The Big Long? A Deep Dive on US Housing (Part 6) — What Drives Home Prices and Buy vs Rent

Theme and Background

This chapter focuses on the divergent views on U.S. home price trends, aiming to clarify the true state of the current market through objective data. The report argues that while the media often hypes fears of a 2008-style crash, the fundamental factors supporting home prices are equally strong, and the market is not uniformly bearish.

Core Thesis

The author's core argument is: the primary short-term driver of home prices is employment growth, not macro panic or common indicators such as income ratios. A counterintuitive finding is that, based on historical data from 2010–2019, changes in employment over the past two years at the MSA (Metropolitan Statistical Area) level explain 64% of the variance in year-over-year home price appreciation, far outperforming other variables. This implies that as long as employment remains stable, home prices in most markets are unlikely to crash and may even continue to rise modestly.

Key Arguments and Data

1. Comparison of core data from bulls and bears:

Bearish Arguments	Data	Bullish Arguments	Data
Median home price increase	+36.5% from Q2 2019 to Q2 2022	Wage growth	+16.1% from Q1 2019 to Q1 2022, +6.7% YoY
Existing home sales MoM decline	-5.9% in July 2022 vs. June 2022	Employment level	Exceeded pre-pandemic levels
30-year fixed-rate mortgage	Rose to 6.02% on Sept 15, 2022	Remote work contribution	NBER study suggests it may account for half of home price gains
Price-to-income ratio	At historic highs	Single-family new home permits decline	-11.7% YoY in July 2022
Macro risks	Recession, inflation, stock market slump	Multi-family permits increase	+26.2% YoY in July 2022
		NAR comment	"Housing sales and construction recession, but home prices are not in recession; nearly 40% of homes still sold at full price"
		Millennial demand	26–41 age group in 2022 is 6–7 million larger than Gen X

2. Divergence in home price forecasts:

• Zillow forecast: +1.4% YoY
• Moody's forecast: 0% to -5% decline

3. Core forecasting model:

• Regression on 2010–2019 data shows: changes in employment over the past two years explain 64% of the variance in year-over-year home price appreciation across MSAs (sample includes MSAs with more than 400,000 workers, roughly the size of Tulsa, Oklahoma).
• Adding rolling 1-year and 90-day changes in employment improves the model's predictive power to about 70%.
• Other variables (housing supply, demographics, wage growth, etc.) have a smaller impact in short-term forecasts.

4. Home-buying interest remains intact:

• According to a UBS Consumer Labs Research report, from late May to late August 2022, search interest for existing homes rose 1.6% YoY, and search interest for new homes rose 22.1% YoY.

Companies/Assets Involved

• Zillow: Provides the ZHVI index as a benchmark for home prices; forecasts a 1.4% YoY increase.
• Moody's: Forecasts a 0% to -5% decline in home prices.
• NAR (National Association of Realtors): Cited for the view that "housing sales and construction are in recession, but home prices are not."
• UBS Consumer Labs Research: Provides home search interest data.
• National Bureau of Economic Research (NBER): Cited for a working paper suggesting remote work may account for half of home price gains.

Investment Implications

• Focus on employment data in the short term: Investors should shift away from excessive concern over macro panic and instead concentrate on employment change trends in each MSA. Markets with strong employment growth over the past two years face lower home price downside risk; markets with weak employment warrant caution.
• Avoid national-level panic: Indicators like the national price-to-income ratio can be misleading. Actual homebuyers are concentrated in specific income percentiles, and most markets remain affordable (even with mortgage rates above 6.5%).
• Structural opportunities: Single-family new home supply is slowing (permits down 11.7%), while multi-family construction is accelerating (permits up 26.2%), suggesting single-family supply constraints may support prices, while the multi-family market could face oversupply risk.
• Specific directions: Go long on MSAs with strong employment growth and limited supply (e.g., Sun Belt, tech hubs); short or avoid MSAs with weak employment and ample supply.

---

Theme and Background

This chapter focuses on the performance of two key predictive indicators following COVID: labor market changes and the rent-to-own ratio imbalance. The report argues that traditional models using changes in employment to predict home prices became less effective during the pandemic, while the labor force became a better indicator. Meanwhile, the rent-to-own ratio (monthly rent / monthly mortgage servicing cost) has deviated from its historical equilibrium in almost all major MSAs, forming a core mechanism exerting pressure on current home prices.

Core Thesis

The author's core judgment is: The current rent-to-own ratio imbalance is the most important driver of home price trends over the next few months to a year. Counterintuitively, although the market generally focuses on interest rates and employment, the report argues that the correction of the rent-to-own ratio—through rising rents or falling home prices—is the key to determining whether home prices face downward pressure. Additionally, the author notes that even in markets with zero labor force growth, home prices rose by about 20%, indicating that post-pandemic price increases have partially decoupled from traditional fundamentals.

Key Arguments and Data

1. Evolution of Labor Indicators: During the pandemic, changes in the labor force (employed + unemployed seeking work) were better predictors of home price trends than changes in employment. Even in MSAs with zero labor force growth, home prices still rose by roughly 20%, suggesting that other factors (low interest rates, remote work) dominated the gains.

2. Rent-to-Own Ratio Imbalance: Taking Austin as an example, using MLS data to compare homes with 3 bedrooms, 2 baths, 1,200–2,000 sq ft, and lots of 4,000–15,000 sq ft:

• For-sale home ($570,000): Monthly payment with 20% down is approximately $3,900
• Rental home 1 (slightly larger): Monthly rent $2,375
• Rental home 2: Monthly rent $2,000
• Annualized difference: Renting saves $18,000–$22,500 per year (based on a $150,000 pre-tax income)

3. Rent-to-Own Ratio and Inventory Relationship: The further the rent-to-own ratio deviates from its pre-pandemic baseline (i.e., renting is relatively cheaper), the faster for-sale inventory increases, shifting the seller advantage toward buyers and putting downward pressure on home prices.

4. Correction Path: Assuming current interest rates and home prices remain unchanged, rents in the top 10 MSAs would need to rise by an average of 30% to bring the rent-to-own ratio back to its pre-pandemic equilibrium. However, if the 30-year fixed mortgage rate falls below 4%, the imbalance would largely disappear.

Companies/Assets Involved

Company/Data Source	Role	Key Data
Zillow	Provides home price (ZHVI) and rent (ZORI) data	Used to construct the rent-to-own ratio index, covering MSAs nationwide
Austin Board of Realtors/MLS	Provides more precise local transaction data for Austin	Comparison of 3-bed, 2-bath homes: Sale price $570,000 vs. monthly rent $2,375/$2,000

Realtor.com	Provides for-sale inventory data	Used to verify the relationship between the rent-to-own ratio and inventory changes
National Bureau of Economic Research (NBER)	Academic research	Remote work may have accounted for half of the home price gains

Investment Implications

• Short/Avoid Overvalued Markets: Home price downside risk is greatest in MSAs where the rent-to-own ratio is severely deviated from historical equilibrium and labor force growth is weak. Investors should focus on short opportunities in real estate-related assets (e.g., REITs, homebuilders) in these markets.
• Monitor Rent Growth Potential: Correction of the rent-to-own ratio requires either rising rents or falling home prices. If rents can rise quickly (e.g., in markets with strong population inflows), home prices may prove more resilient; otherwise, home price downside pressure is greater.
• Interest Rate Sensitivity: If the 30-year mortgage rate falls back below 4%, the rent-to-own ratio imbalance would ease rapidly, potentially supporting home prices. Investors need to closely track the Fed's policy path.
• Structural Changes: Remote work may permanently alter the equilibrium level of the rent-to-own ratio. The new equilibrium could be higher than pre-pandemic levels, but current levels remain unsustainable. Investors should avoid betting on a simple mean reversion.

---

Theme and Background

This chapter summarizes Voss Capital’s overarching conclusions for the entire report. While acknowledging the prevalence of negative sentiment ("doom and gloom") in the market, the author reiterates a core judgment: the housing market is not black and white, with a complex interplay of bullish and bearish factors, but key indicators still point to structural support.

Core View

The author argues that despite media portrayals of pessimism, the fundamentals of the U.S. housing market have not collapsed; instead, multiple supporting factors remain. The core investment thesis is: the housing market will not experience a deep recession, and expenditures related to Repair & Remodel in particular will remain resilient. This view stands in sharp contrast to the market’s widely anticipated "housing crash," representing a contrarian stance.

Key Arguments and Data

The author supports the conclusion with three core arguments:

1. Employment and Inventory: Employment growth remains strong (no specific figure provided, but described as "robust"), while new home inventory growth has slowed to a "trickle" or even halted entirely. This limits supply-side pressure.

2. Consumer Balance Sheets: Consumer balance sheets are among the "strongest in modern history," supported by FRED data (series number TDSP).

3. Demographic Demand: Millennials and Gen Z show strong home-buying intentions. Surveys indicate that the vast majority of young people who do not yet own a home are still waiting for prices to drop before entering the market. This is cited from a Business Insider report from September 2022.

Comparative Data (implicit in the original logic) :

Bearish Market Factors	Supporting Factors Cited by the Author
High home prices, rising interest rates	Strong employment growth, healthy consumer balance sheets
Increasing new home inventory	New home inventory growth has slowed or stopped
Young people unable to afford homes	Young people are still actively waiting for price declines to enter the market

Companies/Assets Involved

This chapter does not directly name specific companies but clarifies the investment direction: the portfolio’s housing-related exposure is almost entirely concentrated on Repair & Remodel expenditures. The author believes this sector has shown "significant resilience" over the past few months and expects this trend to continue. This implies a bullish stance on companies tied to housing maintenance and renovation (such as home improvement retailers, building material suppliers, and contractors), rather than on new home developers.

Investment Implications

For investors, the implications of this chapter are clear:

• Avoid excessive pessimism: Do not short the housing market broadly based on media-hyped "doom and gloom."
• Focus on structural opportunities: The Repair & Remodel sector is the most certain investment direction at present, benefiting from healthy consumer balance sheets, the aging of existing homes, and renovation demand from young people delaying home purchases.
• Be cautious on new home construction risk: The author does not explicitly short new home construction, but the portfolio largely avoids it, implying a cautious stance on near-term prospects for new housing.