Understanding Affordable Housing In Skagit County

Welcome to the Skagit County branch of the Affordable Housing Insights Hub! This resource is designed to assist data-driven decision making around housing in Skagit County, WA by bringing together federal, state, county, and local data from publicly available sources. Lunous believes in the “housing first” model of solving homelessness and thus primarily focuses on data surrounding housing affordability, supply, and demand. However, we also recognize that homelessness is an incredibly complex issue and requires acknowledgement of the many contributing factors such as mental health challenges, substance abuse, domestic violence, and intergenerational poverty. Our goal is to bring clarity and transparency to data that may otherwise be confusing and scattered in order to assist our community in the effort to end homelessness.

Throughout this page, you will find visual representations of the challenges that any one of our neighbors may be facing, such as lack of housing, unstable housing, or being burdened by their rent. This is paired with other data that aims to create a comprehensive picture around the health of the Skagit County community as it relates to affordable housing.

Select from the list below to navigate this page and review the data that we have compiled on each section.

People Experiencing Homelessness

The first step to ending homelessness is understanding how significant the need in your community is. Having an accurate understanding of how many people are experiencing homelessness in your community will be integral to the decision-making process around resource allocation, policy, etc.

Homelessness takes many forms - including many that are “invisible”. Through Title 24 of the Code of Federal Regulations (CFR), Section 578.3, the federal government defines homelessness in four parts:

  1. Those who are “literally homeless”

  2. Those who are at imminent risk of experiencing literal homelessness

  3. Those fleeing or attempting to flee domestic violence

  4. Those who are defined as homeless in other federal statutes

Legal definitions aside, the important thing to remember is that people experiencing homelessness may not always “look” homeless or fit our public perception of what homelessness looks like. They may be someone sleeping in their car, couch-surfing between friends' homes, sheltered, unsheltered, or any combination. These people are our neighbors - we share life’s many moments with them every day - and many of us may not even be aware.

To visualize the number of people experiencing homelessness in Skagit County and beyond, Lunous utilizes data from the Department of Housing and Urban Development (HUD) and the Washington State Department of Commerce. This data is a count of sheltered and unsheltered people experiencing homelessness on a single night each January, known as the annual Point-in-Time (PIT) count. The minimum standards for collecting this data are dictated by HUD (see the PIT methodology guide here) and follow legal requirements, however, this methodology is often criticized as being insufficient in the effort to gain an accurate understanding of how many people are experiencing homelessness in any given area. HUD, in collaboration with other federal departments such as the Department of Health and Human Services (HHS) and the Department of Veterans Affairs (VA), also sets standards for another collection of data around homelessness and housing - the Homeless Management Information System (HMIS). This data is regarded to have higher accuracy than the PIT Count however, it includes personally identifiable information and Lunous was unable to establish a collaboration with local agencies to obtain de-identified data while developing this tool (though we remain hopeful!).

These counts from the PIT Count and HMIS help to inform policy, allocate funding, and aid service providers in planning for the year ahead.

When considering data-driven decision making, it’s also useful to have a way to compare two or more areas that may vary widely in population. For example, 500 people experiencing homelessness in an area with 100,000 people is a much higher rate (0.5%) than 500 people experiencing homelessness in an area with one million people (0.05%). In order to present these raw numbers in a relatable way, we utilize a calculation that makes this possible, known as per capita. Essentially, this gives you a number of people per 100,000 that you can compare between two areas with differences in population, such as Skagit County vs. King County. To calculate this value, we divide the measure (number of people experiencing homelessness in Skagit Co.), by the population of the area (the total number of people living in Skagit Co.), and multiply by your scale population (100,000 on this page). This allows us to compare different areas in an understandable way.

 

 Skagit County in comparison

Let’s take a look at the rates of homelessness in Skagit County.

Based on the most recent data available (left) - 2023 - Skagit County was 9th highest out of Washington’s 39 counties, with 402 people experiencing homelessness per capita. Compare that to the rate of homelessness in neighboring counties:

Whatcom - 450 per capita

Snohomish - 149 per capita

Chelan - 531 per capita

San Juan - 279 per capita

Island - 151 per capita

Okanagan - 645 per capita

Skagit County was even found to have higher rates of homelessness than King County in 2023, which had 276 people experiencing homelessness per capita - that’s nearly 1.5 times higher!

When reviewing the data over time (below), Skagit County has seen an improvement in rates of homelessness since 2010, however, there has been an increase in recent years (2022 and 2023). Despite the improvement from 2010, the community consistently has higher rates of homelessness than the nation as a whole, with the exception of 2013, and is often higher than the amount of people experiencing homelessness per capita across Washington State.

Leading Indicators of Homelessness

Now that we have gained an understanding of how many people experience homelessness in Skagit County, it is important to review some of the housing-related leading indicators of homelessness in the area. This includes various metrics such as residents spending too much on their rent, eviction rates, vacancy rates, and the availability of affordable housing across income levels.

Housing Instability

Housing instability is the difficulty a household faces to maintain their housing. Any crisis, such as a job change, medical bills, or sudden change in financial status, could put someone at imminent risk of experiencing homelessness. With stagnant wage growth and increasing costs of necessities, you and many of our neighbors face the chance that some catastrophic event will lead to homelessness.

 

Rent Burdened

The U.S. department of Housing and Urban Development defines “affordable” housing as “housing on which the occupant is paying no more than 30 percent of gross [pre-tax] income for housing costs, including utilities“. When a person or household is paying more than 30% of their gross income on their housing, they are considered “cost-burdened”. The data available to visualize this best is from the American Community Survey (ACS), an annual survey conducted by the U.S. Census Bureau. The ACS collects data on the percent of renters paying greater than 30% of their income on rent alone (“rent-burdened”), which is more significant than being cost-burdened due to the fact that other housing costs are not taken into account. In most years since 2010, more than half of all renters in Skagit County have been found to be rent-burdened (right).

Evictions

Per the eviction research network, the number of evictions per capita filed in Skagit County has been increasing each year since 2020. Of note, there was a moratorium on evictions in Washington State from March 18, 2020 to June 30, 2021 due to the COVID-19 pandemic.

 

Rental Vacancy Rate

The “rental vacancy rate” is the number of vacant rental units divided by the total number of rental housing units in a given area. Vacancy rates can be informative as additional housing is created to determine if an area is reaching a stable housing supply (between 3-6% vacancy rate). Vacancy rate is also a lagging indicator - there is usually a 12-24 month lag between the approval to build new housing and those units coming to market.

Interestingly, vacancy rate was one of the few indicators identified to have a correlation to homelessness in the book Homelessness is a Housing Problem by Gregg Colburn and Clayton Page Aldern, which uses data to identify which factors believed to cause homelessness are actually seen to show a correlation with higher rates of homelessness in the United States.

Supply and Demand of Affordable Housing

Having considered the rate of homelessness and some of the leading indicators of homelessness in Skagit County, the next step is to visualize the supply and demand of affordable housing in the community. In the following sections, you will see four visualizations that allow us to begin to understand:

  • How much money people typically make in Skagit County (area median income)

  • Households in Skagit County, broken down by their income level

  • Housing units in Skagit County, broken down by how much they cost

  • How many housing units in Skagit County are affordable to each income level

Lunous uses the HUD definition of affordable housing, which is that an occupant should pay no more than 30% of their gross income on housing costs, including utilities.

Area Median income

Area median income, or AMI, is the midpoint of all incomes in a given area, determined by the Department of Housing and Urban Development. The importance of AMI primarily lies in the fact that it is used to determine eligibility for various housing programs and is one of the most common measures of income that is referenced in discussions about housing. Ideally, data regarding affordable housing would be based around AMI. Unfortunately, data from the American Community Survey is segmented into income groups that do not always overlap with AMI.

 
 

Number of Affordable Housing Units

When considering whether there is sufficient affordable housing in a community, it is important to know the incomes of households in that area, what their monthly housing costs are, and how the housing stock compares in price to those levels of income. In these visualizations, we utilized ACS datasets for reported housing costs and reported household income. While these visualizations indicate a general idea of the number of units and how they compare to income, because the data provided by ACS in this context is only for occupied units, we are unable to provide a complete cross-sectional evaluation of all housing units in Skagit County. This means that each data point in the surrounding graphs represents a household that is currently housed, how much their income is, and how much their housing costs are. Information from ACS misses a significant piece of the picture by not having data on the income of our neighbors who are unhoused, the cost of units that are currently vacant, or a way to identify if households are renting above or below what is affordable to them by HUD standards. The Census Bureau also identifies many key groups as being hard to count and/or historically undercounted in the ACS, such as low-income individuals, undocumented immigrants, minorities, and people who do not live in traditional housing. The presented visualizations are an attempt by us at Lunous to present the most robust information, while acknowledging where gaps exist in the data.

The two graphs above begin to paint this picture by showing the number of households by income and the number of occupied housing units by cost each year since 2010 (all adjusted for inflation). In 2014, two additional brackets were added to the ACS under housing costs to allow for more granularity in higher cost brackets. When comparing the most recent data (2023) to 2010, the most significant changes can be found in income levels above $8,333 per month (more than 13,000 additional households) and in the number of occupied housing units which cost above $2,000 per month (more than 9,000 additional units).

Next, we developed visualizations (right and below) to identify how many of the occupied housing units are affordable and which income brackets may have more or less units than required. Since the ACS divides income and housing costs into consistent brackets that do not fit nicely into affordability constraints (30% of gross income), we at Lunous fit each cost bracket into the provided income brackets, ensuring that cost of housing never exceeds 30% of gross income. It appears from this data that the lowest two income brackets (up to $1,249.92 per month) did not have sufficient affordable housing units, with 3,400 total households and only 2,483 affordable units.

Future Insights

TBA