Introduction:

The US housing market in late 2024 is facing a variety of challenges, primarily centered around rising home prices and diminished affordability. Among the biggest obstacles today is the ongoing issue of home affordability. Over the past several years, home prices have increased significantly due to factors like rising mortgage rates and inflationary pressures. As mortgage rates climb, borrowing becomes more expensive, significantly impacting new homebuyers’ ability to afford homes. This, combined with the already-high home prices, has created a situation where fewer people are able to purchase homes.

Another significant issue is the limited housing supply, particularly in desirable urban and suburban areas. Homeowners are less motivated to sell their properties, especially considering the low mortgage rates they secured in previous years. This "lock-in effect" has contributed to the tight housing market. Builders, meanwhile, are facing significant challenges related to supply chain shortages and increased construction costs, further exacerbating the shortage of affordable housing options.

Our Objective

To understand how effective CLTs like Urban Suburban Affordables are in maintaining long-term affordability, it's important to examine various factors, such as home prices, property values, and neighborhood stability. This research could focus on several key aspects, including: Current Home Prices vs. Initial Purchase Prices: By comparing how much homes in USA’s land trust are selling for today versus their original purchase price, we can assess whether the homes have remained affordable over time. Property Turnover and Resale Trends: The frequency of buying and selling within the CLT can provide insight into homeownership stability. If properties are frequently resold, it may suggest a lack of long-term stability, whereas fewer sales might indicate a stronger sense of community and ownership. Neighborhood Impact: Understanding how USA’s CLT affects the broader community can offer insights into how well it helps stabilize the local housing market and foster resilient, thriving neighborhoods. The goal of this research is to measure the trends and sale prices of USA’s Homes, and its impact on the affordability and stability of Hartford’s housing market, and potentially offer lessons for other cities considering similar initiatives. These findings could also provide valuable feedback to the Center for Leadership and Justice, informing improvements or adjustments to their own affordable housing programs. Accessor data was found via https://gis.vgsi.com/westhartfordct/Search.aspx (West Hartford GIS. "West Hartford Property Search." Accessed November 24, 2024. https://gis.vgsi.com/westhartfordct/Search.aspx.).

Embed each of your published visualizations as an HTML iframe code, following instructions in Chapter 9 of HODV, similar to the sample below.

Purchase Price of Property vs. Current Value

EDIT CAPTIONS like this -- Figure 1: Explore the interactive chart AND ADD your description of the chart here. Make sure your caption includes a direct link to your published chart or map in case the embed code fails to display.

Findings

Create a separate section to describe how you obtained your data, key steps in your process, and cautions for interpreting its meaning. Write for an audience of future Trinity College students who may wish to replicate your steps. Write in HTML format and always include links to data sources, like this example from CT Open Data. Also link to your shared Google Sheets when appropriate.

Give credit to people, organizations, resources, and tools that helped you to create this data story. Write in HTML format and include links when appropriate. When you paraphrase or quote from a specific reading, cite it using any standard academic citation style (such as MLA or APA inline citations), and include the full reference in a bibliography section at the end of your data story. For help with creating citations, I highly recommend the Zbib.org tool. Insert any URL, but you may need to click the Edit button to manually add missing details, such as author and date if the tool does not automatically recognize them, as shown in Image 1 and 2 below.

Image 1: After inserting a URL into the ZBib.org tool, you may need to click the Edit button to manually add missing details.

Image 2: Clicking the Edit button in ZBib allows you to enter or correct missing details, such as the full Website Title.

Below are sample sentences with MLA inline citations that would appear in the body of the data story, followed by the full references that would appear in the bibliography at the bottom:

Sample sentences

The City of Hartford recently created a housing code that requires the registration of the full names and contact information for all owners of apartment buildings -- including the officers of Limited Liability Corporations (LLCs) -- in order to "close municipal loopholes that allow anonymous slumlords to operate unchecked" (Lurye).

In most towns, the percentage of high-needs students enrolled in traditional public schools surpasses those enrolled in magnet, charter, and technical schools in the most recent academic year (“Resident Town Export”).

...later, insert a bibliography at the end of your data story:

Works Cited:

Lurye, Rebecca. “New Housing Code in Hartford Would Keep Slumlords from Hiding Behind LLCs.” Hartford Courant, May 31, 2019. https://www.courant.com/community/hartford/hc-news-hartford-housing-code-20190531-hcke2jo2x5fpdgz75xf4hlv2ki-story.html.

“Resident Town Export.” CT.Gov EdSight, https://public-edsight.ct.gov/Overview/Resident-Town-Dashboard/Resident-Town-Export. Accessed 29 Nov. 2022.

Optional Hint: To display a clickable web link in the bibliography, look at the HTML code in GitHub for the examples above. See how the URL appears twice: once in the "href" and again in the display text. This is not required for your data story, but it looks good and helps readers to click and view your sources.

Methods and Citations

All of your data visualizations should be interactive. But if you need to insert a static image, you can upload a JPG or PNG to the GitHub repo, and insert it using the HTML image tag ("img") that points to a source image ("src") stored in your repo, as shown below:

Figure 2: Describe your image in a caption, and always credit the source if someone else created it.

Optional Subheaders

Use subheader tags (such as "h4") to break up long sections of text without creating a new section.

Collaborate with Co-Author

Compose and edit your data story in Google Docs, where co-authors can work simultaneously. When you're ready to migrate to GitHub, create ONE data story template in ONE author's GitHub account, because only ONE person can edit at a time. But the GitHub account owner can go to Settings > Collaborators > Add People to invite a co-author by using their GitHub username, as shown below. But be careful not to overwrite each other's edits!

Change background colors

This template uses Bootstrap background colors. For example, search this "index.html" file for "bg-primary", which sets the navigation bar (line 28), header (line 56), and footer (around line 245) to blue. Changing it to "bg-secondary" switches those colors to gray. Learn about other color options at the link above.

Quicker Edits on your Local Computer

Instead of slowly making edits on GitHub and waiting for them to appear online, you can quickly make multiple edits in your local computer and view them instantly in your browser. Here's a list of steps:

Go to your GitHub repo and select Code > Download Zip and uncompress the folder.

Install a code editor tool. My favorite free open-source option is the open-source Pulsar text editor, but there are many other options.
Open the "index.html" file with your code editor and make edits.
In your browser, go to File > Open to view the "index.html" file that is on your local computer. Since this version is temporarily stored on your local computer, your browser bar will display its location in a local format "file..." rather than the online format "https..."

In your code editor, save changes to your "index.html" file, then refresh your browser to instantly view your changes made on your local computer.

After editing, upload the contents of "index.html" from your local computer to your online GitHub account, then view your edits the public web.

Two Options for Tables

If you need to create a table, first try the Datawrapper Tables tool -- see HODV Chapter 8 -- and embed the results like this:

Table 1: Add your standalone caption here.

A second option is to use the Tables Generator HTML tool. Go to File > Import or manually enter your table data, then Generate the HTML code, and paste it here, similar to this sample:

Header A	Header B	Header C
123	456	789
987	654	321

Table 2: Add your caption here.