Proposition 33 Analysis: Who Supported Rent Control?

California's Proposition 33, which appeared on the November 5, 2024 ballot, proposed repealing the Costa-Hawkins Rental Housing Act of 1995 and prohibiting the state from limiting local governments' authority to enact rent control ordinances. This measure would have expanded cities' and counties' ability to implement rent control on various types of residential properties, including newer buildings, single-family homes, and condominiums.

Our analysis reveals several surprising insights about what drives rent control support in California. While partisan identity remains the strongest predictor (with Democrats strongly favoring and Republicans opposing), other factors play significant independent roles: housing tenure creates a stark renter/owner divide, younger voters (25-34) show much stronger support than older voters (55-64), and communities with more non-citizens and Spanish-speaking households demonstrate stronger support regardless of income levels.

Using comprehensive data from The Ballot Book, we analyzed voting patterns for this rent control initiative across hundreds of California cities. Specifically, our analysis includes data from all California cities with populations over 1,000, giving us a comprehensive view across communities of different sizes and regions. We examined hundreds of demographic, housing, voter registration, and economic characteristics in two ways:

1. First, we calculated correlations to see which individual factors most strongly relate to rent control support
2. Then, we ran a regression analysis to identify which factors remain important when all variables are considered together

This two-step approach helps us move beyond simple assumptions to uncover what genuinely shapes perspectives on housing policy.

The Correlation Findings: Individual Relationships

Our initial correlation analysis revealed several key factors that showed the strongest relationships with support for rent control in California communities. It's important to note that these correlations show statistical relationships but don't necessarily prove causation. They tell us which factors tend to appear together, not that one directly causes the other. These correlation values (ranging from -1 to +1) show the strength and direction of each individual relationship:

1. Housing Status Creates Clear Divides

While partisan divisions remain important (as we'll discuss shortly), housing tenure—whether people rent or own their homes—creates one of the most pronounced divides on rent control support. Communities with higher percentages of renters showed substantially stronger support for Proposition 33, with a correlation of 0.64. Conversely, communities with higher homeownership rates showed equally strong opposition (-0.64).

This stark division isn't surprising given the direct economic interests at stake, but the strength of this relationship confirms that housing status shapes perspectives on rent regulation even when controlling for other factors like income, education, and demographics. Renters see direct potential benefits from price controls, while homeowners may worry about property values or rental income impacts.

2. Party Registration Remains Fundamental

Partisan identity continues to be the strongest predictor of policy preferences, with Democratic registration showing the highest positive correlation (0.65) with Proposition 33 support, while Republican registration showed the strongest negative correlation (-0.68).

What's notable is how closely aligned partisan identity and housing policy preferences have become. The rent control divide tracks almost perfectly with partisan divisions, suggesting that housing policy has become deeply integrated into broader political worldviews about market intervention and government regulation.

3. Age Demographics Reveal Generational Divides

Our analysis uncovered significant generational differences in rent control perspectives. Communities with higher percentages of 25-34 year old voters showed much stronger support (0.63), while those with more 55-64 year old voters showed stronger opposition (-0.59).

This generational divide likely reflects different housing market experiences. Younger voters have entered housing markets during periods of rapidly escalating costs and may view intervention as necessary, while older voters experienced different market conditions during their formative years and may hold different perspectives on government regulation of housing.

4. Immigration and Citizenship Status Matter

Communities with higher percentages of non-citizens, particularly those from Latin America, showed significantly stronger support for rent control measures (correlations around 0.59-0.60). This suggests immigrant communities bring unique housing perspectives that translate into stronger support for price regulations.

Many immigrant households face particular housing challenges: higher housing cost burdens, larger household sizes, different access to credit markets, and potentially less familiarity with tenant protection laws. These circumstances appear to translate into stronger support for explicit price controls in the housing market.

5. Language and Household Composition Show Clear Patterns

Communities with more Spanish-speaking households showed stronger support for rent control (0.59), while those with predominantly English-only households showed stronger opposition (-0.57). Similarly, areas with higher percentages of married couples (particularly without children) showed significantly lower support.

These patterns suggest that housing policy preferences connect to broader lifestyle circumstances and family structures that shape economic priorities and perspectives on housing stability.

Economic Status: Complex and Nuanced Relationships

One of the most interesting findings is that high-income indicators actually showed weaker correlations with rent control opposition than many demographic factors. While households earning over $200,000 showed negative correlation with Proposition 33 support (-0.50), this relationship was less strong than factors like housing tenure, age, or party registration.

This suggests that perspectives on rent control aren't solely determined by income level or wealth. Instead, they appear more strongly connected to housing experiences, generational perspectives, and cultural factors that transcend simple economic status.

From Correlation to Causation: The Combined Analysis

So far, we've looked at individual correlations—how each factor relates to Proposition 33 support on its own. But what happens when we examine all these factors simultaneously? This is where our regression analysis becomes valuable.

Our statistical model combines all the top factors to determine which ones truly matter when everything is considered together. 

Most importantly, this analysis helps distinguish between factors that merely happen to correlate with rent control support versus those that have genuine independent influence. Several key findings emerge:

• Party registration maintains significant impact even when controlling for demographic and economic factors, confirming that political identity shapes housing policy views beyond simple self-interest

• Housing tenure (renter vs. owner status) remains a powerful predictor regardless of income, age, or political affiliation—the experience of renting versus owning creates fundamentally different perspectives

• Age demographics (particularly the 25-34 and 55-64 cohorts) continue to show strong independent effects, suggesting different generational experiences with housing markets create lasting attitude differences

• Immigration status contributes uniquely to the model, indicating that immigrant communities bring distinctive housing perspectives regardless of income or other factors

The Bigger Picture: Housing Policy and Identity

These findings reveal how deeply housing policy preferences have become intertwined with broader political and social identities. Support for rent control doesn't simply reflect economic self-interest—it connects to generational experiences, immigration journeys, family structures, and partisan worldviews.

For political professionals, these insights offer important strategic considerations:

1. Beyond economic messaging: Communications about rent control that focus solely on economic impacts may miss the identity-based and experiential factors that shape perspectives.

2. Demographic targeting: The strong correlations with specific demographic groups (younger voters, renters, immigrant communities) provide clear guidance for outreach efforts.

3. Bridging divides: The pronounced polarization on this issue suggests that persuasion efforts might most effectively focus on connecting rent control to shared values rather than technical policy details.

4. Geographic implications: These demographic correlations translate into clear geographic patterns of support and opposition across California's diverse communities.

This analysis was conducted using data from The Ballot Book, California's most comprehensive political data platform. By integrating election results, demographic data, and analytics for over 1,500 jurisdictions, The Ballot Book enables nuanced analysis of voting behavior that reveals insights beyond traditional political divisions.