Only a few of the major races on Milwaukee’s spring ballot were competitive. Most notably, the latest Milwaukee Public School District funding referendum passed by fewer than 2,000 votes. Both Biden and Trump put up relatively weak showings in their respective pro forma presidential preference votes. Evan Goyke handily won a landslide victory against the incumbent Milwaukee City Attorney.

The following discussion is based on complete, but unofficial, election night vote totals. All demographic data is from the 2020 census. Registered voter statistics are based on the number of registrants entering election day; they do not include same-day registrants.

MPS Referendum

The referendum received about 41,600 “yes” votes to 39,900 “no” votes. The No’s actually won more wards—172 to 164.

As the map below shows, support for the referendum was strongest in neighborhoods along the lake and on the near west side. Opposition was strongest on the far south and southwest sides. Most north and northwest side wards also voted against the referendum.

These patterns do somewhat follow Milwaukee’s racial divisions. The “Yes” vote won majority non-Hispanic white wards (53.2% for “Yes”) while narrowly losing both majority Black wards (48.4% “Yes”) and majority Latino wards (49.4% “Yes”).

But these differences are small. The presence of children in a ward correlates much more strongly with the referendum vote.

In wards where fewer than 20% of households include a child under 18, the “Yes” vote won by nearly two-thirds of the vote, 65.8%. But in places where more households have kids, it lost. In wards where 20% to 40% of households have a kid, 45.9% of voters supported the referendum. Where 40% to 60% of households have a kid, the “Yes” vote took 46.9%.

These are just correlations. We don’t have data on how parents themselves voted. But we can say that the MPS referendum was most popular in the parts of the city with the fewest children.

Presidential Preference

No candidate remained campaigning against Biden or Trump in their Wisconsin presidential primaries. Still, both candidates put up relatively weak showings.

Across the entire county, Trump received 73.2% from Republican primary voters. Nikki Haley’s defunct campaign still got 16.6%. In 2020 (with no other named candidates on the ballot), Trump won 97% support among Republican primary voters.

Biden received 84.5% of the vote, compared with 12.2% for uninstructed delegates, and 2.5% for Dean Phillips. The last primary featuring an incumbent Democratic president was 2012. In that year, Obama won 99.1% of the Milwaukee County vote, and uninstructed delegates received 0.7%.

The table below shows the primary results in each municipality.

A slim majority of voters participated in the Republican primary in Hales Corners and Franklin. Democrats were in the majority everywhere else.

Among Republican primary voters, Trump generally did best in the southern suburbs, garnering 80% or better in West Milwaukee, Oak Creek, Cudahy, and Hales Corners. Haley did best in the wealthier north shore suburbs, receiving 30% or better among GOP voters in Shorewood, Fox Point, Whitefish Bay, and River Hills.

Activists opposing Biden’s handling of the war in Gaza campaigned in support of the “uninstructed delegation” option in the Democratic primary. “Uninstructed” support varied between municipalities with the most support coming in two usually quite different places. Shorewood is the most Democratic municipality in the entire county, and 15% of its Democratic primary participants supported the uninstructed campaign. But “Uninstructed” support was even higher, 16%, in Franklin, one of the county’s most conservative suburbs. In general, uninstructed support was higher in the southern suburbs and lower on the north shore.

Within the city of Milwaukee, the uninstructed campaign generally performed best in the Riverwest neighborhood, with pockets of significant support scattered elsewhere in the city.

Milwaukee City Attorney

Evan Goyke won 63.3% of the vote, defeating Tearman Spencer in the race for City Attorney. He performed particularly well in the Washington Heights neighborhood and the neighborhoods along the lake. Spencer’s support was mainly limited to parts of the north side of the city.

Goyke carried 211 wards (to Spencer’s 124) and 10 of the city’s 15 aldermanic districts. Goyke won more than three quarters of the vote in the 3^rd, 14^th, 10^th, and 4^th districts.

Spencer’s best district was the 1^st, where he won two-thirds of the vote, followed by the 2^nd, where he won 63%.

Overall Turnout

Interpreting turnout is always challenging, because factors like the mix of elections on a ballot and the competitiveness of those races always vary from one election year to another. Turnout in April 2024 appears to have been middling, compared to recent past cycles.

• In 2020, about 210,000 voters, or 41% of registered voters, cast a ballot.
• April 2022 saw about 145,000 voters, or 29% of registered voters.
• This year, 165,000 voters participated, about 34% of those registered.

As a share of registered voters, turnout was highest on the north shore. The top-5 municipalities were Glendale, Greendale, Shorewood, Fox Point, and Bayside, among which turnout ranged from 42.1% to 45.4% of registered voters.

The lowest turnout came in West Milwaukee (22.6%), Cudahy (30.7%), West Allis (31.4%), and Milwaukee (31.6%).

Most landlords are small, but the largest 1% of networks own more than 40% of rental units.

By John Johnson and Mitchell Henke.

During the late 2010s, companies owned by a single landlord, Curtis Hoff, generated 5% of all evictions filed in Milwaukee despite owning just 0.5% of the rental stock. His properties racked up code violations at a rate three times that of other large landlord operating in the same parts of the city. The annual number of evictions they filed exceeded 90% of their total housing units.

Despite posting these eye-watering numbers, Hoff’s companies largely flew under the radar until a series of investigative articles in the early 2020s brought them to light, just as he was getting out of the business. That’s because Hoff’s properties were distributed among about 20 different limited liability corporations (LLCs), each of which was the official, legal owner of a different small set of properties.

It’s not that Hoff was trying to hide. Each of these companies began with the letter “A,” a practice dating back to the era when the courts heard each day’s eviction cases in alphabetical order. They all had their taxes mailed to the same address on Good Hope Road—an office building with a large “Anchor Properties” sign.

Still, if you searched the city’s property ownership dataset or the court system’s database, you would have no simple way of telling that all these properties were connected. And so, for years, few people figured it out. As the executive director of the Legal Aid Society of Milwaukee told the Journal Sentinel, “Maybe we’re not connecting the dots like we should be. Nobody’s able to officially track who the problem landlords are.”

To help address this, we’ve built MKEPropertyOwnership.com, a website that lets anyone quickly discover the connections between legal property owners that already exist in publicly available data. A user can simply enter the address of any landlord-owned property in the city, and the website will show that parcel’s official owner, the other owners connected to it, and the total list of properties in the “ownership network.” We also include network-level code violation and eviction annualized rates.

Our process works by standardizing owner names, the addresses at which they receive tax bills, and their corporate registration addresses. We then use network analysis software to identify connected owner names. More methodological details are available on the “About” page. All our data sources are public, and we publish the complete code and source data in this public repository. The data updates each weeknight with the latest version of the city’s property ownership database.

Curtis Hoff no longer owns any properties in Milwaukee, but here is what our website might have shown in 2019, if it had existed. Each green triangle shows a different owner name and each orange circle shows a tax bill address. The lines show the number of times each of the two nodes are connected.

Although Hoff is gone, practically all other large landlords also use multiple companies. For instance, Milwaukee’s largest landlord is Joe Berrada, well-known as the “boulder guy” for his unique style of landscaping. His companies own around 9,000 rental units spread across more than 800 parcels in the City of Milwaukee. Our website identifies over 100 distinct companies associated with Berrada, each of which individually own fewer than 300 units.

Research from many cities shows that landlord size corresponds to different rental practices. Large landlords are much more likely to file evictions. They may also raise rents more aggressively than small landlords. On the other hand, small landlords may employ more discriminatory tenant screening methods than larger, more professional companies. In any case, there is much variation between the behavior of large landlords. As with Curtis Hoff, a handful of companies can account for a greatly disproportionate of eviction cases, for instance. All this means that targeted interventions by housing advocates can be quite successful.

In Milwaukee, we identify about 49,000 landlord-owned parcels in the city containing around 148,000 housing units. This is comparable with the Census Bureau’s estimate of tenant-occupied and vacant housing units. There are about 21,500 distinct owner networks in the data. Of those networks, 15,500 (or 72%) own just a single property. Only about 130 ownership networks own more than 25 rental properties. Nonetheless, those 130-odd networks collectively own more than a fifth of the city’s rental units.

Put another way: the majority of landlords own just 1 or 2 rental units, but the typical tenant rents from a much larger landlord. Our data shows that 44% of rental units are owned by the largest 1% of landlord networks.

We hope this website will be useful to a wide variety of users, including government agencies, community organizations, prospective homebuyers, and tenants; and we are committed to maintaining and improving the project for the foreseeable future.

New apartment construction in American cities tends toward large buildings with small units, leaving fewer new options for households with more than 2 members.

Complaints abound about the lack of apartments suitable for a family with kids. In Milwaukee, I often hear questions like, “Who is going to live in these?” and “Where will families go?”

The truth is, even the robust growth of studio and 1-bedroom apartments has failed to meet the even more rapid rise in the number of these households. Over the past decade, the city of Milwaukee added around 9,300 1-person households versus about 2,200 new studio or 1-bedroom housing units.

Surely, not all these 1-person households will want to live in a small unit, but judging by current dwelling behavior, many clearly do. The growing gap between potential residents of small units and available inventory is larger than that for any other market segment.

Bigger buildings, smaller units

The next two graphs show annual construction statistics for the Midwest. In 2022, 63% of new apartment units came from buildings of at least 50 units, compared to just 21% in 2005. Apartment buildings with 2-4 units are hardly built anymore. They contributed just 1% of new apartments last year, down from 11% in 2005. Likewise, small apartment buildings with 5 to 9 units contributed 22% of new units in 2005 and just 4% in 2022.

As apartment buildings have grown larger, units have grown smaller by every measure. Seventy-eight percent of apartments built in 2005 contained at least 2 bedrooms, falling to 50% in 2022.

From 2000-2009, studio apartments made up about 1.5% of annual apartment construction. During the first three years of the 2020s, studios comprised 12.3% of new construction.

In 2005, 28% of new apartments were under 1,000 sq. ft. and 10% were 1,800 sq. ft. or larger. In 2022, 51% of new units were under 1,000 sq. ft. and just 2% were at least 1,800 sq. ft.

Growing demand for small units

Often, reasons for this dearth of “family-sized” apartments are given from the supply side. Zoning codes often make it hard to build the kinds of small apartment buildings that would fit in residential neighborhoods. Where room allows, bigger buildings are both more profitable. U.S. fire codes require large apartment buildings to be built around a central hallway. These “double-loaded” floor plans limit the number of multi-bedroom apartment units common elsewhere.

In cities like Milwaukee, there is also tremendous demand for small apartment units.

Even as Milwaukee’s population has fallen over the past 50 years, the number of households (or occupied housing units), has remained stable due to the growing number of people living by themselves.

Just over the past decade, the city added 9,300 1-person households and 1,500 2-person households, while losing 11,500 households with 3 or more members.

Milwaukee’s housing stock has, overall, not caught up to these changes.

Recent census estimates count about 87,000 single-member households in Milwaukee, compared with an available supply of 52,000 studio or 1-bedroom apartments.

In sharp contrast, Milwaukee holds 23,000 more 2-unit dwellings than 2-person households and 53,000 more 3-unit dwellings than 3-person households. Four-person households are closely matched to the number of 4-bedroom homes, and the number of households with 5 or more members (though shrinking) still outstrips the number of 5+ bedroom houses by about 16,000.

Of course, households do not match house sizes in the neat way those numbers suggest. Children in large families have always shared bedrooms and small households sometimes want more space. As I began writing this piece, I wondered if the relationship might run in reverse. Perhaps parents have less money to spend, and so wind up in smaller houses, while couples without children might be able to afford the largest houses.

As it turns out, this is not the case. Within the constraints of Milwaukee’s housing supply, people generally wind up choosing homes that closely match their household size.

The most common situation, involving 37% of households, is when the number of bedrooms exactly matches the number of residents. Another quarter of households have one extra bedroom. Fourteen percent have two extra bedrooms, and another 14% have 1 more person than they do bedrooms. Only 9% of households have at least two fewer bedrooms than people.

Forty percent of 1-person households live in either a studio or a 1-bedroom apartment. Another third live in a two-bedroom unit. The modal 2-person household lives in a 2-bedroom unit (41%), and just over half of 3-person households also live in a 3-bedroom home.

More of a mismatch exists for larger families, those with 4 or more members. Half of 4-member households live in a 3-bedroom house, a quarter have 4 or more bedrooms, and another quarter live somewhere with fewer than three.

Among households with 5 or more people, just 9% live in a house with 5 or more bedrooms, reflecting the lack of supply in this category. Large families are still the most likely group to live in one of these uncommonly large houses.

In a city like Milwaukee, with little available land for new construction, it comes as no surprise that most new construction is tailored to the only market segment with significant growth—adults without kids, usually living alone. Three-bedroom units abound, albeit primarily in aging housing stock.

The big challenge for builders and policymakers will be figuring out how to build enough smaller units that are appealing and affordable to the growing numbers single-member households. The large apartment buildings that dominate the current construction landscape are an important part of that. Milwaukee also needs to advance strategies like accessory dwelling units and corner quadplexes that accommodate shrinking household sizes in popular, already built-out residential neighborhoods.

Data Note

The Census Bureau does not publish a table counting households by members and bedrooms, so I computed this data from the most recent batch of census microdata. Due to limitations with the dataset, these statistics include Milwaukee County’s north shore suburbs.

Additional statistics are drawn from the 2017-21 American Community Survey, the 2008-12 ACS, decennial censuses from previous years, and the Survey on Construction.