Estimating Rent Increases Resulting from Colorado House Bill 26-1106:
Modeling Litigation Risk, Supply-Side Effects, and Regressive Cost Incidence in Rental Housing
Preliminary economic modeling of litigation risk, supply-side effects, and regressive cost incidence in Colorado rental housing as a direct result of proposed policy in HB26-1106.
Key Findings
Contents
Introduction
1.1 Background
The relationship between tenant-protection legislation and rental market outcomes is among the most extensively studied topics in urban economics. A robust and growing body of empirical research has established that policies which increase the difficulty or cost of evicting tenants tend to raise market rents in equilibrium. The mechanism is intuitive: when housing providers face higher expected costs from the eviction process—whether through longer timelines, increased legal fees, additional hearings, or deferred rent recovery—they incorporate these costs into the price of housing. In competitive rental markets, this cost pass-through is substantial, often approaching 70–100% over time.
Colorado's House Bill 26-1106, introduced in the Second Regular Session of the Seventy-Fifth General Assembly, proposes to fundamentally alter the state's eviction process through multiple provisions that collectively extend eviction timelines, increase procedural requirements, and reduce housing providers' ability to recover unpaid rent during appeals. This paper provides a rigorous economic analysis of the bill's likely impact on rental prices.
We do not dispute that eviction is a disruptive event for tenants, nor that some procedural protections serve legitimate purposes. The question this paper addresses is narrower and empirical: what is the likely magnitude of rent increases resulting from the cost-raising provisions of HB26-1106, and how are those increases distributed across housing segments?
1.2 Research Questions
This paper addresses three interrelated questions. First, what additional costs will HB26-1106 impose on housing providers per eviction event, and what is the expected statewide aggregate? Second, how will these additional costs transmit into equilibrium rents, and what is the likely magnitude of the resulting rent increase? Third, how will the rent impact be distributed across housing price segments—will lower-cost housing bear a disproportionate burden?
Provisions of HB26-1106 and Cost-Raising Mechanisms
HB26-1106 modifies Colorado's existing forcible entry and detainer statutes (Article 40, Title 13, C.R.S.) in several significant ways. Each provision directly or indirectly increases the expected cost and duration of the eviction process.
Summary: Taken together, these provisions could extend the typical eviction process by 2 to 5 months beyond the current baseline, depending on the case, jurisdiction, and time of year.
Literature Review: Eviction Policy and Rental Market Outcomes
A significant and rapidly growing body of peer-reviewed research has established the empirical relationship between tenant-protection policies and rental market outcomes. We review the most relevant studies.
3.1 Coulson, Le, Ortego-Marti, and Shen (2025)
Journal of Urban Economics. Construct a Tenant Rights Index (TRI) spanning 1997–2016 using state-level variation in 12 landlord-tenant law categories. A one-unit increase in the TRI reduces the eviction rate by 8.9% but makes rental housing 6.1% more expensive. The mechanism operates through a search-and-matching model: more stringent regulations reduce evictions but raise the relative demand for housing, tightening rental markets and pushing up rents. They also find that increased TRI correlates with higher homelessness rates. Colorado, identified as having a relatively pro-housing-provider legal environment, would be particularly susceptible to rent increases from a sudden shift toward stronger tenant protections.
3.2 Abramson (2024)
Journal of Finance. Develops a dynamic equilibrium model calibrated to micro data on evictions, rents, and homelessness in San Diego County. Central finding: "Right-to-Counsel" policies—which like HB26-1106 increase the cost and complexity of eviction proceedings—drive up rents so much that homelessness increases by 15% and aggregate welfare declines. The key driver is the persistent nature of income shocks underlying rent delinquency: because defaults are typically caused by persistent rather than transitory income losses, extending the eviction process delays but does not prevent eviction.
3.3 Collinson, Humphries, Mader, Reed, and Tannenbaum (2024)
Quarterly Journal of Economics. Related work by these authors finds that housing providers pass through $20 to $40 per month of costs induced by a legal aid program designed to prevent or delay evictions in New York City. This direct empirical estimate of cost pass-through is central to our modeling framework and demonstrates that eviction-related cost increases are transmitted into rents with substantial efficiency.
3.4 Humphries et al. (2024)
Becker Friedman Institute Working Paper. Use detailed data from housing-provider ledgers to study the relationship between tenant nonpayment and eviction decisions. When eviction costs increase, housing providers respond by raising rents, tightening screening criteria, or both—with each response disproportionately affecting lower-income applicants.
3.5 Corbae and Glover (2024)
NBER Working Paper. Develop a general-equilibrium model of eviction. Eviction restrictions calibrated to a two-month average delay deliver lower lifetime utility at birth than the optimal policy and are "even inferior to the laissez-faire policy that allows immediate evictions." They find eviction restrictions better reserved for rare crises, and that direct rent support paid to housing providers is a more effective tool. This is directly relevant to HB26-1106, which would impose delays well in excess of two months.
3.6 Diamond, McQuade, and Qian (2019)
American Economic Review. Study rent control expansion in San Francisco. While protected tenants benefited in the short run, the policy reduced rental housing supply by 15% as housing providers converted properties to condos or other uses, ultimately increasing market rents by 5.1% citywide. Illustrates the supply-side channel through which regulatory costs affect rents.
Synthesis: The literature converges on a consistent finding—policies that increase eviction costs raise rents. Empirical estimates range from approximately 1–6% depending on the policy's severity and the market context. All three mechanisms (direct cost pass-through, risk-adjusted pricing, supply contraction) are relevant to HB26-1106.
Data and Calibration
We calibrate our model using publicly available Colorado-specific data on rental housing stock, rent levels, eviction filings, and eviction costs.
The baseline expected eviction cost per unit is calculated as:
Expected Cost = Filing Rate × Cost per Eviction
= 0.051 × $4,400
= $224 per unit per year (~$18.70/mo)
This represents roughly 1.07% of the average monthly rent. Colorado's tight market (4.5% vacancy, 50%+ of renters cost-burdened) indicates housing providers have significant pricing power and tenants have limited ability to absorb cost increases.
Key Calibration Parameters
| Parameter | Baseline Value | Sensitivity Range |
|---|---|---|
| Renter-occupied units | 783,000 | 760,000–810,000 |
| Average monthly rent | $1,750 | $1,600–$1,900 |
| Annual eviction filings | 40,000 | 30,000–50,000 |
| Eviction filing rate | 5.1% | 3.8%–6.4% |
| Baseline cost per eviction | $4,400 | $3,500–$5,250 |
| Expected eviction cost/unit/mo | $18.70 | $11–$28 |
| Rental vacancy rate | 4.5% | 4.0%–5.5% |
Economic Model
We model the transmission from HB26-1106's provisions to equilibrium rents through three channels: (1) direct cost pass-through from increased per-eviction costs, (2) risk-adjusted pricing reflecting higher variance in returns, and (3) supply-side contraction from reduced profitability at the margin.
5.1 Housing Provider Profit Function
A competitive housing provider sets rent R to maximize expected profit:
Π = R − C − p · E[Ce]
// Break-even rent condition
R* = C + (p · E[Ce]) / 12
// When HB26-1106 increases E[Ce] by ΔCe
ΔR = p · ΔCe / 12
Where R is monthly rent, C represents non-eviction operating costs, p is the annual eviction probability, and E[Ce] is the expected eviction cost. In competitive equilibrium, profit approaches zero, so every cost increase passes through to rents.
5.2 Estimating the Additional Cost per Eviction (ΔCe)
Based on our analysis of the bill's provisions, we estimate the aggregate delay extension at 2 to 5 months. At an average rent of $1,750/month, the additional cost from lost rent alone ranges as follows, plus $500–$2,000 in additional legal fees:
| Component | Low | Mid | High |
|---|---|---|---|
| Lost rent (delay) | $3,500 | $6,125 | $8,750 |
| Additional legal fees | $500 | $1,250 | $2,000 |
| Total ΔCe per eviction | $4,000 | $7,375 | $10,750 |
5.3 Pass-Through Rate
Empirical estimates from the housing literature suggest pass-through rates of 50–100% for persistent cost shocks in rental markets. We model three pass-through rates: 50% (conservative), 75% (moderate), and 100% (full pass-through). In Colorado's tight rental market, housing providers have relatively strong pricing power, suggesting pass-through closer to the upper end of this range.
5.4 Cost Pass-Through to All Units
A critical feature is that housing providers spread the expected cost across all units as a form of risk pooling — similar to how insurance premiums reflect the average expected loss across a portfolio:
// θ = pass-through rate (0.5, 0.75, or 1.0)
// p = eviction filing rate (0.051)
// ΔCe = additional cost per eviction
This model implies that every renter in the state bears some portion of the increased eviction cost, regardless of whether they personally face eviction risk.
Quantitative Estimates
| Scenario | 50% pass-through | 75% pass-through | 100% pass-through |
|---|---|---|---|
| Low (ΔCe = $4,000) | $8.50 | $12.75 | $17.00 |
| Mid (ΔCe = $7,375) | $15.68 | $23.52 ← central | $31.34 |
| High (ΔCe = $10,750) | $22.86 | $34.28 | $45.69 |
The central estimate (mid-cost, 75% pass-through) yields a monthly rent increase of approximately $23.52, or 1.34% of the baseline $1,750 average rent. The range across all scenarios spans from $8.50 (0.49%) to $45.69 (2.61%).
6.2 Aggregate Annual Cost to Colorado Renters
| Scenario | θ = 50% | θ = 75% | θ = 100% |
|---|---|---|---|
| Low (ΔCe = $4,000) | $79.9M | $119.8M | $159.7M |
| Mid (ΔCe = $7,375) | $147.3M | $221.0M ← central | $294.6M |
| High (ΔCe = $10,750) | $214.8M | $322.2M | $429.5M |
The central estimate produces an aggregate annual cost of approximately $221 million. Across the full range, the annual cost spans from $80 million to $430 million. These are recurring annual costs that compound over time as they become embedded in the rental rate structure.
Regressive Incidence: Disproportionate Impact on Lower-Cost Housing
A critical finding of this analysis is that the rent increases caused by HB26-1106 will be regressive—that is, they will represent a larger percentage burden for lower-cost housing than for higher-cost housing.
7.1 The Fixed-Cost Mechanism
Eviction litigation costs are largely fixed per event, not proportional to rent. Filing fees, attorney fees, court administrative costs, and vacancy turnover expenses are approximately the same whether the unit rents for $900 or $3,000. Because the fixed component of ΔCe does not depend on R, the percentage rent increase declines as rent increases:
// R appears in denominator → percentage increase inversely related to rent
// ∂(ΔR/R)/∂R < 0 — lower-rent units face larger percentage increases
7.2 The Eviction-Probability Mechanism
Compounding the fixed-cost mechanism, lower-cost housing has substantially higher eviction rates than higher-cost housing — an empirical regularity documented across multiple studies and jurisdictions.
| Housing Segment | Monthly Rent Range | Est. Annual Eviction Rate |
|---|---|---|
| Low-cost | < $1,200 | 8–15% |
| Mid-market | $1,200–$2,000 | 4–8% |
| Higher-cost / luxury | > $2,500 | 1–3% |
7.3 Numerical Illustration
Using a mid-range additional eviction cost of $6,000 and a 75% pass-through rate:
| Segment | Avg. Rent | Eviction Rate | Monthly ΔR | % Increase | Annual ΔR |
|---|---|---|---|---|---|
| Low-cost | $1,000 | 10% | $37.50 | 3.75% | $450 |
| Mid-market | $1,800 | 5% | $18.75 | 1.04% | $225 |
| Higher-cost | $3,000 | 2% | $7.50 | 0.25% | $90 |
The low-cost segment faces a percentage rent increase that is 15 times larger than the higher-cost segment (3.75% vs. 0.25%). Even in dollar terms, the monthly increase for a $1,000/month unit ($37.50) is five times the increase for a $3,000/month unit ($7.50).
7.4 Relative Impact Visualization
The tenants most affected by the resulting rent increases are precisely the tenants the bill purports to protect: lower-income renters in affordable housing. A 3–5% rent increase for a household already paying 40–50% of income on rent pushes the cost burden substantially higher, potentially forcing housing tradeoffs or exit from the market entirely. This is consistent with Abramson (2024), who finds that right-to-counsel policies paradoxically increase homelessness by driving up rents for the most cost-sensitive tenants.
Supply-Side Effects
Beyond the direct cost pass-through, HB26-1106 will produce supply-side effects as reduced profitability causes some housing providers to exit the rental market.
| Segment | Rent | Oper. Cost | Baseline Π | Eviction Cost* | New Π |
|---|---|---|---|---|---|
| Low-cost | $1,000 | $875 | $125 | $50 | $75 |
| Mid-market | $1,800 | $1,440 | $360 | $25 | $335 |
| Higher-cost | $3,000 | $2,250 | $750 | $10 | $740 |
*Expected monthly eviction cost increase per unit (from Table 6, using 75% pass-through before rent adjustment).
For the low-cost segment, the eviction cost increase reduces profit by 40% ($125 to $75). For some providers operating at thinner margins, the cost increase may push units below break-even, triggering exit from the rental market through sale to owner-occupants, conversion to short-term rental use, or redevelopment.
The literature suggests short-run supply elasticities for rental housing of 0.2–0.5. If HB26-1106 causes even a modest supply contraction of 0.5–1.5% in the affordable segment, the resulting rent increase could range from an additional 1–4%, stacking on top of the direct cost pass-through. Diamond et al. (2019) documented a 15% supply reduction in San Francisco from rent control with a 5.1% aggregate rent increase. While HB26-1106 is not rent control, the supply-side mechanism is analogous.
Sensitivity Analysis
| Assumption Set | Monthly ΔR | % of Avg. Rent | Annual Aggregate |
|---|---|---|---|
| Most conservative | $5.60 | 0.32% | $52.6M |
| Low scenario | $12.75 | 0.73% | $119.8M |
| Central estimate | $23.52 | 1.34% | $221.0M |
| High scenario | $34.28 | 1.96% | $322.2M |
| Upper bound | $45.69 | 2.61% | $429.5M |
Even under the most conservative assumptions, the analysis indicates a measurable rent increase. Even if the bill's provisions produce only a 1-month average delay extension (well below our low estimate), the monthly rent increase under central assumptions would be approximately $5.60. If the average delay exceeds 5 months — plausible for cases involving multiple excusable delays, inclement-weather postponements, and appeals without rent deposit — the monthly increase would exceed $45.
Colorado's low vacancy rate (4.5%) and tight market conditions suggest pass-through rates closer to 75–100%. At 100% pass-through with mid-range cost estimates, the monthly increase reaches $31.34. These figures do not include the additional supply-side effects described in Section 8, which would push total increases higher.
Conclusions
10.1 HB26-1106 Will Raise Rents
The bill's provisions—daily scheduling caps, mandatory hearings, expanded excusable delays, elimination of rent deposits during appeal, 30-day writ extensions, and inclement-weather prohibitions—collectively extend the eviction timeline by an estimated 2 to 5 months and increase per-eviction costs by approximately $4,000 to $10,750.
Our central estimate projects a statewide average rent increase of approximately $23.52 per month (1.34%), with a plausible range of $8.50 to $45.69 per month (0.49–2.61%). Including supply-side effects, total rent increases could reach 2–3% for the statewide average. The aggregate annual cost to Colorado renters is estimated at $130 million to $430 million.
10.2 The Impact is Regressive
Because eviction costs are largely fixed per event and eviction rates are structurally higher in lower-cost housing, the bill's rent impact is regressive:
<$1,200/month
$24–$60/mo increase
$1,200–$2,000/month
$14–$44/mo increase
>$2,500/month
$7–$30/mo increase
10.3 Supply Contraction Will Compound the Impact
By compressing profit margins in the affordable housing segment, HB26-1106 will accelerate the exit of marginal housing providers from the market. The resulting supply contraction will further increase rents, with the largest effects concentrated in exactly the housing segments that are already undersupplied in Colorado's tight rental market.
10.4 The Bill's Costs Are Borne by All Renters
A crucial insight from this analysis is that the bill's costs are not limited to units that actually experience eviction proceedings. Housing providers spread expected eviction costs across their entire portfolio as part of standard risk-adjusted pricing. As a result, every Colorado renter—including the vast majority who will never face eviction—will pay higher rent as a consequence of this bill.
HB26-1106 will raise rents for Colorado tenants. It will raise rents the most for those who can least afford it. And it will do so while reducing the supply of the affordable housing the state most urgently needs.
References
- Boaz Abramson. "Housing Market Spillovers from Right-to-Counsel." In: Journal of Finance 79.6 (2024), pp. 3733–3789.
- Robert Collinson, Nicholas Mader, and Davin Reed. "The Effects of Legal Aid on Tenant Outcomes and Rent." Working paper, NYU Wagner. 2024.
- Robert Collinson et al. "Eviction and Poverty in American Cities." In: Quarterly Journal of Economics 139.1 (2024), pp. 57–120.
- Dean Corbae and Andrew Glover. "Eviction, Homelessness, and the Safety Net." NBER Working Paper No. 32709. 2024.
- N. Edward Coulson et al. "Tenant Rights, Eviction, and Rent Affordability." In: Journal of Urban Economics 147 (2025), p. 103715.
- Denver7 News. Eviction Filings in Denver Continue to Rise. Retrieved from denver7.com. 2025.
- Matthew Desmond. Evicted: Poverty and Profit in the American City. New York: Crown Publishers, 2016.
- Rebecca Diamond, Timothy McQuade, and Franklin Qian. "The Effects of Rent Control Expansion on Tenants, Landlords, and Inequality: Evidence from San Francisco." In: American Economic Review 109.9 (2019), pp. 3365–3394.
- Enterprise Community Partners. New Data on 150,000 Colorado Eviction Filings Points Toward Stable Housing Solutions. Retrieved from enterprisecommunity.org. 2022.
- John Eric Humphries et al. "Landlord Decisions and the Eviction Process." Becker Friedman Institute Working Paper No. 2024-150. 2024.
- National Low Income Housing Coalition. Out of Reach: Colorado. Retrieved from nlihc.org. 2024.
- RentCafe. Average Rent in Colorado. Retrieved from rentcafe.com. 2026.
- Albert Saiz. "The Geographic Determinants of Housing Supply." In: Quarterly Journal of Economics 125.3 (2010), pp. 1253–1296.
- U.S. Census Bureau. American Community Survey 1-Year Estimates, Table DP04: Selected Housing Characteristics, Colorado. 2024.
Formal Mathematical Model
A.1 Basic Cost Pass-Through Model
Let N denote the total number of renter-occupied units statewide, F the annual number of eviction filings, and p = F/N the average annual eviction probability per unit. Let Ce denote the cost per eviction under current law, and ΔCe the additional cost per eviction attributable to HB26-1106.
ΔR = θ · (p · ΔCe) / 12
// (10) Percentage rent increase
ΔR/R = θ · (p · ΔCe) / (12R)
// (11) Aggregate annual statewide cost
Total = ΔR · N · 12 = θ · p · ΔCe · N
A.2 Regressive Incidence Proof
Decompose ΔCe into fixed and variable components: ΔCe = Cf + t · R, where Cf is the fixed cost component, t is the additional delay in months, and R is monthly rent.
ΔRⱼ/Rⱼ = θ · pⱼ · (Cf + t · Rⱼ) / (12 · Rⱼ)
// (13) Simplified
ΔRⱼ/Rⱼ = (θ · pⱼ · Cf) / (12 · Rⱼ) + (θ · pⱼ · t) / 12
// Term 1: inversely proportional to Rⱼ (regressive)
// Term 2: independent of Rⱼ (flat)
// Because pⱼ is negatively correlated with Rⱼ, both terms are
// larger for lower-rent segments — proving regressive impact.
A.3 Supply-Side Model
Let Πj = Rj − Cj − pj · E[Ce]/12 be the monthly profit for a unit in segment j. A unit exits the rental market when Πj ≤ 0. The additional rent increase from supply contraction is approximately:
ΔRsupply = ΔQⱼ / εd
// εd (short-run demand elasticity) ≈ 0.3–0.7
// Even 1% supply contraction → 1.4–3.3% additional rent increase
Cooper Thayer is a practicing real estate broker associate (REALTOR®) and market trends expert based in Denver, Colorado. He has represented or coordinated more than 300 residential transactions across the Denver Metro and Colorado Springs markets, totaling more than $350 million in closed sales volume. As Chief Market Strategist for the Keller Williams Colorado Region, he briefs more than 2,600 agents on housing supply dynamics and market risk indicators.
He serves the Colorado Association of REALTORS® (CAR) as a Market Trends Spokesperson and Legislative Policy Committee Member, and as Trustee for the Colorado Association of REALTORS® Political Action Committee (CARPAC). He also serves as Treasurer of the Board of Directors for the Denver Metro Association of REALTORS® (DMAR).
Recent speaking engagements include the CAR Economic Summit (2024–2026), the Keller Williams Colorado Broker Summit (2025), and the HB23-1253 State Legislative Task Force on Corporate Housing Ownership (2024). He holds a B.S. in Business Administration with dual emphases in Finance and Real Estate from the University of Colorado Boulder's Leeds School of Business.