The Reasons Behind Minnesota's National Property Tax Rankings

Our enhanced 50-State Property Tax Comparison Study now offers new perspective on and understanding about what drives Minnesota's effective property tax rates and rankings.

Ever since we published our first 50-State Property Tax Comparison Study over 20 years ago, we’ve cautioned readers that that the comparative property tax burdens and rankings each tax system generates are only part of a larger story.  Context matters, and any particular property tax ranking is best interpreted – perhaps even rationalized – by also understanding the framework and environment in which that property tax system operates.  How much of the responsibility for funding local services like K-12 education falls to the property tax?  Do local governments have viable options to the property tax – like a local sales or income tax – to finance their operations?

Answers to these and other questions can have a major impact on how one interprets the study’s rankings.  Now thanks to a collaborative effort with our partners at the Lincoln Institute of Land Policy, this study offers new perspective and understanding on the causes and reasons behind the rankings.

The “Fiscally Standardized City”

If you’re familiar with our 50-State Property Tax Study, you’ll notice differences in the newest edition – in a positive way.  We spent a great deal of time over the last eight months working with our partners at Lincoln to overhaul the report.  The result is evident with major upgrades in general readability and in how information is organized and presented.  But, the most notable change is a creative piece of research and analysis on why effective property tax rates (taxes as a share of a property’s value) differ between various locations.

Such an analysis was possible by matching our property tax work with an ongoing and groundbreaking research initiative at Lincoln: the “Fiscally Standardized Cities” (FiSC) database.

The challenge with making fiscal comparisons between cities is that public service delivery can be organized in very different ways in different cities.  While in some places city governments provide a wide array of public services for their residents and businesses, in other places a variety of overlapping governmental units (think counties, schools and special districts like the Three Rivers Park District) share responsibilities more equally.  Making fiscal comparisons using just city government data can thus be highly misleading, especially when looking across states.

The FiSC database accounts for these differences in how governments deliver services, making it possible to compare local government finances for 150 of the largest U.S. cities across more than 120 categories of revenues, expenditures, debt, and assets.  Lincoln constructs the FiSCs for each city by estimating the proportion of each overlying government unit’s revenues that city residents and businesses pay and the proportion of their spending that benefits city residents and businesses.  They then add those estimates to the city’s own revenues and spending.  Thus, FiSCs provide a full picture of revenues local governments raise within each city and spend on their residents’ and business’ behalf.

Our 50-State Property Tax Study includes 73 large U.S. cities that are also part of the Lincoln FiSC database.  Lincoln research staff performed a regression analysis and found that four factors explain about 75% of the variation in the effective property tax rates for median-valued homes among these cities (at very high levels of statistical significance).  Those factors are:

  • The degree to which local governments rely on property tax revenues
  • Business subsidization of homeowners’ taxes
  • Median home values
  • Total local government spending

Notably, Lincoln found that these same four factors explained a substantial amount of the variation in effective tax rates for all four property types in the study – homes, commercial, industrial, and apartments – in a statistically significant way.

Classification Benefits Offset by Higher Spending

A closer look at these findings yields some interesting insights into the relative influence these factors have on effective property tax rates in these 73 cities.

The effective tax rate on a median-valued home in Minneapolis in 2015 was 1.42%, which ranks 27th highest of these 73 cities.  The 3.35% tax rate on a $1 million-valued commercial property ranks the city 7th of 73.  The accompanying table shows how each of the four factors Lincoln identified is expected to change the effective tax rate in Minneapolis relative to a scenario where the city had the average value for that variable.  For example, local governments in Minneapolis had the 24th highest reliance on property taxation.  Based on the statistical modeling, this higher-than-average reliance on property taxation increases the effective tax rate on a median-valued home by 0.16 percentage points.  Another way to interpret the data: if Minneapolis’ local governments had just average property tax reliance and all other relevant tax and spending characteristics were unchanged, the effective tax rate on median-valued homes would be 0.16 percentage points lower, which at 1.26% would fall to 34th among the 73 cities.

The comparative influence of local spending and business subsidization of homeowner property taxes is particularly noteworthy.  Lincoln estimates that Minnesota’s higher-than-average business subsidization of homeowner taxes lowers Minneapolis homeowners’ effective property tax rates by about 0.14%.  Thus, if businesses provided only a national “average” level of subsidization, the owner of a median-valued home in Minneapolis would have a tax rate of about 1.56% – moving the rank of 27th up four spots to 23rd.

Table 1: Influence of Various Property Tax Factors on Effective Tax Rates

Interestingly, this classification just about offsets the higher property taxes that result from higher-than-average local government spending in the city.  In other words,  higher local government spending offsets most of the benefit a Minneapolis homeowner realizes from the state’s classification scheme.

The reverse is true for owners of business commercial property.  The 3.25% effective rate the owner of a $1 million commercial property pays ranks 7th in the nation.  That high ranking is influenced by both higher-than-average local government spending (a 0.15% bump) but also by the classification scheme (a 0.24% bump).  From a competitiveness standpoint, it’s a one-two punch.  Reducing the effective rate on commercial properties down to 2.86% would effectively put Minneapolis in a tie with Milwaukee, with the 10th highest rate.

Tax Prices Matter

A fundamental tenet of this organization is that accurate tax pricing is a cornerstone of good government.  It’s a key to ensuring that the levels of service that citizens demand of government are well matched with their desire to pay for them.  While federal and state aids and other mechanisms provide important assistance in addressing public policy needs and not every citizen is equally able to pay for government services, Minnesota’s tax system should not unduly insulate the majority of voters from financing government spending.

This is especially true for property taxes, where lawmakers’ desire to protect voters from the tax is as least as strong as the public’s hostility toward the tax itself.  But preferential tax treatment arrangements like classification can backfire by distorting local tax prices and increasing demand for public spending beyond what the public would otherwise be willing to support – eventually leading to higher property tax burdens for everyone.

Our Issue Brief on the Minnesota-related findings of the 50-State Property Tax Study provides more data to support this hypothesis.  As we have done for many years, the Issue Brief compares trends in property collections between states that subsidize homeowner property taxes and those that do not.  As Table 2 shows, between 1998 and 2013 property tax collections have grown more slowly per capita, and fallen twice as fast relative to income, in the ten states that offer little or no homeowner subsidy.1

Table 2: Property Tax Collections, FY 1998 and FY 2013, for States With No Homeowner Specific Assessment Limitations and With Classification Ratios < 1.05 and Remaining States

We don’t claim causality in these findings; lots of factors are obviously at play in this relationship.  However, we do not believe that these 15-year trends are mere coincidence either.  It makes fundamental sense (and academic research supports this idea) that greater homeowner sensitivity to property taxation would play a role in slowing overall property tax growth.

This highlights the political and fiscal problem for state lawmakers always so eager to protect citizens from the financial implications of their own local decisions.  Over time, local property taxpayers can become so desensitized to the actual tax cost of providing local services that even eminently reasonable and affordable increases in local property tax prices will seem excessive and unjustifiable.  Juxtaposing Voss report findings with ongoing complaints about property tax levels provides plenty of evidence of this phenomenon.  It’s something we urge policymakers to keep in mind when the next round of requests for more state spending on aids for local government inevitably come along.

  • 1 Those states being Delaware, Kentucky, New Jersey, Nebraska, New Hampshire, Nevada; North Carolina, Washington, Wisconsin, and Wyoming.