Comparing Minnesota s Prices of Local Government

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1 Comparing Minnesota s Prices of Local Government Executive Summary Where in Minnesota is local government s claim on the economy and the income of local citizens the greatest? How does local government s fiscal footprint differ across the state? And how does the ability to export local tax burden to non-residents affect this footprint? In this Issue Brief we examine Minnesota s Price of Local Government. Based on most recently available data (2012/2013) we replicate the methodology employed by the Minnesota Department of Management and Budget in assembling the state s Price of Government Report and apply it at the county level to derive a Price of Local Government (or POLG ) for all 87 Minnesota counties. We also examine four other alternative Price of Local Government measures based on modifications to the POLG numerator and denominator: a per capita POLG analysis which reflects dollar burdens imposed for local benefits delivered; a money income POLG analysis which captures local governments claim on earnings that local residents can actually use to pay taxes and fees; a POLG estimate net of local tax exporting to non-residents; and a local effort property tax POLG. The Price of Local Government across Minnesota depends heavily on the lens through which one views this topic. Not only do individual Prices of Local Government change often dramatically depending on the measure used, regional patterns are also affected. When looking at total own source local revenues as a percent of local personal income, POLGs are generally highest in the northern and northeast areas of the state. Switching to a per capita basis changes the landscape and shifts some of the largest burdens to both the most populous and least populous areas of the state. When analyzed based on money income earnings that local residents can actually use to pay local taxes and fees the POLG commonly increases 15-25% around the state. However, in several counties money income POLG jumps substantially higher, likely reflecting more challenging demographics in those areas; and increases more modestly in other counties reflecting their strong wage, salary, and related income bases. The ability of local governments to export some types of local taxes to non-residents has a major impact on reducing the POLG primarily in northern Minnesota. When defining POLG based solely on the property tax effort of local residents and businesses, there is substantially more uniformity across Minnesota than with any other POLG measure with concentrations of below average POLG primarily in the western part of the state. We conclude that local price of government metrics offer some potential as a benchmarking tool. Peer counties of similar demographic, economic, and geographic characteristics but lower POLG metrics suggest some areas of the state are able to support local services at lower cost. In seeking service delivery strategies and designs that offer opportunities to improve cost efficiencies, POLG offers one avenue for beginning these investigations. 1 info@fiscalexcellence.org

2 INTRODUCTION Where in Minnesota is local government s claim on the economy and the income of local citizens the greatest? How do local governments fiscal footprints differ across the state? And how does the ability to export local tax burden to non-county residents affect this footprint? From all indications, the 2015 legislative session will feature policy agendas likely to be influenced as much by geography as political party and accompanied by debates about equity, fairness and the appropriate role of the state in supporting local government. Policymakers would likely find answers to the questions above highly relevant to their task this year. In this Issue Brief we examine the Price of Local Government across Minnesota. The Minnesota Price of Government (POG) report, prepared and published by Minnesota Management and Budget (MMB), is a familiar talking point in discussing the cost Minnesota s state and local governments collectively impose on the state s economy and its citizenry. MMB calculates the statewide POG by taking the sum of all state and local government own source revenues 1 and dividing that total by total state personal income as calculated by the federal Bureau of Economic Analysis (BEA) to derive a measure of government s claim on the state s economic activity. We replicate this methodology at the county level calculating the ratio of total local own source revenues collected in the county to personal income in the county to derive a Price of Local Government (or POLG ) for all 87 Minnesota counties. In this brief we also calculate and report several alternative POLG measures. Readers of our publications are aware that we have expressed reservations about the use of and reliance on a single POG metric to measure relative government cost and affordability. 2 We have argued that a dashboard of metrics offers superior transparency and a more complete perspective on governments fiscal footprint. Towards this end, we also calculate and report on four complementary Minnesota POLG measures: a per capita POLG analysis to capture local burdens imposed for local benefits delivered; a money income POLG analysis to assess ability to pay and affordability issues stemming from local governments claims on local residents; a POLG estimate net of local tax exporting to non-county residents; and a local effort property tax POLG We end with some summary thoughts and conclusions based on our findings. METHODOLOGY We gathered data from the following sources to calculate our various POLG amounts: 2012 city, township and county governmental fund revenue data from the Office of the State Auditor school district property tax levies from the University of Minnesota s Minnesota Land Economics (MLE) program 4 Other school district general fund revenues from the Minnesota Department of Education Metropolitan Council s finances from its 2013 consolidated annual financial report personal income by county from the federal Bureau of Economic Analysis 7 1 Own source revenues: all state and local revenues less intergovernmental revenues grants from one unit of government to another, such as state Local Government Aid given to cities. 2 See Indicator or Dashboard: Redesigning the Minnesota Price of Government from the September-October 2014 edition of our Fiscal Focus newsletter, available at ; information provided upon request. 5 See Financial Profile data at info@fiscalexcellence.org

3 Property taxes paid by class, by county, Minnesota Department of Revenue Property Tax Division (by request) Some cities and school districts, along with the Metropolitan Council, are located in multiple counties. In these cases, we allocated the jurisdiction s property tax and special assessment revenues to counties based on net tax capacity shares because these revenues have a strong relationship to property values. We allocated all other revenues, such as licenses and permits or charges for services, based on population shares. For such schools, the data provided by MLE allowed us to allocate the tax levies to the appropriate counties. We allocated all other school revenues based on net tax capacity because school district population, by county, was not immediately available. For the Metropolitan Council, we allocated property taxes by net tax capacity and all other revenues by population. Like the statewide Price of Government metric, our analysis includes only own-source revenues those revenues raised by local governments themselves. Where the state s POG metric leaves out federal grants to state and local governments; our analysis leaves out both federal and state grants to local governments. This provides an accurate estimation of the burdens actually imposed by local governments. The analysis excludes special districts 8 except for the Metropolitan Council because time and effort needed to collect financial data for each of these small government units was prohibitive. Our analysis also excludes enterprises operated by local governments including but not limited to golf courses, liquor stores and municipal utilities. These ventures are not part of the standard suite of local government services. 7 See Local Area Personal Income and Employment tables at 8 Example of special districts include park districts, housing and redevelopment districts, and watershed districts. 3 info@fiscalexcellence.org

4 PERSPECTIVE #1: TRADITIONAL POLG (Total Own Source Revenues Collected in County / County Personal Income) Figure 1 shows the POLG for each of Minnesota s 87 counties in 2012 using the traditional personal income statistic to measure local governments claim on economic activity (which is what personal income measures). The figure highlights the considerable variation in the burdens local governments across the state impose. These burdens range from a minimum of % of personal income in McLeod County to a high of 7.0% in Cook County. The median and mean statewide POLG are identical, suggesting a normal distribution of POLG burdens across the state. Figure 1: Price of Local Government, 2012, by County Kittson Norman Clay Marshall 5.5 Pennington Red Lake Polk Roseau Lake of the Woods 6.3 Mahnomen 6.2 Becker Wilkin Otter Tail Traverse Big Stone Lac Qui Parle 3.2 Lincoln Pipestone Rock Grant Stevens Yellow Medicine Lyon Murray Nobles Swift Douglas Pope Chippewa Clearwater 5.8 Redwood Beltrami Hubbard 5.5 Wadena Todd Kandiyohi Cottonwood 4.8 Jackson Renville Stearns Meeker Brown Watonwan Martin Cass Crow Wing 5.4 Morrison McLeod Koochiching 4.8 Itasca 5.9 Mille Lacs Benton Sherburne Wright Sibley Nicollet Blue Earth Faribault 3.5 Carver Le Sueur Aitkin 5.6 Kanabec Isanti 3.5 Anoka Hennepin Scott Waseca Rice Freeborn Dakota Steele Carlton Pine Chisago St. Louis Goodhue Wabasha Dodge Mower Olmsted Ramsey Washington Fillmore Winona 3.1 Lake Houston Cook 7.0 >25% below state average 10% - 25% below state average Within 10% of state average 10% - 25% above state average >25% above state average Average: 0% Median: 0% St. Dev. ±0.73% As the map illustrates, there are some regional patterns in the Price of Local Government. All 9 counties where the PLOG exceeds the state average by 25% are in located in northern Minnesota. On the other hand, many counties along the western- and southern-most strips of the state have well below average Prices of Local Government. The seven-county Twin Cities area shows noticeable diversity. Carver, Dakota and Washington Counties are considerably below the statewide average; Anoka, Hennepin and Scott Counties are near the statewide average; and Ramsey County is above average. 4 info@fiscalexcellence.org

5 PERSPECTIVE #2: PER CAPITA POLG (Total Own Source Revenues Collected in County / County Population) Looking at the Price of Local Government on a per capita basis shifts the perspective from claim on the economy to size of dollar burdens that local governments collectively impose to fund their local services. Since local governments collect significant revenues from businesses, a per capita analysis does not indicate the actual burdens directly imposed on residents. However, this perspective does communicate a sense of the relative effort residents are making, on a dollar-basis, for local government services. Figure 2 shows the POLGs for 2012 on a per capita basis. These burdens range from a minimum of $1,175 per person in Winona and McLeod Counties to a high of $3,158 in Cook County. Despite this large differential between the two ends of the spectrum, half of Minnesota s counties have per capita POLGs within 10% of the statewide average of $1,973 per person. Figure 2: 2012 Price of Local Government, by County, Per Capita Basis 2,153 1,896 1,792 Kittson 2,235 Marshall 2,689 Pennington 1,886 Red Lake 1,857 Polk 1,906 Norman 1,719 Clay 1,421 Roseau 1,479 Mahnomen 2,020 Becker 1,674 Wilkin 2,247 Otter Tail 1,598 Grant Traverse 2,401 2,948 Stevens Big Stone Lac Qui Parle 1,872 Lincoln 2,373 Pipestone Rock 1,923 1,955 Yellow Medicine Lyon 1,809 Murray 1,922 Nobles 1,615 Swift 2,450 Douglas 2,051 Pope 1,849 Chippewa 2,017 Clear- Water 1,860 Redwood 1,859 Lake of the Woods 2,163 Beltrami 1,298 Hubbard 1,861 Wadena 1,529 Todd 1,324 Kandiyohi 2,051 Cottonwood 2,320 Jackson 2,512 Renville 2,244 Stearns 1,594 Meeker 1,703 Brown 1,722 Watonwan 1,769 Martin 2,273 Cass 1,947 Crow Wing 1,898 Morrison 1,436 McLeod 1,175 Koochiching 1,735 Benton 1,572 Wright 1,795 Sibley 2,066 Nicollet 1,507 Blue Earth 1,621 Itasca 2,060 Mille Lacs 1,357 Sherburne 1,743 Faribault 1,966 Aitkin 1,906 Kanabec 1,511 Isanti 1,334 Anoka 1,664 Hennepin Carver 2,545 2,198 Scott 1,894 Le Sueur 1,863 Waseca 1,674 Rice 1,436 Steele 1,653 Freeborn 1,783 Dakota 1,820 Carlton 1,491 Pine 1,353 Chisago St. Louis 1,826 Goodhue 2,094 Wabasha Dodge 1,647 Mower 1,454 Olmsted 1,889 Ramsey 2,163 1,660 Washington 1,871 Fillmore 1,647 Winona 1,175 Lake 2,218 Houston 1,697 1,657 Cook 3,158 >25% below state average 10% - 25% below state average Within 10% of state average 10% - 25% above state average >25% above state average Average: $1,973 Median: $1,857 St. Dev. ±$365 At first glance, it is difficult to discern any particular geographical pattern or demographic theme. But closer examination reveals some interesting findings regarding the relationship between the per capita price of local government and urban status. For starters, it is particularly striking that the highest per capita 5 info@fiscalexcellence.org

6 prices of local government occur at the opposite ends of the population spectrum Hennepin County (1.2 million people) and Traverse County (3,451 people). Looking more closely at the relationship between population and POLG, we grouped Minnesota counties by urban status. The federal Office of Management and Budget (OMB) defines two types of urban areas: Metropolitan Statistical Areas: groups of counties with at least one urbanized area of 50,000 or more and neighboring counties with a high degree of social and economic integration as measured by commuting ties Micropolitan Statistical Areas: counties with at least 10,000 in urban population and may also include adjacent counties with strong commuting ties According to the OMB, 27 counties in Minnesota are included in eight different metropolitan statistical areas (note that such areas often cross state borders). 9 Minnesota also has sixteen micropolitan statistical areas that include seventeen counties. 10 The remaining 43 counties are predominantly rural in nature neither metropolitan nor micropolitan. Table 1 summarizes per capita POLG based on this urban classification with the predominantly rural counties grouped together in the Other Counties category. While Minnesota s most urban counties had a combined average per capita POLG that was 3.3% above the statewide average, predominantly rural counties had a combined average per capita POLG that was 5.6% below the statewide average and micropolitan counties largely non-metropolitan regional centers were 15.8% below the statewide average. Table 1: Average Per Capita POLG, 2012, for Metropolitan, Micropolitan, and Other Counties Urban Status of County Average Per Above (Below) Capita POLG State Average Metropolitan Statistical Area (n=27) $2, % Micropolitan Statistical Area (n=17) $1,661 (15.8%) Other (n=43) $1,863 (5.6%) These per capita findings also suggest the possibility of an optimum population density in the delivery of local services. Three of Minnesota s seven most sparsely populated counties have per capita POLGs that are 25% or more above the state average. When looking only at counties with a population density of 80 people or less per square mile (Figure 3 on the next page), there is a inverse correlation between population density and per capita POLG. As density decreases, POLG goes up. 9 As of 2012 Minnesota s metropolitan counties were: Carlton and St. Louis (Duluth MSA); Clay (Fargo MSA); Polk (Grand Forks MSA); Houston (La Crosse-Onalaska MSA); Blue Earth and Nicollet (Mankato-North Mankato MSA); Anoka, Carver, Chisago, Dakota, Hennepin, Isanti, Le Sueur, Mille Lacs, Ramsey, Scott, Sherburne, Sibley, Washington and Wright (Minneapolis-St. Paul-Bloomington MSA); Dodge, Fillmore, Olmsted and Wabasha (Rochester MSA); and Benton and Stearns (St. Cloud MSA). 10 As of 2012 Minnesota s micropolitan counties were: Beltrami, Brown, Cass, Crow Wing, Douglas, Freeborn, Goodhue, Kandiyohi, Lyon, McLeod, Mower, Nobles, Otter Tail, Rice, Steele, Wilkin, and Winona. 6 info@fiscalexcellence.org

7 Figure 3: 2012 Price of Local Government, Per Capita Basis, Relative to Population Density; Counties with 80 People per Square Mile or Fewer People per Square Mile R² = ,000 1,500 2,000 2,500 3,000 3,500 POLG per Capita However, when looking only at counties exceeding 80 people per square mile the relationship between population density and per capita POLG is reversed now greater density is correlated with higher POLG (Figure 4). There are undoubtedly many contributing factors to this complicated relationship, but these results do seem to support an idea found in public finance studies: that there are also potential diseconomies of scale in the provision of public services because higher population densities can create a harsher and more challenging service environment, leading to higher per unit costs. Figure 4: 2012 Price of Local Government, Per Capita Basis, Relative to Population Density; Counties with More Than 80 People per Square Mile People per Square Mile 3, , , , , , R² = ,000 1,500 2,000 2,500 3,000 POLG per Capita 7 info@fiscalexcellence.org

8 PERSPECTIVE #3: POLG BASED ON MONEY INCOME (Total Own Source Revenues Collected in County / County Money Income) The BEA s personal income statistic includes several items that represent economic activity but can t be used to pay taxes primarily employers contributions for pensions and insurance benefits, imputed rental and imputed interest income, government transfer payments to nonprofit institutions, and the value of government-sponsored medical benefits (largely Medicare and Medicaid). 11 A measure that evaluates governments claims against a more limited money income measure the actual income people use to pay local taxes and fees offers a better perspective on the affordability of local government. Our money income metric modifies BEA personal income in two ways. First, we remove these five noncash items from the income totals. BEA provides county-specific information for three of them: employers contributions for pensions and insurance benefits, government transfer payments to nonprofits and the value of government-sponsored medical benefits. For imputed rental and imputed interest income, we assume that each county has such income in proportion to its overall share of statewide dividends, interest and rent the income category in which these revenue streams are located and reduced county income totals accordingly. Second, we add capital gains income, which is not included in BEA personal income, into our calculations of money income. Figure 5 on the next page presents our POLG findings on a money income basis. Unsurprisingly, the primary effect of defining the POLG by money income is that every county s POLG increases generally by about 15% to 25%. The exclusion of non-cash income from the denominator (which on a statewide basis amounts to around 20% of total personal income) more than offsets the inclusion of capital gains income. The state POLG average based on money income is 5.1% ranging from a high of 9.3% in Cook County to a low of % in McLeod County. However, a comparison with Figure 1 shows that the impact of switching the analysis from a personal income to a money income perspective differs across the state. In eleven counties (led by Mahnomen, Wadena, and Koochiching), this switch increases the POLG in excess of 30%, suggesting a larger proportion of personal income is in these non-cash income streams. Conversely, the POLG is least affected in counties where wage income comprises a large share of the personal income base. Carver, Washington, Scott, Wright, and Dodge Counties are those least affected by this switch. 11 For far more on the issue of money income vs. personal income, see our Issue Brief Minnesota s Troubled Price of Government, available at 8 info@fiscalexcellence.org

9 Figure 5: Price of Local Government, 2012, by County, Money Income Basis 5.2 Kittson 5.3 Norman Clay Marshall 6.4 Pennington 4.8 Red Lake 5.7 Polk 5.4 Roseau Lake of the Woods 7.9 Mahnomen 9.0 Becker 5.2 Wilkin 5.1 Otter Tail Traverse 5.4 Big Stone Lac Qui Parle Lincoln 6.0 Pipestone Rock Grant 5.4 Stevens Yellow Medicine Lyon Murray Nobles Swift 6.2 Douglas 6.3 Pope Chippewa Clearwater 7.7 Redwood Beltrami 5.3 Hubbard 7.0 Wadena 6.6 Todd Kandiyohi 5.5 Cottonwood 5.9 Jackson Renville 5.1 Stearns 5.2 Meeker 5.2 Brown Watonwan Martin 5.6 Cass 6.3 Crow Wing 7.1 Morrison McLeod Koochiching 6.5 Itasca 7.6 Mille Lacs 5.8 Benton 5.1 Sherburne 5.7 Wright 5.3 Sibley 5.5 Nicollet Blue Earth 5.1 Faribault Carver Le Sueur 5.4 Aitkin 7.4 Kanabec 5.8 Isanti Anoka Hennepin 5.2 Scott Waseca Rice Freeborn 5.3 Dakota Steele 4.8 Carlton 5.9 Pine 5.7 Chisago St. Louis 5.9 Goodhue 5.7 Wabasha Dodge Mower Olmsted Ramsey Washington Fillmore Winona Lake 6.4 Houston Cook 9.3 >25% below state average 10% - 25% below state average Within 10% of state average 10% - 25% above state average >25% above state average Average: 6% Median: 5.11% St. Dev. ±1.08% PERSPECTIVE #4: ESTIMATED POLG NET OF TAX EXPORTING (Total Own Source Revenues Collected in County Less Shares of Cabin, Local Sales, and Local Lodging Taxes / Personal Income) The price of government communicates a consumer perspective: what the cost of government services is for local residents. The focus on the revenues local governments themselves collect distinguishes the Price of Local Government from the much larger Cost of Local Government that would be measured if federal and state support for local government services were added to the analysis. But even after removing intergovernmental aids, assembling a price of local government how much do residents and businesses themselves pay to their local governments? is complicated by the issue of tax exporting. Local governments can readily export three taxes directly to non-county residents: cabin taxes (billed directly to owners who live elsewhere), lodging taxes (billed directly to hotel/motel guests who visit an area), and local sales taxes (billed directly on sales to out-of-town purchasers). Table 1 on the next page shows the share of these three taxes in each county to its total own source revenues. As the table illustrates, although the statewide average is % the ability of local governments to export tax burdens varies 9 info@fiscalexcellence.org

10 significantly around the state. In 39 counties these three revenue streams are less than 1% of total ownsource revenues while in 15 counties they represent over 10% of own-source revenues. Table 1: Total Cabin Property, Local Sales Tax, and Local Lodging Taxes Relative to All Own- Source Revenues, by County, 2012 Rank County Amount Rank County Amount Rank County Amount 1 Cook 41.6% 31 Polk % 61 Waseca 0.3% 2 Cass 32.0% 32 Brown % 62 Washington 0.3% 3 Crow Wing 25.6% 33 Murray 2.7% 63 Winona 0.3% 4 Aitkin 2% 34 Benton 2.7% 64 Pipestone 0.2% 5 Hubbard 2% 35 Wadena % 65 Watonwan 0.2% 6 Otter Tail 19.7% 36 Clearwater % 66 Scott 0.2% 7 Lake 18.7% 37 Wabasha % 67 Chippewa 0.2% 8 Becker 17.7% 38 Mower % 68 Swift 0.2% 9 Lake of the Woods 1% 39 Wright 2.3% 69 Marshall 0.2% 10 Douglas 1% 40 Nobles % 70 Martin 0.2% 11 Todd 11.4% 41 Traverse 1.8% 71 Faribault 0.2% 12 Pine 11.3% 42 Isanti 1.8% 72 Redwood 0.1% 13 St. Louis 11.0% 43 Ramsey 1.7% 73 Carver 0.1% 14 Pope 10.7% 44 Chisago 1.6% 74 Anoka 0.1% 15 Mille Lacs 10.7% 45 Roseau 1.5% 75 Clay 0.1% 16 Itasca 9.6% 46 Lincoln 1.4% 76 Cottonwood 0.1% 17 Kandiyohi 7.9% 47 Nicollet 1.3% 77 Renville 0.1% 18 Morrison 6.9% 48 Sherburne 1.1% 78 Dakota 0.1% 19 Mahnomen 6.1% 49 Fillmore 0.8% 79 Norman 0.1% 20 Beltrami 5.7% 50 Houston 0.8% 80 Yellow Medicine 0.1% 21 Stearns 5.4% 51 Blue Earth 0.7% 81 Lac Qui Parle <0.1% 22 Olmsted 5.1% 52 Rice 0.6% 82 Sibley <0.1% 23 Kanabec % 53 Goodhue 0.6% 83 Pennington <0.1% 24 Koochiching % 54 Steele 0.5% 84 Red Lake <0.1% 25 Meeker % 55 Jackson 0.5% 85 Wilkin <0.1% 26 Big Stone % 56 Stevens 0.4% 86 Rock <0.1% 27 Hennepin % 57 Kittson 0.4% 87 Dodge Grant % 58 McLeod 0.3% Statewide Average % 29 LeSueur 3.3% 59 Lyon 0.3% 30 Carlton 3.2% 60 Freeborn 0.3% It is not possible to determine the precise share of these taxes paid by county residents versus non-county residents. Our estimate of the POLG net of local tax exporting is based on the following assumptions: Local sales taxes According to the Department of Revenue s Tax Incidence Study 12 approximately 20% of local sales taxes are paid by out of state residents. We assume that an additional 10% of local sales taxes are paid by Minnesota residents who are not residents of the county in which the purchase was made info@fiscalexcellence.org

11 Cabin property taxes According to the Tax Incidence Study, out-of-state residents directly pay about 20% of the local property taxes imposed on cabins. In addition, a significant share of cabin property taxes are paid by Minnesotans who are not residents of the county in which the cabins are located. Based on communication with county assessors, our estimate assumes that 80% of total local cabin property taxes are exported to non-county residents. Local lodging taxes Given the nature of lodging, we assume 90% of local lodging taxes are paid by individuals who are not residents of the county. Figure 6 presents findings based on these assumptions. From a statewide perspective local tax exporting has seemingly little impact there is little color shifting among counties compared to Figure 1, and the average statewide POLG after exporting declines only modestly, from 0% to 0%. However, a closer look at the values shows that for some counties especially in the northern part of the state heavily Figure 6: 2012 Price of Local Government, by County, Personal Income Basis, After Exporting Cabin Property, Local Sales, and Local Lodging Taxes Kittson Norman Clay Marshall 5.5 Pennington Red Lake Polk Roseau Lake of the Woods 5.6 Mahnomen 5.9 Becker Wilkin Otter Tail Traverse Big Stone Lac Qui Parle 3.2 Lincoln 4.8 Pipestone Rock Grant Stevens Yellow Medicine Lyon Murray 3.3 Nobles Swift Douglas Pope 3.3 Chippewa Clearwater 5.7 Redwood Beltrami Hubbard Wadena Todd Kandiyohi Cottonwood 4.8 Jackson Renville Stearns Meeker Brown Watonwan Martin Cass Crow Wing Morrison McLeod Koochiching Itasca 5.4 Mille Lacs Benton Sherburne Wright Sibley Nicollet Blue Earth Faribault 3.5 Carver Le Sueur Aitkin Kanabec Isanti Anoka Hennepin Scott Waseca Rice Freeborn Dakota Steele Carlton Pine Chisago St. Louis Goodhue Wabasha Dodge Mower Olmsted Ramsey Washington Fillmore Winona 3.1 Lake Houston Cook >25% below state average 10% - 25% below state average Within 10% of state average 10% - 25% above state average >25% above state average Average: 0% Median: 9% St. Dev. ±0.59% dependent on cabin property taxes and/or tourism for their own source revenues the ability to export local taxes brings the POLG much closer to state average. The prime example is Cook County, where tax exporting capabilities reduce the POLG by almost 30%, from 7.0% to % of personal income. 11 info@fiscalexcellence.org

12 PERSPECTIVE #5: LOCAL EFFORT PROPERTY TAX PRICE OF LOCAL GOVERNMENT (Business, Residential, and Local Share of Cabin Property Taxes / Personal Income) As decades of tax policy debates in Minnesota have shown, perceptions about the price and affordability of local government hinge on levels of property taxation. Despite the fact that property taxes routinely pay far less than half of total local government costs, local property tax prices are essentially synonymous with the price of local government in the eyes of most citizens. Our final POLG perspective considers the relationship between property taxes paid by individuals and businesses resident in the county and county personal income. It includes all property taxes paid within the county, except for the 80% of cabin taxes we assume are exported to non-county residents per our previous discussion. Figure 7 presents the findings. The average county-level property tax burden relative to personal income is 2% with significant clustering around that average. 46 counties are within 10% of the average burden and only six counties have property tax burdens that are more than 25% away from it. Figure 7: 2012 Local Effort Property Tax Price of Local Government, by County, Relative to Personal Income 2.3 Kittson Norman Clay Marshall Pennington 2.0 Red Lake Polk Roseau 2.1 Lake of the Woods 3.5 Mahnomen 3.3 Becker 2.3 Wilkin Otter Tail 2.3 Traverse 3.1 Big Stone Lac Qui Parle Lincoln 3.1 Pipestone Rock 2.4 Grant 3.1 Stevens Yellow Medicine Lyon Murray 2.4 Nobles Swift 3.3 Douglas 3.0 Pope 2.3 Chippewa Clearwater 3.3 Redwood Beltrami Hubbard Wadena Todd Kandiyohi Cottonwood 2.7 Jackson Renville 3.0 Stearns Meeker Brown 2.4 Watonwan Martin 3.2 Cass Crow Wing 3.0 Morrison McLeod 1.9 Koochiching 1.8 Itasca 3.2 Mille Lacs Benton Sherburne 3.5 Wright 3.1 Sibley 3.1 Nicollet Blue Earth Faribault Carver Le Sueur Aitkin Kanabec Isanti Anoka Hennepin 3.0 Scott Waseca Rice Freeborn 3.0 Dakota Steele 2.7 Carlton 3.0 Pine Chisago St. Louis 2.7 Goodhue 3.5 Wabasha Dodge Mower Olmsted 2.7 Ramsey 3.0 Washington Fillmore Winona Lake 2.7 Houston 2.7 Cook 2.0 >25% below state average 10% - 25% below state average Within 10% of state average 10% - 25% above state average >25% above state average Average: 2% Median: 2.75% St. Dev. ±0.39% 12 info@fiscalexcellence.org

13 The local voter property tax price of local government perspective has by far the biggest transformational impact on the POLG map. Many areas of the state that were consistently highest in the earlier POLG metrics are now near or even below state average levels. In many respects, the findings presented in Figure 7 mirror those reported by the Department of Revenue in their annual Residential Homestead Property Tax Burden (Voss) Report, perhaps not surprising since residential taxes are more than half of all local property taxes imposed statewide. Table 2 presents a regional summary of our findings based on urban status. Table 2: 2012 Prices of Local Government, Summarized by Urban Status or Region Metropolitan Statistical Area Personal Income Basis Per Capita Basis Price of Local Government Measure Money Net of Local Income Tax Exporting* Basis Local Effort Property Taxes* Duluth 6% $1, % 8% 2.70% Fargo-Moorhead 9% $1,421 4% 8% 4% Grand Forks 7% $1, % 7% 4% La Crosse-Onalaska 7% $1,697 3% 4% 2.78% Mankato-North Mankato 5% $1, % 3% 8% Minneapolis-Saint Paul- Bloomington 9% $2,123 7% 4% 0% Rochester 7% $1, % 9% 2.74% Saint Cloud 1% $1, % 0% 7% All Metropolitan Statistical Areas All Micropolitan Statistical Areas 9% $2,039 0% 2% 7% 4% $1, % 8% 0% Remainder of State 8% $1, % 6% 8% * Personal Income Basis 13 info@fiscalexcellence.org

14 SUMMARY AND CONCLUSIONS The Price of Local Government in Minnesota depends heavily on the lens through which one views and defines this metric. Total own-source local revenues relative to local personal income are generally highest in the northern and northcentral areas of the state. Switching to a per capita basis changes the landscape and shifts some of the largest burdens to both the most populous and least populous areas of the state. When analyzed based on money income earnings that can actually be used to pay local taxes and fees the POLG jumps substantially in several counties, likely reflecting demographic stresses; but increases more modestly in other counties, reflecting their stronger wage, salary, and related income bases. If we define the POLG as own-source revenues less estimated exported local taxes, there is little change in the measure on a statewide basis but some counties, especially in northern Minnesota, see major reductions. When defining POLG based solely on the property tax effort of local residents and businesses, there is substantially more uniformity across the state than with any other POLG measure with concentrations of below average POLG primarily in western Minnesota. We conclude that although Minnesota s current state/local government finance system is not intentionally designed to equalize local effort property tax burden relative to personal income, the combined net effect of intergovernmental aids, the use of alternative own source revenues and the ability to export certain burdens to non-residents does a rather respectable job in delivering that outcome. Although variations in local property tax effort POLG clearly exist across Minnesota, over two-thirds of counties representing 87% of the state s population and 89% of statewide personal income have aggregate local voter property tax prices as a percent of personal income within 15% of the state average. Moreover, four of the eight counties that are 15% or more above the state average have very high shares of property taxes coming from utilities including the three with the highest shares. These counties generally home to power plants are rather unique in the ability to directly export property taxes to utility users outside county borders. If we exported these taxes, property tax effort POLGs across Minnesota would likely look even more homogenous. That said, the Price of Local Government does vary across the state and occasionally rather significantly regardless of the measure chosen. A significant share of local spending activity especially school and county spending is highly uniform in nature with respect to service delivery due to state mandates. Differences in those costs and the resulting local effort being made to pay for them may partially reflect more challenging service delivery environments that local governments cannot control. However, some of this variance is undoubtedly due to local preferences regarding the type, level, and quality of local services being provided. Moreover, some extra local effort may reflect differences in internal administration, organization, and related management and delivery cost structures over which local governments themselves exercise considerable direct control. Therefore, we also conclude that Price of Local Government metrics offer at least some potential as a benchmarking tool. We believe POLG findings offer the potential for identifying peer counties with similar demographic, economic, and geographic qualities but featuring lower POLG metrics. There has been considerable interest expressed with many success stories regarding local government redesign in all its forms: program consolidation, intergovernmental coordination, shared service delivery, etc. with the objective of supporting excellence in local services at lower cost. POLG offers one avenue for beginning these investigations. 14 info@fiscalexcellence.org