NCAC-APA Conference, 2016 Sidney Wong, Ph.D., Community Data Analytics Daniel Miles, Ph.D., Econsult Solutions, Inc. Rinoa Guo, Econsult Solutions, Inc.

1. NCAC-APA, June 2016
Projecting Development
Impacts for Sustainable and
Fiscally Responsible Growth
Speakers
Sidney Wong, Ph.D., Community Data Analytics
Daniel Miles, Ph.D., Econsult Solutions, Inc.
Rinoa Guo, Econsult Solutions, Inc.
American Planning Association
The National Capital Area Chapter
Conference
June 4, 2014

2. Bise, C. 2007. Fiscal Impact Analysis: How Today’s Decisions Affect
Tomorrow’s Budgets, ICMA Report; 2010. Fiscal Impact Analysis:
Methodologies for Planners
Bunnell, G. 1997. “Fiscal Impact Studies as Advocacy and Story
Telling,” Journal of Planning Literature, 12(2): 136-151
Burchell, R. W. & D. Listokin. 1978. The Fiscal Impact Handbook.
Edwards, M. 2009. “Fiscal Impact Analysis: State of the Art”, Lincoln
Institute of Land Policy Paper
Edwards, M. & J. Huddleston. 2010. “Prospects and Perils of Fiscal
Impact Analysis,” Jr. American Plg Assoc., 76 (1): 25-41
Projecting Development Impacts for
Sustainable and Fiscally Responsible Growth
American Planning Association
The National Capital Area Chapter Conference – June 4, 2016
Sidney Wong, Ph.D., CDA
Daniel Miles, Ph.D., ESI
Rinoa Guo, ESI
Critical Data Sources to Estimate Impact
2006 Demographic Multipliers Series
 Based on records collected in the 1990s
 State level ratios by housing type for newly built units
 Cannot reflect recent changes
 Not geographically specific
Current Public Use Microdata Sample (PUMS) Records
 Based on annually updated survey
 Reporting unit at 100,000 person unit (PUMA)
 Variety of samples
 Expanded list of ratios
 Robust, more geographically specific, and cover
multiple types of impacts
Estimation Biases Using Old Multipliers
 Average household size is declining or has remained
unchanged in 35 states between 2000-2010
 Tend to overestimate impacts in suburban areas
 Tend to underestimate impacts in established urban
centers and corridors
Findings in the Capital Region
 Number of School-Age Children (SAC) increased in
all housing types in Maryland between 2000 and
2014
 The 2014 SAC for 2-bedroom multifamily units varies
from 0.09 to 0.6 among the 19 PUMAs in the National
Capital Area
 The SAC for 3-bedroom single-family units ranges
from 0.2 to 0.7 within the region.
 School impact for single family units is higher in the
suburban area except in the southeast of Prince
George’s County
 Ratios for Silver Spring area are lower than Maryland
 SAC in multifamily units is above the average in the
southeast of Prince George’s County
Fiscal Impact Analysis
 The framework was developed by Robert Burchell
and David Listokin in The Fiscal Impact Handbook.
 Lincoln Institute attempted to rethink the framework
around 2007
 Defined geography and direct impacts
Fiscal Impact Analysis Methods
 There are 6 main approaches to conducting an FIA
 The Average Cost approach is the simpler, more
commonly used method
 The Marginal Cost approach relies on an analysis of
the supply and demand relationship for public
services. It views growth in a non-linear manner
 The two approaches may result in dramatically
different estimates of development impact
 A Mixed Average Cost/Case Study approach
combines the simplicity and ease-of-use of the
Average Cost approach. It acknowledges that
straight Average Cost approach is not ideal, but
includes aspects of the Marginal Cost approach
 Fiscal Impact Analysis is entirely dependent on the
assumptions and data used. PUMS data can
provide better estimates of the key variables
underlying the impacts
Pennytown Case
 Worked closely with the client and school district to
understand the community
 Conducted a 10-year trend analysis of enrollment,
expenses by service and interviewed administrators
to understand service capacity
 Used multiple methods and tested the multipliers
over ten years, and adjusted for the nature of the
occupants
Sample of FIA Study Reports
 Pennytown Report: http://bit.ly/CDA-PennytownFIA
 Beazer Report: http://bit.ly/CDA-BeazerFIA
FOR MORE INFORMATION 1435 Walnut Street, Ste. 400
Philadelphia, PA 19102
215-717-2777
cda-esi.com
econsultsolutions.com
Sidney Wong, wong@econsultsolutions.com
Daniel Miles, miles@econsultsolutions.com
Rinoa Guo, guo@econsultsolutions.com
Resources and References
Juntunen, L. & G. Knaap. 2011. “Fiscal impact analysis and the
costs of alternative development patterns,” The Oxford
Handbook of Urban Economics and Planning
Kotval, Z. & J. Mullin. 2006. “Fiscal Impact Analysis: Methods,
Cases, and Intellectual Debate,” Lincoln Institute of Land
Policy Paper
Lamie, R. et al. 2010. “The fiscal-geographic nexus,” Applied
Geography, 32(1): 54–60

3. NCAC-APA, June 2016
Introduction
• Development Impact, Fiscal
Benefits and Costs
• Data Sources
• The National Capital Area
• Fiscal Impact Analysis Practice
• Discussions

4. NCAC-APA, June 2016
Why Do We Care about
Development Impacts?
• Fiscal
• Economic
• School
• Traffic
• Environment
• Social
• Political
• Others

5. NCAC-APA, June 2016
Fiscal Benefits
Which is most important?
• Property Tax Revenues
• Local Wage Tax Revenues
• Sales Tax Revenues
• Other Levies
• User Charges, Fees and Fines
• Increment of Property Values / Tax Base
Expansion
• Others

6. NCAC-APA, June 2016
Fiscal Costs
• School Expenditures
• Government Operating Expenses
• Capital Improvement Costs
• Traffic Improvement Expenditures
• Debt Financing
• Others
Which is most important?

7. NCAC-APA, June 2016
Critical Information to Estimate
Impacts and Fiscal Costs
Occupants
• Age
• School-Age Children
• Public School Attendees
• Household Income
• Number of Cars Available
• Year of Moving In
• Other Information
Housing Units
• Structure Types
• Number of Bedrooms
• Rental o r Owned
• Year Structure Built
• Other information
School
Traffic

8. NCAC-APA, June 2016
Possible Data Sources
• Census (Summary 1 File)
• American Community Survey
• American Housing Survey
• Customized Survey
• Administrative Records
• Public Use Microdata Sample
X
X
X
X
X


9. NCAC-APA, June 2016
Public Use Microdata Sample
Viable, Robust and Workable
but not so easy to use

10. NCAC-APA, June 2016
2006 Fannie Mae Demographic
Multiplier Series
• 2000 PUMS, i.e. survey data in the 1990s
• State level data
• Occupied Units built between 1990 and
1999
• A variety of housing configurations
• Average Number of Occupants
• Average Number of School-Age Children

11. NCAC-APA, June 2016
Issues of the 2006 Multipliers
• Statewide averages cannot reflect
local characteristics
• Took 3 to 4 years to prepare
• Not updated afterward
• Drastic Demographic Changes
• Estimation biases

12. NCAC-APA, June 2016
2000 to 2016
Many Changes
Average Household Size as an illustration

13. NCAC-APA, June 2016
Average Household Size
2.20
2.30
2.40
2.50
2.60
2.70
2.80
Maine North
Dakota
Vermont Montana South
Dakota
Wisconsin New
Hampshire
Michigan US Louisiana New
Mexico
Alaska
2000 2010
By 10 States with Largest Decline between 2000
and 2010
Sources: Table H12, 2000 and 2010 Census SF1

14. NCAC-APA, June 2016
Public Use Microdata Sample
(PUMS)
• Un-tabulated records about individuals,
households, and housing units
• Census, ACS 1-year, 3-year, and 5-year
• Most recent: 2010-2014 5-YR ACS PUMS

15. NCAC-APA, June 2016
Public Use Microdata Areas
(PUMAs)
• Geographic Areas:
Region, Division, State, and PUMA
• Areas containing about 100,000 residents
• Boundaries changed: 2000, 2010

16. NCAC-APA, June 2016
Our Research of 2014 PUMS
• PUMA level
• Expanded List of Planning Ratios
– School-Age Children
– Public School Attendees
– Cars Available
– Average Household Income
• Special Samples
– Householders 55+
– Transit-Commuter Households
– Movers
– Condominium Households
– Low & Moderate Income Households

17. NCAC-APA, June 2016
National
Capital Area
Map of 19 PUMAs
• Geography
– District of Columbia
– Montgomery County
– Prince George's County
• Population (2010)
– ranges from 104,000 to
178,000
• Great variations

18. NCAC-APA, June 2016
National Capital Area
District of Columbia
101
District of Columbia
(West) PUMA
102
District of Columbia
(North) PUMA
103
District of Columbia
(Northeast) PUMA
104
District of Columbia
(East) PUMA
105
District of Columbia
(Central) PUMA

19. NCAC-APA, June 2016
National Capital Area
Montgomery County
1001
Olney,
Damascus,
Clarksburg &
Darnestown
PUMA
1002
Germantown &
Montgomery
Village PUMA
1003
Rockville,
Gaithersburg Cities
& North Potomac
PUMA
1004
Bethesda, Potomac &
North Bethesda PUMA
1006
Fairland,
Calverton,
White Oak &
Burtonsville
PUMA
1005
Wheaton,
Aspen Hill &
Glenmont
PUMA
1007
Takoma Park City &
Silver Spring PUMA

20. NCAC-APA, June 2016
National Capital Area
Prince George's County
1101
College Park City &
Langley Park PUMA
1102
Laurel, Greenbelt
(North & East)
Cities & Beltsville
PUMA1103
New Carrollton &
Hyattsville (Southeast)
Cities PUMA
1104
Seat Pleasant City,
Capitol Heights Town
& Landover PUMA
1107
Oxon Hill, Hillcrest
Heights & Temple Hills
PUMA
1105
Bowie City,
Kettering, Largo,
Mitchellville &
Lanham PUMA
1106
Clinton, Fort
Washington (South),
Rosaryville & Croom
PUMA

21. NCAC-APA, June 2016
Findings in the National Capital
Area
1. New Residents vs New Units
2. Changes between 2000 and 2014
3. Local Variations
4. Location-Specific Data Needed

22. NCAC-APA, June 2016
1. New Residents vs New Units:
School-Age Children
Sources: Econsult Solutions, Inc. Community Data
Analytics, based on 2010-2014 5-Year PUMS
2014 Maryland State Level Ratio, by Housing Types and Bedroom Size
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
All
1BD/ST
2BD
3BD
4BD
5+BD
Owner-All
Owner-1BD/ST
Owner-2BD
Owner-3BD
Owner-4BD
Owner-5+BD
Renter-All
Renter-1BD/ST
Renter-2BD
Renter-3BD
Renter-4BD
Renter-5+BD
SF-All
SF-1BD/ST
SF-2BD
SF-3BD
SF-4BD
SF-5+BD
MF-All
MF-1BD/ST
MF-2BD
MF-3BD
New Units New Residents

23. NCAC-APA, June 2016
2. Changes between 2000 and
2014: School-Age Children
Maryland State Level Ratios for 3-Bedroom,
by Housing Types, New Residents Sample
Sources: Econsult Solutions, Inc. Community Data Analytics,
based on 2000 Census and 2010-2014 5-Year PUMS
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
0.0
0.2
0.4
0.6
0.8
1.0
1.2
All Occupied
Units
Owner-
Occupied
Renter-
Occupied
SF Detached SF Attached MF 2-4 Units MF 5+ Units
2000 2014 % Change

24. NCAC-APA, June 2016
3. Capital Area Local Variations:
School-Age Children
0
0.2
0.4
0.6
0.8
101 102 103 104 105 1001 1002 1003 1004 1005 1006 1007 1101 1102 1103 1104 1105 1106 1107 MD
Sources: Econsult Solutions, Inc. Community Data
Analytics, based on 2010-2014 5-Year PUMS
2014 PUMA Level Ratios for 2-Bedroom Multi-family Units,
New Residents Sample
District of Columbia Montgomery County Prince George's County MD

25. NCAC-APA, June 2016
3. Capital Area Local Variations:
School-Age Children
Sources: Econsult Solutions, Inc. Community Data Analytics,
based on 2010-2014 5-Year PUMS
2014 PUMA Level Ratios for 3-Bedroom, Single-family Units,
New Residents Sample
0
0.2
0.4
0.6
0.8
1104 104 1001 1006 1004 1003 1103 1106 MD 1002 1105 1101 1102 1007 1107 1005 101 102 105 103
Top 4 Maryland Bottom 3

26. NCAC-APA, June 2016
1104
Seat Pleasant
City, Capitol
Heights Town &
Landover PUMA
104
District of Columbia
(East) PUMA
1001
Olney,
Damascus,
Clarksburg &
Darnestown
PUMA
102
District of Columbia
(North) PUMA
103
District of Columbia
(Northeast) PUMA105
District of
Columbia
(Central)
PUMA
1106
Clinton, Fort
Washington (South),
Rosaryville & Croom
PUMA

27. NCAC-APA, June 2016
0.0
0.2
0.4
0.6
0.8
1.0
K - GRADE 4 GRADE 5 - 8 GRADE 9 - 12 All
2014 PUMA 1001 Ratios for 4-Bedroom, SF Detached Units,
New Residents Sample
4. Location-Specific Data Needed
Sources: Econsult Solutions, Inc. Community Data
Analytics, based on 2010-2014 5-Year PUMS
Public School Attendees Non-Public School Attendees

28. Fiscal Impact Analysis
Practice

29. NCAC-APA, June 2016
Fiscal Impact Analysis
“[a] projection of the direct, current, public
costs, and revenues associated with
residential or nonresidential growth to the
local jurisdiction(s) in which this growth is
taking place.”
Page 1,
Burchell, Robert W. and David
Listokin, 1978. The Fiscal
Impact Handbook : Estimating
Local Costs and Revenues of
Land Development.
The Fiscal Impact Handbook, 1978
Source: http://www.transactionpub.com/title/The-
Complete-Illustrated-Book-of-Development-
Definitions-978-1-4128-5504-4.html

30. NCAC-APA, June 2016
“Is growth good or bad for my
for community?”
• It depends…
• Development generates a host of new costs for
a municipality.
• But is will also generate new revenue.
• It is important that municipalities determine if
the new revenues offset the associated costs.
• FIA can help elected officials make fiscally
sound land use decisions.

31. NCAC-APA, June 2016
The Uses of FIA
• Planning Applications of FIA include:
– Land Use Policies
– Rezonings
– Annexations
– Redevelopment
• Budget and Finance Applications
– Capital Improvement Programming
– Revenue Forecasting
– Fiscal Planning
– Level of Service Changes

32. NCAC-APA, June 2016
Methods of Fiscal Impact
Analysis
• There are number of standard approaches to
choose from.
• The two most common include:
– The Average Cost Approach
– The Marginal Cost Approach
• The distinction between the two is fundamental
to FIA.
• They may result in dramatically different
estimates of the fiscal impacts.

33. NCAC-APA, June 2016
The Hybrid Approach
• Combines the Average Cost Approach with
a Case Study analysis.
• The Average Cost Approach is used to
calculate per-capita costs and revenues.
• The Case Studies are used to identify areas
of capacity constraints.
– This helps bring in the benefits of the Marginal
Approach.

34. NCAC-APA, June 2016
Data Needs
• At a minimum a good FIA requires:
– Description of the development
– Local Revenue and Expenditure Data
– Local Property Value Data and Tax rates
– Number of existing Residents and Workers

35. NCAC-APA, June 2016
FIA Steps
• Step 1: Estimate the number of
residents and/or employees
– Total Population
– School Children
• Based on the type of housing units
– PUMS data provides the most up-to-date
information

36. NCAC-APA, June 2016
FIA Steps
• Step 2: Estimate the costs associated
with the development.
– Not all spending categories will be
impacted.
• Step 3: Allocate Costs between
residential and non-residential uses
– The method depends on the cost
categories.

37. NCAC-APA, June 2016
FIA Steps
• Step 4: Derive per-capita and per-
employee expenditure estimates
• Step 5: Calculate total costs
– Operating Costs vs. Capital Costs
– Use case studies and interviews to
understand potential capital costs
– Assess need for new capacity

38. NCAC-APA, June 2016
FIA Steps
• Step 7: Estimate the revenue
associated with the project.
– Property vs. other revenue
• Step 8: Allocate other revenue to land
uses
– Estimate per-capita and per-employee
revenues

39. NCAC-APA, June 2016
FIA Steps
• Step 9: Calculate Revenue
– Property taxes
– Other revenue
– One-time revenue
• Step 10: Calculate the net-fiscal
impacts
– Revenue - Costs

40. NCAC-APA, June 2016
Potential Issues
• Property Tax Abatements
– Could pose an issue for the period where
any taxes are abated.
• The outputs are only as good as the
inputs.

41. NCAC-APA, June 2016
Pennytown FIA Case Study
• Hybrid Methods
– Modified per capita method, Case Study, Proportional
Valuation, Average Parcel-Value Method
• Operating and Capital Expenditures
• Tracking Expenditures for 10 Years
• Examining Trends and Exploring Fiscal Stress
• Identifying Slack Capacity
• Marginal Cost Adjustment
• Adjusting for inflation
• Adjusting for the characteristics of occupants
http://bit.ly/CDA-PennytownFIA

42. NCAC-APA, June 2016
CONCLUSIONS
• Fiscal Impact Analysis remains one of the
important tools
• Better data (current and geographically
specific) must be used
• Hybrid method should be used
• Questions and Discussions

43. NCAC-APA, June 2016
Basic Model of Fiscal Impact Analysis

44. 1435 Walnut Street, Ste. 300
Philadelphia, PA 19102
215-717-2777
cda-esi.com
econsultsolutions.com
FOR MORE INFORMATION:
Dick Voith, voith@econsultsolutions.com
Sidney Wong, wong@econsultsolutions.com
Daniel Miles, miles@econsultsolutions.com
Bénédicte Clouet, clouet@econsultsolutions.com
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