What Does the Data Say About Connecticut’s Housing Stock? The Connecticut Housing Finance Authority (CHFA) Needs Assessment


By: Andrew Bolger, Senior Research and Data Analyst, and Kayla Giordano, Senior Program and Data Analyst, Connecticut Housing Finance Authority

This past November, the Connecticut Housing Finance Authority (CHFA) had the privilege of presenting at the Partnership for Strong Communities annual Affordable Housing Conference. With partners from the real estate, advocacy, and home builder industries, our session focused on sharing work from CHFA’s recently published 2023 Housing Needs Assessment (HNA). That one hour conversation covered just a piece of our research. In this blog, we’ll expand on our presentation by bringing you key findings from the HNA including a highlight of gaps in Connecticut’s housing stock and the influencing factors that have shaped the state’s housing market in recent years. Want more? Be sure to read to the full report on our website.

Connecticut’s Housing Stock & Demographics

In order to understand Connecticut’s housing needs, it’s important to recognize the state’s changing demographics, particularly around population and household growth. Despite the popular idea that Connecticut is shrinking in size, recent American Community Survey data shows the state’s population is actually on the rise by just under half a percent. While not every county in Connecticut saw population increases, they all experienced notable increases in levels of household formation. Increasing household formation reflects movements of residents from place to place. For example, household formation occurs when a recent college graduate moves from their parent’s house into a place of their own. Between the 2016 and 2021 Five Year ACS periods, Connecticut saw a 3.15% increase in the overall number of households.

Figure 1: Change in Population and Household by County – 2016 to 2021

Connecticut also has the sixth oldest housing stock of any state (including Washington DC) with a median year built of 1966 compared to 1980 for the rest of the country. This is driven by the fact that Connecticut has been well below the historic average for newly issued building permits in recent years. Between 1990 and 2005, Connecticut towns issued an annual average of roughly 9,500 permits for new privately owned housing. This permitting dropped drastically during the Great Recession and has seen a very slow recovery, particularly in construction of single-family homes. This historic underproduction, paired with the increase in population and households, means that more people are competing for a limited number of available and affordable homes. As demonstrated in the next section, this increased demand leads to higher housing costs for Connecticut residents.

Figure 2: Connecticut Building Permits – New Privately-Owned Housing

Connecticut also has the sixth oldest housing stock of any state (including Washington DC) with a median year built of 1966 compared to 1980 for the rest of the country. This is driven by the fact that Connecticut has been well below the historic average for newly issued building permits in recent years. Between 1990 and 2005, Connecticut towns issued an annual average of roughly 9,500 permits for new privately owned housing. This permitting dropped drastically during the Great Recession and has seen a very slow recovery, particularly in construction of single-family homes. This historic underproduction, paired with the increase in population and households, means that more people are competing for a limited number of available and affordable homes. As demonstrated in the next section, this increased demand leads to higher housing costs for Connecticut residents.

COVID-19 Implications

The onset of the COVID-19 pandemic in early 2020 had dramatic effects on the housing market in Connecticut and nationwide. The pandemic led many, especially millennials, to enter the home purchase market for the first time. In 2021, Connecticut saw over 61,000 single-family home (1 to 4 units) sales, the highest number since the start of the Great Recession in 2008. Correspondingly the median sales price in Connecticut jumped from $234,500 in 2019 to $310,000 in 2022, an increase of 32%.

For-sale inventory levels typically operate in a cyclical nature, growing in early spring, peaking in summer, and ebbing in the fall and winter months when the school year and holidays dissuade people from moving. However, with the onset of the pandemic, Connecticut did not see the same seasonal increase in inventory as in previous years (Figure 3). As of May 2023, Connecticut had roughly 5,900 homes listed for sale, just 30 percent of the for-sale inventory in May 2019.

Decreased inventory, combined with increased household formation and homeownership demand among millennials, resulted in a dramatic uptick in the percentage of listings sold above their asking price. Prior to March 2020, only about 20% of home listings sold above their original asking price on average across all counties (Figure 4). During the pandemic period, that number grew to 50% on average, with some markets in Connecticut reaching above 70% depending on the month and market. Interestingly, despite cooling across U.S. markets, Connecticut’s share of listings sold above asking price has remained higher than the national average, indicating the state’s market has remained hotter than the country at large.

Figure 3: For-Sale Inventory by Month and Metro-area

Figure 4: Percent of Listings Sold Above Listing Price by Month and Metro-area

As home values and sales prices increased, so did the competition for listings. Across all of Connecticut’s markets, the average number of days a home is listed has decreased significantly, even after the primary pandemic surge in demand had passed. For example, in the Hartford Metro-Statistical Area (MSA), the average number of days between list date and sale pending date was 13 days in May 2023 compared to an average of 53 days in May 2019. Quick turn times resulted in many homebuyers taking risks such as waiving home inspections and other contingencies that were previously commonplace in order to be competitive. As noted above, homebuyers were also routinely offering above asking price, putting lower income buyers with less cash on hand at a disadvantage.

Figure 5: Mean Number of Days Until Pending by Metro-area

Additionally, as the Federal Reserve attempts to combat inflation, higher interest rates have further limited options for homebuyers. Between October 2021 and October 2022, the average 30-year fixed rate mortgage increased by 3.91 percentage points according to Freddie Mac. This represents the largest year-over-year increase in mortgage interest rates since 1981 and has created further affordability challenges for homebuyers. According to a nationwide analysis by Harvard’s Joint Center for Housing Studies (JCHS), “In April 2021, a household had to earn at least $79,600 a year to afford payments on the median priced home of $340,700. One year later, the income requirement stood at $107,600.”

The pandemic also had dramatic effects on the rental market. Driven by strong demand for units and a competitive home sales market, rental vacancy rates in every Connecticut metro area dropped significantly in 2020. Consequent to low vacancy rates, landlords gained additional power to raise rents. As demonstrated in Figure 7, all Connecticut metros saw large year over year rent growth during 2020, with Norwich leading the pack at 12%. Rising costs have consequences for all renters but particularly for those with low incomes who are already struggling with housing cost burden. 

Figure 6: Rental Vacancy Rate by Quarter and Metro-area

Figure 7: Year over Year Rent Growth by Quarter and Metro-area

Housing Affordability Gaps

It is generally accepted that a household is said to be “cost burdened” when it spends more than 30% of its income on housing. Anything over this 30% marker is considered unaffordable. The housing affordability gap analysis seeks to answer this question: “Are there enough units affordable to all Connecticut households?” Of course, the answer is no. As such, the next step is to assess both how many households exist in each income bracket and how many units are available to those households. We also evaluate the extent to which higher or lower income households occupy housing that is more or less expensive than what they can afford.

Unsurprisingly, analysis finds that the affordability gap is most intense for the lowest income renters. Renters at the 0-30% income bracket do not have an adequate supply of affordable units so many households reside in units affordable to higher income brackets. This leads to high rates of cost burden and greater competition for housing among households in the 31-50% income bracket. In theory, renters in the 31-50% income bracket have more than adequate affordable units in the stock. However, households from both lower and higher income brackets occupy a large proportion of these units. Consequently, many renters earning 31-50% AMI must seek out other, typically higher cost housing, contributing to high rates of cost burden in this income bracket. An example of this phenomena is demonstrated below in Figure 8.

Figure 8: Example – Households and Units Among 31-50% AMI Renters in Hartford County

Renters in the 51-80% income bracket are less likely to be cost burdened than those at lower incomes despite most of the housing stock in their income bracket being occupied by lower- and upper-income households. They frequently avoid being cost burdened by occupying lower cost housing. Renters earning greater than 80% of AMI are the least likely to be cost burdened. There are more renters in this income bracket than units so many are likely choosing rental units that are also affordable to households at the lower income brackets. Building more units affordable to renters earning between 51-100% AMI could provide more appropriate and affordable housing units to these households while opening up housing opportunities for lower income households. Arguably, incentives for households in these income brackets to voluntarily pay more for their housing would need to be strong. Such incentives might include better on-site amenities, access to quality public transit, and proximity to jobs.

Figure 9: Connecticut Renter Households and Units by AMI

Ultimately, CHFA finds a gap of over 92,000 units affordable to extremely low-income renters, although this does not reflect a one-to-one ratio of units that need to be built. Rather, it suggests the number of units which need to be available to extremely low-income households and which are not occupied by other income brackets. This estimate is in line with other publications, including those from the National Low Income Housing Coalition. To learn more about the housing affordability and gap analysis, including full methodology and analysis by income bracket for both renters and homeowners, please see sections five and six of the full housing needs assessment.

Thank you very much to the Partnership for Strong Communities for highlighting our publication. Our hope is that it provides our partners with the knowledge they need to advance their work around expanding and promoting the development of affordable housing. Have questions or want to learn more? Please reach out to research@chfa.org to connect with our research team or check out our blog, The Intersect.


Andrew Bolger is a Senior Research and Data Analyst in the Connecticut Housing Finance Authority’s Research, Marketing, and Outreach Department. In this role he manages CHFA’s housing database, tracks and analyzes housing market conditions, and evaluates CHFA programs. He received a BA in Economics and Political Science and an MA in Public Policy from the University of Connecticut.

Kayla Giordano is a Senior Program & Data Analyst in the Research Marketing and Outreach Department at the Connecticut Housing Finance Authority. Here she provides housing market research and data analytics to inform the authority and educate key stakeholders. Through program evaluation and strategic planning initiatives, her goal is to advance the authority’s ability to fulfil its vision for an affordable Connecticut for all. Prior to her role with CHFA, Kayla worked with a Community Development Financial Institution in underwriting affordable housing projects and assessing community impact. She holds a Masters degree in Community Development Policy & Practice from the Carsey School at the University of New Hampshire as well as undergraduate degrees in Political Science and Economics from Eastern Connecticut State University.

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