Trends in Households and Possible Demand Effects on Housing in America’s Cities Peter Hayward University of California—Santa Barbara Supply Demand Demand 2

Project Plan Analyze possible demand changes for city housing due to the influence of changes in households Relate preference surveys with forecasted changes of household ages and household types Set up weighted analyses for household cohorts Compare cohorts

Preference Surveys American LIVES; Fannie Mae National Housing Survey; NAHB: What Home Buyers Want Survey Express typical American homebuyer preferences Statistical breakdown of preferences: –By household age and household type –Percent that prefers each type of housing (suburban ranch, city townhouse, city SFH, etc) –Mean and standard deviation of housing preferences

Household Preferences by Age

Preference Surveys (2) Limitations: –Not regionalized –Not expanded preferences –Only sample of population –Only looking at household ages and types –Preferences are not consumption

Household Trends U.S. Census Bureau –Projections to 2010: absolutes and percents –Household age and type Joint Center for Housing Studies –Mobility rates –Homeownership Rates –Household age and type

Household Trends (2) Weighted analysis –(cohort’s projected growth)*(mobility rate)*(homeownership rate) Statistical breakdown of weighted household cohorts –Positive and negative mean –Standard deviation –Cohorts with discernable effects on demand Limitations –Outside considerations (government intervention, disease, etc.) –Housing constructions mirror household growth

Relating Household Trends and Preferences Four Outcomes: –Growing Household Cohort (Above Positive Mean) + Higher than Average Preference for City Housing = Higher Demand –Growing Household Cohort (Above Positive Mean) + Lower than Average Preference for City Housing = Lower Demand –Shrinking Household Cohort (Below Negative Mean) + Higher than Average Preference for City Housing = Lower Demand –Shrinking Household Cohort (Below Negative Mean) + Lower than Average Preference for City Housing = Higher Demand

Preferences by Household Age

Further Analysis and Conclusions Further analysis –Greater than 1 standard deviation above & below means –Greater than 2 standard deviations above & below means Conclusions and impacts –Not exact demand statistics but general idea of future changes –Understanding of future social landscape of America’s cities –May aid contractors, developers, local & regional governments –Replication of methodology

Acknowledgements University of California—Santa Barbara Geography Department Dr. Reginald Golledge United States Census Bureau Joint Center for Housing Studies American LIVES Fannie Mae National Association of Homebuyers