Michael A. Pagano Dean, College of Urban Planning and Public Affairs Professor, Public Administration University of Illinois at Chicago
The Fiscal Policy Space of Cities
The generous support of the John D. and Catherine T. MacArthur Foundation is greatly appreciated.
Fiscal Policy Space: Sets of attributes that define the range of fiscal policy options available to officials.
Change frame from averages to variation
Change frame from fiscal condition to fiscal behavior.
-10.00%
-5.00%
0.00%
5.00%
1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Change in Constant Dollar Revenue (General Fund) Change in Constant Dollar Expenditures (General Fund)
0.0
10.0
20.0
30.0 Actual Ending Balance as % of Expenditures
Fiscal Policy Space Attributes • The intergovernmental context, including both state-imposed and locally-
imposed limitations on taxes and expenditures.
• The fiscal base, the linkage between a city’s economic base and its fiscal architecture or authority to tap into a city’s underlying economy.
• The demands and preferences of citizens for a quantity and quality of
services and the local political culture that creates a set of expectations, norms of conduct and behavior, and informal rules.
Boise
Seattle
Portland
Reno Salt Lake City
Los Angeles Phoenix
Omaha
Denver
Albuquerque
Austin
Oklahoma City
Wichita
Little Rock
Baton Rouge
Kansas City
Des Moines
Minneapolis
Milwaukee Chicago
Indianapolis
Louisville
Nashville
Jackson Montgomery Augusta
Jacksonville
Virginia Beach
Dayton Columbus
Grand Rapids Buffalo
Pittsburgh
Baltimore Philadelphia
New York
Bridgeport Providence
Boston
Anchorage
Honolulu
Houston
Dallas
San Francisco
San Diego
San Antonio
Detroit
San Jose
Cape Coral
Las Vegas
Sacramento
Memphis
Cleveland
Tampa
Riverside
St. Louis
El Paso
Tucson
Fresno
Stockton
Bakersfield
Cincinnati
Charlotte
Durham
New Orleans
Tulsa
Orlando
Colorado Springs
Greensboro
Raleigh
Birmingham
Toledo
Rochester
Richmond
Lexington
Madison
Corpus Christi
Oxnard
Akron
Winston-Salem
Worcester
Ft. Wayne
Knoxville Chattanooga
Modesto
Atlanta
Spokane
Lincoln
Springfield
Miami
Shreveport
Santa Rosa
Mobile
Fayetteville
Lubbock
Syracuse Hartford
Huntsville
New Haven
McAllen
Property + Sales + Income
Property + Sales or Income
Property or Sales Only
Map 1: City Fiscal Authority
Source notes: State-by-state information on local tax authority is drawn from several sources: 1. Critical Issues in State-Local Tax Policy: A Guide to Local Option Taxes (National Conference of State Legislatures, 1997); 2. Home Rule in America, by Dale Krane, et. al. (1999); and 3. Updated information from state and local government websites conducted in 2014-15.
Boise
Seattle
Portland
Reno Salt Lake City
Los Angeles Phoenix
Omaha
Denver
Albuquerque
Austin
Oklahoma City
Wichita
Little Rock
Baton Rouge
Kansas City
Des Moines
Minneapolis
Milwaukee Chicago
Indianapolis
Louisville
Nashville
Jackson Montgomery Augusta
Jacksonville
Virginia Beach
Dayton Columbus
Grand Rapids Buffalo
Pittsburgh
Baltimore Philadelphia
New York
Bridgeport Providence
Boston
Anchorage
Honolulu
Houston
Dallas
San Francisco
San Diego
San Antonio
Detroit
San Jose
Cape Coral
Las Vegas
Sacramento
Memphis
Cleveland
Tampa
Riverside
St. Louis
El Paso
Tucson
Fresno
Stockton
Bakersfield
Cincinnati
Charlotte
Durham
New Orleans
Tulsa
Orlando
Colorado Springs
Greensboro
Raleigh
Birmingham
Toledo
Rochester
Richmond
Lexington
Madison
Corpus Christi
Oxnard
Akron
Winston-Salem
Worcester
Ft. Wayne
Knoxville Chattanooga
Modesto
Atlanta
Spokane
Lincoln
Springfield
Miami
Shreveport
Santa Rosa
Mobile
Fayetteville
Lubbock
Syracuse Hartford
Huntsville
New Haven
McAllen
> 78.4%
63.6% - 78.4%
48.7% - 63.5%
33.8% - 48.6%
< 33.8%
Map 2: Own Source Revenues as a % of General Revenues
Source Note: U.S. Census of Governments, 2012
Mean: 63.6% Standard Deviation: 14.9%
Boise
Seattle
Portland
Reno Salt Lake City
Los Angeles Phoenix
Omaha
Denver
Albuquerque
Austin
Oklahoma City
Wichita
Little Rock
Baton Rouge
Kansas City
Des Moines
Minneapolis
Milwaukee Chicago
Indianapolis
Louisville
Jackson Montgomery Augusta
Jacksonville
Dayton Columbus
Grand Rapids
Pittsburgh Philadelphia
Honolulu
Houston
Dallas
San Francisco
San Diego
San Antonio
Detroit
San Jose
Cape Coral
Las Vegas
Sacramento
Cleveland
Tampa
Riverside
St. Louis
El Paso
Tucson
Fresno
Stockton
Bakersfield
Cincinnati
Charlotte
Durham
New Orleans
Tulsa
Orlando
Colorado Springs
Greensboro
Raleigh
Birmingham
Toledo
Lexington
Madison
Corpus Christi
Oxnard
Akron
Winston-Salem
Ft. Wayne
Modesto
Atlanta
Spokane
Lincoln
Miami
Shreveport
Santa Rosa
Mobile
Fayetteville
Lubbock
Huntsville
McAllen
> 24.8%
17.7% - 24.8%
3.2% - 17.6%
< 3.2%
Map 3: State Aid as a % of General Revenues
Source Note: U.S. Census of Governments, 2012
Mean: 10.4% Standard Deviation: 7.2%
Boise
Seattle
Portland
Reno Salt Lake City
Los Angeles Phoenix
Omaha
Denver
Albuquerque
Austin
Oklahoma City
Wichita
Little Rock
Baton Rouge
Kansas City
Des Moines
Minneapolis
Milwaukee Chicago
Indianapolis
Louisville
Nashville
Jackson Montgomery Augusta
Jacksonville
Virginia Beach
Dayton Columbus
Grand Rapids Buffalo
Pittsburgh
Baltimore Philadelphia
New York
Bridgeport Providence
Boston
Anchorage
Honolulu
Houston
Dallas
San Francisco
San Diego
San Antonio
Detroit
San Jose
Cape Coral
Las Vegas
Sacramento
Memphis
Cleveland
Tampa
Riverside
St. Louis
El Paso
Tucson
Fresno
Stockton
Bakersfield
Cincinnati
Charlotte
Durham
New Orleans
Tulsa
Orlando
Colorado Springs
Greensboro
Raleigh
Birmingham
Toledo
Rochester
Richmond
Lexington
Madison
Corpus Christi
Oxnard
Akron
Winston-Salem
Worcester
Ft. Wayne
Knoxville Chattanooga
Modesto
Atlanta
Spokane
Lincoln
Springfield
Miami
Shreveport
Santa Rosa
Mobile
Fayetteville
Lubbock
Syracuse Hartford
Huntsville
New Haven
McAllen
No TELs
Nonbinding Property Tax Limit
Potentially Binding Property Tax Limit
Potentially Binding Property Tax Limit + General Revenue/Expenditure Limit
Map 4: State Tax and Expenditure Limits (TELs)
Source notes: State-by-state information on TELs is drawn from the following sources: 1. National Conference of State Legislatures (various years); 2. Home Rule in America, by Dale Krane, et. al. (1999); 3. The Lincoln Institute of Land Policy’s tracking of local property tax limits, and 4. Updated information from a search of state and local government websites conducted in 2014-15.
-0.8
-0.6
-0.4
-0.2
0.0
0.2
0.4
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Non-binding TEL cities Binding-TEL cities
TEL gap by binding/non-binding TELs
The fiscal base is the weighted average of per capita values of properties, retail sales, and income compared to the reliance of a city on property, sales, and income tax receipts.
0.00
0.50
1.00
1.50
2.001
23
Economic base for 1) property tax, 2) sales tax, and 3) income tax
Tax ratio of 1) property tax, 2) sales tax, and 3) income tax
0.00
0.20
0.40
0.60
0.80
1.001
23
Economic base for 1) property tax, 2) sales tax, and 3) income tax
Tax ratio of 1) property tax, 2) sales tax, and 3) income tax
Orlando Buffalo
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.401
23
Economic base for 1) property tax, 2) sales tax, and 3) income tax
Tax ratio of 1) property tax, 2) sales tax, and 3) income tax
Denver
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.401
23
Economic base for 1) property tax, 2) sales tax, and 3) income tax
Tax ratio of 1) property tax, 2) sales tax, and 3) income tax
Boston
A measure of local demand that combines political ideology, housing affordability, and public sector unionization.
Low Demand 2002 2012 High Demand 2002 2012
Ft. Wayne IN -0.42 -1.11 Hartford CT 1.91 1.8
Lubbock TX -1 -1.39 New Haven CT 1.89 1.84
Virginia Beach VA -1.04 -1.08 Providence RI 1.71 1.44
Wichita KS -1.08 -0.97 Boston MA 1.67 1.42
Winston-Salem NC -1.09 -0.85 Bridgeport CT 1.63 1.39
Lincoln NE -1.13 -1.25 Detroit MI 1.22 1.78
Huntsville AL -1.4 -1.07 Miami FL 1.2 1.44
Colorado Springs CO -1.42 -1.29
Boise
Seattle
Portland
Reno Salt Lake City
Los Angeles Phoenix
Omaha
Denver
Albuquerque
Austin
Oklahoma City
Wichita
Little Rock
Baton Rouge
Kansas City
Des Moines
Minneapolis
Milwaukee Chicago
Indianapolis
Louisville
Nashville
Jackson
Jacksonville
Virginia Beach
Dayton Columbus
Grand Rapids Buffalo
Baltimore Philadelphia
New York
Bridgeport Providence
Boston
Anchorage
Honolulu
Houston
Dallas
San Francisco
San Diego
San Antonio
Detroit
Cape Coral
Las Vegas
Sacramento
Memphis
Cleveland
Tampa
Riverside
St. Louis
El Paso
Fresno
Stockton
Bakersfield
Cincinnati
Charlotte
Durham
New Orleans
Tulsa
Orlando
Colorado Springs
Greensboro
Raleigh
Birmingham
Toledo
Rochester
Richmond
Lexington
Madison
Corpus Christi
Oxnard
Akron
Winston-Salem
Worcester
Ft. Wayne
Knoxville Chattanooga
Atlanta
Spokane
Lincoln
Springfield
Shreveport
Santa Rosa
Mobile
Fayetteville
Lubbock
Hartford
Huntsville
McAllen
4 FPS Attributes (N=11)
3 FPS Attributes (N=30)
2 FPS Attributes (N=32)
1 or No Attribute(s) (N=18)
Map 5: Fiscal Policy Space – City Clusters (2010)
-200
-150
-100
-50
0
50
Total Tax License/Permit Fines, Forfeitures,Penalties
Charges Federal and StateAid
Other Total Non-Tax TOTAL REVENUE
Per Capita Revenue Change, 2007-2012 (Governmental Funds, 2012 dollars)
Cluster 1 Cluster 2 Cluster 3 Cluster 4
-350
-300
-250
-200
-150
-100
-50
0
50
100
General Gov Public Safety Public Works Health Culture & Rec Capital Outlays Debt service Other TOTALEXPENDITURES
Ending Balance
Per Capita Spending Change from 2007-2012 (Governmental Funds, 2012 dollars)
Cluster 1 Cluster 2 Cluster 3 Cluster 4
The FPS is a behavioral frame and needs to be better understood in order to:
• Analyze the efficacy of fiscal decisions, • Design federal and state programs, and • Identify appropriate changes to constraints that can enhance city
leaders’ abilities to efficiently, effectively, and fairly pursue pathways to improving conditions in cities.
Thank you Contact information: Michael Pagano: [email protected] Chris Hoene: [email protected]
Public access to the data base of 100 cities with 600+ variables covering the time period 1992-2012 can be found at: http://www.srl.uic.edu/fiscalpolicyspace/index.php
Putting Municipal Fiscal Health in Context
Tracy Gordon
City Economic and Fiscal Resilience: How can we measure it? How can we improve it?
September 8th 2016
System of federal grants evolved to address things the local public sector cannot do well
Phases of American Federalism
Dual Federalism 1787–1933
Cooperative Federalism 1933–1962
Creative Federalism 1962–1968
New Federalism 1968–1980
Fend for Yourself Federalism 1980–1992
New Flexibility 1992–2000
New Accountability/Executive
Federalism/etc.
2000+
How to allocate grant dollars? Suggestive evidence they are not going where they should
• Revenue capacity US average tax rate multiplied by state base
• Expenditure need US average per capita spending multiplied by state population and adjusted for costs and demographics
• Fiscal gap at capacity Difference between the two measures, with federal grants added in
Gap at Capacity After Transfers
< -$1,000 -$1,000 -- $0 $0 -- $1,000 > $1,000
AK ME
WI VT NH
WA ID MT ND MN IL MI NY MA
OR NV WY SD IA IN OH PA NJ CT RI
CA UT CO NE MO KY WV VA MD DE
AZ NM KS AR TN NC SC DC
OK LA MS AL GA
HI TX FL
U R B AN I NS TI TU TE
Source: Urban Institute calculationsNote: Gap at capacity after transfers equals a state's revenue capcity plus federal transfers minus expenditure need.
This is also an issue for state grants to local governments
Fisher & Prasad (2012):
• Mostly per capita formulas with minimums
• Need, but not cost factors included
• Suspended in times of state fiscal crisis
Many alternative methods for directing aid dollars Category Concept Source Method Indicators
Economic
Index of Center City
Hardship
Nathan and Adams (1976) Urban to suburban ratios, weighted
Unemployment, dependency
of population, education,
income, crowded housing,
poverty
Indices of Social,
Economic and Fiscal
Need
CBO (1978) Composite scores from point-in-
time indicators and outside indices
Social Need: Nathan and
Adams index, plus
unemployment and per capita
income
Economic: 6 indicators
Fiscal effort: tax effort,
property tax base, and two
comprehensive measures
developed by HUD
Fiscal Capacity ACIR (1971) Representative Revenue System
Revenues collected divided by
revenue capacity
ACIR (1977) Fiscal Pressure
Tax effort divided by change
in tax effort
Need-capacity Gap
Ladd and Yinger (1989),
Ratcliffe, Riddle & Yinger
(1990), Reschovsky (1993)
Revenue-raising capacity minus
standardized expenditure need,
expressed as a % of capacity
Standardized expenditure
need from costing functions,
regressions, and
environmental cost factors
Revenue capacity is revenue
that can be raised by applying
a uniform tax burden, as a %
of resident income
Alternatives, cont’d Fiscal & Financial
Urban Fiscal Strain
Treasury (1978)
Average change in weighted
variables; combined with other
indices
Population, per capita income,
own-source revenue burden,
long-term debt per capita,
property value (full market)
Fiscal stress warning
signs
ACIR (1973) Based on qualitative evaluation of
cities’ financial status
One-year operations,
continuous operations,
working capital, short-term
operating loan balance,
property tax delinquency,
property valuation
Fiscal strain
Clarke and Ferguson (1983)
Measure based on fiscal outputs
divided by population indicators.
Produces twenty separate
indicators.
Fiscal outputs include general
expenditures, own revenues,
common functions, and debt.
Population factors include
median family income,
population change, and city
wealth index
Financial Condition
Ratios
Aronson & King (1978) Focus on debt-serve combined a
rising ratio of debt service to
income
Seven ratios, focused on debt,
debt service and income
Brown (1993) 10-Point Scale Total revenues/population,
own-source General Fund
(GF) Revenues /GF revenue,
GF sources from other
funds/Total GF sources,
OpEx/Total expenditures
Total revenue/total
expenditures, Unreserved GF
Balance/GF revenues
GF cash and investments/GF
liabilities, GF liabilities/GF
Yet more alternatives
Comprehensive
Fiscal Trend
Monitoring System
(FTMS)
International City/County
Managers (ICAMA, 1980)
Groves and Valente (1994)
Nolleberger (2003)
36 individual indicators across 7
categories, measure them each
individually over time.
7 categories:
Revenue, expenditure,
operating position, debt,
unfunded liability,
capital plant, and community
needs and resources
Groves, Godsey, and
Shulman (1981)
ICMA FTMS Ask city representatives in 50
cities to use and give feedback
on ICMA FTMS.
Hendrick (2004) Three-dimensional fiscal health
measurement.
Spending needs and revenue wealth,
balance with the environment,
and fiscal slack
Revenue wealth and spending
need indicators obtained
through regression analysis,
similar to Ladd and Yinger.
Fiscal balance is
revenue/wealth and
spending/need
Fiscal slack is % unreserved
fund balance, % capital
expenditures, % enterprise
income, and % debt service
Focus on financial indicators Financial Condition Ratio Formula
Liquidity Current ratio Current assets/current liabilities Working capital Current assets – current liabilities Quick ratio (Cash + marketable securities + accounts receivable)/current liabilities Net position ratio Total net position/expenses Current liabilities Current liabilities/total revenues Solvency Debt-to-asset ratio Total liabilities/total assets Operating position Total revenues/total expenditures Profit margin ratio Surplus (or deficit)/revenue Return-on-assets ratio Surplus (or deficit)/total assets Continuing services ratio Unrestricted net assets/total expenses Fund balance ratio Unrestricted general fund balance/general fund expenditures Operating deficit ratio General fund surplus or deficit/net operating expenditures Operating expenses Operating expenditures/total expenditures Sustainability Net worth ratio Restricted and unrestricted net assets/total expenses Sustainability ratios Total revenues, tax revenues, or expenditures/population Debt service ratios Debt service expenditure/total revenues or expenditures Long-term debt per capita Long-term debt outstanding/population Pension underfunding Unfunded pension liability/population Diversification Common size ratio Line item amount/total amount (e.g., cash to total assets) Capacity Debt-to-assessment ratio Debt/assessment Effective tax rate Taxes (or own-source revenues)/taxable assessment Risk Tax leverage factor Total operating expenditures/property tax revenue Risk exposure factor (Investment revenue + intergovernmental revenue + transfers in)/property tax revenue
Transfer dependency Transfers/total revenues Charge-to-expense ratio Charges for services/total expenses
What if … an Early Warning System?
GovRank recently collected nearly 100,000 government financial reports and manually extracted “top line” figures
A preliminary finding: lots of “stickiness” in city fiscal conditions
Bottom 25 % Top 25% Bottom 25 % Top 25%
Bottom 25 % 11.3% 3.1% Bottom 25 % 18.1% 0.4%
Top 25% 3.7% 11.3% Top 25% 0.4% 18.9%
Bottom 25 % Top 25% Bottom 25 % Top 25%
Bottom 25 % 17.3% 0.9% Bottom 25 % 16.9% 0.4%
Top 25% 0.4% 17.2% Top 25% 0.9% 17.7%
Continuing
services 2009
Net worth
2009
Continuing services ratio 2009 vs 2014: Net worth ratio 2009 vs 2014:
Continuing services 2014 Net worth 2014
% of Cities with 2012 CoG pop >=25,000
N=1,217
*Observations include cities with financial health indicators (profit margin ratio, debt-to-assets ratio, continuing services ratio, and net worth) for 2009 and 2014.
Debt-to-asset ratio 2009 vs 2014:
Debt-to-asset 2014
Debt-to-asset
2009
Profit margin ratio 2009 vs 2014:
Profit margin 2014
Profit margin
2009
What to do?
• Recognize variation is hallmark of local government
• Recognize data availability and comparability issues
• Refine goals and decide
What is it we want to measure and why?
By this I mean high rates of poverty and high rates of elderly living in your city. Both groups will consume more in services than they contribute in tax revenues. This is typically not a serious problem as long as the share of city population in these two groups is modest, but if their combined share gets much over 35 % then the city has real fiscal problems.
“BAD” DEMOGRAPHICS:
“BAD” ECONOMICS
City’s economy is dominated by low skilled occupations – and thus low real wages and thus home values and low capital intensity – and/or the industries of the city are cyclically sensitive.
Also city economies dominated by a single industry will be more at risk than a economically diversified city economy.
“BAD” POLICIES: These will typically be policies that redistribute the economic surplus earned by efficient agglomeration to those who do not produce the surplus. Such policies arise from fiscal redistributions, and when those redistributions get “large enough” – that is, greater than private sector benefits of being in the city – then the taxed firms and households will leave. Examples include income redistribution policies, paying for prior debt and unfunded pensions, neglected infrastructure, non-competitive public employee labor contracts.
USUALLY IT TAKES A “PERFECT STORM” ➔ FISCAL CRISIS
DEMOGRAPHICS ECONOMY POLICIES CITIES
GOOD GOOD GOOD Indianapolis; Minneapolis
GOOD GOOD WEAK ?
WEAK GOOD GOOD NYC in 1990s
WEAK GOOD WEAK D.C., Phila up to 1989
WEAK WEAK GOOD Pittsburgh in 60's/70's
WEAK WEAK WEAK Camden, Phila (90), Newark, Bridgeport
PHILADELPHIA AS A CASE STUDY In June, 1990 Mayor Wilson Goode proposed and City Council approved a balanced budget. The state accepted that budget as valid. By the Fall of 1990 it was revealed to be a bogus budget – full of holes. What had been a balanced budget (under Mayor Green) had become a $250 million deficit on a $2 billion budget by 1990. Just as the city was creating this “structural deficit,” the national economy fell into recession lowering city tax bases and thus also city revenues. By the winter of 1990 /1991 the deficit going forward looked to be perhaps as large as $400 million. Four years of fiscal austerity (under Mayor Rendell) were required to restore taxes and spending into balance.
CAUSES?
10 YEARS OF EXPENSIVE LABOR CONTRACTS STATE IMPOSED POVERTY OBLIGATIONS NEIGHBORHOOD SPENDING DECLINING TAX BASE WITH INEFFICIENT TAX STRUCTURE NOW “STIR IN” THE 1990 RECESSION
ONE STRUCTURAL PROPOSAL
REGIONAL FUNDING OF CITY POVERTY OBLIGATIONS
OR
“TREAT PHILADELPHIA LIKE PITTSBURGH”
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