How to Analyze Rental Markets

When you build a crazy number of new apartments, rents fall even in the most affordable (Class C) market-rate units. You can see it here: In 29 MSAs, Class C rents fell more than 3.5% over the last year. In 26 of those, new supply expansion rates topped the national average. Coincidence? Of course not. This data directly debunks the myth that new apartments -- generally built at the highest price points due to construction costs -- don't help with affordability at other rent levels. Here's what is happening: It's a process academics call "filtering." When you build new Class A+ apartments, you pull up higher-income renters out of Class B+/A- apartments. In turn, those units cut rents to lure up Class C's highest income renters. And in turn, that opens up availability at the lowest price points. And in these highest-supplied areas, Class C apartments often have to cut rents the MOST (of all asset classes) in order to fill back up. Why? Because to expand the demand funnel, they might have to cut rents enough to draw in renters who were previously priced out of market-rate rentals all together. That's what we see happening here. Takeaways: 1) Building Class A+ apartments in large numbers helps improve affordability even at the lowest price points. 2) In periods of high supply + economic expansion, renters in healthy financial shape tend to move "up market" -- paying similar or higher rents to move into newer, better-amenitized apartments (Class B+ to A+). 3) Class C apartments tend to feel the biggest impact from high supply, with rent cuts often exceeding those of Class A (excluding lease-ups with concessions) and Class B ... and perhaps also with deeper path toward a rent rebound, given they've lost some of their financially stronger renters and drawn in renters previously priced out. 4) This only holds true in high-supplied areas. In low- or moderated-supplied markets, Class C is more insulated from the impact and more likely to still be producing solid rent growth. (Indeed, Class C rents are still growing 4%+ in lower-supplied markets like Pittsburgh, Rochester, Little Rock, etc.). 5) Check out Austin, the "Exhibit A" of high-supplied big markets. Class C rents falling nearly 12%. Bottom line: If you truly care about rental affordability, put away the boogeyman conspiracy theories and build, baby, build. #rents #apartments #affordability

Here are some data points about the Phoenix market that really surprised me. It feels like it's easy to beat up on the Phoenix market right now, but some below-the-surface demand metrics suggest there's more than meets the eye in comparison to the market's headline stats. 1) Absorption of lease-up properties in Phoenix is... actually around all-time high levels. Take a look at the dark purple line which shows total number of lease-up units absorbed. This is a six month moving average to smooth out the noisier monthly figure, but you can see that - at nearly 750 units per month - more renters are moving into lease-up units than ever before. 2) Do concessions stimulate demand? Not really... Sure, some periodic movement might happen, but generally speaking the average number of days discounted among lease-up units is about 35 days over the past five years (or in other words, about one month free which is pretty standard for lease-ups). While concessions might be a tool in the marketers toolbox, this chart suggests that a concession doesn't necessarily translate to demand generation. There's some fun macroeconomic theory we could play with here but let's save that for another time. 3) What's happening to rents then? Well, as you probably know if you're in this market already they're falling for existing assets. But believe it or not, that's true EVEN among lease-ups. And get this - the average ASKING rent (not even the effective in this case) - among lease-up properties has actually come down by roughly $20 over the past year. Based on the above then, it seems like Phoenix demand is at least in decent shape. But as you're probably well aware, there's wayyyyy more product working through lease-up today. A total of 97 Phoenix MSA-based properties are in lease-up right now totaling more than 20,000 units. Last September that number was 14,500 units among 63 properties. So the takeaway is that demand is fine - but supply is watering down the rent growth one would expect given relatively strong demand.

The new StreetEasy Market Report shows the detrimental effects of extremely low vacancy rates in New York City as renters increasingly defer their next move amid the affordability crisis. Considering soaring rents and upfront costs, New Yorkers earning the city’s average annual wage could afford less than 5% of rentals on the market in 2023. 📉 As renters stay put, demand is slowing. The citywide median asking rent remained at $3,800 between May and June, even though rents tend to rise in the summer as New Yorkers look for new homes before their leases lapse. 🌡 Meanwhile, few vacancies in the city’s rental buildings are keeping a ceiling on rental inventory, balancing the softer demand. Despite the gradual inventory growth, those looking to move have limited options with 20.4% fewer rentals on the market this year compared to 2019. 📈 As a result, asking rents won’t decline anytime soon in NYC. The median rent in June was still up 1.3% from a year ago although this growth rate is much slower than double-digit increases last year. 🏗 Is there any solution? Building more homes can make a difference. New developments are driving rental inventory growth in NYC with the Bronx leading the city in both affordable and market-rate rental supply. There were 1,031 market-rate rentals in the Bronx in June, a 15.5% jump from a year ago, with a median asking rent of $2,825. 🔑 Targeted rezonings in the past led to a surge of new rentals joining the market in neighborhoods such as Mott Haven and Greenpoint, expanding options for all renters. Reducing redtapes and maintaining tax incentives will greatly improve the effectiveness of a new zoning plan. #realestate #rental #housing #affordability

How to Leverage City-Data.com for Smarter Real Estate Investing In today’s data-driven world, making informed decisions is key to real estate investing success. One often overlooked but incredibly powerful tool in your arsenal is City-Data.com. Here’s how City-Data.com can elevate your investment strategy and an example to show its impact: What is City-Data.com? City-Data.com aggregates public data to provide detailed information about neighborhoods, towns, and cities across the United States. The platform offers insights into: • Demographics (age, income levels, education, population density) • Crime rates • School rankings • Home values and trends • Commuting patterns • Amenities and attractions nearby Why Use City-Data.com for Real Estate Investing? 1. Neighborhood Insights: Understand the character and livability of an area. This is crucial for deciding whether a location matches your target market (e.g., families, professionals, students). 2. Risk Assessment: Analyze crime rates and other data to ensure the property is in a safe, desirable area. 3. Market Trends: Spot opportunities by examining home value trends and economic data. 4. Tenant Attraction: Use demographics to identify what type of tenants you might attract in a specific neighborhood. Real-Life Example: Using City-Data.com to Evaluate a Potential Investment Let’s say you’re considering a duplex in Nashville, Tennessee. 1. Crime Rates: City-Data.com reveals crime rates are significantly lower in a specific ZIP code compared to the city average. This signals safety for potential renters. 2. Demographics: The area shows a high percentage of young professionals (ages 25-34), with an average household income above $75K. 3. Commuting Patterns: Many residents commute downtown in under 20 minutes, indicating demand for rental properties catering to professionals. 4. School Rankings: If your target renters are families, you’ll find data on local schools to assess whether the area appeals to this demographic. 5. Home Value Trends: City-Data.com shows consistent year-over-year growth in home values, signaling potential appreciation. With these insights, you confidently purchase the duplex, market it to young professionals, and enjoy steady occupancy rates while watching the property appreciate. The Bottom Line City-Data.com is a treasure trove for real estate investors. It empowers you to back decisions with data, reducing risk and maximizing ROI. Whether you're investing in a single-family home or a multifamily property, this tool can help you uncover hidden opportunities and avoid costly mistakes. Have you used City-Data.com in your real estate journey? Share your experiences or strategies below! 👇 #RealEstateInvesting #DataDrivenDecisions #CityData #InvestmentStrategy #PropertyAnalysis

From my experience, a common mistake real estate investors make is not doing enough research before jumping straight into a deal; sometimes, they simply forget to ask ALL of the right questions. Here’s my framework to make sure you have all the bases covered. I’m happy to share my editable deal analysis checklist – shoot me an email at lilian@accentir.com. - 1. Market - Supply: Current inventory and new developments entering the market. - Demand: Drivers of demand, such as population growth and business activity. - Context: External factors like adjacent markets, news, or events influencing the market. 2. Financials - Initial Investment: Development costs, acquisition costs, and capital expenditures. - Operations: Projected revenue (rental income and other streams) and operating expenses. - Financing: Debt structure, equity contributions, and cost of capital. 3. Strategy & Risk Management - Execution Plan: Timeline, milestones, and key actions to achieve the business plan. - Risk Analysis: Identification and mitigation of potential risks (e.g., leasing risks, market shifts). - Exit Strategy: Long-term goals and options for exiting the investment, such as refinancing or selling.

🏠 𝗥𝗲𝗻𝘁 𝗖𝗼𝗻𝘁𝗿𝗼𝗹: 𝗠𝘆𝘁𝗵𝘀 𝘃𝘀. 𝗥𝗲𝗮𝗹𝗶𝘁𝘆 🏠 In my recent interview with Carl Gomez, Chief Economist at CoStar, we explored the truth about rent control and its impact on the Canadian real estate market. Here’s a summary of the key takeaways: 𝗖𝗮𝗻𝗮𝗱𝗮’𝘀 𝗥𝗲𝗻𝘁 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝗜𝗺𝗽𝗮𝗰𝘁: Strict rent control policies in cities like Toronto and Vancouver (with increases capped at 2.5%) lead to deferred property maintenance, limited housing supply, and tenants staying in units longer than needed. Developers shy away from building rental properties, worsening the supply-demand imbalance. 𝗚𝗹𝗼𝗯𝗮𝗹 𝗖𝗼𝗺𝗽𝗮𝗿𝗶𝘀𝗼𝗻: Unlike in the U.S., where rising rents lead to oversupply and market corrections, rent control in Canada disconnects rents from actual demand, further constraining supply. 💡 𝗖𝗮𝗿𝗹’𝘀 𝗘𝗰𝗼𝗻𝗼𝗺𝗶𝗰 𝗣𝗲𝗿𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲: Economists, including Carl, argue that rent control distorts the market by suppressing rent prices and restricting supply, ultimately harming the housing market in the long run. 🎥 Watch the full interview for more insights from Carl Gomez. Link in comments. 💬 What do you think about rent control? Let’s discuss! #RentControl #CoStar #RealEstateInsights #MarketTrends #CanadianHousing

Multifamily rent growth remains modest, but steady. And some of the weakest metros are starting to turn a corner. May brought a $6 increase in average U.S. advertised rents to $1,761, with YoY growth holding at 1.0%. While gains are concentrated in the Midwest and Northeast, markets like Austin, Denver, and San Francisco are showing early signs of a rebound. This tells me two things: -Demand is holding, even in high-supply metros -Wage growth is outpacing rent, keeping renter fundamentals strong We’re watching absorption trends closely in markets we once considered overheated. A plateau might be the foundation for the next cycle. Join our investor network to get ongoing data-backed insights like this.

You don’t lose money in real estate because of bad markets. You lose money because of bad decisions. Most new investors don’t fail because of external factors. They fail because they make predictable mistakes—mistakes that experienced investors know to avoid. 1. Ignoring Cap Rates – Buying a property without understanding its true return. Solution: Always compare cap rates to market averages and your investment goals. 2. Underestimating Operating Expenses – Hidden costs like maintenance, vacancies, and management fees can kill profits. Solution: Budget at least 20-30% of gross income for expenses. 3. Overleveraging – Taking on too much debt with little room for market shifts. Solution: Stress-test your deal with higher interest rates and vacancy assumptions. 4. Skipping Due Diligence – Rushing into deals without inspecting financials, tenants, or property conditions. Solution: Verify everything—leases, expenses, and even zoning laws . 5. Misjudging Market Cycles – Buying at the peak or ignoring economic trends. Solution: Study local supply and demand, interest rates, and future development plans. 6. Emotional Decision-Making – Falling in love with a deal instead of letting numbers guide you. Solution: Stick to your investment criteria and let data drive your choices. 7. Not Having an Exit Strategy – Investing with no clear plan for resale, refinancing, or repositioning. Solution: Always have multiple exit strategies before signing the deal. The best investors don’t guess—they analyze, verify, and plan before they buy. What’s the biggest mistake you’ve made—or almost made—in real estate? 🔃If you found this post helpful, repost it with your network. #realestate #inspiration

🏘️ Why Smart Investors Look Beyond the Surface: The Power of Cost-Adjusted Income Data If you're a Multifamily or BTR investor, here’s a critical factor you can’t afford to ignore: median income adjusted for cost of living. 📍The map below, by Visual Capitalist and WalletHub, reveals an eye-opening reality—nominal income figures don’t tell the full story. For example, California’s median income might seem high at $124K, but when adjusted for cost of living, it tells a very different affordability story than, say, Utah ($90K) or Wisconsin ($73K). 💡 Why it matters: Understanding local purchasing power helps you: Identify markets where residents can truly afford your rents Avoid overestimating affordability in high-cost states Pinpoint undervalued, income-stable regions with stronger ROI potential 🔍 Methodology Breakdown: Median household income was sourced from the U.S. Census Bureau. It was then adjusted using the Cost of Living Index (COLI) from the Council for Community and Economic Research. The index considers six categories of spending: groceries, housing, utilities, transportation, health care, and miscellaneous. This approach accounts for the fact that a $70K income in Mississippi stretches much further than the same amount in Massachusetts. 📊 The result? A more realistic view of resident affordability and market strength which is foundational for setting effective rent strategies, identifying expansion areas, and mitigating tenant risk. 👀 Curious insights: Highest COLI-adjusted income: Washington D.C. ($162K) Lowest: Mississippi ($47K) Surprisingly strong: Hawaii ($142K), Alaska ($114K), and Utah ($90K) #MultifamilyInvesting #BTR #RealEstateInvesting #MarketResearch #IncomeAdjusted #CostOfLiving #AffordableHousing 📌 Source: Visual Capitalist – Mapped: Median Income by State in 2024

I had a conversation with a friend that bought 15 short term rentals in the last 12 months, all off-market. He uses AI to find off-market deals and make offers on them. Here’s how he does it: 1. Scrape Listings: He uses web scraping tools (e.g., Beautiful Soup + GPT APIs) to scan Airbnb for properties in his target areas. 2. Image Analysis: He then trained an AI model to analyze listing photos. It flags homes with potential (good structure, layout, location) that are undervalued due to low-quality photos. He has had a lot of success finding homes that generate revenue but due to bad photos, don’t reach their potential. 3. Natural Language Processing: He also trained a NLP model to look for poorly worded Airbnb descriptions that he believes if written better can generate more revenue. 4. Market Comparison: Then he leverages Zillow Zestimate APIs to compare similar properties in the area and AirDNA to forecast what the property should rent for if the description and images were better. 5. Property List: All the properties based on this criteria get dumped into a google sheet. 6. Automate Outreach: For the final step he uses Claude to draft personalized outreach emails and Airbnb DMs to homeowners. Essentially his whole strategy is to identify underpriced homes that look worse online than they actually are. After the conversation my mind was blown 🤯