Demographic Multipliers: Recent National and State Findings

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Demographic Multipliers Recent National and
State Findings

• Prepared ByDAVID LISTOKIN, Ph.D.
• ROBERT W. BURCHELL, Ph.D.
• Prepared ForNATIONAL IMPACT FEE ROUND TABLE
  (NIFR)NATIONAL CONFERENCE
• ARLINGTON, VIRGINIA
• OCTOBER 2006

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PRESENTATION OVERVIEW

• Perspective on Demographic Multipliers
  definition, application, and literature
• Changes in Multipliers Over Time
• Results of New National Data
• Results of New State Data (New Jersey example)
• Conclusions

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DEFINITIONS OF DEMOGRAPHIC MULTIPLIERS

• Demographic multipliers the number and profile
  of the populations associated with new
  residential and nonresidential development
• Residential multipliers Resident population
  associated with housing
• Nonresidential multipliers Worker population
  associated with commercial and other business
  uses

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USE OF DEMOGRAPHIC MULTIPLIERS

• Interlinked Applications
• Impact fees
• Fiscal impact analysis
• School enrollment projections
• Public staffing analysis
• Market studies
• Calculating development standards
• Cost of sprawl studies
• Other applications

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DEMOGRAPHIC MULTIPLIERS LITERATURE OVERVIEW
(EXAMPLES)

• The Fiscal Impact Handbook (1978)
• The Practitioners Guide to Fiscal Impact
  Analysis (1985)
• Development Impact Assessment Handbook and Model
  (1994)
• Planners Estimating Guide (2004)
• Residential Demographic Multipliers (2006)
• Fiscal and Impact Fee Studies (1970s-2000s)
• Other
• Conclusion Extensive literaturebut of
  varying quality and dating is often an issue

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U.S. RESIDENTIAL DEMOGRAPHIC MULTIPLIERS OVER TIME
Conclusion There are generally significant
decreases over time in household size and school
children in most standard housing types. Current
data is therefore essential.
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FANNIE MAE FOUNDATION (FMF) RUTGERS
RESIDENTIAL DEMOGRAPHIC MULTIPLIERS STUDY

• Author Center for Urban Policy Research,
  Rutgers University
• Data 2000 PUMS, U.S. Housing Constructed
  1990-2000
• Geography All U.S., 50 States, and District of
  Columbia
• Release Mid-2006 and available from FMF
  DataPlace (http//www.dataplace.org/newsarticle.h
  tml?aid59)

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FANNIE MAE FOUNDATION (FMF) RUTGERS
RESIDENTIAL DEMOGRAPHIC MULTIPLIERS DATA
FIELDS (I)

• Multipliers comprise
• Household size (HS) Total persons per housing
  unit
• Age distribution of household members 0-4,
  5-13, 14-17, 18-24, 25-44, 45-64, 65-74, 75
• Total school-age children (SAC)
• Total public school-age children (PSAC)
• SAC who attend public school
• SAC and PSAC by grade group (K-2, 3-6, 7-9,
  10-12, 9)

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FANNIE MAE FOUNDATION (FMF) RUTGERS
RESIDENTIAL DEMOGRAPHIC MULTIPLIERS DATA
FIELDS (II)

• Multipliers Differentiated by
• Housing Type
• Single-family detached
• Single-family attached
• 2-4 Unit
• 5 Unit
• Mobile home
• Housing Size
• 1-5 bedrooms
• Housing Price (updated to 2005)
• All values
• Terciles (thirds) 1st 33rd percentile, 34th
  66th percentile, 67th 100 percentile
• Housing Tenure
• Ownership or rental

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FANNIE MAE FOUNDATION (FMF) RUTGERS
RESIDENTIAL DEMOGRAPHIC MULTIPLIERS SELECTED
FINDINGS (I)
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FANNIE MAE FOUNDATION (FMF) RUTGERS
RESIDENTIAL DEMOGRAPHIC MULTIPLIERS SELECTED
FINDINGS (II)
Conclusion Variations in demographics associated
with housing type, housing size, housing value,
and housing tenure.
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FANNIE MAE FOUNDATION (FMF) RUTGERS
RESIDENTIAL DEMOGRAPHIC MULTIPLIERS SELECTED
FINDINGS (III)
Conclusion Need to pay more attention to the age
distribution of household members
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NJ OFFICE OF SMART OF GROWTH (OSG) RUTGERS
DEMOGRAPHIC MULTIPLIERS STUDY

• Author Center for Urban Policy Research,
  Rutgers University
• Data 2000 PUMS, NJ Housing Constructed
  1990-2000, Field studies and other
• Geography NJ, All State and 3 regions
• Multiplier fields
• HS, SAC and PSAC by housing type, size, value,
  tenure, and state region
• Statistics
• Regression analysis of characteristics associated
  with variation in multipliers
• Multipliers presented with sample size, standard
  error, and confidence interval
• Other affordable housing, transit oriented
  development (TOD), and nonresidential multipliers

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OSG RUTGERS RESIDENTIAL DEMOGRAPHIC
MULTIPLIERS SELECTED FINDINGS (I)
Conclusion Variation in demographics associated
with housing type, housing size, and housing
value (housing tenure and region)
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OSG RUTGERS RESIDENTIAL DEMOGRAPHIC
MULTIPLIERS SELECTED FINDINGS (II)
Conclusion Variations around multiplier averages
warrant heightened attention
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OSG RUTGERS RESIDENTIAL DEMOGRAPHIC
MULTIPLIERS SELECTED FINDINGS (III)

• B. Case Study Investigation Average PSAC for
  affordable housing units of 0.52but range of
  0.22 to 1.42

Conclusion What are appropriate multipliers for
affordable housing?
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OSG RUTGERS RESIDENTIAL DEMOGRAPHIC
MULTIPLIERS SELECTED FINDINGS (IV)

• Transit Oriented Development (TOD)
• Field investigation of 10 TODs with 2,200 housing
  units found they contained 50 public school-age
  children (PSAC)or a PSAC multiplier of 0.02 per
  housing unit
• Application of standard residential multipliers
  (average 0.14 PSAC per unit) would have projected
  about 300 PSAC

Conclusion What are appropriate multipliers for
emerging housing types such as TODs?
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OSG RUTGERS NONRESIDENTIAL DEMOGRAPHIC
MULTIPLIERS SELECTED EXAMPLES (V)

• Variation in nonresidential multipliers retail
  example
• Employees per 1,000 ft.2
• State of Washington (1998) 0.57
• CBECS (2001) 0.83-1.95
• CA Dept. Energy (1996) 1.70
• ITE Trip Generation (1997) 2.00
• Census of Retail (1997) 2.44
• Conclusion Need better data on nonresidential
  multipliers

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DEMOGRAPHIC MULTIPLIERS CONCLUSION

• Critical data with many applications
• Moving target changing figures over time
• Variations in residential demographic multipliers
  have been associated with such characteristics as
  housing type, housing size, housing value, and
  housing tenure
• Emerging areas of inquiry
• Statistical analysis
• Household age distribution
• Emerging residential development categories
• Nonresidential multipliers