KUER0%

What Utah could learn from Austin’s housing boom and falling rents 65%

By Sean Higgins0%

4/3/2026, 8:00:00 AM

BS Summary: This article contains 25 faulty reasoning types, including Hasty Generalization, Confirmation Bias, and False Dilemma, with Post Hoc (False Cause) as the most egregious example at 15.3% saturation with 123 hits. Analysis detected 1,171 faulty-reasoning hits from 802 analyzed words, generating a BS Score of 59.3% and a BS Rank of 65% (7,495 of 21,180 articles). This article is worse (more manipulative) than 64.60% of the article peer group.

Does building more homes actually lower prices? 
New research from the Pew Charitable Trusts says yes. 
With Utah staring down a potential housing deficit of 235,000 homes over the next 30 years, researchers say the state could learn a thing or two from Austin, Texas. 
For starters, an analysis by Pew found the city managed to drop the median rent by 4%  or about $250 a month  over the last five years through big changes to zoning and permitting that caused a new housing surge. 
According to the analysis, Austin’s explosive growth in the 2010s saw the city fall into a housing crisis where “too many people were competing for too few homes.” 
In that decade, rents rose by 93%, and home prices shot up 82%. 
Pew Housing Policy Initiative Director Alex Horowitz sees similarities in Austin’s situation a decade ago to Utah’s housing landscape today, with high-paying tech jobs and the lure of the outdoors helping fuel the state’s historic growth and expensive housing market. 
“Utah is a state that has added a lot of population and has added more housing than most states, but has not been able to keep up with the influx of residents,” Horowitz said. 
“We were able to learn a lot by looking at Austin's experience and studying how they added so much housing.” 
Beginning in 2015, Horowitz said Austin implemented a series of changes. 
Reforms included zoning regulations that made it easier to build apartment buildings and a permitting process to allow for faster development and lower costs. 
What followed was an influx of new housing between 2015 and 2024 to the tune of 120,000 units  a 30% increase in the city’s total housing stock. 
While housing affordability can sometimes feel like an unsolvable problem, “it's within reach if we make it easy enough to build,” Horowitz said. 
“Builders are ready to build homes, but they're facing too many regulatory barriers, and so they only end up building for really the top end of the market or large apartment buildings.” 
In short, he believes the biggest thing governments can do is get out of the way. 
Salt Lake City passed sweeping zoning reform in 2023, but there still haven’t been significant changes on a statewide level. 
One bill in the 2026 legislative session that would have made it easier to build homes on small lots did not even make it out of committee. 
For Utah League of Cities and Towns Policy Director Karson Eilers, it will take more than zoning changes to address the problem. 
“For every house, you need to make sure you have adequate drinking water, adequate sewer supply, adequate transportation; all of these systems that are typically public systems,” he said. 
“We're rapidly growing, and that means that we have really significant infrastructure challenges to be able to keep accommodating that.” 
Eilers pointed out that many of the permitted housing lots in the state are in areas where essential utilities such as sewer, water and electricity might be lacking. 
“We have a lot of these high-growth areas that are sort of on the urban periphery,” he said. 
“You have a ton of entitlements, legal entitlements, that have been given there, but we're all trying to figure out how to make sure that there's water there.” 
To address that very issue, there has been some movement on the policy front. 
This year, state lawmakers passed legislation aimed at making large infrastructure projects cheaper through low-cost loans. 
Over time, advocates say that could also increase housing supply and help drive down prices. 
Statewide measures like incentivizing transit-oriented development and national factors like low interest rates during the early pandemic years led to a surge in new supply. 
Now, those tools are again resulting in some progress in Utah’s rental market. 
According to Zillow, rents in Utah have been on a slow decline since mid-2025. 
When it comes to what type of housing is the best to build, experts like Horowitz say any new housing  even if it’s on the higher end of the market  helps drive down costs for everyone. 
“When there's not enough housing, it's low-income renters who end up paying the steepest price, because high-income renters move into middle-income neighborhoods and middle-income renters move into low-income neighborhoods,” he said. 
“Even if new housing is expensive, adding a lot of it ends up benefiting low-income renters the most.” 
Eilers urged a little patience to see how recent changes at the state and local levels play out before people start clamoring for more drastic adjustments. 
“Cities don't build housing,” Eilers said. 
“We plan for housing, and many of these tools that we've created, these bites of the apple, have only really started to come into fruition relatively recently.” 
Article reasoning-pattern comparisonThis article: 11.3%Sean Higgins: 2.5%KUER: 2.8%Confirmation Bias11.3%This article: 0.0%Sean Higgins: 0.9%KUER: 1.3%Anchoring Bias0.0%This article: 3.6%Sean Higgins: 2.8%KUER: 3.4%Availability Heuristic3.6%This article: 8.5%Sean Higgins: 1.7%KUER: 1.2%Representativeness Heuristic8.5%This article: 2.5%Sean Higgins: 0.4%KUER: 0.5%Hindsight Bias2.5%This article: 6.1%Sean Higgins: 2.1%KUER: 1.9%Overconfidence Bias6.1%This article: 0.7%Sean Higgins: 5.2%KUER: 7.4%Framing Effect0.7%This article: 0.0%Sean Higgins: 0.9%KUER: 1.3%Loss Aversion0.0%This article: 5.7%Sean Higgins: 1.1%KUER: 1.2%Status Quo Bias5.7%This article: 3.4%Sean Higgins: 0.1%KUER: 0.3%Sunk Cost Effect3.4%This article: 8.5%Sean Higgins: 4.1%KUER: 4.4%Optimism Bias8.5%This article: 2.5%Sean Higgins: 1.9%KUER: 2.4%Pessimism Bias2.5%This article: 5.0%Sean Higgins: 5.3%KUER: 6.3%Negativity Bias5.0%This article: 0.0%Sean Higgins: 4.2%KUER: 2.2%Self-Serving Bias0.0%This article: 7.9%Sean Higgins: 0.7%KUER: 0.9%Fundamental Attribution Error7.9%This article: 0.0%Sean Higgins: 0.2%KUER: 0.2%Actor-Observer Bias0.0%This article: 0.0%Sean Higgins: 2.7%KUER: 1.9%In-Group Bias0.0%This article: 0.0%Sean Higgins: 0.8%KUER: 0.6%Out-Group Homogeneity Bias0.0%This article: 0.0%Sean Higgins: 2.1%KUER: 2.3%Halo Effect0.0%This article: 0.0%Sean Higgins: 0.0%KUER: 0.1%Horn Effect0.0%This article: 0.0%Sean Higgins: 0.0%KUER: 0.0%Dunning-Kruger Effect0.0%This article: 5.1%Sean Higgins: 1.2%KUER: 1.2%Recency Bias5.1%This article: 0.0%Sean Higgins: 0.5%KUER: 0.3%Primacy Effect0.0%This article: 0.0%Sean Higgins: 0.1%KUER: 0.1%Blind-Spot Bias0.0%This article: 0.0%Sean Higgins: 0.5%KUER: 0.6%Ad Hominem0.0%This article: 0.0%Sean Higgins: 0.6%KUER: 0.4%Straw Man0.0%This article: 5.9%Sean Higgins: 4.1%KUER: 4.7%Appeal to Authority5.9%This article: 9.1%Sean Higgins: 2.2%KUER: 1.7%False Dilemma9.1%This article: 0.0%Sean Higgins: 0.7%KUER: 1.1%Slippery Slope0.0%This article: 3.5%Sean Higgins: 0.2%KUER: 0.2%Circular Reasoning3.5%This article: 14.5%Sean Higgins: 4.7%KUER: 4.1%Hasty Generalization14.5%This article: 1.7%Sean Higgins: 0.2%KUER: 0.2%Red Herring1.7%This article: 0.0%Sean Higgins: 0.6%KUER: 0.7%Bandwagon0.0%This article: 3.2%Sean Higgins: 5.5%KUER: 5.6%Appeal to Emotion3.2%This article: 3.0%Sean Higgins: 0.8%KUER: 0.7%Begging the Question3.0%This article: 15.3%Sean Higgins: 2.5%KUER: 2.4%Post Hoc (False Cause)15.3%This article: 0.0%Sean Higgins: 0.1%KUER: 0.1%Tu Quoque0.0%This article: 0.0%Sean Higgins: 0.3%KUER: 0.4%Burden of Proof0.0%This article: 3.6%Sean Higgins: 0.3%KUER: 0.2%Appeal to Nature3.6%This article: 5.0%Sean Higgins: 0.3%KUER: 0.3%Composition/Division5.0%This article: 3.5%Sean Higgins: 2.4%KUER: 3.1%Anecdotal3.5%This article: 0.0%Sean Higgins: 0.2%KUER: 0.1%No True Scotsman0.0%This article: 6.9%Sean Higgins: 1.8%KUER: 1.5%Ambiguity (Equivocation)6.9%This article: 0.0%Sean Higgins: 0.0%KUER: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Sean Higgins: 0.2%KUER: 0.2%Middle Ground0.0%This article: 0.0%Sean Higgins: 0.1%KUER: 0.1%Personal Incredulity0.0%This article: 0.0%Sean Higgins: 0.1%KUER: 0.1%Special Pleading0.0%This article: 0.0%Sean Higgins: 0.1%KUER: 0.2%Genetic Fallacy0.0%This article: 0.0%Sean Higgins: 0.9%KUER: 0.8%Unattributed Quote0.0%This article: 0.0%Sean Higgins: 0.8%KUER: 0.7%Quote-first Misdirection0.0%This article: 0.0%Sean Higgins: 1.4%KUER: 2.2%Biased Writer Voice0.0%This article: 0.0%Sean Higgins: 2.4%KUER: 1.6%Indoctrination0.0%This article: 0.0%Sean Higgins: 1.3%KUER: 0.8%Politically Left Leaning Bias0.0%This article: 0.0%Sean Higgins: 0.3%KUER: 0.3%Politically Right Leaning Bias0.0%This article: 0.0%Sean Higgins: 0.6%KUER: 1.0%Attempt to Sell a Product or S…0.0%

802 words analyzed.

Speakers

5speakers64%attributed speech288writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 11 words • 0.0% coverageWriter's voice • 7 words • 0.0% coveragePew Charitable Trusts • 9 words • 0.0% coverageWriter's voice • 29 words • 0.0% coveragePew • 42 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageAlex Horowitz • 40 words • 0.0% coverageAlex Horowitz • 34 words • 0.0% coverageAlex Horowitz • 20 words • 0.0% coverageAlex Horowitz • 11 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageAlex Horowitz • 23 words • 0.0% coverageAlex Horowitz • 32 words • 0.0% coverageAlex Horowitz • 16 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageKarson Eilers • 22 words • 0.0% coverageKarson Eilers • 29 words • 0.0% coverageKarson Eilers • 20 words • 0.0% coverageKarson Eilers • 28 words • 0.0% coverageKarson Eilers • 18 words • 0.0% coverageKarson Eilers • 28 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageZillow • 14 words • 0.0% coverageAlex Horowitz • 38 words • 0.0% coverageKarson Eilers • 31 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageKarson Eilers • 26 words • 0.0% coverageKarson Eilers • 6 words • 0.0% coverageKarson Eilers • 27 words • 0.0% coverage
Selected voice

Pew

100%flagged-word coverage
42 attributed words8.2% of attributed speech88% writer coverage

No manipulation-pattern hits were found in this speaker's attributed words or the writer's voice.

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.