A year-over-year change in commercial and multifamily mortgage debt compares the outstanding balance at one point with the balance a year earlier. It describes how the stock of mortgage debt changed—not how much lenders originated during that year. The exact chart edition, observation period and plotted values for “Chart of the Week” are not established here, so its specific rate cannot be stated.
What the year-over-year measure tells you
Outstanding mortgage debt is the balance of loans held or represented by investors and securitization vehicles. A year-over-year comparison measures the change in that balance against the same point in the prior year. A rising balance can coexist with lower new lending, while repayments, maturities, defaults, sales and other changes to existing loans also affect the total.
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Do not read a change in debt outstanding as the volume of new originations. MBA Vice President of Commercial Real Estate Research Jamie Woodwell attributed the 2.7% decline in U.S. commercial and multifamily mortgage debt during 2010, when the balance ended at $2.4 trillion, to a decline in outstanding CMBS loans. World Property Journal reported the MBA analysis in 2011.
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Historical reporting on MBA’s revised commercial and multifamily measure says it excluded acquisition, development and construction loans, as well as loans secured by owner-occupied commercial properties. The stated aim was to better isolate mortgages on income-producing properties. A statistic labelled “commercial mortgage debt” may use a different coverage definition, so check the series documentation before comparing figures. The 2011 report describes the exclusions.
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Historical examples are not the chart’s current reading
Separate historical figures illustrate why the period and comparison basis matter. A 2018 DWS outlook, citing Federal Reserve data, reported 5.8% year-over-year commercial mortgage growth as of September 2017. That is a historical commercial-mortgage figure, not a current reading for the chart’s combined commercial and multifamily series. DWS’s March 2018 outlook provides the cited context.
The MBA’s 2025 quarterly reports provide debt levels and quarter-over-quarter changes, not the chart’s year-over-year rate:
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| Period and geography | Debt outstanding | Change from previous quarter | What the figure measures |
|---|---|---|---|
| U.S., end of Q1 2025 | $4.81 trillion | +$46.8 billion, or 1.0% | Quarter-over-quarter change in total commercial and multifamily mortgage debt, as reported by World Property Journal from MBA data. Q1 2025 report |
| U.S., end of Q2 2025 | $4.88 trillion | +$47.1 billion, or 1.0% | Quarter-over-quarter change in total commercial and multifamily mortgage debt, as reported by World Property Journal from MBA data. Q2 2025 report |
These quarterly increases cannot be substituted for a year-over-year percentage. In its Q1 2025 report, MBA Associate Vice President of Commercial Real Estate Research Reggie Booker noted that total debt rose “Despite lower origination volumes.” That is a concrete example of why outstanding debt and new lending are different measures.
How to read the Chart of the Week
MBA’s archive includes related historical charts: a June 3, 2016 chart on changes in the outstanding balance and an October 14, 2016 chart on Q2 investor-group gains and losses. Those archive entries do not establish which chart edition the supplied title refers to or reveal its plotted values. MBA’s Chart of the Week archive is the place to identify the specific chart and its accompanying definitions.
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- CONFIDENTLY AND EASILY SOLVE: Clients' financial questions whether they're buyers, sellers, investors or renters. Increase your perceived professionalism as a new agent, experienced broker or seasoned loan officer. Close more home sales and impress your clients with fast, accurate answers to all their real estate finance questions from PITI Payments to IRR, NPV and Cashflows
- DEDICATED BUYER QUALIFYING KEYS: Enter client's income, debt and expenses to pre-qualify them to only show properties they can afford. Include tax, insurance and mortgage insurance then compare loan options and payment solutions to give your client choices before they make an offer to buy
- FIGURE OUT THE RIGHT LOAN: For your client at the press of a button for jumbo, conventional, FHA/VA, or even 80:10:10 or 80:15:5 combo loans; check to see if ARMs or bi-weekly loans, quarterly payments or if interest-only payments are the answer; giving your client more choices; easily perform what if loan or TVM calculations find loan amount, term, interest or PITI or PI payments
- BECOME AN INVALUABLE RESOURCE: To your clients by reducing their confusion and uncertainty; ensuring they are able to make a purchase offer; knowing they can afford the down payment; and determining which is the right loan for them. Date-math for listings and contracts too. Comes with a protective slide cover, quick reference guide, pocket user's guide, and long-life battery
When viewing a copy of the chart, verify these details before drawing a conclusion:
- Geography and period: Confirm that the data cover the United States and identify the observation date and the year-ago comparison point.
- Unit: Determine whether the chart shows dollar changes, percentage changes or both.
- Coverage: Check whether it uses MBA’s revised definition and excludes the construction/development and owner-occupied loans noted above.
- Debt category: Separate total commercial debt from multifamily debt if the chart breaks them out.
- Holder group: If the chart attributes gains or losses to investor groups, distinguish each group’s contribution from the change in the total balance.
- Timing: Do not compare a year-over-year figure with a quarter-over-quarter change as if they used the same baseline.
What can and cannot be concluded from the available figures
The latest numerical period established by the cited reports here is Q2 2025. It shows U.S. commercial and multifamily debt of $4.88 trillion at quarter-end and a 1.0% increase from Q1; it does not establish a 2026 year-over-year rate or identify the exact values in the chart named in the title. Those conclusions require the chart’s specific vintage and its underlying series data.
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