While turbulence in the financial markets and volatility in commercial real estate have become “par for the course,” the housing market continues to captivate analysts and researchers. In this issue, Outlook on Real Estate features an article by Isaac Hacamo of the Kelley School of Business that quantifies the impact baby boomers downsizing and moving out of family-sized homes will have on housing affordability. Monitoring the Metrics showcases a data-driven article from Matt Nowlin of the Indiana Association of Realtors, which illustrates just how willing Indiana homebuyers are to put their money where their mouths are when it comes to getting closer to nature. Don’t forget to keep your eye on our Power Grid of demand drivers, which are updated monthly, and the latest real estate research in this issue — all part of our focus on integrating research and practice.
– Sara Coers, Associate Director, IU Center for Real Estate Studies
– Doug McCoy, Al and Shary Oak Director of the IU Center for Real Estate Studies
Sara Coers, Associate Director, IU Center for Real Estate Studies
Updated monthly, our Power Grid dashboard gives a simple and clear picture of how Indiana and the U.S. are performing on key metrics that correlate to real estate demand.
If you think our latest Power Grid update is sending mixed economic signals, you’re not alone. The positive upward trend in GDP we saw in the second and third quarters of 2025 came to a screeching halt by the end of the year, with both Indiana and U.S. economic growth beginning to stagnate, driven in part by the lengthy federal government shutdown last fall. But February’s employment and wage data are slightly more positive, at least in Indiana, which is showing growth in the previously flat manufacturing sector. Private employment growth softened in February, but remained positive, and private wages began to grow again. Economic indicators continue to confound — trends are hard to predict and real numbers often defy expectations — illustrating that volatility abounds in the market. It is tough to be a real estate decision-maker right now, which is why I encourage you to check in with the Power Grid regularly to watch where our fundamentals are trending.
Sara Coers, Associate Director, IU Center for Real Estate Studies
We read a lot of journals and research papers here at the Kelley School and the Center for Real Estate Studies, as you can imagine. We want to share some of the more interesting and compelling studies with you, providing a brief summary and a link. Enjoy!
The U.S. housing market was fundamentally reshaped from 2019 to 2025, with work-from-home trends and mortgage interest rates increasing worker mobility and price affordability until 2022, then greatly reducing both through 2025. Home prices rose over 50% from January 2019 to November 2025, driven by low interest rates. Increased demand from remote work also reduced the importance of proximity to city centers, boosting suburban markets. Mortgage rate increases later caused sales to decrease and created a powerful lock-in effect on homeowners. Housing supply shortages and rent growth exacerbated the housing price increases, further eroding affordability. Structural changes to the housing market have created a high-price, low-mobility housing equilibrium and necessitate a re-thinking of policies related to interest rates, mortgages, and incentives.
by Golnaz Bahrami, Matthew Gustafson, and Eva Steiner
December 5, 2024
With the scientific community calling on government to expand protected areas to conserve biodiversity, the resulting limits on how land can be developed substantially impact land values and land use. The authors of this paper found that land near boundaries of protected areas loses about 50% of its value compared to unprotected land due to significant restrictions on development. The impact on land values is highest in areas with high development activity, though the negative effect diminishes over distance from the conservation area borders. This research highlights the tradeoff between conservation and real estate development, showing that the conservation of natural areas comes at a cost to the local economies of conservation areas due to decreased development potential and resulting land values.
by Joshua Coven, Sebastian Golder, Arpit Gupta, and Abdoulaye Ndiaye
June 19, 2025
Higher property taxes may be a solution to unlocking homes owned by older households and shifting homeownership to younger households. Housing markets rely on the ability of households to relocate based on employment, family, or lifestyle changes. Homeownership, particularly of larger homes, has been disproportionately held by older households due to the lock-in effect of high housing prices and financial constraints. Older households are more sensitive to property tax; if property taxes are increased, as in this study where California property taxes were modeled to increase to Texas levels, the authors determined homeownership would increase 6% and young household ownership would increase 8% due to the capitalization of higher property taxes, resulting in lower purchase prices.
Are Baby Boomer Homes the Answer to Housing Affordability?
Isaac Hacamo, Professor of Finance, Indiana University
The “silver tsunami” — the impending wave of baby boomers downsizing, moving to assisted living, or passing away — is expected to put a large number of homes back on the market and make housing more affordable for the next generation. This is a common argument in housing policy. The story is simple and intuitive: Baby boomers, born between 1946 and 1964, are the largest generation of homeowners in American history, and many are aging in place in homes they bought decades ago, often three- or four-bedroom houses where they now live alone or only with a spouse. When they downsize, move into assisted living, or pass away, many of these family-sized homes could in principle become available to younger buyers.
At first glance, that argument makes sense. Across the 50 largest metropolitan areas in the U.S., about 8% of all owner-occupied homes are held by baby boomers living in underused and likely affordable housing — defined here as homes with at least two more bedrooms than occupants, occupied by just one or two people born during the baby boom, and priced below the 75th percentile of the local market. That is a large stock of family-sized homes held by older households who, in many cases, no longer need the space. If even part of that stock turned over, it could expand the supply of affordable housing for younger families.
But we might already expect that, in cities where young families most need housing, the stock of underused boomer homes is already small. In these places, high prices — driven by high demand — should theoretically create pressure for aging boomers to sell underused homes and move to smaller units or retirement destinations. If this mechanism is working smoothly, the gap between boomer-held supply and young-family demand should be small in areas where affordability issues are most acute.
To examine this idea more carefully, I turned to data from the American Community Survey (2020–2024, 5-year estimates), which aggregates five years of survey data for roughly 3.5 million addresses in the U.S., creating a large and detailed individual-level dataset. I built two metro-level measures for the 50 largest U.S. metropolitan areas. First, I computed the share of households headed by a person aged 25 to 45 with children under 18 who are renters, which I use as a proxy for young-family housing demand. This is still a conservative measure because it leaves out households without children that would like to have them but may be delaying family formation until they can buy a home. Second, I calculated the share of owner-occupied homes held by baby boomers living in one- or two-person households, with at least two excess bedrooms, and valued below the metro-area 75th percentile, which I use as a measure of affordable, underused boomer housing supply. Figure 1 shows the relationship across metropolitan areas.
Figure 1: Young Renter Families (Head Aged 25-45) with Children vs. Affordable Boomer Underused Homes across the 50 Largest U.S. Metros
Bubble size = metro population
Y-axis: Boomer (1946-1964) underused homes (2+ excess BR), 1-2 persons total, valued below metro P75, as share of all owner-occupied homes
Source: ACS 5-Year (2020-2024), IPUMS, 50 largest metro areas
The figure suggests some boomer house turnover could help the market, but not nearly enough to treat demographic turnover as a one-size-fits-all solution to the affordability problem. Across metros, places with more underused boomer homes do tend to have fewer young families with children stuck renting. The correlation is negative (-0.23, dashed gray line): metros with more affordable boomer-held supply tend to have less young-family rental pressure, and vice versa. But this is only a modest relationship, and the graph still shows many places where the mismatch remains large.
A closer look at individual metros makes that mismatch more concrete. For example, Washington, D.C., and Atlanta stand out as places where the numbers come closer to balancing. In D.C., roughly 10% of owner-occupied homes are affordable, underused, and boomer-held, while about 6.3% of households are young renter families with children — a near one-to-one ratio of roughly 150,000 potential boomer homes to 155,000 young renting families. Atlanta looks similar: 10.6% of homes fit the boomer-underused profile against 6.9% young renter families, with about 161,000 boomer units for 163,000 young renters. More surprisingly, Houston and San Antonio fall in the low boomer-supply part of the figure, despite being large Sun Belt metros where one might have expected more underused affordable boomer housing.
The picture is much worse in some of the highest cost metros. In Los Angeles, only 6.7% of owner-occupied homes fit the boomer-underused category, while 9.0% of households are young renter families with children. In raw numbers, that comes to about 146,000 potential boomer homes against 430,000 young renting families — roughly one boomer home for every three families that need one. New York faces a similar gap: 263,000 boomer homes for 611,000 young renters, a ratio of 0.43. Miami also shows a large imbalance. San Francisco, by contrast, is better described as sitting in the moderate part of the graph rather than in the most extreme group. Its mismatch is real, but not as profound as I expected, given the level of house prices in the Bay Area.
Of course, even where the numbers appear to line up, moving boomer-held housing to young families is far from automatic. Many baby boomers have strong reasons to stay put: property tax rules (such as California's Proposition 13), low mortgage rates locked in years ago, and the capital gains exclusion on primary residences all reduce the incentive to sell. Underused boomer homes are also not always where young families most want to live; they may be in suburban or exurban areas far from jobs, schools, or transit. Some of these homes are older and may need costly repairs before they appeal to younger buyers. And even when boomers do sell, it is naive to assume the whole stock of underused homes will be bought by young families in need. Some will go to investors, second-home buyers, trade-up households, or downsizing older adults instead.
The supply of housing available for boomers is too small relative to demand, and the affordability crisis is too severe to be solved by demographic turnover alone.
What does this suggest? There is some truth to the idea that house turnover by baby boomers will release housing supply and ease affordability pressures, but the effect will vary a lot across cities. In metros like Atlanta, Philadelphia, Washington, D.C., and Jacksonville, where boomer-underused homes make up a relatively large share of the owner-occupied stock and young renter families make up less of the market, demographic turnover could provide some real relief. In Pittsburgh and Detroit, the ratio of potential boomer supply to young-family demand is above one, which suggests genuine room for easing. But in many of the largest and most expensive metros, the math still does not work. The boomer housing supply is too small relative to demand, and the affordability crisis is too deep to be solved by demographic turnover alone, suggesting that, in those places, building more housing is still needed, as the silver tsunami won’t be big enough to wash away affordability issues.
Monitoring the Metrics
Beyond the Backyard: How Natural Amenities Affect Residential Pricing
By Matt Nowlin, Senior Director, Indiana Association of REALTORS®
How Much Does Nature Boost Home Value?
Quality of life may be a subjective concept, but the lifestyle preferences of homeowners and homebuyers ultimately create empirical measures: The attractions and amenities that appeal to us create a price premium as we compete for finite housing options convenient to them. In 2024, we explored this dynamic in the walkable, often pre-war neighborhoods around Indiana’s urban centers and found a notable increase in demand leading to faster price appreciation (even from a much more affordable baseline in many cases) in these areas.
In this sense, walkability is often about density in our built environment. But what about natural amenities and the man-made developments meant to help us explore and enjoy the outdoors?
Indiana boasts hundreds of lakes and has completed more than a hundred miles of new trails in the last seven years. Waterfront development has been a focus of regional planning along the White River in Central Indiana and communities along the Ohio River at the state’s southern border.
Indiana also has more than 2,500 parks, from the sprawling 16,000 acres of Brown County State Park to local neighborhood pocket parks; a recent analysis from the IU Polis Center found that less than one in three Hoosiers live within a half-mile of one of them.
But what price are Indiana homeowners willing to pay for proximity to these outdoor features that connect them to nature “beyond their backyards?”
How We Studied Price Impacts
Homebuyers pay a premium to live near trails, parks, and water; moreover, the impact on property value gets stronger — and faster — as properties are closer to the amenity. We analyzed 10,000 home sales from 2021 to 2023 to measure the effect of these amenities, controlling for other factors (size of the home, age of the home, and ZIP Code).
We created a statistical model to measure how much distance to four amenities — parks, trails, lakes, and streams — impacted home prices. To isolate the effect of these amenities, we included square footage, age, and ZIP Code in our model. This means we “controlled” for characteristics of the home and the neighborhood. While there are more detailed ways to measure home and neighborhood factors, our model consistently explained 67% of the price difference from one home to another, showing that it is robust and accurate.
Distance matters exponentially more as you get closer and closer to an amenity — being able to walk to a lake is nice, but having lake views or being on the shoreline is worth much more. To account for this, we built a model that separately measures effects within 1,000 feet and beyond 1,000 feet. Even within those categories, price impacts are still exponential — prices rise faster and faster as you get near a park for example, so we reflect the price premium every time you cut the distance to an amenity in half (see Figure 1).
Figure 1: The Numbers: Just How Much Proximity Pays Off
Lakes Are a Game-Changer
Figure 2: Home Value Gains from
Lake Proximity
We found that lakes have the strongest effect on prices. A home within 60 feet of a large lake (at least 500 acres) is worth 81% more than the same home if it were 1,000 feet from the lake. The price premium is 27% for medium lakes (100-499 acres) and minimal for small lakes. Medium and large lakes have the strongest effect on prices. The impact of a lake depends on its size, so we measured small (less than 100 acres), medium (100-499 acres), and large lakes (500 acres or more). As examples, Lake Wawasee, Indiana’s largest natural lake, is over 2,000 acres, while Eagle Creek Reservoir is 1,400 acres.
Bartholomew County’s Grandview Lake is about 400 acres. For homes within 1,000 feet of a large lake, value rise 15-20% each time the distance to the lake is halved. All else being equal, a home 500 feet from a large lake is worth 16% more than an equivalent home 1,000 feet away. Compared to 1,000 feet, the price premium is 35% at 250 feet, 56% at 125 feet, and 81% at about 60 feet, which, for many properties, would be adjacent to the lake.
For example, homes near Geist Reservoir often sell for two to 10 times the county-average sale price, and the adjacent ZIP Codes are among the most expensive in the state. One home only 65 feet from Morse Reservoir sold for $266 per square foot, while a home 200 feet away on the same road sold for only $163 per square foot.
Medium lakes have about one third of the effect on prices that large lakes have. For homes within 1,000 feet, prices increase 7% each time the distance is halved. A home is worth 27% more if it is 60 feet from a medium-sized lake compared to 1,000 feet.
Beyond 1,000 feet, large lakes still have some positive influence on prices, while medium lakes do not. Small lakes have no statistical effect on home values statewide, though in some counties they do have an effect.
Figure 2 shows how being closer to an amenity can increase a home’s value — even when the home’s size, age, and neighborhood stay the same. For this example, we imagined a home worth $250,000 located 1,000 feet from the amenity.
Indiana’s largest natural lake (Lake Wawasee) is located in Kosciusko County, and it has stronger price effects than the statewide average (see Figure 3). A home 60 feet from the lake is worth 124% more than the same home 1,000 feet from the lake. The effect of medium and small lakes is also much stronger in the county; the area’s 100+ natural lakes are a collective selling point, so it is likely that properties around smaller bodies of water benefit from a halo effect bestowed by the unique concentration.
Figure 3: Lake Proximity Price Effects in Northeast Kosciusko County
Even small lakes in Kosciusko County add a price bump, and large lakes more than double home prices.
Bartholomew County’s largest lake is Grandview, which falls in the “medium lake” category. Home values double between 1,000 feet from the lake and 60 feet from the lake (see Figure 4). The effect continues beyond 1,000 feet, with a positive price impact that is about as strong as the statewide impact of trails. No homes in Bartholomew County are within 1,000 feet of a large lake, but even beyond 1,000 feet, large lakes have a positive impact on home prices in Bartholomew County. This may indicate increased value as homes are closer to Lake Monroe and the higher property values of Brown County.
Figure 4: Lake Proximity Price Effects in Bartholomew County
Small lakes boost prices in Bartholomew County and homes next to medium lakes are double the price of an equivalent home 1,000 feet away.
In Brown County, lakes command an even stronger price premium than the state average (see Figure 5). Trails and parks, while plentiful in the county, do not show a clear positive relationship with prices — though their presence in the county is certainly a desirable amenity for many residents. Brown County’s medium-sized lakes are Yellowwood Lake (123 acres) and Sweetwater Lake (279 acres). A property on the shore of one of these lakes is estimated to sell for three times the price of an equivalent property 1,000 feet away (213% price premium). Estimated home price increases by 30-50% each time you halve the distance to the lake. Nearby large lakes include Lake Lemon and Lake Monroe (in Monroe County). These command a premium on par with the state average.
Figure 5: Lake Proximity Price Effects in Brown County
Medium lakes have the strongest impact in Brown County. While trails and parks do not have a hyperlocal price effect, they likely support county-wide values.
Streams and Rivers Offer a Modest, but Measurable Boost
We consider streams and rivers together, and they have a positive impact on home prices (see Figure 6). For homes within 1,000 feet, value increase 3% every time that distance is halved. That means, compared to a home 1,000 feet away from a stream or river, value will be 3% higher at 500 feet, 6% higher at 250 feet, 9% higher at 125 feet, and 12% at about 60 feet (likely adjacent to the water).
Beyond 1,000 feet, home values tend to decrease slightly when closer to a river. This may reflect the fact that rivers tend to run through older, more industrial parts of cities, but the effect is very small even if it is statistically significant.
Parks Add Value, Especially Close By
Parks have a similar effect to streams and rivers: a 3% increase in value every time you cut the distance to a park in half (see Figure 7). Compared to a home 1,000 feet from a park, value will be 3% higher at 500 feet, 5% higher at 250 feet, 8% higher at 125 feet, and 11% higher at about 60 feet.
Figure 6: Home Value Gains from Proximity to
Streams and Rivers
Figure 7: Home Value Gains from Proximity
to Parks
Figure 8: Home Value Gains from Trail Proximity
Trails: Some Stand Out More Than Others
Homes within 1,000 feet of a trail have a 1.5% price premium every time that distance is halved, meaning value rises by 3% at 250 feet from a trail and 6% at about 60 feet from a trail (see Figure 8). However, this effect varies from trail to trail, which we discuss in the next section.
In Madison, trails have a very strong price premium (see Figure 9). The trails in the area include the Riverfront Trails as well as the network of hiking trails in Clifty Falls State Park. It may be proximity to the park itself that drives these prices up. Rivers and streams do not show a positive price effect in this ZIP Code, though that could be because the older part of town was built closest to the river. Though it is historic and charming, it is also generally lower-valued than the outlying subdivisions. However, looking at median sale price trends in this ZIP (47250) and the township (Madison) that includes the downtown district is suggestive of the success of redevelopment strategies capitalizing on adjacency to the Ohio River: Five-year price appreciation for the ZIP (64%) and township (62%) run well ahead of Jefferson County as a whole (55%).
Figure 9: Trail Proximity Price Effects in Madison County
Trails in Madison boost prices, while other amenities did not have a measurable effect on prices.
In addition, the Monon Trail shows a very high price premium equivalent to the impact of a medium-sized lake (see Figure 10). Quite literally, properties along the Monon benefit from a beachfront-scale price bump. A home about 60 feet from the trail is worth 24% than one 1,000 feet from the trail. In this analysis, we only considered home sales in Hamilton and Marion counties and within one mile of the Monon. We tested the Cardinal Greenway (from Marion to Richmond), the Nickel Plate Trail (from Rochester to Kokomo and Noblesville to Indianapolis), and the Fall Creek Trail (Indianapolis), but found no price effect. Those who are familiar with Central Indiana, however, may recognize that home values in areas around completed portions of the Nickel Plate (in Hamilton County) and Fall Creek (particularly the neighborhoods around 38th Street) were being influenced by other commercial and public infrastructure investments during the study period, making it difficult to parse trail effects.
Figure 10: Monon Trail Proximity Price Effects in Marion and Hamilton Counties
The Monon Trail has the same price impact as beachfront property on a medium-sized lake.
Benefits from Multiple Amenities Can “Stack”
In some communities with multiple, overlapping amenities, we measure real price benefits from lakes, streams, trails, and parks.
In Porter, Lake, and La Porte Counties, four amenities have a positive relationship to price: parks, streams, medium lakes, and large lakes. In this area, large lakes are obviously dominated by Lake Michigan, and the price premium for large lakes is lower than the state average. While some areas have very desirable lakefront property, in other communities, being close to the lake means being next to industrial sites. Medium-sized lakes, however, command an above average premium (see Figure 11).
Figure 11: Proximity Price Effects in Lake and Porter Counties
Parks and streams have more of a price impact here than in the state, and medium lakes offer the largest price premium.
In the Lake County portion of the shoreline, being close to the lake does not always lead to high property values, but near Beverly Shores and Michigan City, homes near the lake sell at twice the county average or higher (see Figure 12).
Figure 12: Proximity Price Effects along Lake Michigan Shoreline
What This Means for the Indiana Real Estate Market
Proximity to natural amenities — particularly lakes, trails, parks, and streams — has a measurable and often substantial impact on home values in Indiana. Among all amenities studied, large lakes consistently generate the highest price premiums, with the value of homes rising significantly as distance to the lake decreases. Even medium-sized lakes show strong, positive effects on price within 1,000 feet. Trails, streams, and parks also enhance property values, though the magnitude varies, especially in the case of trails where specific corridors, like the Monon Trail, exhibit unusually high premiums.
These effects are most pronounced within close range — typically within 1,000 feet — and grow exponentially stronger as distance is halved. This underscores the value of direct access and views. Furthermore, localized analyses confirm that these statewide trends hold true — or are even amplified — in amenity-rich counties like Kosciusko, Bartholomew, and areas along the Monon Trail.
Our results are consistent with similar research. In a review of 33 studies, the price premium for being adjacent to a park was generally 8-10%. Locally, Indiana University’s Public Policy Institute found that, in 2019, homes within 250 feet of an Indianapolis park were worth $14,000 more than the county average. Within a quarter-mile of a park, property values grew faster than the county average from 2016-2019 (15% compared to 11% county-wide).
Nearby greenway trails likewise usually add value, though the effect is often more modest. A 2019 synthesis of 20+ trail impact studies found that homes adjacent to recreational trails were typically 3–5% higher in price compared to similar homes away from the trail. However, the impact of trails can be specific to certain trails. A 2003 study on the impact of greenways in Indianapolis found that, while the Monon Trail had a positive impact on nearby property values, other greenways at the time did not. We find similar results across the state — the Monon still shows strong price impacts along with trails in Madison, Indiana, while the Nickel Plate Trail, Cardinal Greenway, and Fall Creek Trail have no statistical effect.
Available consumer preference surveys also show growing affinity for these amenities among real estate consumers. In the MIBOR 2022 Community Preference Survey (covering a region accounting for roughly 40% of Indiana’s annual residential transactions on average), 65% of respondents ranked the availability of parks, trails and playgrounds nearby as important or very important to their quality of life, up from 60% in 2018.1
State, regional, and local actors recognize this desire and are working to develop more trails and parks. Indiana has embarked on its largest single infusion of state funding for trail development over the past eight years ($180 million in the Next Level Trails program). 2 Through two rounds of the state’s billion-dollar READI grant program, dozens of regional trail and park projects received funding.3
Conclusion
This analysis reinforces a central finding in urban and environmental economics: proximity to natural amenities is capitalized into housing prices in clear, measurable, and highly localized ways. Across Indiana, access to lakes, parks, trails, and waterways is not merely a lifestyle preference but a durable component of residential value, with price effects that intensify sharply at close distances. These premiums persist even after accounting for housing characteristics and neighborhood context, underscoring the independent economic significance of natural and recreational infrastructure.
For housing markets more broadly, the results highlight how amenity-driven demand shapes patterns of residential sorting and price stratification. Large and medium-sized lakes, in particular, function as powerful anchors of value, while parks, streams, and select trail corridors contribute more modest, but still meaningful, premiums. The steep gradient of these effects within short distances suggests that access and visibility — not just general proximity — are critical mechanisms through which natural amenities influence prices.
For planners, policymakers, and developers, these findings provide empirical support for investments in green and blue infrastructure as tools for place-making and long-term value creation. The evidence suggests that well-designed parks, trails, and waterfront projects can generate measurable housing market returns, strengthen local tax bases and enhance the attractiveness of communities to residents and employers alike. At the same time, the concentration of price premiums near high-quality amenities raises important equity considerations. Without complementary housing and land-use strategies, investments intended to improve quality of life may also accelerate affordability pressures in surrounding neighborhoods.
Finally, this study contributes to a growing body of literature demonstrating that natural amenities are not peripheral to housing markets but central to how households evaluate place. As regions across the Midwest and beyond seek to attract residents, support workforce growth, and adapt to changing preferences for outdoor access and quality of life, understanding the price effects of these amenities can inform more intentional, balanced approaches to development and policy.
