Demographic Multipliers: Recent National and State Findings

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

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

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

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

DEMOGRAPHIC MULTIPLIERS LITERATURE OVERVIEW (EXAMPLES) • The Fiscal Impact Handbook (1978) • The Practitioner’s Guide to Fiscal Impact Analysis (1985) • Development Impact Assessment Handbook and Model (1994) • Planner’s Estimating Guide (2004) • Residential Demographic Multipliers (2006) • Fiscal and Impact Fee Studies (1970s-2000s) • Other Conclusion: Extensive literature—but of varying quality and dating is often an issue

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.

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.html?aid=59)

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)

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

FANNIE MAE FOUNDATION (FMF) – RUTGERS RESIDENTIAL DEMOGRAPHIC MULTIPLIERS: SELECTED FINDINGS (I)

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.

FANNIE MAE FOUNDATION (FMF) – RUTGERS RESIDENTIAL DEMOGRAPHIC MULTIPLIERS: SELECTED FINDINGS (III) Conclusion: Need to pay more attention to the age distribution of household members

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

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)

OSG – RUTGERS RESIDENTIAL DEMOGRAPHIC MULTIPLIERS: SELECTED FINDINGS (II) Conclusion: Variations around multiplier averages warrant heightened attention

OSG – RUTGERS RESIDENTIAL DEMOGRAPHIC MULTIPLIERS: SELECTED FINDINGS (III) B. Case Study Investigation – Average PSAC for affordable housing units of 0.52—but range of 0.22 to 1.42 Conclusion: What are appropriate multipliers for affordable housing?

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?

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

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

Demographic Multipliers: Recent National and State Findings