Figure 1: Equilibrium Maturity Outcomes
(a) Borrowers’ Indifference Conditions
(b) Lenders’ Optimality Conditions
Notes: Panel (a) plots the paydown above which borrowers
default (red dashed line, \(\overline{P}_b\)), and the one above which
borrowers maintain the property if they extend (green line, \(M^*_b\)). Red, yellow, and green regions
show where borrowers with a debt yield of \(n\) would choose to default, neglect, and
maintain, (respectively), given an extension offer of \(p\) and a \(\kappa\) draw such that paying off the loan
is not optimal. Panel (b) adds the minimum paydown lenders will accept
(solid blue line, \(\underline{P}_l\)),
and lenders’ optimal paydown when not constrained by borrowers’ default
or maintenance decisions (blue dashed line, \(P^*_l\)). The colored regions denote the
outcomes at a given debt yield for lenders’ optimal paydown rate.
The figure contains two side-by-side charts. In both panels, the horizontal axis is debt yield, running from 0 to 0.08, and the vertical axis is principal paydown, running from a little below -0.05 to 0.25. Panel (a) is titled 'Borrowers' Indifference Conditions.' It plots a red dashed curve for the paydown above which borrowers default and a green solid curve for the paydown above which borrowers maintain the property if they extend. The red dashed curve starts near -0.07 when debt yield is zero, rises gradually, reaches about -0.02 near a debt yield of 0.03, then turns nearly vertical just below 0.04 and jumps to about 0.12. After that jump, it rises slowly, reaching roughly 0.16 by a debt yield of 0.08. The green curve appears only in a narrow region centered around debt yields from about 0.034 to 0.041. It starts a little above 0.10, slopes down steeply, crosses zero just below 0.04, and ends near -0.06. The colored regions in panel (a) show borrower actions for a given debt yield and paydown. The region above the red dashed line is red to denote where borrowers default, the area under the two curves is yellow to denote where borrowers neglect the property, and the area to the right of the two curves is green to denote that borrowers maintain the property. Panel (b) is titled 'Lenders' Optimality Conditions.' It adds two blue lender curves to the borrower curves from panel (a): a blue solid curve for the minimum paydown lenders will accept and a blue dashed curve for lenders' unconstrained optimal paydown. The blue solid curve is negative at low debt yields, rising from about -0.07 to about -0.025 by roughly 0.03, then bending downward again just before 0.04. The blue dashed curve appears only to the right of about 0.038, beginning around 0.20 and sloping down sharply to below zero by about 0.05. With these added conditions, the outcome regions become: default for debt yields below about 0.028, neglect for a narrow range from about 0.028 to just under 0.04, and maintain or payoff for debt yields above that range.
Figure 2: Observed Extension Outcomes
(a) Equilibrium Principal Paydowns
(b) Eventual Loan Performance
Notes: Panel (a) plots equilibrium principal paydowns (black
line, left scale), and the probability that various maturity outcomes
occur (colored regions, right scale). Red, yellow, green, and blue
regions show the probability that borrowers would choose to default,
neglect, maintain, and pay off a loan (respectively), given an extension
offer of \(p^*(n)\). Panel (b) adds
information on ultimate performance; hollow red dots show the
probability that a loan with a given \(n\) eventually defaults, and solid red dots
show the probability that a loan would have defaulted if extensions were
not available. The red area shows the decline in the probability of
eventual default due to extensions.
This figure again has two side-by-side charts with debt yield on the horizontal axis from 0 to 0.08. In both panels, the left vertical axis shows paydown rate and the right vertical axis shows outcome probability from 0 to 1. Panel (a), titled 'Equilibrium Principal Paydowns,' plots the equilibrium paydown schedule as a black line. The line first appears slightly under a debt yield of 0.03 at a paydown just below zero, around -0.02. It rises slowly at first, crosses zero near 0.036, then jumps almost vertically to about 0.12 just below a debt yield of 0.04. It stays flat briefly at that peak (when the liquidity constraint is binding), then declines as debt yield rises further, reaching zero by about 0.048 and staying at zero for higher debt yields. The colored regions in panel (a) describe outcomes along the debt-yield distribution. For debt yields below about 0.027 to 0.028, the entire height of the plot is red, indicating default. Extensions start occurring slightly under 0.03, and the maturity outcome in that interval is mainly extend-neglect, shown by the yellow region. That neglect region runs from just under 0.03 to just under 0.04. Once debt yield rises above that region, the outcome shifts to extend-maintain and payoff, shown by green and blue regions. In other words, the figure shows default at the weakest debt yields, extension with neglect in a narrow middle band, and either payoff or extension with maintenance above that band. Panel (b), titled 'Eventual Loan Performance,' repeats the black paydown schedule and adds two red series on the probability scale. Hollow red circles show the probability that a loan eventually defaults when extensions are available. Solid red circles show the probability of default if extensions were not available. At very low debt yields, both default probabilities are essentially 1. The hollow-circle series begins to drift down around debt yields in the low 0.03 range, then falls sharply from high values to near zero between roughly 0.036 and 0.041. The solid-circle series drops more slowly as avoidable defaults emerge for debt yields where borrowers would be willing to pay down the loan for an extension due to a bad sale offer, but are unable to. The red shaded wedge between the two series is largest just above the threshold where paydowns start to rise materially..
Figure 3: Extend-and-Pretend Incentives (χ: 0→1%)
(a) Lenders’ required paydowns shift down
(b) Observable outcomes
Notes: The solid blue and red lines in panel (a) show the
minimum paydown acceptable to lenders and the maximum paydown borrowers
will make, respectively. The dashed blue line shows how lenders’
required paydowns shift if \(\chi\)
increases to 0.01. The highlighted area demonstrates the range of debt
yields that newly receive extensions due to the change in lenders’
objective function. Panel (b) provides outcomes at maturity when \(\chi=.01\). Red, yellow, green and blue
regions represent the probability of default, neglect, maintain, and pay
off. The black line gives required pay downs by debt yield (left axis)
and red hollow dots the probability that a loan ultimately defaults
(right axis).
This figure shows how the model changes when the cost to loss recognition, denoted chi, rises from 0 to 1 percent. Panel (a) is a paydown-against-debt-yield chart. The red curve is the borrowers' maximum paydown schedule, and the two blue curves are lenders' required paydowns with and without the new incentive. The solid blue curve for chi equals 0 starts near -0.07 and rises toward about -0.02 by a debt yield a little under 0.03. The dashed blue curve for chi equals 0.01 lies below the solid blue curve over that low-debt-yield range, but converges to the other curve as debt yield rises and the would be losses become smaller.. A vertical dashed line marks the previous extension boundary at about 0.028. The yellow highlighted area to the left of that line shows the range of new extensions created by the lower required paydown. In other words, the added incentive mainly creates new extensions for the weakest loans. Panel (b), titled 'Observable outcomes,' shows the new equilibrium when chi equals 0.01. The black equilibrium paydown schedule is again slightly negative at very low debt yields, rises toward zero near 0.03, jumps to about 0.12 around 0.038, and declines back to zero by roughly 0.047. A vertical dashed line labeled 'Previous Boundary' again marks the old threshold. To the left of that line, the region is now yellow rather than red, indicating that loans that previously would have defaulted at maturity are now being extended (but neglected). The probability of eventual default, shown by red hollow dots, is near 1 to the left of the previous modification boundary. Everything to the right of that boundary is identical to Figure 2.b.
Figure 4: Outcomes of Pending CRE Loan Maturities
(a) Maturity Outcomes
(b) Extension Rate over Time
Notes: The left figure shows the share of outstanding loan
balances that are paid off (blue), extended (yellow), performing past
their maturity date (orange) and past due or liquidated (red) by the
quarter of scheduled maturity. Sample is composed of loans that are four
quarters from the scheduled maturity. The right panel shows the share of
balances that are extended, corresponding to the yellow region in the
left chart.
The figure has two panels. Panel (a) is a stacked area chart from 2017 through 2025 showing four outcomes for loans with pending maturities: paid off in blue, extended in yellow, ballooned in orange, and past due or liquidated in red. Paid off and extended are always the dominant outcomes. The blue payoff share is generally around one-half of balances before 2020, falls sharply to about one-third during the pandemic, rebounds late-2021, and then drops to below 40% starting in 2023. The orange ballooned share is small throughout, usually only a few percentage points, but becomes a bit more visible late in the sample. The red past-due or liquidated share is also small early on and grows somewhat in 2024 and 2025. The yellow region shows the share of loans that are extended, which are plotted in the right chart. Panel (b) is a line chart of the extension share over time, corresponding to the yellow region in panel (a). The line mostly fluctuates between 40 and 45 percent, then spikes to the low 60s in 2020, falls back into the low to upper 40s in the pandemic recovery, and rises again to the highs 40s or low 50s after 2023.
Figure 5: Maturity Extensions by Risk Characteristics
(a) Extensions by Debt Yield and Time Period
(b) Stress period Extensions by Debt Yield and
Recourse
Notes: Figure presents semi-linear regression estimates of
the probability of extension as a function of a loan’s debt yield and
bank-quarter fixed effects. Estimates come from a cubic B-spline,
restricted to have a continuous second derivative, using the binsreg
package of [Cattaneo et al., 2024]. Dots provide binscatter
estimates by quartile. Sample includes stabilized loans with recent NOI
updates that are scheduled to mature in four quarters. The left panel
compares loans slated to mature before the pandemic (blue) and during
the stress period (red). The right panel analyzes extension rates during
the period of stress for recourse (lavender) and non-recourse (pink)
loans.
Panel (a) plots extension share against debt yield from 0 to 0.20, with a vertical scale from about 20 to 60 percent. The blue pre-COVID curve starts a little above 50 percent at very low debt yields, declines to the low 40s for debt yields above 0.05. The red 2023-on curve starts much lower, around 30 percent at very low debt yields, and then rises to the low 40s (similar to the prepandemic extension rate) above 0.05. The largest gap between the two periods is therefore at the weakest debt yields, where stress-period extension rates are around 20 percentage points lower than pre-COVID ones. Panel (b) focuses only on the stress period and separates recourse and non-recourse loans. The lavender recourse curve starts is near 40 percent for the whole range of debt yields. The pink non-recourse curve starts much lower, around 20 percent at the lowest debt yields, then climbs steeply and meets the recourse curve near 0.07 to 0.08. Beyond that point, the two series are similar.
Figure 6: Maturity Extensions by Risk Characteristics, Regression Estimates
Notes: Figure presents estimates of \(\beta\) from the specification \[100\times\text{Extension}_{i,t+1}=(\beta'X_{i,t})\times\text{2023-on}_{t}\times\text{Maturing}_{i,t}+\gamma'\text{Lower
Level Controls}_{i,t}+\tau_{b(i),t}+\epsilon_{i,t}\] where \(\tau_{b(i),t}\) is a bank quarter fixed
effect. Blue dots (lines) present point estimates (95% confidence
intervals) for how much particular risk factors increased the
probability that maturing loans received extensions during the period of
stress relative to before the pandemic. Red dots (lines) present
equivalent estimates of the probability that loans are delinquent as of
maturity. Estimates correspond to columns (3) and (6) from Table A4.
This figure is a coefficient plot with a vertical dashed line at zero. Blue points and horizontal lines show estimates for changes in extension probabilities, and red points and lines show estimates for delinquency at maturity. Each point is labeled with its value. The overall effect for maturing loans in 2023 and later is -3.65 percentage points for extensions and +1.52 percentage points for delinquency. For low-debt-yield loans, the blue extension estimate is -6.91, while the red delinquency estimate is +5.46. For non-recourse loans, the blue estimate is -4.91 and the red estimate is +3.79. Small office loans are close to flat for extensions, at +0.18, but still show a delinquency increase of +2.04. Large office loans are the one category with higher extension rates, at +3.01, and they also show the largest delinquency increase, at +7.64. Loans with missing debt yield show -1.04 for extensions and +1.84 for delinquency. Visually, most blue estimates lie to the left of zero while all red estimates lie to the right of zero. That means riskier loans generally became less likely to receive maturity extensions even as they became more likely to be delinquent, with the main exception being large office loans.
Figure 7: Paydowns by Debt Yield
(a) All Extensions
(b) Office Loan Extensions
Notes: The left panel presents semi-linear regression
estimates of the probability an extension entails a principal paydown of
at least 5% as a function of a loan’s debt yield, controlling for
amortization and bank-quarter fixed effects. Estimates come from a cubic
B-spline, restricted to have a continuous second derivative, using the
binsreg package of [Cattaneo et al., 2024]. Dots provide binscatter
estimates by quartile. Sample includes loan extensions with recent NOI
updates. Estimates for pandemic-era extensions are in blue and
stress-era extensions in red. The right panel presents the same
estimates, but with the sample restricted to extensions of office
loans.
The figure has two line charts with debt yield on the horizontal axis from 0 to 0.20. The vertical axis is the share of extensions with a principal paydown of at least 5 percent. Panel (a), for all extensions, shows a blue pre-COVID curve and a red 2023-on curve. The blue curve starts near 11 percent at the lowest debt yields, declines fairly smoothly to about 4 percent by a debt yield around 0.10, and stays low thereafter. The red curve starts much higher, around 24 percent at the lowest debt yields, declines steadily to around 10 percent by about 0.10, and falls to around 5 percent for the highest debt yield loans. Panel (b), restricted to office loan extensions, uses a vertical scale up to about 60 percent. The blue pre-COVID curve starts around 12 percent, and declines to under 5 percent for high debt yields. The red 2023-on office curve starts above 30 percent, then declines and levels off to a bit under 20 percent at higher debt yields. In both panels, the red stress-period curve lies well above the blue pre-COVID curve at almost every debt yield. The gap is largest at very low debt yields and is especially pronounced for office loans. The figure therefore shows that low-debt-yield loans, and office loans in particular, became much more likely to require meaningful principal paydowns when they were extended after 2022.
Figure 8: Paydowns by Risk Characteristic
Notes: The figure presents \(\beta\) estimates from equation (3), pertaining to changes in the
frequency with which extensions have paydowns of at least 5% during the
stress period. The blue dot presents the estimated coefficient on
Extension\(_{i,t}\times\)2023-on\(_{t}\) in the specification without the
risk interactions, while the red dots present estimates of the \(\beta\) vector from the fully-interacted
specification. Lines present 95% confidence intervals based on standard
errors that are clustered at the bank-quarter level.
This is a second coefficient plot, now for whether an extension includes a principal paydown of at least 5 percent. The horizontal axis measures percentage-point effects. A blue baseline estimate at the top equals +5.15, meaning that stress-period extensions were about 5 percentage points more likely to include a paydown even before adding risk interactions. The comparable red interacted estimate for 'Extension x 2023-on' in the triple interaction is +2.42. The red risk-specific estimates are all positive. Low-debt-yield loans have an additional effect of +4.08, non-recourse loans +2.34, small office loans +3.66, large office loans +13.29, and loans with missing debt yield +1.21. The confidence interval for low-debt-yield loans is wide and stretches across a broad range, while the large office estimate is both very large and clearly to the right of zero. The visual pattern is straightforward: the move toward paydowns in the stress period was broad-based, but it was strongest for large office loans and meaningfully positive for the other displayed risk categories as well.
Figure 9: Payoff Rates Over Time
(a) Extended Loans
(b) Other Maturing Loans
Notes: Blue lines plot the share of loan balances that pay
off over time before (dashed), during (dotted) and after (solid) the
pandemic. Red lines plot the share of loan balances that are delinquent
or liquidated at that time. The left panel plots performance for loans
that were extended by the number of quarters since extension, while the
right plots performance for non-extended loans by the number of quarters
to maturity.
Panel (a) tracks extended loans by quarters since extension, from 1 to 6. The blue lines show the share paid off, with separate dashed, dotted, and solid series for pre-COVID, COVID, and 2023-on periods. All three payoff lines rise steadily over time. The pre-COVID series is highest, starting around 20 percent in quarter 1 and reaching roughly 66 percent by quarter 6. The COVID series is slightly lower, ending around 60 percent. The 2023-on series starts slightly under percent and reaches about 58 percent by quarter 6. Red lines show the share delinquent or liquidated. Those lines are relatively flat: roughly 4 to 5 percent for pre-COVID, around 7 percent for COVID, and about 10 to 11 percent for 2023-on. Panel (b) tracks other maturing loans by quarters to maturity, from -3 through +2. The blue payoff series rise sharply through the maturity date. The pre-COVID series goes from about 10 percent three quarters before maturity to about 53 percent at the maturity quarter and around 68 percent two quarters later. The 2023-on series follows the same shape but at lower levels, rising from roughly 8 percent at -3 to about 39 percent at 0 and 52 percent by +2. The red delinquency series for 2023-on remains low before maturity, spikes to about 13 percent at the maturity quarter, and then eases only slightly afterward. The earlier-period red lines also spike at maturity, but at noticeably lower levels.
Figure 10: Extension Policies by Bank Capitalization
(a) Change for Low Capital Banks
(b) Change Relative to High Capital Banks
Notes: The left figure plots the predicted changes in
extension outcomes during the stress period for low capital banks.
Outcomes considered are the predicted change in the probability that a
nonmaturing loan is extended (blue), that a maturing loan is extended
(red) and that an extended loan receives a principal paydown of at least
5%. These estimates come from fully-interacting the specifications in
equations (2) and (3) with a
low capital indicator. The average effect comes from the specification
excluding interactions with loan risk factors, and the other estimates
provide predictions for a loan with a single risk factor (besides the
"No Risk Factor" line which pertains to loans where all of the
indicators in \(X_{i,t}\) are 0). The
right panel presents estimates of the change in policies at low capital
banks net of the change at high capital banks (e.g., for paydowns, the
No Risk Factor dot plots the coefficient on Low Capital\(_{b(i),t}\times\)2023-on\(_{t}\times\)Extension\(_{i,t}\), while the others add the
coefficient on the relevant quadruple interaction).
The figure contains two coefficient plots. In each plot, blue estimates refer to extensions of non-maturing loans, red estimates refer to extensions of maturing loans, and green estimates refer to the probability that an extension includes a paydown. Panel (a) shows predicted changes during the stress period for low-capital banks alone. The average effect row shows about -0.76 for non-maturity extensions, -5.45 for maturity extensions, and +7.62 for paydowns. For loans with no listed risk factors, the estimates are about 0.00, -2.85, and +4.36 (for non-maturity extensions, for maturity extensions, and paydowns, respecitive). For low-debt-yield loans, they are about -0.12, -11.83, and +7.58. For non-recourse loans, about -0.19, -1.96, and +10.16. For small office loans, about +0.84, -3.99, and +8.40. For large office loans, about +2.27, -2.46, and +13.29. Panel (b) compares low-capital banks with high-capital banks. The average-effect row is close to zero for extensions, around -0.41 for non-maturing extensions and -0.81 for maturing extensions, with paydowns at about +2.70. The no-risk row is roughly 0.00, -2.28, and +1.74. Low-debt-yield loans are about -0.58, -2.12, and +1.23. Non-recourse loans are about -0.33, +7.44, and +6.30. Small office loans are about +0.75, -2.57, and +1.59. Large office loans are about +1.51, +0.48, and -11.36.
Figure A1: What Drives Extensions
(a) Just Search Costs (\(\Lambda=1\))
(b) Just Foreclosure Cost (\(\alpha=\infty\))
(c) Just Capital Costs (\(\chi=.01,
\alpha=\infty, \Lambda=1\))
Notes: Each chart presents a stacked area chart showing the
probability that a loan with a given debt yield defaults (red), extends
and neglects (yellow), extends and maintains (green), or pays off at
maturity (blue). Black line plots \(p^*(n)\). Parameters are as in Table A1, except only including one friction at
a time. Panel (a) just has search costs (\(\Lambda=1\)). Panel (b) just has
foreclosure costs (\(\alpha=\infty\)).
Panel (c) just has capital costs (setting \(\chi=.01\) and turning off search and
foreclosure costs).
This appendix figure contains three vertically stacked charts. All three use debt yield from 0 to 0.08 on the horizontal axis and paydown rate on the left vertical axis, with outcome probability on the right axis. Panel (a), 'Just Search Costs,' shows a black equilibrium paydown line that first appears just under 0.04, jumps to about 0.12, and declines to zero by around 0.044. The colored outcome regions switch directly from default at lower debt yields to maintain and payoff at higher debt yields, with no neglect region. Panel (b), 'Just Foreclosure Cost,' has a black paydown line that starts around a debt yield of 0.027 at a slightly negative paydown, rises gradually, and reaches a small positive paydown just below 0.036. The color pattern is red for lower debt yields, yellow in the middle where extensions occur, and blue (payoff) to the right of about 0.036. Panel (c), 'Just Capital Costs,' has the black paydown line sits only at extremely low debt yields, staying negative and ending around a debt yield of 0.01, with paydowns always being deeply negative (-.07 to -.05). Very low debt yield (under 0.01) result in extend-neglect, low debt yields (up to 0.035) result in default, and debt yields above that pay off.
Figure A2: Loan Outcomes by Time to Maturity
(a) Pre-COVID
(b) 2023-on
Notes: These figures report loan outcomes by the number of
quarters to maturity. Each bar shows the share of outstanding loan
balances that are paid off (blue), extended (yellow) and delinquent or
liquidated (red). The top panel shows results for the years 2016-2019,
and the bottom years from 2023-2025. Quarters to maturity is based on
the previous quarter’s maturity date. For example, the 0 bar shows the
outcomes for loans that were scheduled to mature that quarter as of the
previous quarter. I do not show a bar for ballooned loans since that
outcome can only occur following maturity.
This figure has two stacked bar charts. The horizontal axis is quarters to maturity, from -2 through 20, and the vertical axis is the share of loan balances. Each bar is split into blue paid off, yellow extended, and red default. In panel (a), pre-COVID, the bar spikes at time 0, with roughly one-quarter paid off, over half extended, and only a small red default slice. There is a slow upward trend in loans getting extended or paid off before maturity, peaking at around 20% (mostly from pay offs) in the quarter before maturity. Panel (b), for 2023 onward, has the same overall shape but with fewer payoffs in the quarters leading up to maturity.
Figure A3: Outcomes of Pending CRE Loan Maturities, By Stabilization
(a) Maturity Outcomes, Stabilized Properties
(b) Extension Rates, Stabilized Properties
(c) Maturity Outcomes, Non-stabilized Properties
(d) Extension Rates, Non-stabilized Properties
Notes: The left figures show the share of outstanding loan
balances that are paid off (blue), extended (yellow), performing past
their maturity date (orange) and past due or liquidated (red) by the
quarter of scheduled maturity. The right panels show the share of
balances that are extended, corresponding to the yellow region in the
left charts. The top panels pertain to stabilized properties, and the
bottom panels non-stabilized properties. Loan balances and scheduled
maturity dates are measured as of four quarters before the scheduled
maturity.
The figure contains four panels. The top row pertains to stabilized properties and the bottom row to non-stabilized properties. In each left panel, a stacked area chart shows paid off in blue, extended in yellow, ballooned in orange, and past due or liquidated in red from 2017 through 2025. In each right panel, a labeled line chart shows the extension rate over time. Patterns are generally the same as in Figure 4, with payoffs in the low 40s before and immediately after the pandemic, and payoffs dropping during COVID and after 2023 (with a larger drop during COVID). The drop in payoffs during COVID mostly reflected an increase in extensions, while the drop after 2023 partly reflect higher delinquency.
Figure A4: Outcomes of Pending CRE Loan Maturities, By Property Type
(a) Maturity Outcomes, Office Properties
(b) Extension Rates, Office Properties
(c) Maturity Outcomes, Non-office Properties
(d) Extension Rates, Non-office Properties
Notes: The left figures show the share of outstanding loan
balances that are paid off (blue), extended (yellow), performing past
their maturity date (orange) and past due or liquidated (red) by the
quarter of scheduled maturity. The right panels show the share of
balances that are extended, corresponding to the yellow region in the
left charts. The top panels pertain to office properties, and the bottom
panels non-office properties. Loan balances and scheduled maturity dates
are measured as of four quarters before the scheduled maturity.
This figure also has four panels, now split between office properties on the top row and non-office properties on the bottom row. The left panels are stacked area charts for maturity outcomes and the right panels are line charts of extension rates. For office properties, the left panel shows a marked deterioration after 2022. The blue payoff share is around 50 percent before 2020, falls to about 30 percent around 2021, and then declines further to roughly 20 percent by 2024 to 2025. The yellow extension share rises as payoff falls, and the red past-due or liquidated share becomes much larger late in the sample, peaking at around a quarter of loans in 2024 For non-office properties, patterns are generally the same as in Figure 4, with payoffs in the mid-to-low 40s before and immediately after the pandemic, and payoffs dropping during COVID and after 2023 (with a larger drop during COVID). The drop in payoffs during COVID mostly reflected an increase in extensions, while the drop after 2023 partly reflect higher delinquency.
Figure A5: Maturity Extension Rates by Loan Size
Notes: This figure plots the estimated probability of
extension as a function of a loan’s size and bank-quarter fixed effects.
Each dot estimates the share of loans with pending maturities that get
extended by decile of the outstanding loan balance (on a logarithmic
scale). Estimates for loans slated to mature before the pandemic are in
blue and during the stress period in red.
This is a scatter plot with loan balance on a logarithmic horizontal axis and extension share on the vertical axis. Blue dots show pre-COVID estimates and red dots show 2023-on estimates. The blue pre-COVID dots are fairly flat, rising from 38 percent for the smallest loans, to around 45 percent for $10 million loans, and edging down to about 42 percent for $40 million dollar loans. The red stress-period dots begin much lower for the smallest loans, around 30 percent, then rise steadily with loan size, moving into the low 40s for medium loans and reaching 50 percent for loans over $30 million.
Figure A6: Maturities in Next Two Years
Notes: This figure plots the share of outstanding CRE loans
that are scheduled to mature in the next two years over time (the top of
the blue area), and the portion of those loans accounted for by loans
that have received extensions in the past two years (the red area), and
the share of pending maturities coming from recent extensions (white
dots).
This figure is a stacked area chart from 2013 to 2025. The top of the blue area shows the share of all outstanding CRE loan balances scheduled to mature within the next two years. That total starts near 0.40 in 2013, declines to about 0.35 by 2018, then falls to a low near 0.26 around 2020. After 2020 it recovers gradually, reaching about 0.30 by 2023 to 2024 and then rising further to about 0.39 by the end of the sample. The red area at the bottom shows the portion of those pending maturities coming from loans that were extended within the prior two years. That component is fairly flat at a bit under 10 percent for most of the sample, and rises back to around 10 percent by the end of the sample. It is flat under 30 percent in the prepandemic period, spikes to over 35 percent during the pandemic, retraces during the pandemic recovery, and remains under 30 percent during the stress period.
Figure A7: Extensions by Property Type and Period
(a) Weighted
(b) Unweighted
Notes: Each panel plots the share of loans with pending
(four quarters ahead) maturities that get extended by property type.
Blue, orange, and red bars give extension rates before, during and after
the pandemic, respectively. The left panel weights by loan balance and
the right is unweighted.
This figure has two grouped bar charts. The left panel is weighted by loan balance and the right panel is unweighted. In both panels, the horizontal categories are hotel, retail, office, multifamily, and industrial. Each category has three bars: blue for pre-COVID, orange for 2020 to 2022, and red for 2023 onward. Hotels have the highest extension rates, typically a bit over 50 percent weighted, and a bit under 50 percent unweighted across time periods. Industrial properties normally have the lowest at under 40 percent pre-pandemic (either weighted or unweighted), though extension rates rose to 40 or 50 percent (unweighted and weighted, respectively) after 2023. All property types see extensions rise during COVID. All property types besides retail see extensions rise after 2023 relative to before the pandemic on a weighted basis, while only office, multifamily and industrial see increases on an unweighted basis, with only industrial seeing extensions rise by more than a couple of percentage points.