Revenue Generation as Budget Strategy: Predictors
of Per Capita Local Health Department Non‐Local
Government Revenues
Senay Goitom
Robert M. La Follette School of Public Affairs
Andrew M. Reschovsky, PhD
Robert M. La Follette School of Public Affairs
Susan Zahner, DrPH, RN
School of Nursing
Acknowledgments
• Support for this research was provided by a
grant from the Robert Wood Johnson
Foundation’s Public Health Practice-Based
Research Networks program, and
• A Health Policy Assistantship funded by grant
#1UL1RR025011 from the Clinical and
Translational Science Award program of the
National Center for Research Resources,
NIH
Effect of Economic Crisis on LHDs
 Housing collapse and “Great Recession” have led
to steep budget cuts at all levels of government
 In Wisconsin, as in many other states, recent budget
deficits have been closed primarily through cuts in
spending
 In Wisconsin, constraints have been placed on
LHDs in the form of property tax levy limits
 This will impact the single largest source of
revenue for LHDs
Rationale
 Given the constraints facing local governments,
non-local government sources will become
increasingly important
 This study represents a first step in understanding
the factors affecting these revenue sources
Local Health Departments in WI
 In Wisconsin, 94 LHDs provide public health
services including:
 Communicable disease control
• Immunization
• Investigation of disease outbreaks
• Education
 Chronic disease prevention and control
• Wellness programs
 Environmental health
• Water testing
• Restaurant and lodging inspections
Research Question
 What community and LHD characteristics affect
growth of non-local government revenue?
Description of Data
 Panel dataset
 92 health departments
• Representing 70 counties and 42 municipalities
 2002-2009
 Total panel size N=746
 Includes data from the following sources:
 Wisconsin Department of Health Services Local Health
Department Survey (2002-2009)
• LHD Revenue Data
• Local Health Department Inventory
• Data on Services Provided
 Demographic Data
 Wisconsin Department of Revenue
• Equalized Property Value Data
• Property Tax, Sales Tax, Shared Revenue Data
Local Health Department (LHD) Financing in
Wisconsin
 In Wisconsin, LHDs receive revenue from the
following sources:
 County/municipal sources (e.g. taxes)





Fees for services
Federal grants
State grants
Private grants
Donations from individuals
Focus of this
presentation
Sources of Non-Local Government Revenue
 Fees for services
 Restaurant and private well inspections
 Medicare and medicaid reimbursements
 Federal Grants
 Maternal and Child Health Block Grant
 WIC
 State grants
 Childhood lead
 Well Woman programs
 Private grants
 Donations from individuals
Percent of Total Revenue 2002-2009
Share of Total Revenue (%)
mean
SD
min
max
Tax Revenue
51.4
16.1
0
100
Federal Grants
Fee for Services
21.8
17.8
12.4
11.6
0
0
75.7
61.1
State Grants
7.5
7.3
0
53.9
Private Grants
1
2.3
0
26.5
Donations
0.4
2.3
0
46.1
Regression Model
 We are looking at why some health departments are
obtaining more revenue than others
ln 𝑅𝑒𝑣 = 𝛽0 + 𝜷𝟏 𝑿𝟏 + 𝜷𝟐 𝑿𝟐 + 𝜹𝒀𝒆𝒂𝒓 + ε
Where:
𝑅𝑒𝑣 is non-local government sources of revenue
𝑿𝟏 is a vector of community characteristics
𝑿𝟐 is a vector of LHD characteristics
𝒀𝒆𝒂𝒓 corresponds to a vector of time dummy variables
Estimation Method
 Log transformation where appropriate (dependent
variable and some RHS variables)
 Lag structure
 Include one and two year lagged values of
dependent variable
 Pooled OLS regression
 Robust standard errors using LHDs as clusters
Summary Statistics of Variables in Final Model
mean
sd
min
max
Per capita non-local government revenue
13.58
9.29
0.00
90.78
LHD population (1000s)
59.91
81.45
4.59
595.96
Per capita personal income (1000s)
34.03
5.32
21.00
62.16
Per capita EQV (1000s)
87.36
42.70
35.45
359.99
Under-18 poverty (%)
15.26
6.93
2.70
51.10
Over 65 (%)
14.69
3.34
9.16
26.04
County health ranking (z-score)
0.13
0.86
-1.73
3.00
Share of total services (%)
50.90
13.42
6.57
78.20
Majority of BOH non-elected (0,1)
0.43
-
0
1
DHS inspection agent (0,1)
0.59
-
0
1
Regression Results-Community Characteristics
Full Model
No Lags
Final Model (with lags)
county unemp. rate
-0.0189
(0.0281)
-0.0546
(0.0667)
county poverty rate
0.0227
(0.0200)
0.0587*
(0.0335)
county under 18 pov.
-0.0264**
(0.0123)
-0.0680***
(0.0205)
-0.0121**
(0.0049)
county health ranking
0.0730*
(0.0409)
0.0686
(0.0677)
0.0512*
(0.0287)
per capita EQV
0.0550
(0.0925)
0.1207
(0.1638)
0.0697
(0.0542)
per capita pers. inc.
-0.5319**
(0.2612)
-1.6301***
(0.5314)
-0.3148*
(0.1733)
county pop. non-white
0.0006
(0.0038)
0.0010
(0.0083)
county pop. under 20
0.0025
(0.0125)
-0.0081
(0.0272)
county pop. 65+
0.0182
(0.0135)
0.0451
(0.0286)
0.0058
(0.0061)
Standard errors in parentheses
* p < 0.10, ** p < 0.05, *** p < 0.01
Regression Results (cont’d)-LHD Characteristics
Full Model
Local gov’t GPR
No Lags
0.0177
(0.0654)
Non-local gov't rev. (L1)
0.4558***
(0.0801)
0.4702***
(0.0722)
Non-local gov't rev. (L2)
0.2369***
(0.0383)
0.2438***
(0.0348)
LHD population
-0.1006**
(0.0490)
-0.2800***
(0.0935)
-0.0811**
(0.0349)
pct of tot LHD services
0.0054***
(0.0017)
0.0187***
(0.0030)
0.0054***
(0.0017)
Indp LHD indicator
0.0176
(0.0589)
0.0282
(0.1403)
County LHD indicator
-0.0362
(0.0816)
0.0732
(0.2138)
BOH non-elect. Indicator
0.0333
(0.0387)
0.1529
(0.1000)
0.0191
(0.0288)
Indp BOH indicator
-0.0223
(0.0564)
-0.0549
(0.1414)
DHS inspec agnt indicator
0.0569
(0.0359)
0.1403
(0.0995)
0.0622**
(0.0288)
Constant
4.3313
(4.9239)
17.2202**
(7.8844)
3.8235**
(1.7124)
Observations
Adjusted R2
Standard errors in parentheses
* p < 0.10, ** p < 0.05, *** p < 0.01
406
0.722
-0.0438
Final Model (with lags)
414
0.543
(0.1282)
412
0.734
Interpretation of Regression Coefficients
Variable
Unit change
Percent change in non
local government revenue
Under 18 poverty rate
+1 percentage point
-1.2%
County Health Ranking
+ one standard deviation
+5.2%
Per capita personal income +1%
-0.3%
Non-local government
revenue (lagged one year)
+1%
+0.5%
Non-local gov’ t revenue
(lagged two years)
+1%
+0.2%
LHD population
+1%
-0.08%
% of total services
+1 percentage point
+0.5%
LHD is DHS Inspection
Agent
N/A
+6.4%
Policy Implications
 Two variables point to possible strategies for
health departments
 Percent of total services
 Whether the LHD is an agent of DHS
 The model suggests that changes that increase
the number of services provided by LHDs have a
positive, statistically significant association with
revenue
Contact information
 Senay Goitom
 goitom@wisc.edu
 312-520-7115
 Andrew Reschovsky
 reschovsky@lafollette.wisc.edu
 608-263-0447
 Susan Zahner
 sjzahner@wisc.edu
 608-263-5282