1. The Collection of Municipal Fees Prepared for the City of Milwaukee Budget and Management Division By: Melissa Berger Stephen Collins Paco Fuchs Emily Ley Lara Rosen

2. Overview 1.What is the problem? 2.Which factors explain fee payment? 3.Statistical analysis 4.Policy options and suggestions for further research

3. Defining Municipal Fees and Special Charges Municipal Fees: Property-related fees issued for city services, utilities, and violations Special Charges: Municipal fees authorized by the Common Council to be added to owners’ property tax bills if unpaid

4. What is the Problem? Total Dollar Value of Special Charges 2004-2010 Number of Special Charges 2004-2010 Source: Calculated with data from the City of Milwaukee Assessor’s Office

5. What is the Problem? An increasing share of Milwaukee’s property-related municipal fees is not being paid in a timely fashion. – From 17.3% in 2007 to 20.3% in 2010 Any delay in receiving payment is costly – Debt service – Lost interest revenue – Outsourced collections – Time and resources of staff to collect and track fees

6. Which factors explain fee payment? Characteristics of Fees – Issuing department – Fee type – Fee anticipation – Fee amount Characteristics of Properties – Assessment class – Assessed property value – Owner occupancy – Aldermanic district Characteristics of Collection Practices – Billing notifications – Late penalties – Payment options

7. Characteristics of Fees Issuing departments – Department of Neighborhood Services (DNS) – Department of Public Works (DPW) – Milwaukee Water Works (MWW) Type – Utilities – Minor Violations – City Services – Blight Fee anticipation – Expected – Unexpected Fee amount

8. Average Collections Rates by Fee Characteristic and Type, 2007-2010 Source: Calculated with data from Milwaukee Water Works and the City’s Departments of Neighborhood Services and Public Works

9. Characteristics of Fees Issuing departments – Department of Neighborhood Services (DNS) – Department of Public Works (DPW) – Milwaukee Water Works (MWW) Type – Utilities – Minor Violations – City Services – Blight Fee anticipation – Expected – Unexpected Fee amount

10. Characteristics of Properties Percentage of Properties per Assessment Class 2007-2010 Median Assessed Property Values 2007-2010 Comparing Properties in the City of Milwaukee and Properties with Special Charges ResidentialCommercial Mercantile Apartments (4+ units) Other* All Milwaukee Properties 79%4%3%13% Properties with Minor Violation Charges 82%8%7%3% Properties with Blight Charges 81%7% 5% Properties with Delinquent Utility Charges 89%4% 2% Properties with City Service Charges 51%24%13%11% Median Assessed Property Values 2007-2010 All Milwaukee Properties $115,375 Properties with Minor Violation Charges $88,125 Properties with Blight Charges $77,225 Properties with Delinquent Utility Charges $98,125 Properties with City Service Charges $314,450 Source: Calculated with data from Milwaukee Water Works, the City’s Departments of Neighborhood Services and Public Works, and Milwaukee’s Master Property Record (MPROP)

11. Characteristics of Properties Owner-Occupancy 2007-2010 Source: Calculated with data from Milwaukee Water Works and the City’s Departments of Neighborhood Services and Public Works, and Milwaukee’s Master Property Record (MPROP)

12. Characteristics of Properties Total Value of Special Charges 2007-2010 by Aldermanic District Source: Calculated with data from Milwaukee Water Works, the City’s Departments of Neighborhood Services and Public Works, and Milwaukee Master Property Record (MPROP)

13. Characteristics of Collection Billing notifications: type and frequency – DNS: Some letters, some invoices sent once – DPW: Invoices sent once (*one exception) – MWW: Invoices sent quarterly Late penalties – DNS: None – DPW: $10 one time fee (*two exceptions) – MWW: 5% and 3% compounded quarterly Payment types accepted – DNS and DPW: Cash and check only – MWW: Cash, Check, MasterCard, Discover, E-Check, AutoPay

14. Statistical Analysis Department of Public Works (DPW) Department of Neighborhood Services (DNS) About 140,000 observations Observations are individual municipal fees issued 2007-2010

15. Statistical Analysis Higher probability of payment Characteristics of fees – Increased expectedness – Fire prevention permit fees – Apartment garbage collection fees Characteristics of properties – Assessed property value – Owner living in Wisconsin Characteristics of collection – Late penalties – Expected invoices Lower probability of payment Characteristics of fees – Fee amount – Condemned building razing fees Characteristics of properties – Tax delinquency – Owner occupancy – Duplexes (relative to single- family properties) – Multifamily properties (relative to single-family properties) Characteristics of collection – None

16. Statistical Analysis Invoices: mostly positive increases in probability of payment – Expected invoices to unexpected letters Residential: 25 percent increase Commercial: 41 percent increase Mercantile: 6 percent increase – Other relationships varied (less data) Late penalties: large positive increases in probability of payment – For both expected and unexpected fees Residential: 17 percent increase Commercial: 18 to 21 percent increase Mercantile: 29 percent increase

17. Three Key Policy Options 1.Mail invoices with due dates for all fees 2.Issue late penalties for all unpaid fees 3.Offer credit card payment options for all fees

18. Suggestions for Further Analysis 1.Trend Analysis 2.Cost-Effectiveness Analysis Prerequisites for Analyses: Improve data maintenance Require departments to register each billing and payment event for each fee issued Implement uniform coding protocol Collect detailed information on administrative costs

19. For further information Contact the La Follette School’s publications office at 608-263-7657 or publications@lafollette.wisc.edu Or see www.lafollette.wisc.edu/publications/workshops.html Thank you

21. Data Interviews (January - April 2011) Departmental accounts receivable files (2007-2010) Master Property Record (2007-2010) Assessor data (2004-2010) Treasurer records (2007-2010)

22. Regression Methodology Multivariate probit regression model Dependent variable = 0 if the fee was placed on the property tax bill and = 1 if it was paid in full and not placed on the property tax bill Explanatory variables: characteristics of fees, properties, and collection practices. Add equation Departments of Neighborhood Services and Public Works data only

23. Regression Methodology 138,200 observations in 3 distinct categories: 1. residential properties (89,238) 2. mercantile apartments (23,628) 3. commercial properties (25,334) Divide by “expected” versus “unexpected” For each sample, we estimate the effects of – billing type (invoices and letters) – late penalty issuance

24. Process Departments collect a portion of municipal fees October: departments submit list of unpaid fees (now special charges) to Assessor for placement on tax bills December: Treasurer mails property tax bills If owners do not pay in January, City Attorney sends four warning letters, then employs Kohn Law Firm (KLF) to collect. If KLF cannot collect, City forecloses on property