time periods across markets
• The algorithm adjusts for market size and activity level through volume thresholds
• Price cut moving averages smooth out weekly volatility for more reliable trend identification. We also conduct an additional outlier revision to weed out markets with unusual shifts.
• The methodology captures both long-term trends (since pandemic onset) and current market conditions

This methodology provides a robust framework for identifying markets with significant supply-demand imbalances and elevated price cut activity. By incorporating multiple data types, property categories, and analytical approaches, it offers a comprehensive assessment of market dynamics and potential risks in the U.S. residential real estate market.